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jborean93/smbprotocol
smbprotocol/open.py
Open.query_directory
def query_directory(self, pattern, file_information_class, flags=None, file_index=0, max_output=65536, send=True): """ Run a Query/Find on an opened directory based on the params passed in. Supports out of band send function, call this function with send=False to return a tuple of (SMB2QueryDirectoryRequest, receive_func) instead of sending the the request and waiting for the response. The receive_func can be used to get the response from the server by passing in the Request that was used to sent it out of band. :param pattern: The string pattern to use for the query, this pattern format is based on the SMB server but * is usually a wildcard :param file_information_class: FileInformationClass that defines the format of the result that is returned :param flags: QueryDirectoryFlags that control how the operation must be processed. :param file_index: If the flags SMB2_INDEX_SPECIFIED, this is the index the query should resume on, otherwise should be 0 :param max_output: The maximum output size, defaulted to the max credit size but can be increased to reduced round trip operations. :param send: Whether to send the request in the same call or return the message to the caller and the unpack function :return: A list of structures defined in query_info.py, the list entry structure is based on the value of file_information_class in the request message """ query = SMB2QueryDirectoryRequest() query['file_information_class'] = file_information_class query['flags'] = flags query['file_index'] = file_index query['file_id'] = self.file_id query['output_buffer_length'] = max_output query['buffer'] = pattern.encode('utf-16-le') if not send: return query, self._query_directory_response log.info("Session: %s, Tree Connect: %s - sending SMB2 Query " "Directory Request for directory %s" % (self.tree_connect.session.username, self.tree_connect.share_name, self.file_name)) log.debug(str(query)) request = self.connection.send(query, self.tree_connect.session.session_id, self.tree_connect.tree_connect_id) return self._query_directory_response(request)
python
def query_directory(self, pattern, file_information_class, flags=None, file_index=0, max_output=65536, send=True): """ Run a Query/Find on an opened directory based on the params passed in. Supports out of band send function, call this function with send=False to return a tuple of (SMB2QueryDirectoryRequest, receive_func) instead of sending the the request and waiting for the response. The receive_func can be used to get the response from the server by passing in the Request that was used to sent it out of band. :param pattern: The string pattern to use for the query, this pattern format is based on the SMB server but * is usually a wildcard :param file_information_class: FileInformationClass that defines the format of the result that is returned :param flags: QueryDirectoryFlags that control how the operation must be processed. :param file_index: If the flags SMB2_INDEX_SPECIFIED, this is the index the query should resume on, otherwise should be 0 :param max_output: The maximum output size, defaulted to the max credit size but can be increased to reduced round trip operations. :param send: Whether to send the request in the same call or return the message to the caller and the unpack function :return: A list of structures defined in query_info.py, the list entry structure is based on the value of file_information_class in the request message """ query = SMB2QueryDirectoryRequest() query['file_information_class'] = file_information_class query['flags'] = flags query['file_index'] = file_index query['file_id'] = self.file_id query['output_buffer_length'] = max_output query['buffer'] = pattern.encode('utf-16-le') if not send: return query, self._query_directory_response log.info("Session: %s, Tree Connect: %s - sending SMB2 Query " "Directory Request for directory %s" % (self.tree_connect.session.username, self.tree_connect.share_name, self.file_name)) log.debug(str(query)) request = self.connection.send(query, self.tree_connect.session.session_id, self.tree_connect.tree_connect_id) return self._query_directory_response(request)
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train
https://github.com/jborean93/smbprotocol/blob/d8eb00fbc824f97d0f4946e3f768c5e6c723499a/smbprotocol/open.py#L1230-L1276
jborean93/smbprotocol
smbprotocol/open.py
Open.close
def close(self, get_attributes=False, send=True): """ Closes an opened file. Supports out of band send function, call this function with send=False to return a tuple of (SMB2CloseRequest, receive_func) instead of sending the the request and waiting for the response. The receive_func can be used to get the response from the server by passing in the Request that was used to sent it out of band. :param get_attributes: (Bool) whether to get the latest attributes on the close and set them on the Open object :param send: Whether to send the request in the same call or return the message to the caller and the unpack function :return: SMB2CloseResponse message received from the server """ # it is already closed and this isn't for an out of band request if not self._connected and send: return close = SMB2CloseRequest() close['file_id'] = self.file_id if get_attributes: close['flags'] = CloseFlags.SMB2_CLOSE_FLAG_POSTQUERY_ATTRIB if not send: return close, self._close_response log.info("Session: %s, Tree Connect: %s - sending SMB2 Close Request " "for file %s" % (self.tree_connect.session.username, self.tree_connect.share_name, self.file_name)) log.debug(str(close)) request = self.connection.send(close, self.tree_connect.session.session_id, self.tree_connect.tree_connect_id) return self._close_response(request)
python
def close(self, get_attributes=False, send=True): """ Closes an opened file. Supports out of band send function, call this function with send=False to return a tuple of (SMB2CloseRequest, receive_func) instead of sending the the request and waiting for the response. The receive_func can be used to get the response from the server by passing in the Request that was used to sent it out of band. :param get_attributes: (Bool) whether to get the latest attributes on the close and set them on the Open object :param send: Whether to send the request in the same call or return the message to the caller and the unpack function :return: SMB2CloseResponse message received from the server """ # it is already closed and this isn't for an out of band request if not self._connected and send: return close = SMB2CloseRequest() close['file_id'] = self.file_id if get_attributes: close['flags'] = CloseFlags.SMB2_CLOSE_FLAG_POSTQUERY_ATTRIB if not send: return close, self._close_response log.info("Session: %s, Tree Connect: %s - sending SMB2 Close Request " "for file %s" % (self.tree_connect.session.username, self.tree_connect.share_name, self.file_name)) log.debug(str(close)) request = self.connection.send(close, self.tree_connect.session.session_id, self.tree_connect.tree_connect_id) return self._close_response(request)
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Closes an opened file. Supports out of band send function, call this function with send=False to return a tuple of (SMB2CloseRequest, receive_func) instead of sending the the request and waiting for the response. The receive_func can be used to get the response from the server by passing in the Request that was used to sent it out of band. :param get_attributes: (Bool) whether to get the latest attributes on the close and set them on the Open object :param send: Whether to send the request in the same call or return the message to the caller and the unpack function :return: SMB2CloseResponse message received from the server
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train
https://github.com/jborean93/smbprotocol/blob/d8eb00fbc824f97d0f4946e3f768c5e6c723499a/smbprotocol/open.py#L1294-L1331
jborean93/smbprotocol
smbprotocol/security_descriptor.py
SIDPacket.from_string
def from_string(self, sid_string): """ Used to set the structure parameters based on the input string :param sid_string: String of the sid in S-x-x-x-x form """ if not sid_string.startswith("S-"): raise ValueError("A SID string must start with S-") sid_entries = sid_string.split("-") if len(sid_entries) < 3: raise ValueError("A SID string must start with S and contain a " "revision and identifier authority, e.g. S-1-0") revision = int(sid_entries[1]) id_authority = int(sid_entries[2]) sub_authorities = [int(i) for i in sid_entries[3:]] self['revision'].set_value(revision) self['identifier_authority'].set_value(id_authority) self['sub_authorities'] = sub_authorities
python
def from_string(self, sid_string): """ Used to set the structure parameters based on the input string :param sid_string: String of the sid in S-x-x-x-x form """ if not sid_string.startswith("S-"): raise ValueError("A SID string must start with S-") sid_entries = sid_string.split("-") if len(sid_entries) < 3: raise ValueError("A SID string must start with S and contain a " "revision and identifier authority, e.g. S-1-0") revision = int(sid_entries[1]) id_authority = int(sid_entries[2]) sub_authorities = [int(i) for i in sid_entries[3:]] self['revision'].set_value(revision) self['identifier_authority'].set_value(id_authority) self['sub_authorities'] = sub_authorities
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train
https://github.com/jborean93/smbprotocol/blob/d8eb00fbc824f97d0f4946e3f768c5e6c723499a/smbprotocol/security_descriptor.py#L160-L180
Thibauth/python-pushover
pushover.py
MessageRequest.poll
def poll(self): """If the message request has a priority of 2, Pushover keeps sending the same notification until the client acknowledges it. Calling the :func:`poll` function fetches the status of the :class:`MessageRequest` object until the notifications either expires, is acknowledged by the client, or the callback url is reached. The status is available in the ``status`` dictionary. Returns ``True`` when the request has expired or been acknowledged and ``False`` otherwise so that a typical handling of a priority-2 notification can look like this:: request = p.message("Urgent!", priority=2, expire=120, retry=60) while not request.poll(): # do something time.sleep(5) print request.status """ if not self.status["done"]: r = Request("get", self.url + ".json", {"token": self.payload["token"]}) for param, when in MessageRequest.params.iteritems(): self.status[param] = bool(r.answer[param]) self.status[when] = int(r.answer[when]) for param in ["acknowledged_by", "acknowledged_by_device"]: self.status[param] = r.answer[param] self.status["last_delivered_at"] = int(r.answer["last_delivered_at"]) if any(self.status[param] for param in MessageRequest.params): self.status["done"] = True return self.status["done"]
python
def poll(self): """If the message request has a priority of 2, Pushover keeps sending the same notification until the client acknowledges it. Calling the :func:`poll` function fetches the status of the :class:`MessageRequest` object until the notifications either expires, is acknowledged by the client, or the callback url is reached. The status is available in the ``status`` dictionary. Returns ``True`` when the request has expired or been acknowledged and ``False`` otherwise so that a typical handling of a priority-2 notification can look like this:: request = p.message("Urgent!", priority=2, expire=120, retry=60) while not request.poll(): # do something time.sleep(5) print request.status """ if not self.status["done"]: r = Request("get", self.url + ".json", {"token": self.payload["token"]}) for param, when in MessageRequest.params.iteritems(): self.status[param] = bool(r.answer[param]) self.status[when] = int(r.answer[when]) for param in ["acknowledged_by", "acknowledged_by_device"]: self.status[param] = r.answer[param] self.status["last_delivered_at"] = int(r.answer["last_delivered_at"]) if any(self.status[param] for param in MessageRequest.params): self.status["done"] = True return self.status["done"]
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train
https://github.com/Thibauth/python-pushover/blob/420bde9a2bd7981b5ea8f0c1cb8875d5f676f368/pushover.py#L90-L119
Thibauth/python-pushover
pushover.py
Pushover.sounds
def sounds(self): """Return a dictionary of sounds recognized by Pushover and that can be used in a notification message. """ if not Pushover._SOUNDS: request = Request("get", SOUND_URL, {"token": self.token}) Pushover._SOUNDS = request.answer["sounds"] return Pushover._SOUNDS
python
def sounds(self): """Return a dictionary of sounds recognized by Pushover and that can be used in a notification message. """ if not Pushover._SOUNDS: request = Request("get", SOUND_URL, {"token": self.token}) Pushover._SOUNDS = request.answer["sounds"] return Pushover._SOUNDS
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train
https://github.com/Thibauth/python-pushover/blob/420bde9a2bd7981b5ea8f0c1cb8875d5f676f368/pushover.py#L163-L170
Thibauth/python-pushover
pushover.py
Pushover.verify
def verify(self, user, device=None): """Verify that the `user` and optional `device` exist. Returns `None` when the user/device does not exist or a list of the user's devices otherwise. """ payload = {"user": user, "token": self.token} if device: payload["device"] = device try: request = Request("post", USER_URL, payload) except RequestError: return None else: return request.answer["devices"]
python
def verify(self, user, device=None): """Verify that the `user` and optional `device` exist. Returns `None` when the user/device does not exist or a list of the user's devices otherwise. """ payload = {"user": user, "token": self.token} if device: payload["device"] = device try: request = Request("post", USER_URL, payload) except RequestError: return None else: return request.answer["devices"]
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train
https://github.com/Thibauth/python-pushover/blob/420bde9a2bd7981b5ea8f0c1cb8875d5f676f368/pushover.py#L172-L185
Thibauth/python-pushover
pushover.py
Pushover.message
def message(self, user, message, **kwargs): """Send `message` to the user specified by `user`. It is possible to specify additional properties of the message by passing keyword arguments. The list of valid keywords is ``title, priority, sound, callback, timestamp, url, url_title, device, retry, expire and html`` which are described in the Pushover API documentation. For convenience, you can simply set ``timestamp=True`` to set the timestamp to the current timestamp. An image can be attached to a message by passing a file-like object to the `attachment` keyword argument. This method returns a :class:`MessageRequest` object. """ payload = {"message": message, "user": user, "token": self.token} for key, value in kwargs.iteritems(): if key not in Pushover.message_keywords: raise ValueError("{0}: invalid message parameter".format(key)) elif key == "timestamp" and value is True: payload[key] = int(time.time()) elif key == "sound" and value not in self.sounds: raise ValueError("{0}: invalid sound".format(value)) else: payload[key] = value return MessageRequest(payload)
python
def message(self, user, message, **kwargs): """Send `message` to the user specified by `user`. It is possible to specify additional properties of the message by passing keyword arguments. The list of valid keywords is ``title, priority, sound, callback, timestamp, url, url_title, device, retry, expire and html`` which are described in the Pushover API documentation. For convenience, you can simply set ``timestamp=True`` to set the timestamp to the current timestamp. An image can be attached to a message by passing a file-like object to the `attachment` keyword argument. This method returns a :class:`MessageRequest` object. """ payload = {"message": message, "user": user, "token": self.token} for key, value in kwargs.iteritems(): if key not in Pushover.message_keywords: raise ValueError("{0}: invalid message parameter".format(key)) elif key == "timestamp" and value is True: payload[key] = int(time.time()) elif key == "sound" and value not in self.sounds: raise ValueError("{0}: invalid sound".format(value)) else: payload[key] = value return MessageRequest(payload)
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train
https://github.com/Thibauth/python-pushover/blob/420bde9a2bd7981b5ea8f0c1cb8875d5f676f368/pushover.py#L187-L214
Thibauth/python-pushover
pushover.py
Pushover.glance
def glance(self, user, **kwargs): """Send a glance to the user. The default property is ``text``, as this is used on most glances, however a valid glance does not need to require text and can be constructed using any combination of valid keyword properties. The list of valid keywords is ``title, text, subtext, count, percent and device`` which are described in the Pushover Glance API documentation. This method returns a :class:`GlanceRequest` object. """ payload = {"user": user, "token": self.token} for key, value in kwargs.iteritems(): if key not in Pushover.glance_keywords: raise ValueError("{0}: invalid glance parameter".format(key)) else: payload[key] = value return Request("post", GLANCE_URL, payload)
python
def glance(self, user, **kwargs): """Send a glance to the user. The default property is ``text``, as this is used on most glances, however a valid glance does not need to require text and can be constructed using any combination of valid keyword properties. The list of valid keywords is ``title, text, subtext, count, percent and device`` which are described in the Pushover Glance API documentation. This method returns a :class:`GlanceRequest` object. """ payload = {"user": user, "token": self.token} for key, value in kwargs.iteritems(): if key not in Pushover.glance_keywords: raise ValueError("{0}: invalid glance parameter".format(key)) else: payload[key] = value return Request("post", GLANCE_URL, payload)
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Send a glance to the user. The default property is ``text``, as this is used on most glances, however a valid glance does not need to require text and can be constructed using any combination of valid keyword properties. The list of valid keywords is ``title, text, subtext, count, percent and device`` which are described in the Pushover Glance API documentation. This method returns a :class:`GlanceRequest` object.
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train
https://github.com/Thibauth/python-pushover/blob/420bde9a2bd7981b5ea8f0c1cb8875d5f676f368/pushover.py#L216-L234
Wramberg/adaptfilt
adaptfilt/misc.py
mswe
def mswe(w, v): """ Calculate mean squared weight error between estimated and true filter coefficients, in respect to iterations. Parameters ---------- v : array-like True coefficients used to generate desired signal, must be a one-dimensional array. w : array-like Estimated coefficients from adaptive filtering algorithm. Must be an N x M matrix where N is the number of iterations, and M is the number of filter coefficients. Returns ------- mswe : numpy.array One-dimensional array containing the mean-squared weight error for every iteration. Raises ------ TypeError If inputs have wrong dimensions Note ---- To use this function with the adaptive filter functions set the optional parameter returnCoeffs to True. This will return a coefficient matrix w corresponding with the input-parameter w. """ # Ensure inputs are numpy arrays w = np.array(w) v = np.array(v) # Check dimensions if(len(w.shape) != 2): raise TypeError('Estimated coefficients must be in NxM matrix') if(len(v.shape) != 1): raise TypeError('Real coefficients must be in 1d array') # Ensure equal length between estimated and real coeffs N, M = w.shape L = v.size if(M < L): v = v[:-(L-M)] elif(M > L): v = np.concatenate((v, np.zeros(M-L))) # Calculate and return MSWE mswe = np.mean((w - v)**2, axis=1) return mswe
python
def mswe(w, v): """ Calculate mean squared weight error between estimated and true filter coefficients, in respect to iterations. Parameters ---------- v : array-like True coefficients used to generate desired signal, must be a one-dimensional array. w : array-like Estimated coefficients from adaptive filtering algorithm. Must be an N x M matrix where N is the number of iterations, and M is the number of filter coefficients. Returns ------- mswe : numpy.array One-dimensional array containing the mean-squared weight error for every iteration. Raises ------ TypeError If inputs have wrong dimensions Note ---- To use this function with the adaptive filter functions set the optional parameter returnCoeffs to True. This will return a coefficient matrix w corresponding with the input-parameter w. """ # Ensure inputs are numpy arrays w = np.array(w) v = np.array(v) # Check dimensions if(len(w.shape) != 2): raise TypeError('Estimated coefficients must be in NxM matrix') if(len(v.shape) != 1): raise TypeError('Real coefficients must be in 1d array') # Ensure equal length between estimated and real coeffs N, M = w.shape L = v.size if(M < L): v = v[:-(L-M)] elif(M > L): v = np.concatenate((v, np.zeros(M-L))) # Calculate and return MSWE mswe = np.mean((w - v)**2, axis=1) return mswe
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Calculate mean squared weight error between estimated and true filter coefficients, in respect to iterations. Parameters ---------- v : array-like True coefficients used to generate desired signal, must be a one-dimensional array. w : array-like Estimated coefficients from adaptive filtering algorithm. Must be an N x M matrix where N is the number of iterations, and M is the number of filter coefficients. Returns ------- mswe : numpy.array One-dimensional array containing the mean-squared weight error for every iteration. Raises ------ TypeError If inputs have wrong dimensions Note ---- To use this function with the adaptive filter functions set the optional parameter returnCoeffs to True. This will return a coefficient matrix w corresponding with the input-parameter w.
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train
https://github.com/Wramberg/adaptfilt/blob/9bb943bb5e4162e10a8aaabfc68339b8fc06c11a/adaptfilt/misc.py#L7-L57
Wramberg/adaptfilt
adaptfilt/nlms.py
nlms
def nlms(u, d, M, step, eps=0.001, leak=0, initCoeffs=None, N=None, returnCoeffs=False): """ Perform normalized least-mean-squares (NLMS) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True """ # Check epsilon _pchk.checkRegFactor(eps) # Num taps check _pchk.checkNumTaps(M) # Max iteration check if N is None: N = len(u)-M+1 _pchk.checkIter(N, len(u)-M+1) # Check len(d) _pchk.checkDesiredSignal(d, N, M) # Step check _pchk.checkStep(step) # Leakage check _pchk.checkLeakage(leak) # Init. coeffs check if initCoeffs is None: initCoeffs = np.zeros(M) else: _pchk.checkInitCoeffs(initCoeffs, M) # Initialization y = np.zeros(N) # Filter output e = np.zeros(N) # Error signal w = initCoeffs # Initial filter coeffs leakstep = (1 - step*leak) if returnCoeffs: W = np.zeros((N, M)) # Matrix to hold coeffs for each iteration # Perform filtering for n in xrange(N): x = np.flipud(u[n:n+M]) # Slice to get view of M latest datapoints y[n] = np.dot(x, w) e[n] = d[n+M-1] - y[n] normFactor = 1./(np.dot(x, x) + eps) w = leakstep * w + step * normFactor * x * e[n] y[n] = np.dot(x, w) if returnCoeffs: W[n] = w if returnCoeffs: w = W return y, e, w
python
def nlms(u, d, M, step, eps=0.001, leak=0, initCoeffs=None, N=None, returnCoeffs=False): """ Perform normalized least-mean-squares (NLMS) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True """ # Check epsilon _pchk.checkRegFactor(eps) # Num taps check _pchk.checkNumTaps(M) # Max iteration check if N is None: N = len(u)-M+1 _pchk.checkIter(N, len(u)-M+1) # Check len(d) _pchk.checkDesiredSignal(d, N, M) # Step check _pchk.checkStep(step) # Leakage check _pchk.checkLeakage(leak) # Init. coeffs check if initCoeffs is None: initCoeffs = np.zeros(M) else: _pchk.checkInitCoeffs(initCoeffs, M) # Initialization y = np.zeros(N) # Filter output e = np.zeros(N) # Error signal w = initCoeffs # Initial filter coeffs leakstep = (1 - step*leak) if returnCoeffs: W = np.zeros((N, M)) # Matrix to hold coeffs for each iteration # Perform filtering for n in xrange(N): x = np.flipud(u[n:n+M]) # Slice to get view of M latest datapoints y[n] = np.dot(x, w) e[n] = d[n+M-1] - y[n] normFactor = 1./(np.dot(x, x) + eps) w = leakstep * w + step * normFactor * x * e[n] y[n] = np.dot(x, w) if returnCoeffs: W[n] = w if returnCoeffs: w = W return y, e, w
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Perform normalized least-mean-squares (NLMS) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> y, e, w = nlms(u, d, M, step, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True
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train
https://github.com/Wramberg/adaptfilt/blob/9bb943bb5e4162e10a8aaabfc68339b8fc06c11a/adaptfilt/nlms.py#L5-L154
Wramberg/adaptfilt
adaptfilt/ap.py
ap
def ap(u, d, M, step, K, eps=0.001, leak=0, initCoeffs=None, N=None, returnCoeffs=False): """ Perform affine projection (AP) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. K : int Projection order, must be integer larger than zero. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note: len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True """ # Check epsilon _pchk.checkRegFactor(eps) # Check projection order _pchk.checkProjectOrder(K) # Num taps check _pchk.checkNumTaps(M) # Max iteration check if N is None: N = len(u)-M-K+1 _pchk.checkIter(N, len(u)-M+1) # Check len(d) _pchk.checkDesiredSignal(d, N, M) # Step check _pchk.checkStep(step) # Leakage check _pchk.checkLeakage(leak) # Init. coeffs check if initCoeffs is None: initCoeffs = np.zeros(M) else: _pchk.checkInitCoeffs(initCoeffs, M) # Initialization y_out = np.zeros(N) # Filter output e_out = np.zeros(N) # Error signal w = initCoeffs # Initial filter coeffs I = np.identity(K) # Init. identity matrix for faster loop matrix inv. epsI = eps * np.identity(K) # Init. epsilon identiy matrix leakstep = (1 - step*leak) if returnCoeffs: W = np.zeros((N, M)) # Matrix to hold coeffs for each iteration # Perform filtering for n in xrange(N): # Generate U matrix and D vector with current data U = np.zeros((M, K)) for k in np.arange(K): U[:, (K-k-1)] = u[n+k:n+M+k] U = np.flipud(U) D = np.flipud(d[n+M-1:n+M+K-1]) # Filter y = np.dot(U.T, w) e = D - y y_out[n] = y[0] e_out[n] = e[0] # Normalization factor normFactor = np.linalg.solve(epsI + np.dot(U.T, U), I) # Naive alternative # normFactor = np.linalg.inv(epsI + np.dot(U.T, U)) w = leakstep * w + step * np.dot(U, np.dot(normFactor, e)) if returnCoeffs: W[n] = w if returnCoeffs: w = W return y_out, e_out, w
python
def ap(u, d, M, step, K, eps=0.001, leak=0, initCoeffs=None, N=None, returnCoeffs=False): """ Perform affine projection (AP) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. K : int Projection order, must be integer larger than zero. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note: len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True """ # Check epsilon _pchk.checkRegFactor(eps) # Check projection order _pchk.checkProjectOrder(K) # Num taps check _pchk.checkNumTaps(M) # Max iteration check if N is None: N = len(u)-M-K+1 _pchk.checkIter(N, len(u)-M+1) # Check len(d) _pchk.checkDesiredSignal(d, N, M) # Step check _pchk.checkStep(step) # Leakage check _pchk.checkLeakage(leak) # Init. coeffs check if initCoeffs is None: initCoeffs = np.zeros(M) else: _pchk.checkInitCoeffs(initCoeffs, M) # Initialization y_out = np.zeros(N) # Filter output e_out = np.zeros(N) # Error signal w = initCoeffs # Initial filter coeffs I = np.identity(K) # Init. identity matrix for faster loop matrix inv. epsI = eps * np.identity(K) # Init. epsilon identiy matrix leakstep = (1 - step*leak) if returnCoeffs: W = np.zeros((N, M)) # Matrix to hold coeffs for each iteration # Perform filtering for n in xrange(N): # Generate U matrix and D vector with current data U = np.zeros((M, K)) for k in np.arange(K): U[:, (K-k-1)] = u[n+k:n+M+k] U = np.flipud(U) D = np.flipud(d[n+M-1:n+M+K-1]) # Filter y = np.dot(U.T, w) e = D - y y_out[n] = y[0] e_out[n] = e[0] # Normalization factor normFactor = np.linalg.solve(epsI + np.dot(U.T, U), I) # Naive alternative # normFactor = np.linalg.inv(epsI + np.dot(U.T, U)) w = leakstep * w + step * np.dot(U, np.dot(normFactor, e)) if returnCoeffs: W[n] = w if returnCoeffs: w = W return y_out, e_out, w
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Perform affine projection (AP) adaptive filtering on u to minimize error given by e=d-y, where y is the output of the adaptive filter. Parameters ---------- u : array-like One-dimensional filter input. d : array-like One-dimensional desired signal, i.e., the output of the unknown FIR system which the adaptive filter should identify. Must have length >= len(u), or N+M-1 if number of iterations are limited (via the N parameter). M : int Desired number of filter taps (desired filter order + 1), must be non-negative. step : float Step size of the algorithm, must be non-negative. K : int Projection order, must be integer larger than zero. Optional Parameters ------------------- eps : float Regularization factor to avoid numerical issues when power of input is close to zero. Defaults to 0.001. Must be non-negative. leak : float Leakage factor, must be equal to or greater than zero and smaller than one. When greater than zero a leaky LMS filter is used. Defaults to 0, i.e., no leakage. initCoeffs : array-like Initial filter coefficients to use. Should match desired number of filter taps, defaults to zeros. N : int Number of iterations to run. Must be less than or equal to len(u)-M+1. Defaults to len(u)-M+1. returnCoeffs : boolean If true, will return all filter coefficients for every iteration in an N x M matrix. Does not include the initial coefficients. If false, only the latest coefficients in a vector of length M is returned. Defaults to false. Returns ------- y : numpy.array Output values of LMS filter, array of length N. e : numpy.array Error signal, i.e, d-y. Array of length N. w : numpy.array Final filter coefficients in array of length M if returnCoeffs is False. NxM array containing all filter coefficients for all iterations otherwise. Raises ------ TypeError If number of filter taps M is not type integer, number of iterations N is not type integer, or leakage leak is not type float/int. ValueError If number of iterations N is greater than len(u)-M, number of filter taps M is negative, or if step-size or leakage is outside specified range. Minimal Working Example ----------------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> ulen = 2000 >>> coeff = np.concatenate(([4], np.zeros(10), [-11], np.zeros(7), [0.7])) >>> u = np.random.randn(ulen) >>> d = np.convolve(u, coeff) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K) >>> print np.allclose(w, coeff) True Extended Example ---------------- >>> import numpy as np >>> >>> np.random.seed(1337) >>> N = 1000 >>> coeffs = np.concatenate(([13], np.zeros(9), [-3], np.zeros(8), [-.2])) >>> u = np.random.randn(20000) # Note: len(u) >> N but we limit iterations >>> d = np.convolve(u, coeffs) >>> >>> M = 20 # No. of taps >>> step = 1 # Step size >>> K = 5 # Projection order >>> y, e, w = ap(u, d, M, step, K, N=N, returnCoeffs=True) >>> y.shape == (N,) True >>> e.shape == (N,) True >>> w.shape == (N, M) True >>> # Calculate mean square weight error >>> mswe = np.mean((w - coeffs)**2, axis=1) >>> # Should never increase so diff should above be > 0 >>> diff = np.diff(mswe) >>> (diff <= 1e-10).all() True
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train
https://github.com/Wramberg/adaptfilt/blob/9bb943bb5e4162e10a8aaabfc68339b8fc06c11a/adaptfilt/ap.py#L5-L176
vmalyi/adb_android
adb_android/adb_android.py
bugreport
def bugreport(dest_file="default.log"): """ Prints dumpsys, dumpstate, and logcat data to the screen, for the purposes of bug reporting :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_BUGREPORT] try: dest_file_handler = open(dest_file, "w") except IOError: print("IOError: Failed to create a log file") # We have to check if device is available or not before executing this command # as adb bugreport will wait-for-device infinitely and does not come out of # loop # Execute only if device is available only if _isDeviceAvailable(): result = _exec_command_to_file(adb_full_cmd, dest_file_handler) return (result, "Success: Bug report saved to: " + dest_file) else: return (0, "Device Not Found")
python
def bugreport(dest_file="default.log"): """ Prints dumpsys, dumpstate, and logcat data to the screen, for the purposes of bug reporting :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_BUGREPORT] try: dest_file_handler = open(dest_file, "w") except IOError: print("IOError: Failed to create a log file") # We have to check if device is available or not before executing this command # as adb bugreport will wait-for-device infinitely and does not come out of # loop # Execute only if device is available only if _isDeviceAvailable(): result = _exec_command_to_file(adb_full_cmd, dest_file_handler) return (result, "Success: Bug report saved to: " + dest_file) else: return (0, "Device Not Found")
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L28-L47
vmalyi/adb_android
adb_android/adb_android.py
push
def push(src, dest): """ Push object from host to target :param src: string path to source object on host :param dest: string destination path on target :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_PUSH, src, dest] return _exec_command(adb_full_cmd)
python
def push(src, dest): """ Push object from host to target :param src: string path to source object on host :param dest: string destination path on target :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_PUSH, src, dest] return _exec_command(adb_full_cmd)
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L50-L58
vmalyi/adb_android
adb_android/adb_android.py
pull
def pull(src, dest): """ Pull object from target to host :param src: string path of object on target :param dest: string destination path on host :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_PULL, src, dest] return _exec_command(adb_full_cmd)
python
def pull(src, dest): """ Pull object from target to host :param src: string path of object on target :param dest: string destination path on host :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_PULL, src, dest] return _exec_command(adb_full_cmd)
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Pull object from target to host :param src: string path of object on target :param dest: string destination path on host :return: result of _exec_command() execution
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L61-L69
vmalyi/adb_android
adb_android/adb_android.py
devices
def devices(opts=[]): """ Get list of all available devices including emulators :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_DEVICES, _convert_opts(opts)] return _exec_command(adb_full_cmd)
python
def devices(opts=[]): """ Get list of all available devices including emulators :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_DEVICES, _convert_opts(opts)] return _exec_command(adb_full_cmd)
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L72-L79
vmalyi/adb_android
adb_android/adb_android.py
shell
def shell(cmd): """ Execute shell command on target :param cmd: string shell command to execute :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_SHELL, cmd] return _exec_command(adb_full_cmd)
python
def shell(cmd): """ Execute shell command on target :param cmd: string shell command to execute :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_SHELL, cmd] return _exec_command(adb_full_cmd)
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L82-L89
vmalyi/adb_android
adb_android/adb_android.py
install
def install(apk, opts=[]): """ Install *.apk on target :param apk: string path to apk on host to install :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_INSTALL, _convert_opts(opts), apk] return _exec_command(adb_full_cmd)
python
def install(apk, opts=[]): """ Install *.apk on target :param apk: string path to apk on host to install :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_INSTALL, _convert_opts(opts), apk] return _exec_command(adb_full_cmd)
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Install *.apk on target :param apk: string path to apk on host to install :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L92-L100
vmalyi/adb_android
adb_android/adb_android.py
uninstall
def uninstall(app, opts=[]): """ Uninstall app from target :param app: app name to uninstall from target (e.g. "com.example.android.valid") :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_UNINSTALL, _convert_opts(opts), app] return _exec_command(adb_full_cmd)
python
def uninstall(app, opts=[]): """ Uninstall app from target :param app: app name to uninstall from target (e.g. "com.example.android.valid") :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_UNINSTALL, _convert_opts(opts), app] return _exec_command(adb_full_cmd)
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Uninstall app from target :param app: app name to uninstall from target (e.g. "com.example.android.valid") :param opts: list command options (e.g. ["-r", "-a"]) :return: result of _exec_command() execution
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L103-L111
vmalyi/adb_android
adb_android/adb_android.py
sync
def sync(): """ Copy host->device only if changed :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_SHELL ,v.ADB_COMMAND_SYNC] return _exec_command(adb_full_cmd)
python
def sync(): """ Copy host->device only if changed :return: result of _exec_command() execution """ adb_full_cmd = [v.ADB_COMMAND_PREFIX, v.ADB_COMMAND_SHELL ,v.ADB_COMMAND_SYNC] return _exec_command(adb_full_cmd)
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Copy host->device only if changed :return: result of _exec_command() execution
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L132-L138
vmalyi/adb_android
adb_android/adb_android.py
_exec_command
def _exec_command(adb_cmd): """ Format adb command and execute it in shell :param adb_cmd: list adb command to execute :return: string '0' and shell command output if successful, otherwise raise CalledProcessError exception and return error code """ t = tempfile.TemporaryFile() final_adb_cmd = [] for e in adb_cmd: if e != '': # avoid items with empty string... final_adb_cmd.append(e) # ... so that final command doesn't # contain extra spaces print('\n*** Executing ' + ' '.join(adb_cmd) + ' ' + 'command') try: output = check_output(final_adb_cmd, stderr=t) except CalledProcessError as e: t.seek(0) result = e.returncode, t.read() else: result = 0, output print('\n' + result[1]) return result
python
def _exec_command(adb_cmd): """ Format adb command and execute it in shell :param adb_cmd: list adb command to execute :return: string '0' and shell command output if successful, otherwise raise CalledProcessError exception and return error code """ t = tempfile.TemporaryFile() final_adb_cmd = [] for e in adb_cmd: if e != '': # avoid items with empty string... final_adb_cmd.append(e) # ... so that final command doesn't # contain extra spaces print('\n*** Executing ' + ' '.join(adb_cmd) + ' ' + 'command') try: output = check_output(final_adb_cmd, stderr=t) except CalledProcessError as e: t.seek(0) result = e.returncode, t.read() else: result = 0, output print('\n' + result[1]) return result
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L178-L202
vmalyi/adb_android
adb_android/adb_android.py
_exec_command_to_file
def _exec_command_to_file(adb_cmd, dest_file_handler): """ Format adb command and execute it in shell and redirects to a file :param adb_cmd: list adb command to execute :param dest_file_handler: file handler to which output will be redirected :return: string '0' and writes shell command output to file if successful, otherwise raise CalledProcessError exception and return error code """ t = tempfile.TemporaryFile() final_adb_cmd = [] for e in adb_cmd: if e != '': # avoid items with empty string... final_adb_cmd.append(e) # ... so that final command doesn't # contain extra spaces print('\n*** Executing ' + ' '.join(adb_cmd) + ' ' + 'command') try: output = call(final_adb_cmd, stdout=dest_file_handler, stderr=t) except CalledProcessError as e: t.seek(0) result = e.returncode, t.read() else: result = output dest_file_handler.close() return result
python
def _exec_command_to_file(adb_cmd, dest_file_handler): """ Format adb command and execute it in shell and redirects to a file :param adb_cmd: list adb command to execute :param dest_file_handler: file handler to which output will be redirected :return: string '0' and writes shell command output to file if successful, otherwise raise CalledProcessError exception and return error code """ t = tempfile.TemporaryFile() final_adb_cmd = [] for e in adb_cmd: if e != '': # avoid items with empty string... final_adb_cmd.append(e) # ... so that final command doesn't # contain extra spaces print('\n*** Executing ' + ' '.join(adb_cmd) + ' ' + 'command') try: output = call(final_adb_cmd, stdout=dest_file_handler, stderr=t) except CalledProcessError as e: t.seek(0) result = e.returncode, t.read() else: result = output dest_file_handler.close() return result
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train
https://github.com/vmalyi/adb_android/blob/de53dc54f27b14dc8c2ae64b136a60a59e1a1cb1/adb_android/adb_android.py#L205-L230
mlavin/django-selectable
selectable/forms/fields.py
BaseAutoCompleteField.has_changed
def has_changed(self, initial, data): "Detects if the data was changed. This is added in 1.6." if initial is None and data is None: return False if data and not hasattr(data, '__iter__'): data = self.widget.decompress(data) initial = self.to_python(initial) data = self.to_python(data) if hasattr(self, '_coerce'): data = self._coerce(data) if isinstance(data, Model) and isinstance(initial, Model): return model_vars(data) != model_vars(initial) else: return data != initial
python
def has_changed(self, initial, data): "Detects if the data was changed. This is added in 1.6." if initial is None and data is None: return False if data and not hasattr(data, '__iter__'): data = self.widget.decompress(data) initial = self.to_python(initial) data = self.to_python(data) if hasattr(self, '_coerce'): data = self._coerce(data) if isinstance(data, Model) and isinstance(initial, Model): return model_vars(data) != model_vars(initial) else: return data != initial
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Detects if the data was changed. This is added in 1.6.
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/forms/fields.py#L29-L42
mlavin/django-selectable
selectable/decorators.py
results_decorator
def results_decorator(func): """ Helper for constructing simple decorators around Lookup.results. func is a function which takes a request as the first parameter. If func returns an HttpReponse it is returned otherwise the original Lookup.results is returned. """ # Wrap function to maintian the original doc string, etc @wraps(func) def decorator(lookup_cls): # Construct a class decorator from the original function original = lookup_cls.results def inner(self, request): # Wrap lookup_cls.results by first calling func and checking the result result = func(request) if isinstance(result, HttpResponse): return result return original(self, request) # Replace original lookup_cls.results with wrapped version lookup_cls.results = inner return lookup_cls # Return the constructed decorator return decorator
python
def results_decorator(func): """ Helper for constructing simple decorators around Lookup.results. func is a function which takes a request as the first parameter. If func returns an HttpReponse it is returned otherwise the original Lookup.results is returned. """ # Wrap function to maintian the original doc string, etc @wraps(func) def decorator(lookup_cls): # Construct a class decorator from the original function original = lookup_cls.results def inner(self, request): # Wrap lookup_cls.results by first calling func and checking the result result = func(request) if isinstance(result, HttpResponse): return result return original(self, request) # Replace original lookup_cls.results with wrapped version lookup_cls.results = inner return lookup_cls # Return the constructed decorator return decorator
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/decorators.py#L16-L39
mlavin/django-selectable
selectable/decorators.py
login_required
def login_required(request): "Lookup decorator to require the user to be authenticated." user = getattr(request, 'user', None) if user is None or not user.is_authenticated: return HttpResponse(status=401)
python
def login_required(request): "Lookup decorator to require the user to be authenticated." user = getattr(request, 'user', None) if user is None or not user.is_authenticated: return HttpResponse(status=401)
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/decorators.py#L50-L54
mlavin/django-selectable
selectable/decorators.py
staff_member_required
def staff_member_required(request): "Lookup decorator to require the user is a staff member." user = getattr(request, 'user', None) if user is None or not user.is_authenticated: return HttpResponse(status=401) # Unauthorized elif not user.is_staff: return HttpResponseForbidden()
python
def staff_member_required(request): "Lookup decorator to require the user is a staff member." user = getattr(request, 'user', None) if user is None or not user.is_authenticated: return HttpResponse(status=401) # Unauthorized elif not user.is_staff: return HttpResponseForbidden()
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/decorators.py#L58-L64
mlavin/django-selectable
selectable/base.py
LookupBase.format_item
def format_item(self, item): "Construct result dictionary for the match item." result = { 'id': self.get_item_id(item), 'value': self.get_item_value(item), 'label': self.get_item_label(item), } for key in settings.SELECTABLE_ESCAPED_KEYS: if key in result: result[key] = conditional_escape(result[key]) return result
python
def format_item(self, item): "Construct result dictionary for the match item." result = { 'id': self.get_item_id(item), 'value': self.get_item_value(item), 'label': self.get_item_label(item), } for key in settings.SELECTABLE_ESCAPED_KEYS: if key in result: result[key] = conditional_escape(result[key]) return result
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Construct result dictionary for the match item.
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/base.py#L67-L77
mlavin/django-selectable
selectable/base.py
LookupBase.paginate_results
def paginate_results(self, results, options): "Return a django.core.paginator.Page of results." limit = options.get('limit', settings.SELECTABLE_MAX_LIMIT) paginator = Paginator(results, limit) page = options.get('page', 1) try: results = paginator.page(page) except (EmptyPage, InvalidPage): results = paginator.page(paginator.num_pages) return results
python
def paginate_results(self, results, options): "Return a django.core.paginator.Page of results." limit = options.get('limit', settings.SELECTABLE_MAX_LIMIT) paginator = Paginator(results, limit) page = options.get('page', 1) try: results = paginator.page(page) except (EmptyPage, InvalidPage): results = paginator.page(paginator.num_pages) return results
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Return a django.core.paginator.Page of results.
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/base.py#L79-L88
mlavin/django-selectable
selectable/base.py
LookupBase.results
def results(self, request): "Match results to given term and return the serialized HttpResponse." results = {} form = self.form(request.GET) if form.is_valid(): options = form.cleaned_data term = options.get('term', '') raw_data = self.get_query(request, term) results = self.format_results(raw_data, options) return self.response(results)
python
def results(self, request): "Match results to given term and return the serialized HttpResponse." results = {} form = self.form(request.GET) if form.is_valid(): options = form.cleaned_data term = options.get('term', '') raw_data = self.get_query(request, term) results = self.format_results(raw_data, options) return self.response(results)
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Match results to given term and return the serialized HttpResponse.
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/base.py#L90-L99
mlavin/django-selectable
selectable/base.py
LookupBase.format_results
def format_results(self, raw_data, options): ''' Returns a python structure that later gets serialized. raw_data full list of objects matching the search term options a dictionary of the given options ''' page_data = self.paginate_results(raw_data, options) results = {} meta = options.copy() meta['more'] = _('Show more results') if page_data and page_data.has_next(): meta['next_page'] = page_data.next_page_number() if page_data and page_data.has_previous(): meta['prev_page'] = page_data.previous_page_number() results['data'] = [self.format_item(item) for item in page_data.object_list] results['meta'] = meta return results
python
def format_results(self, raw_data, options): ''' Returns a python structure that later gets serialized. raw_data full list of objects matching the search term options a dictionary of the given options ''' page_data = self.paginate_results(raw_data, options) results = {} meta = options.copy() meta['more'] = _('Show more results') if page_data and page_data.has_next(): meta['next_page'] = page_data.next_page_number() if page_data and page_data.has_previous(): meta['prev_page'] = page_data.previous_page_number() results['data'] = [self.format_item(item) for item in page_data.object_list] results['meta'] = meta return results
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Returns a python structure that later gets serialized. raw_data full list of objects matching the search term options a dictionary of the given options
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/base.py#L101-L119
mlavin/django-selectable
selectable/forms/base.py
import_lookup_class
def import_lookup_class(lookup_class): """ Import lookup_class as a dotted base and ensure it extends LookupBase """ from selectable.base import LookupBase if isinstance(lookup_class, string_types): mod_str, cls_str = lookup_class.rsplit('.', 1) mod = import_module(mod_str) lookup_class = getattr(mod, cls_str) if not issubclass(lookup_class, LookupBase): raise TypeError('lookup_class must extend from selectable.base.LookupBase') return lookup_class
python
def import_lookup_class(lookup_class): """ Import lookup_class as a dotted base and ensure it extends LookupBase """ from selectable.base import LookupBase if isinstance(lookup_class, string_types): mod_str, cls_str = lookup_class.rsplit('.', 1) mod = import_module(mod_str) lookup_class = getattr(mod, cls_str) if not issubclass(lookup_class, LookupBase): raise TypeError('lookup_class must extend from selectable.base.LookupBase') return lookup_class
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Import lookup_class as a dotted base and ensure it extends LookupBase
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/forms/base.py#L34-L45
mlavin/django-selectable
selectable/forms/base.py
BaseLookupForm.clean_limit
def clean_limit(self): "Ensure given limit is less than default if defined" limit = self.cleaned_data.get('limit', None) if (settings.SELECTABLE_MAX_LIMIT is not None and (not limit or limit > settings.SELECTABLE_MAX_LIMIT)): limit = settings.SELECTABLE_MAX_LIMIT return limit
python
def clean_limit(self): "Ensure given limit is less than default if defined" limit = self.cleaned_data.get('limit', None) if (settings.SELECTABLE_MAX_LIMIT is not None and (not limit or limit > settings.SELECTABLE_MAX_LIMIT)): limit = settings.SELECTABLE_MAX_LIMIT return limit
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Ensure given limit is less than default if defined
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train
https://github.com/mlavin/django-selectable/blob/3d7b8db0526dd924a774c599f0c665eff98fb375/selectable/forms/base.py#L21-L27
desbma/sacad
sacad/sources/google_images.py
GoogleImagesWebScrapeCoverSource.getSearchUrl
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ # build request url params = collections.OrderedDict() params["gbv"] = "2" params["q"] = "\"%s\" \"%s\" front cover" % (artist, album) if abs(self.target_size - 500) < 300: params["tbs"] = "isz:m" elif self.target_size > 800: params["tbs"] = "isz:l" return __class__.assembleUrl(__class__.BASE_URL, params)
python
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ # build request url params = collections.OrderedDict() params["gbv"] = "2" params["q"] = "\"%s\" \"%s\" front cover" % (artist, album) if abs(self.target_size - 500) < 300: params["tbs"] = "isz:m" elif self.target_size > 800: params["tbs"] = "isz:l" return __class__.assembleUrl(__class__.BASE_URL, params)
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See CoverSource.getSearchUrl.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/google_images.py#L33-L44
desbma/sacad
sacad/sources/google_images.py
GoogleImagesWebScrapeCoverSource.parseResults
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse HTML and get results parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("latin-1"), parser) for rank, result in enumerate(__class__.RESULTS_SELECTOR(html), 1): # extract url metadata_div = result.find("div") metadata_json = lxml.etree.tostring(metadata_div, encoding="unicode", method="text") metadata_json = json.loads(metadata_json) google_url = result.find("a").get("href") if google_url is not None: query = urllib.parse.urlsplit(google_url).query else: query = None if not query: img_url = metadata_json["ou"] else: query = urllib.parse.parse_qs(query) img_url = query["imgurl"][0] # extract format check_metadata = CoverImageMetadata.NONE format = metadata_json["ity"].lower() try: format = SUPPORTED_IMG_FORMATS[format] except KeyError: # format could not be identified or is unknown format = None check_metadata = CoverImageMetadata.FORMAT # extract size if not query: size = metadata_json["ow"], metadata_json["oh"] else: size = tuple(map(int, (query["w"][0], query["h"][0]))) # extract thumbnail url thumbnail_url = metadata_json["tu"] # result results.append(GoogleImagesCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=check_metadata)) return results
python
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse HTML and get results parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("latin-1"), parser) for rank, result in enumerate(__class__.RESULTS_SELECTOR(html), 1): # extract url metadata_div = result.find("div") metadata_json = lxml.etree.tostring(metadata_div, encoding="unicode", method="text") metadata_json = json.loads(metadata_json) google_url = result.find("a").get("href") if google_url is not None: query = urllib.parse.urlsplit(google_url).query else: query = None if not query: img_url = metadata_json["ou"] else: query = urllib.parse.parse_qs(query) img_url = query["imgurl"][0] # extract format check_metadata = CoverImageMetadata.NONE format = metadata_json["ity"].lower() try: format = SUPPORTED_IMG_FORMATS[format] except KeyError: # format could not be identified or is unknown format = None check_metadata = CoverImageMetadata.FORMAT # extract size if not query: size = metadata_json["ow"], metadata_json["oh"] else: size = tuple(map(int, (query["w"][0], query["h"][0]))) # extract thumbnail url thumbnail_url = metadata_json["tu"] # result results.append(GoogleImagesCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=check_metadata)) return results
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/google_images.py#L50-L98
desbma/sacad
sacad/rate_watcher.py
AccessRateWatcher.waitAccessAsync
async def waitAccessAsync(self): """ Wait the needed time before sending a request to honor rate limit. """ async with self.lock: while True: last_access_ts = self.__getLastAccess() if last_access_ts is not None: now = time.time() last_access_ts = last_access_ts[0] time_since_last_access = now - last_access_ts if time_since_last_access < self.min_delay_between_accesses: time_to_wait = self.min_delay_between_accesses - time_since_last_access if self.jitter_range_ms is not None: time_to_wait += random.randint(*self.jitter_range_ms) / 1000 self.logger.debug("Sleeping for %.2fms because of rate limit for domain %s" % (time_to_wait * 1000, self.domain)) await asyncio.sleep(time_to_wait) access_time = time.time() self.__access(access_time) # now we should be good... except if another process did the same query at the same time # the database serves as an atomic lock, query again to be sure the last row is the one # we just inserted last_access_ts = self.__getLastAccess() if last_access_ts[0] == access_time: break
python
async def waitAccessAsync(self): """ Wait the needed time before sending a request to honor rate limit. """ async with self.lock: while True: last_access_ts = self.__getLastAccess() if last_access_ts is not None: now = time.time() last_access_ts = last_access_ts[0] time_since_last_access = now - last_access_ts if time_since_last_access < self.min_delay_between_accesses: time_to_wait = self.min_delay_between_accesses - time_since_last_access if self.jitter_range_ms is not None: time_to_wait += random.randint(*self.jitter_range_ms) / 1000 self.logger.debug("Sleeping for %.2fms because of rate limit for domain %s" % (time_to_wait * 1000, self.domain)) await asyncio.sleep(time_to_wait) access_time = time.time() self.__access(access_time) # now we should be good... except if another process did the same query at the same time # the database serves as an atomic lock, query again to be sure the last row is the one # we just inserted last_access_ts = self.__getLastAccess() if last_access_ts[0] == access_time: break
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/rate_watcher.py#L28-L53
desbma/sacad
sacad/rate_watcher.py
AccessRateWatcher.__access
def __access(self, ts): """ Record an API access. """ with self.connection: self.connection.execute("INSERT OR REPLACE INTO access_timestamp (timestamp, domain) VALUES (?, ?)", (ts, self.domain))
python
def __access(self, ts): """ Record an API access. """ with self.connection: self.connection.execute("INSERT OR REPLACE INTO access_timestamp (timestamp, domain) VALUES (?, ?)", (ts, self.domain))
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Record an API access.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/rate_watcher.py#L62-L66
desbma/sacad
sacad/http_helpers.py
aiohttp_socket_timeout
def aiohttp_socket_timeout(socket_timeout_s): """ Return a aiohttp.ClientTimeout object with only socket timeouts set. """ return aiohttp.ClientTimeout(total=None, connect=None, sock_connect=socket_timeout_s, sock_read=socket_timeout_s)
python
def aiohttp_socket_timeout(socket_timeout_s): """ Return a aiohttp.ClientTimeout object with only socket timeouts set. """ return aiohttp.ClientTimeout(total=None, connect=None, sock_connect=socket_timeout_s, sock_read=socket_timeout_s)
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Return a aiohttp.ClientTimeout object with only socket timeouts set.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/http_helpers.py#L15-L20
desbma/sacad
sacad/http_helpers.py
Http.query
async def query(self, url, *, post_data=None, headers=None, verify=True, cache=None, pre_cache_callback=None): """ Send a GET/POST request or get data from cache, retry if it fails, and return a tuple of store in cache callback, response content. """ async def store_in_cache_callback(): pass if cache is not None: # try from cache first if post_data is not None: if (url, post_data) in cache: self.logger.debug("Got data for URL '%s' %s from cache" % (url, dict(post_data))) return store_in_cache_callback, cache[(url, post_data)] elif url in cache: self.logger.debug("Got data for URL '%s' from cache" % (url)) return store_in_cache_callback, cache[url] domain_rate_watcher = rate_watcher.AccessRateWatcher(self.watcher_db_filepath, url, self.min_delay_between_accesses, jitter_range_ms=self.jitter_range_ms, logger=self.logger) for attempt, time_to_sleep in enumerate(redo.retrier(max_attempts=HTTP_MAX_ATTEMPTS, sleeptime=1, max_sleeptime=HTTP_MAX_RETRY_SLEEP_S, sleepscale=1.5), 1): await domain_rate_watcher.waitAccessAsync() try: if post_data is not None: async with self.session.post(url, data=post_data, headers=self._buildHeaders(headers), timeout=HTTP_NORMAL_TIMEOUT, ssl=verify) as response: content = await response.read() else: async with self.session.get(url, headers=self._buildHeaders(headers), timeout=HTTP_NORMAL_TIMEOUT, ssl=verify) as response: content = await response.read() if cache is not None: async def store_in_cache_callback(): if pre_cache_callback is not None: # process try: data = await pre_cache_callback(content) except Exception: data = content else: data = content # add to cache if post_data is not None: cache[(url, post_data)] = data else: cache[url] = data except (asyncio.TimeoutError, aiohttp.ClientError) as e: self.logger.warning("Querying '%s' failed (attempt %u/%u): %s %s" % (url, attempt, HTTP_MAX_ATTEMPTS, e.__class__.__qualname__, e)) if attempt == HTTP_MAX_ATTEMPTS: raise else: self.logger.debug("Retrying in %.3fs" % (time_to_sleep)) await asyncio.sleep(time_to_sleep) else: break # http retry loop response.raise_for_status() return store_in_cache_callback, content
python
async def query(self, url, *, post_data=None, headers=None, verify=True, cache=None, pre_cache_callback=None): """ Send a GET/POST request or get data from cache, retry if it fails, and return a tuple of store in cache callback, response content. """ async def store_in_cache_callback(): pass if cache is not None: # try from cache first if post_data is not None: if (url, post_data) in cache: self.logger.debug("Got data for URL '%s' %s from cache" % (url, dict(post_data))) return store_in_cache_callback, cache[(url, post_data)] elif url in cache: self.logger.debug("Got data for URL '%s' from cache" % (url)) return store_in_cache_callback, cache[url] domain_rate_watcher = rate_watcher.AccessRateWatcher(self.watcher_db_filepath, url, self.min_delay_between_accesses, jitter_range_ms=self.jitter_range_ms, logger=self.logger) for attempt, time_to_sleep in enumerate(redo.retrier(max_attempts=HTTP_MAX_ATTEMPTS, sleeptime=1, max_sleeptime=HTTP_MAX_RETRY_SLEEP_S, sleepscale=1.5), 1): await domain_rate_watcher.waitAccessAsync() try: if post_data is not None: async with self.session.post(url, data=post_data, headers=self._buildHeaders(headers), timeout=HTTP_NORMAL_TIMEOUT, ssl=verify) as response: content = await response.read() else: async with self.session.get(url, headers=self._buildHeaders(headers), timeout=HTTP_NORMAL_TIMEOUT, ssl=verify) as response: content = await response.read() if cache is not None: async def store_in_cache_callback(): if pre_cache_callback is not None: # process try: data = await pre_cache_callback(content) except Exception: data = content else: data = content # add to cache if post_data is not None: cache[(url, post_data)] = data else: cache[url] = data except (asyncio.TimeoutError, aiohttp.ClientError) as e: self.logger.warning("Querying '%s' failed (attempt %u/%u): %s %s" % (url, attempt, HTTP_MAX_ATTEMPTS, e.__class__.__qualname__, e)) if attempt == HTTP_MAX_ATTEMPTS: raise else: self.logger.debug("Retrying in %.3fs" % (time_to_sleep)) await asyncio.sleep(time_to_sleep) else: break # http retry loop response.raise_for_status() return store_in_cache_callback, content
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Send a GET/POST request or get data from cache, retry if it fails, and return a tuple of store in cache callback, response content.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/http_helpers.py#L52-L128
desbma/sacad
sacad/http_helpers.py
Http.isReachable
async def isReachable(self, url, *, headers=None, verify=True, response_headers=None, cache=None): """ Send a HEAD request with short timeout or get data from cache, return True if ressource has 2xx status code, False instead. """ if (cache is not None) and (url in cache): # try from cache first self.logger.debug("Got headers for URL '%s' from cache" % (url)) resp_ok, response_headers = pickle.loads(cache[url]) return resp_ok domain_rate_watcher = rate_watcher.AccessRateWatcher(self.watcher_db_filepath, url, self.min_delay_between_accesses, jitter_range_ms=self.jitter_range_ms, logger=self.logger) resp_ok = True try: for attempt, time_to_sleep in enumerate(redo.retrier(max_attempts=HTTP_MAX_ATTEMPTS, sleeptime=0.5, max_sleeptime=HTTP_MAX_RETRY_SLEEP_SHORT_S, sleepscale=1.5), 1): await domain_rate_watcher.waitAccessAsync() try: async with self.session.head(url, headers=self._buildHeaders(headers), timeout=HTTP_SHORT_TIMEOUT, ssl=verify) as response: pass except (asyncio.TimeoutError, aiohttp.ClientError) as e: self.logger.warning("Probing '%s' failed (attempt %u/%u): %s %s" % (url, attempt, HTTP_MAX_ATTEMPTS, e.__class__.__qualname__, e)) if attempt == HTTP_MAX_ATTEMPTS: resp_ok = False else: self.logger.debug("Retrying in %.3fs" % (time_to_sleep)) await asyncio.sleep(time_to_sleep) else: response.raise_for_status() if response_headers is not None: response_headers.update(response.headers) break # http retry loop except aiohttp.ClientResponseError as e: self.logger.debug("Probing '%s' failed: %s %s" % (url, e.__class__.__qualname__, e)) resp_ok = False if cache is not None: # store in cache cache[url] = pickle.dumps((resp_ok, response_headers)) return resp_ok
python
async def isReachable(self, url, *, headers=None, verify=True, response_headers=None, cache=None): """ Send a HEAD request with short timeout or get data from cache, return True if ressource has 2xx status code, False instead. """ if (cache is not None) and (url in cache): # try from cache first self.logger.debug("Got headers for URL '%s' from cache" % (url)) resp_ok, response_headers = pickle.loads(cache[url]) return resp_ok domain_rate_watcher = rate_watcher.AccessRateWatcher(self.watcher_db_filepath, url, self.min_delay_between_accesses, jitter_range_ms=self.jitter_range_ms, logger=self.logger) resp_ok = True try: for attempt, time_to_sleep in enumerate(redo.retrier(max_attempts=HTTP_MAX_ATTEMPTS, sleeptime=0.5, max_sleeptime=HTTP_MAX_RETRY_SLEEP_SHORT_S, sleepscale=1.5), 1): await domain_rate_watcher.waitAccessAsync() try: async with self.session.head(url, headers=self._buildHeaders(headers), timeout=HTTP_SHORT_TIMEOUT, ssl=verify) as response: pass except (asyncio.TimeoutError, aiohttp.ClientError) as e: self.logger.warning("Probing '%s' failed (attempt %u/%u): %s %s" % (url, attempt, HTTP_MAX_ATTEMPTS, e.__class__.__qualname__, e)) if attempt == HTTP_MAX_ATTEMPTS: resp_ok = False else: self.logger.debug("Retrying in %.3fs" % (time_to_sleep)) await asyncio.sleep(time_to_sleep) else: response.raise_for_status() if response_headers is not None: response_headers.update(response.headers) break # http retry loop except aiohttp.ClientResponseError as e: self.logger.debug("Probing '%s' failed: %s %s" % (url, e.__class__.__qualname__, e)) resp_ok = False if cache is not None: # store in cache cache[url] = pickle.dumps((resp_ok, response_headers)) return resp_ok
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Send a HEAD request with short timeout or get data from cache, return True if ressource has 2xx status code, False instead.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/http_helpers.py#L130-L187
desbma/sacad
sacad/http_helpers.py
Http.fastStreamedQuery
async def fastStreamedQuery(self, url, *, headers=None, verify=True): """ Send a GET request with short timeout, do not retry, and return streamed response. """ response = await self.session.get(url, headers=self._buildHeaders(headers), timeout=HTTP_SHORT_TIMEOUT, ssl=verify) response.raise_for_status() return response
python
async def fastStreamedQuery(self, url, *, headers=None, verify=True): """ Send a GET request with short timeout, do not retry, and return streamed response. """ response = await self.session.get(url, headers=self._buildHeaders(headers), timeout=HTTP_SHORT_TIMEOUT, ssl=verify) response.raise_for_status() return response
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Send a GET request with short timeout, do not retry, and return streamed response.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/http_helpers.py#L189-L198
desbma/sacad
sacad/sources/lastfm.py
LastFmCoverSource.getSearchUrl
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ # build request url params = collections.OrderedDict() params["method"] = "album.getinfo" params["api_key"] = __class__.API_KEY params["album"] = album params["artist"] = artist return __class__.assembleUrl(__class__.BASE_URL, params)
python
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ # build request url params = collections.OrderedDict() params["method"] = "album.getinfo" params["api_key"] = __class__.API_KEY params["album"] = album params["artist"] = artist return __class__.assembleUrl(__class__.BASE_URL, params)
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See CoverSource.getSearchUrl.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/lastfm.py#L36-L45
desbma/sacad
sacad/sources/lastfm.py
LastFmCoverSource.processQueryString
def processQueryString(self, s): """ See CoverSource.processQueryString. """ char_blacklist = set(string.punctuation) char_blacklist.remove("'") char_blacklist.remove("&") char_blacklist = frozenset(char_blacklist) return __class__.unpunctuate(s.lower(), char_blacklist=char_blacklist)
python
def processQueryString(self, s): """ See CoverSource.processQueryString. """ char_blacklist = set(string.punctuation) char_blacklist.remove("'") char_blacklist.remove("&") char_blacklist = frozenset(char_blacklist) return __class__.unpunctuate(s.lower(), char_blacklist=char_blacklist)
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See CoverSource.processQueryString.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/lastfm.py#L47-L53
desbma/sacad
sacad/sources/lastfm.py
LastFmCoverSource.parseResults
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # get xml results list xml_text = api_data.decode("utf-8") xml_root = xml.etree.ElementTree.fromstring(xml_text) status = xml_root.get("status") if status != "ok": raise Exception("Unexpected Last.fm response status: %s" % (status)) img_elements = xml_root.findall("album/image") # build results from xml thumbnail_url = None thumbnail_size = None for img_element in img_elements: img_url = img_element.text if not img_url: # last.fm returns empty image tag for size it does not have continue lfm_size = img_element.get("size") if lfm_size == "mega": check_metadata = CoverImageMetadata.SIZE else: check_metadata = CoverImageMetadata.NONE try: size = __class__.SIZES[lfm_size] except KeyError: continue if (size[0] <= MAX_THUMBNAIL_SIZE) and ((thumbnail_size is None) or (size[0] < thumbnail_size)): thumbnail_url = img_url thumbnail_size = size[0] format = os.path.splitext(img_url)[1][1:].lower() format = SUPPORTED_IMG_FORMATS[format] results.append(LastFmCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, check_metadata=check_metadata)) return results
python
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # get xml results list xml_text = api_data.decode("utf-8") xml_root = xml.etree.ElementTree.fromstring(xml_text) status = xml_root.get("status") if status != "ok": raise Exception("Unexpected Last.fm response status: %s" % (status)) img_elements = xml_root.findall("album/image") # build results from xml thumbnail_url = None thumbnail_size = None for img_element in img_elements: img_url = img_element.text if not img_url: # last.fm returns empty image tag for size it does not have continue lfm_size = img_element.get("size") if lfm_size == "mega": check_metadata = CoverImageMetadata.SIZE else: check_metadata = CoverImageMetadata.NONE try: size = __class__.SIZES[lfm_size] except KeyError: continue if (size[0] <= MAX_THUMBNAIL_SIZE) and ((thumbnail_size is None) or (size[0] < thumbnail_size)): thumbnail_url = img_url thumbnail_size = size[0] format = os.path.splitext(img_url)[1][1:].lower() format = SUPPORTED_IMG_FORMATS[format] results.append(LastFmCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, check_metadata=check_metadata)) return results
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See CoverSource.parseResults.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/lastfm.py#L55-L96
desbma/sacad
sacad/__init__.py
search_and_download
async def search_and_download(album, artist, format, size, out_filepath, *, size_tolerance_prct, amazon_tlds, no_lq_sources, async_loop): """ Search and download a cover, return True if success, False instead. """ # register sources source_args = (size, size_tolerance_prct) cover_sources = [sources.LastFmCoverSource(*source_args), sources.AmazonCdCoverSource(*source_args), sources.AmazonDigitalCoverSource(*source_args)] for tld in amazon_tlds: cover_sources.append(sources.AmazonCdCoverSource(*source_args, tld=tld)) if not no_lq_sources: cover_sources.append(sources.GoogleImagesWebScrapeCoverSource(*source_args)) # schedule search work search_futures = [] for cover_source in cover_sources: coroutine = cover_source.search(album, artist) future = asyncio.ensure_future(coroutine, loop=async_loop) search_futures.append(future) # wait for it await asyncio.wait(search_futures, loop=async_loop) # get results results = [] for future in search_futures: source_results = future.result() results.extend(source_results) # sort results results = await CoverSourceResult.preProcessForComparison(results, size, size_tolerance_prct) results.sort(reverse=True, key=functools.cmp_to_key(functools.partial(CoverSourceResult.compare, target_size=size, size_tolerance_prct=size_tolerance_prct))) if not results: logging.getLogger("Main").info("No results") # download for result in results: try: await result.get(format, size, size_tolerance_prct, out_filepath) except Exception as e: logging.getLogger("Main").warning("Download of %s failed: %s %s" % (result, e.__class__.__qualname__, e)) continue else: return True return False
python
async def search_and_download(album, artist, format, size, out_filepath, *, size_tolerance_prct, amazon_tlds, no_lq_sources, async_loop): """ Search and download a cover, return True if success, False instead. """ # register sources source_args = (size, size_tolerance_prct) cover_sources = [sources.LastFmCoverSource(*source_args), sources.AmazonCdCoverSource(*source_args), sources.AmazonDigitalCoverSource(*source_args)] for tld in amazon_tlds: cover_sources.append(sources.AmazonCdCoverSource(*source_args, tld=tld)) if not no_lq_sources: cover_sources.append(sources.GoogleImagesWebScrapeCoverSource(*source_args)) # schedule search work search_futures = [] for cover_source in cover_sources: coroutine = cover_source.search(album, artist) future = asyncio.ensure_future(coroutine, loop=async_loop) search_futures.append(future) # wait for it await asyncio.wait(search_futures, loop=async_loop) # get results results = [] for future in search_futures: source_results = future.result() results.extend(source_results) # sort results results = await CoverSourceResult.preProcessForComparison(results, size, size_tolerance_prct) results.sort(reverse=True, key=functools.cmp_to_key(functools.partial(CoverSourceResult.compare, target_size=size, size_tolerance_prct=size_tolerance_prct))) if not results: logging.getLogger("Main").info("No results") # download for result in results: try: await result.get(format, size, size_tolerance_prct, out_filepath) except Exception as e: logging.getLogger("Main").warning("Download of %s failed: %s %s" % (result, e.__class__.__qualname__, e)) continue else: return True return False
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Search and download a cover, return True if success, False instead.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/__init__.py#L20-L70
desbma/sacad
sacad/sources/amazondigital.py
AmazonDigitalCoverSource.getSearchUrl
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ url = "%s/search" % (__class__.BASE_URL) params = collections.OrderedDict() params["search-alias"] = "digital-music" params["field-keywords"] = " ".join((artist, album)) params["sort"] = "relevancerank" return __class__.assembleUrl(url, params)
python
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ url = "%s/search" % (__class__.BASE_URL) params = collections.OrderedDict() params["search-alias"] = "digital-music" params["field-keywords"] = " ".join((artist, album)) params["sort"] = "relevancerank" return __class__.assembleUrl(url, params)
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See CoverSource.getSearchUrl.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/amazondigital.py#L58-L65
desbma/sacad
sacad/sources/amazondigital.py
AmazonDigitalCoverSource.parseResults
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse page parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("utf-8"), parser) for page_struct_version, result_selector in enumerate(__class__.RESULTS_SELECTORS): result_nodes = result_selector(html) if result_nodes: break for rank, result_node in enumerate(result_nodes, 1): # get thumbnail & full image url img_node = __class__.IMG_SELECTORS[page_struct_version](result_node)[0] thumbnail_url = img_node.get("src") thumbnail_url = thumbnail_url.replace("Stripe-Prime-Only", "") url_parts = thumbnail_url.rsplit(".", 2) img_url = ".".join((url_parts[0], url_parts[2])) # assume size is fixed size = (500, 500) # try to get higher res image... if self.target_size > size[0]: # ...but only if needed self.logger.debug("Looking for optimal subimages configuration...") product_url = __class__.LINK_SELECTOR(result_node)[0].get("href") product_url = urllib.parse.urlsplit(product_url) product_id = product_url.path.split("/")[3] # TODO don't pick up highest res image if user asked less? for amazon_img_format in AMAZON_DIGITAL_IMAGE_FORMATS: # TODO review this, it seem to always fail now self.logger.debug("Trying %u subimages..." % (amazon_img_format.slice_count ** 2)) urls = tuple(self.generateImgUrls(product_id, __class__.DYNAPI_KEY, amazon_img_format.id, amazon_img_format.slice_count)) url_ok = await self.probeUrl(urls[-1]) if not url_ok: # images at this size are not available continue # images at this size are available img_url = urls size = (amazon_img_format.total_res,) * 2 break # assume format is always jpg format = CoverImageFormat.JPEG # add result results.append(AmazonDigitalCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=CoverImageMetadata.SIZE)) return results
python
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse page parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("utf-8"), parser) for page_struct_version, result_selector in enumerate(__class__.RESULTS_SELECTORS): result_nodes = result_selector(html) if result_nodes: break for rank, result_node in enumerate(result_nodes, 1): # get thumbnail & full image url img_node = __class__.IMG_SELECTORS[page_struct_version](result_node)[0] thumbnail_url = img_node.get("src") thumbnail_url = thumbnail_url.replace("Stripe-Prime-Only", "") url_parts = thumbnail_url.rsplit(".", 2) img_url = ".".join((url_parts[0], url_parts[2])) # assume size is fixed size = (500, 500) # try to get higher res image... if self.target_size > size[0]: # ...but only if needed self.logger.debug("Looking for optimal subimages configuration...") product_url = __class__.LINK_SELECTOR(result_node)[0].get("href") product_url = urllib.parse.urlsplit(product_url) product_id = product_url.path.split("/")[3] # TODO don't pick up highest res image if user asked less? for amazon_img_format in AMAZON_DIGITAL_IMAGE_FORMATS: # TODO review this, it seem to always fail now self.logger.debug("Trying %u subimages..." % (amazon_img_format.slice_count ** 2)) urls = tuple(self.generateImgUrls(product_id, __class__.DYNAPI_KEY, amazon_img_format.id, amazon_img_format.slice_count)) url_ok = await self.probeUrl(urls[-1]) if not url_ok: # images at this size are not available continue # images at this size are available img_url = urls size = (amazon_img_format.total_res,) * 2 break # assume format is always jpg format = CoverImageFormat.JPEG # add result results.append(AmazonDigitalCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=CoverImageMetadata.SIZE)) return results
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See CoverSource.parseResults.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/amazondigital.py#L71-L132
desbma/sacad
sacad/sources/amazondigital.py
AmazonDigitalCoverSource.generateImgUrls
def generateImgUrls(self, product_id, dynapi_key, format_id, slice_count): """ Generate URLs for slice_count^2 subimages of a product. """ for x in range(slice_count): for y in range(slice_count): yield ("http://z2-ec2.images-amazon.com/R/1/a=" + product_id + "+c=" + dynapi_key + "+d=_SCR%28" + str(format_id) + "," + str(x) + "," + str(y) + "%29_=.jpg")
python
def generateImgUrls(self, product_id, dynapi_key, format_id, slice_count): """ Generate URLs for slice_count^2 subimages of a product. """ for x in range(slice_count): for y in range(slice_count): yield ("http://z2-ec2.images-amazon.com/R/1/a=" + product_id + "+c=" + dynapi_key + "+d=_SCR%28" + str(format_id) + "," + str(x) + "," + str(y) + "%29_=.jpg")
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Generate URLs for slice_count^2 subimages of a product.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/amazondigital.py#L134-L140
desbma/sacad
sacad/redo.py
retrier
def retrier(*, max_attempts, sleeptime, max_sleeptime, sleepscale=1.5, jitter=0.2): """ Generator yielding time to wait for, after the attempt, if it failed. """ assert(max_attempts > 1) assert(sleeptime >= 0) assert(0 <= jitter <= sleeptime) assert(sleepscale >= 1) cur_sleeptime = min(max_sleeptime, sleeptime) for attempt in range(max_attempts): cur_jitter = random.randint(int(-jitter * 1000), int(jitter * 1000)) / 1000 yield max(0, cur_sleeptime + cur_jitter) cur_sleeptime = min(max_sleeptime, cur_sleeptime * sleepscale)
python
def retrier(*, max_attempts, sleeptime, max_sleeptime, sleepscale=1.5, jitter=0.2): """ Generator yielding time to wait for, after the attempt, if it failed. """ assert(max_attempts > 1) assert(sleeptime >= 0) assert(0 <= jitter <= sleeptime) assert(sleepscale >= 1) cur_sleeptime = min(max_sleeptime, sleeptime) for attempt in range(max_attempts): cur_jitter = random.randint(int(-jitter * 1000), int(jitter * 1000)) / 1000 yield max(0, cur_sleeptime + cur_jitter) cur_sleeptime = min(max_sleeptime, cur_sleeptime * sleepscale)
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Generator yielding time to wait for, after the attempt, if it failed.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/redo.py#L6-L18
desbma/sacad
sacad/cover.py
CoverSourceResult.get
async def get(self, target_format, target_size, size_tolerance_prct, out_filepath): """ Download cover and process it. """ if self.source_quality.value <= CoverSourceQuality.LOW.value: logging.getLogger("Cover").warning("Cover is from a potentially unreliable source and may be unrelated to the search") images_data = [] for i, url in enumerate(self.urls): # download logging.getLogger("Cover").info("Downloading cover '%s' (part %u/%u)..." % (url, i + 1, len(self.urls))) headers = {} self.source.updateHttpHeaders(headers) async def pre_cache_callback(img_data): return await __class__.crunch(img_data, self.format) store_in_cache_callback, image_data = await self.source.http.query(url, headers=headers, verify=False, cache=__class__.image_cache, pre_cache_callback=pre_cache_callback) # store immediately in cache await store_in_cache_callback() # append for multi images images_data.append(image_data) need_format_change = (self.format != target_format) need_size_change = ((max(self.size) > target_size) and (abs(max(self.size) - target_size) > target_size * size_tolerance_prct / 100)) need_join = len(images_data) > 1 if need_join or need_format_change or need_size_change: # post process image_data = self.postProcess(images_data, target_format if need_format_change else None, target_size if need_size_change else None) # crunch image again image_data = await __class__.crunch(image_data, target_format) # write it with open(out_filepath, "wb") as file: file.write(image_data)
python
async def get(self, target_format, target_size, size_tolerance_prct, out_filepath): """ Download cover and process it. """ if self.source_quality.value <= CoverSourceQuality.LOW.value: logging.getLogger("Cover").warning("Cover is from a potentially unreliable source and may be unrelated to the search") images_data = [] for i, url in enumerate(self.urls): # download logging.getLogger("Cover").info("Downloading cover '%s' (part %u/%u)..." % (url, i + 1, len(self.urls))) headers = {} self.source.updateHttpHeaders(headers) async def pre_cache_callback(img_data): return await __class__.crunch(img_data, self.format) store_in_cache_callback, image_data = await self.source.http.query(url, headers=headers, verify=False, cache=__class__.image_cache, pre_cache_callback=pre_cache_callback) # store immediately in cache await store_in_cache_callback() # append for multi images images_data.append(image_data) need_format_change = (self.format != target_format) need_size_change = ((max(self.size) > target_size) and (abs(max(self.size) - target_size) > target_size * size_tolerance_prct / 100)) need_join = len(images_data) > 1 if need_join or need_format_change or need_size_change: # post process image_data = self.postProcess(images_data, target_format if need_format_change else None, target_size if need_size_change else None) # crunch image again image_data = await __class__.crunch(image_data, target_format) # write it with open(out_filepath, "wb") as file: file.write(image_data)
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Download cover and process it.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L114-L157
desbma/sacad
sacad/cover.py
CoverSourceResult.postProcess
def postProcess(self, images_data, new_format, new_size): """ Convert image binary data to a target format and/or size (None if no conversion needed), and return the processed data. """ if len(images_data) == 1: in_bytes = io.BytesIO(images_data[0]) img = PIL.Image.open(in_bytes) if img.mode != "RGB": img = img.convert("RGB") else: # images need to be joined before further processing logging.getLogger("Cover").info("Joining %u images..." % (len(images_data))) # TODO find a way to do this losslessly for JPEG new_img = PIL.Image.new("RGB", self.size) assert(is_square(len(images_data))) sq = int(math.sqrt(len(images_data))) images_data_it = iter(images_data) img_sizes = {} for x in range(sq): for y in range(sq): current_image_data = next(images_data_it) img_stream = io.BytesIO(current_image_data) img = PIL.Image.open(img_stream) img_sizes[(x, y)] = img.size box = [0, 0] if x > 0: for px in range(x): box[0] += img_sizes[(px, y)][0] if y > 0: for py in range(y): box[1] += img_sizes[(x, py)][1] box.extend((box[0] + img.size[0], box[1] + img.size[1])) new_img.paste(img, box=tuple(box)) img = new_img out_bytes = io.BytesIO() if new_size is not None: logging.getLogger("Cover").info("Resizing from %ux%u to %ux%u..." % (self.size[0], self.size[1], new_size, new_size)) img = img.resize((new_size, new_size), PIL.Image.LANCZOS) # apply unsharp filter to remove resize blur (equivalent to (images/graphics)magick -unsharp 1.5x1+0.7+0.02) # we don't use PIL.ImageFilter.SHARPEN or PIL.ImageEnhance.Sharpness because we want precise control over # parameters unsharper = PIL.ImageFilter.UnsharpMask(radius=1.5, percent=70, threshold=5) img = img.filter(unsharper) if new_format is not None: logging.getLogger("Cover").info("Converting to %s..." % (new_format.name.upper())) target_format = new_format else: target_format = self.format img.save(out_bytes, format=target_format.name, quality=90, optimize=True) return out_bytes.getvalue()
python
def postProcess(self, images_data, new_format, new_size): """ Convert image binary data to a target format and/or size (None if no conversion needed), and return the processed data. """ if len(images_data) == 1: in_bytes = io.BytesIO(images_data[0]) img = PIL.Image.open(in_bytes) if img.mode != "RGB": img = img.convert("RGB") else: # images need to be joined before further processing logging.getLogger("Cover").info("Joining %u images..." % (len(images_data))) # TODO find a way to do this losslessly for JPEG new_img = PIL.Image.new("RGB", self.size) assert(is_square(len(images_data))) sq = int(math.sqrt(len(images_data))) images_data_it = iter(images_data) img_sizes = {} for x in range(sq): for y in range(sq): current_image_data = next(images_data_it) img_stream = io.BytesIO(current_image_data) img = PIL.Image.open(img_stream) img_sizes[(x, y)] = img.size box = [0, 0] if x > 0: for px in range(x): box[0] += img_sizes[(px, y)][0] if y > 0: for py in range(y): box[1] += img_sizes[(x, py)][1] box.extend((box[0] + img.size[0], box[1] + img.size[1])) new_img.paste(img, box=tuple(box)) img = new_img out_bytes = io.BytesIO() if new_size is not None: logging.getLogger("Cover").info("Resizing from %ux%u to %ux%u..." % (self.size[0], self.size[1], new_size, new_size)) img = img.resize((new_size, new_size), PIL.Image.LANCZOS) # apply unsharp filter to remove resize blur (equivalent to (images/graphics)magick -unsharp 1.5x1+0.7+0.02) # we don't use PIL.ImageFilter.SHARPEN or PIL.ImageEnhance.Sharpness because we want precise control over # parameters unsharper = PIL.ImageFilter.UnsharpMask(radius=1.5, percent=70, threshold=5) img = img.filter(unsharper) if new_format is not None: logging.getLogger("Cover").info("Converting to %s..." % (new_format.name.upper())) target_format = new_format else: target_format = self.format img.save(out_bytes, format=target_format.name, quality=90, optimize=True) return out_bytes.getvalue()
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Convert image binary data to a target format and/or size (None if no conversion needed), and return the processed data.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L159-L212
desbma/sacad
sacad/cover.py
CoverSourceResult.updateImageMetadata
async def updateImageMetadata(self): """ Partially download image file(s) to get its real metadata, or get it from cache. """ assert(self.needMetadataUpdate()) width_sum, height_sum = 0, 0 # only download metadata for the needed images to get full size idxs = [] assert(is_square(len(self.urls))) sq = int(math.sqrt(len(self.urls))) for x in range(sq): for y in range(sq): if x == y: idxs.append((x * sq + y, x, y)) for idx, x, y in idxs: url = self.urls[idx] format, width, height = None, None, None try: format, width, height = pickle.loads(__class__.metadata_cache[url]) except KeyError: # cache miss pass except Exception as e: logging.getLogger("Cover").warning("Unable to load metadata for URL '%s' from cache: %s %s" % (url, e.__class__.__qualname__, e)) else: # cache hit logging.getLogger("Cover").debug("Got metadata for URL '%s' from cache" % (url)) if format is not None: self.setFormatMetadata(format) if (self.needMetadataUpdate(CoverImageMetadata.FORMAT) or (self.needMetadataUpdate(CoverImageMetadata.SIZE) and ((width is None) or (height is None)))): # download logging.getLogger("Cover").debug("Downloading file header for URL '%s'..." % (url)) try: headers = {} self.source.updateHttpHeaders(headers) response = await self.source.http.fastStreamedQuery(url, headers=headers, verify=False) try: if self.needMetadataUpdate(CoverImageMetadata.FORMAT): # try to get format from response format = __class__.guessImageFormatFromHttpResponse(response) if format is not None: self.setFormatMetadata(format) if self.needMetadataUpdate(): # try to get metadata from HTTP data metadata = await __class__.guessImageMetadataFromHttpData(response) if metadata is not None: format, width, height = metadata if format is not None: self.setFormatMetadata(format) finally: response.release() except Exception as e: logging.getLogger("Cover").warning("Failed to get file metadata for URL '%s' " "(%s %s)" % (url, e.__class__.__qualname__, e)) if self.needMetadataUpdate(): # did we fail to get needed metadata at this point? if ((self.format is None) or ((self.size is None) and ((width is None) or (height is None)))): # if we get here, file is probably not reachable, or not even an image logging.getLogger("Cover").debug("Unable to get file metadata from file or HTTP headers for URL '%s', " "skipping this result" % (url)) return if ((self.format is not None) and ((self.size is not None) and (width is None) and (height is None))): logging.getLogger("Cover").debug("Unable to get file metadata from file or HTTP headers for URL '%s', " "falling back to API data" % (url)) self.check_metadata = CoverImageMetadata.NONE self.reliable_metadata = False return # save it to cache __class__.metadata_cache[url] = pickle.dumps((format, width, height)) # sum sizes if (width is not None) and (height is not None): width_sum += width height_sum += height if self.needMetadataUpdate(CoverImageMetadata.SIZE) and (width_sum > 0) and (height_sum > 0): self.setSizeMetadata((width_sum, height_sum))
python
async def updateImageMetadata(self): """ Partially download image file(s) to get its real metadata, or get it from cache. """ assert(self.needMetadataUpdate()) width_sum, height_sum = 0, 0 # only download metadata for the needed images to get full size idxs = [] assert(is_square(len(self.urls))) sq = int(math.sqrt(len(self.urls))) for x in range(sq): for y in range(sq): if x == y: idxs.append((x * sq + y, x, y)) for idx, x, y in idxs: url = self.urls[idx] format, width, height = None, None, None try: format, width, height = pickle.loads(__class__.metadata_cache[url]) except KeyError: # cache miss pass except Exception as e: logging.getLogger("Cover").warning("Unable to load metadata for URL '%s' from cache: %s %s" % (url, e.__class__.__qualname__, e)) else: # cache hit logging.getLogger("Cover").debug("Got metadata for URL '%s' from cache" % (url)) if format is not None: self.setFormatMetadata(format) if (self.needMetadataUpdate(CoverImageMetadata.FORMAT) or (self.needMetadataUpdate(CoverImageMetadata.SIZE) and ((width is None) or (height is None)))): # download logging.getLogger("Cover").debug("Downloading file header for URL '%s'..." % (url)) try: headers = {} self.source.updateHttpHeaders(headers) response = await self.source.http.fastStreamedQuery(url, headers=headers, verify=False) try: if self.needMetadataUpdate(CoverImageMetadata.FORMAT): # try to get format from response format = __class__.guessImageFormatFromHttpResponse(response) if format is not None: self.setFormatMetadata(format) if self.needMetadataUpdate(): # try to get metadata from HTTP data metadata = await __class__.guessImageMetadataFromHttpData(response) if metadata is not None: format, width, height = metadata if format is not None: self.setFormatMetadata(format) finally: response.release() except Exception as e: logging.getLogger("Cover").warning("Failed to get file metadata for URL '%s' " "(%s %s)" % (url, e.__class__.__qualname__, e)) if self.needMetadataUpdate(): # did we fail to get needed metadata at this point? if ((self.format is None) or ((self.size is None) and ((width is None) or (height is None)))): # if we get here, file is probably not reachable, or not even an image logging.getLogger("Cover").debug("Unable to get file metadata from file or HTTP headers for URL '%s', " "skipping this result" % (url)) return if ((self.format is not None) and ((self.size is not None) and (width is None) and (height is None))): logging.getLogger("Cover").debug("Unable to get file metadata from file or HTTP headers for URL '%s', " "falling back to API data" % (url)) self.check_metadata = CoverImageMetadata.NONE self.reliable_metadata = False return # save it to cache __class__.metadata_cache[url] = pickle.dumps((format, width, height)) # sum sizes if (width is not None) and (height is not None): width_sum += width height_sum += height if self.needMetadataUpdate(CoverImageMetadata.SIZE) and (width_sum > 0) and (height_sum > 0): self.setSizeMetadata((width_sum, height_sum))
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Partially download image file(s) to get its real metadata, or get it from cache.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L214-L307
desbma/sacad
sacad/cover.py
CoverSourceResult.setFormatMetadata
def setFormatMetadata(self, format): """ Set format image metadata to what has been reliably identified. """ assert((self.needMetadataUpdate(CoverImageMetadata.FORMAT)) or (self.format is format)) self.format = format self.check_metadata &= ~CoverImageMetadata.FORMAT
python
def setFormatMetadata(self, format): """ Set format image metadata to what has been reliably identified. """ assert((self.needMetadataUpdate(CoverImageMetadata.FORMAT)) or (self.format is format)) self.format = format self.check_metadata &= ~CoverImageMetadata.FORMAT
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Set format image metadata to what has been reliably identified.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L313-L318
desbma/sacad
sacad/cover.py
CoverSourceResult.setSizeMetadata
def setSizeMetadata(self, size): """ Set size image metadata to what has been reliably identified. """ assert((self.needMetadataUpdate(CoverImageMetadata.SIZE)) or (self.size == size)) self.size = size self.check_metadata &= ~CoverImageMetadata.SIZE
python
def setSizeMetadata(self, size): """ Set size image metadata to what has been reliably identified. """ assert((self.needMetadataUpdate(CoverImageMetadata.SIZE)) or (self.size == size)) self.size = size self.check_metadata &= ~CoverImageMetadata.SIZE
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Set size image metadata to what has been reliably identified.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L320-L325
desbma/sacad
sacad/cover.py
CoverSourceResult.updateSignature
async def updateSignature(self): """ Calculate a cover's "signature" using its thumbnail url. """ assert(self.thumbnail_sig is None) if self.thumbnail_url is None: logging.getLogger("Cover").warning("No thumbnail available for %s" % (self)) return # download logging.getLogger("Cover").debug("Downloading cover thumbnail '%s'..." % (self.thumbnail_url)) headers = {} self.source.updateHttpHeaders(headers) async def pre_cache_callback(img_data): return await __class__.crunch(img_data, CoverImageFormat.JPEG, silent=True) try: store_in_cache_callback, image_data = await self.source.http.query(self.thumbnail_url, cache=__class__.image_cache, headers=headers, pre_cache_callback=pre_cache_callback) except Exception as e: logging.getLogger("Cover").warning("Download of '%s' failed: %s %s" % (self.thumbnail_url, e.__class__.__qualname__, e)) return # compute sig logging.getLogger("Cover").debug("Computing signature of %s..." % (self)) try: self.thumbnail_sig = __class__.computeImgSignature(image_data) except Exception as e: logging.getLogger("Cover").warning("Failed to compute signature of '%s': %s %s" % (self, e.__class__.__qualname__, e)) else: await store_in_cache_callback()
python
async def updateSignature(self): """ Calculate a cover's "signature" using its thumbnail url. """ assert(self.thumbnail_sig is None) if self.thumbnail_url is None: logging.getLogger("Cover").warning("No thumbnail available for %s" % (self)) return # download logging.getLogger("Cover").debug("Downloading cover thumbnail '%s'..." % (self.thumbnail_url)) headers = {} self.source.updateHttpHeaders(headers) async def pre_cache_callback(img_data): return await __class__.crunch(img_data, CoverImageFormat.JPEG, silent=True) try: store_in_cache_callback, image_data = await self.source.http.query(self.thumbnail_url, cache=__class__.image_cache, headers=headers, pre_cache_callback=pre_cache_callback) except Exception as e: logging.getLogger("Cover").warning("Download of '%s' failed: %s %s" % (self.thumbnail_url, e.__class__.__qualname__, e)) return # compute sig logging.getLogger("Cover").debug("Computing signature of %s..." % (self)) try: self.thumbnail_sig = __class__.computeImgSignature(image_data) except Exception as e: logging.getLogger("Cover").warning("Failed to compute signature of '%s': %s %s" % (self, e.__class__.__qualname__, e)) else: await store_in_cache_callback()
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Calculate a cover's "signature" using its thumbnail url.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L327-L363
desbma/sacad
sacad/cover.py
CoverSourceResult.compare
def compare(first, second, *, target_size, size_tolerance_prct): """ Compare cover relevance/quality. Return -1 if first is a worst match than second, 1 otherwise, or 0 if cover can't be discriminated. This code is responsible for comparing two cover results to identify the best one, and is used to sort all results. It is probably the most important piece of code of this tool. Covers with sizes under the target size (+- configured tolerance) are excluded before comparison. The following factors are used in order: 1. Prefer approximately square covers 2. Prefer covers similar to the reference cover 3. Prefer size above target size 4. If both below target size, prefer closest 5. Prefer covers of most reliable source 6. Prefer best ranked cover 7. Prefer covers with reliable metadata If all previous factors do not allow sorting of two results (very unlikely): 8. Prefer covers with less images to join 9. Prefer covers having the target size 10. Prefer PNG covers 11. Prefer exactly square covers We don't overload the __lt__ operator because we need to pass the target_size parameter. """ for c in (first, second): assert(c.format is not None) assert(isinstance(c.size[0], int) and isinstance(c.size[1], int)) # prefer square covers #1 delta_ratio1 = abs(first.size[0] / first.size[1] - 1) delta_ratio2 = abs(second.size[0] / second.size[1] - 1) if abs(delta_ratio1 - delta_ratio2) > 0.15: return -1 if (delta_ratio1 > delta_ratio2) else 1 # prefer similar to reference sr1 = first.is_similar_to_reference sr2 = second.is_similar_to_reference if sr1 and (not sr2): return 1 if (not sr1) and sr2: return -1 # prefer size above preferred delta_size1 = ((first.size[0] + first.size[1]) / 2) - target_size delta_size2 = ((second.size[0] + second.size[1]) / 2) - target_size if (((delta_size1 < 0) and (delta_size2 >= 0)) or (delta_size1 >= 0) and (delta_size2 < 0)): return -1 if (delta_size1 < delta_size2) else 1 # if both below target size, prefer closest if (delta_size1 < 0) and (delta_size2 < 0) and (delta_size1 != delta_size2): return -1 if (delta_size1 < delta_size2) else 1 # prefer covers of most reliable source qs1 = first.source_quality.value qs2 = second.source_quality.value if qs1 != qs2: return -1 if (qs1 < qs2) else 1 # prefer best ranked if ((first.rank is not None) and (second.rank is not None) and (first.__class__ is second.__class__) and (first.rank != second.rank)): return -1 if (first.rank > second.rank) else 1 # prefer reliable metadata if first.reliable_metadata != second.reliable_metadata: return 1 if first.reliable_metadata else -1 # prefer covers with less images to join ic1 = len(first.urls) ic2 = len(second.urls) if ic1 != ic2: return -1 if (ic1 > ic2) else 1 # prefer the preferred size if abs(delta_size1) != abs(delta_size2): return -1 if (abs(delta_size1) > abs(delta_size2)) else 1 # prefer png if first.format != second.format: return -1 if (second.format is CoverImageFormat.PNG) else 1 # prefer square covers #2 if (delta_ratio1 != delta_ratio2): return -1 if (delta_ratio1 > delta_ratio2) else 1 # fuck, they are the same! return 0
python
def compare(first, second, *, target_size, size_tolerance_prct): """ Compare cover relevance/quality. Return -1 if first is a worst match than second, 1 otherwise, or 0 if cover can't be discriminated. This code is responsible for comparing two cover results to identify the best one, and is used to sort all results. It is probably the most important piece of code of this tool. Covers with sizes under the target size (+- configured tolerance) are excluded before comparison. The following factors are used in order: 1. Prefer approximately square covers 2. Prefer covers similar to the reference cover 3. Prefer size above target size 4. If both below target size, prefer closest 5. Prefer covers of most reliable source 6. Prefer best ranked cover 7. Prefer covers with reliable metadata If all previous factors do not allow sorting of two results (very unlikely): 8. Prefer covers with less images to join 9. Prefer covers having the target size 10. Prefer PNG covers 11. Prefer exactly square covers We don't overload the __lt__ operator because we need to pass the target_size parameter. """ for c in (first, second): assert(c.format is not None) assert(isinstance(c.size[0], int) and isinstance(c.size[1], int)) # prefer square covers #1 delta_ratio1 = abs(first.size[0] / first.size[1] - 1) delta_ratio2 = abs(second.size[0] / second.size[1] - 1) if abs(delta_ratio1 - delta_ratio2) > 0.15: return -1 if (delta_ratio1 > delta_ratio2) else 1 # prefer similar to reference sr1 = first.is_similar_to_reference sr2 = second.is_similar_to_reference if sr1 and (not sr2): return 1 if (not sr1) and sr2: return -1 # prefer size above preferred delta_size1 = ((first.size[0] + first.size[1]) / 2) - target_size delta_size2 = ((second.size[0] + second.size[1]) / 2) - target_size if (((delta_size1 < 0) and (delta_size2 >= 0)) or (delta_size1 >= 0) and (delta_size2 < 0)): return -1 if (delta_size1 < delta_size2) else 1 # if both below target size, prefer closest if (delta_size1 < 0) and (delta_size2 < 0) and (delta_size1 != delta_size2): return -1 if (delta_size1 < delta_size2) else 1 # prefer covers of most reliable source qs1 = first.source_quality.value qs2 = second.source_quality.value if qs1 != qs2: return -1 if (qs1 < qs2) else 1 # prefer best ranked if ((first.rank is not None) and (second.rank is not None) and (first.__class__ is second.__class__) and (first.rank != second.rank)): return -1 if (first.rank > second.rank) else 1 # prefer reliable metadata if first.reliable_metadata != second.reliable_metadata: return 1 if first.reliable_metadata else -1 # prefer covers with less images to join ic1 = len(first.urls) ic2 = len(second.urls) if ic1 != ic2: return -1 if (ic1 > ic2) else 1 # prefer the preferred size if abs(delta_size1) != abs(delta_size2): return -1 if (abs(delta_size1) > abs(delta_size2)) else 1 # prefer png if first.format != second.format: return -1 if (second.format is CoverImageFormat.PNG) else 1 # prefer square covers #2 if (delta_ratio1 != delta_ratio2): return -1 if (delta_ratio1 > delta_ratio2) else 1 # fuck, they are the same! return 0
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Compare cover relevance/quality. Return -1 if first is a worst match than second, 1 otherwise, or 0 if cover can't be discriminated. This code is responsible for comparing two cover results to identify the best one, and is used to sort all results. It is probably the most important piece of code of this tool. Covers with sizes under the target size (+- configured tolerance) are excluded before comparison. The following factors are used in order: 1. Prefer approximately square covers 2. Prefer covers similar to the reference cover 3. Prefer size above target size 4. If both below target size, prefer closest 5. Prefer covers of most reliable source 6. Prefer best ranked cover 7. Prefer covers with reliable metadata If all previous factors do not allow sorting of two results (very unlikely): 8. Prefer covers with less images to join 9. Prefer covers having the target size 10. Prefer PNG covers 11. Prefer exactly square covers We don't overload the __lt__ operator because we need to pass the target_size parameter.
[ "Compare", "cover", "relevance", "/", "quality", "." ]
train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L366-L457
desbma/sacad
sacad/cover.py
CoverSourceResult.crunch
async def crunch(image_data, format, silent=False): """ Crunch image data, and return the processed data, or orignal data if operation failed. """ if (((format is CoverImageFormat.PNG) and (not HAS_OPTIPNG)) or ((format is CoverImageFormat.JPEG) and (not HAS_JPEGOPTIM))): return image_data with mkstemp_ctx.mkstemp(suffix=".%s" % (format.name.lower())) as tmp_out_filepath: if not silent: logging.getLogger("Cover").info("Crunching %s image..." % (format.name.upper())) with open(tmp_out_filepath, "wb") as tmp_out_file: tmp_out_file.write(image_data) size_before = len(image_data) if format is CoverImageFormat.PNG: cmd = ["optipng", "-quiet", "-o1"] elif format is CoverImageFormat.JPEG: cmd = ["jpegoptim", "-q", "--strip-all"] cmd.append(tmp_out_filepath) p = await asyncio.create_subprocess_exec(*cmd, stdin=asyncio.subprocess.DEVNULL, stdout=asyncio.subprocess.DEVNULL, stderr=asyncio.subprocess.DEVNULL) await p.wait() if p.returncode != 0: if not silent: logging.getLogger("Cover").warning("Crunching image failed") return image_data with open(tmp_out_filepath, "rb") as tmp_out_file: crunched_image_data = tmp_out_file.read() size_after = len(crunched_image_data) pct_saved = 100 * (size_before - size_after) / size_before if not silent: logging.getLogger("Cover").debug("Crunching image saved %.2f%% filesize" % (pct_saved)) return crunched_image_data
python
async def crunch(image_data, format, silent=False): """ Crunch image data, and return the processed data, or orignal data if operation failed. """ if (((format is CoverImageFormat.PNG) and (not HAS_OPTIPNG)) or ((format is CoverImageFormat.JPEG) and (not HAS_JPEGOPTIM))): return image_data with mkstemp_ctx.mkstemp(suffix=".%s" % (format.name.lower())) as tmp_out_filepath: if not silent: logging.getLogger("Cover").info("Crunching %s image..." % (format.name.upper())) with open(tmp_out_filepath, "wb") as tmp_out_file: tmp_out_file.write(image_data) size_before = len(image_data) if format is CoverImageFormat.PNG: cmd = ["optipng", "-quiet", "-o1"] elif format is CoverImageFormat.JPEG: cmd = ["jpegoptim", "-q", "--strip-all"] cmd.append(tmp_out_filepath) p = await asyncio.create_subprocess_exec(*cmd, stdin=asyncio.subprocess.DEVNULL, stdout=asyncio.subprocess.DEVNULL, stderr=asyncio.subprocess.DEVNULL) await p.wait() if p.returncode != 0: if not silent: logging.getLogger("Cover").warning("Crunching image failed") return image_data with open(tmp_out_filepath, "rb") as tmp_out_file: crunched_image_data = tmp_out_file.read() size_after = len(crunched_image_data) pct_saved = 100 * (size_before - size_after) / size_before if not silent: logging.getLogger("Cover").debug("Crunching image saved %.2f%% filesize" % (pct_saved)) return crunched_image_data
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Crunch image data, and return the processed data, or orignal data if operation failed.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L460-L491
desbma/sacad
sacad/cover.py
CoverSourceResult.guessImageMetadataFromData
def guessImageMetadataFromData(img_data): """ Identify an image format and size from its first bytes. """ format, width, height = None, None, None img_stream = io.BytesIO(img_data) try: img = PIL.Image.open(img_stream) except IOError: format = imghdr.what(None, h=img_data) format = SUPPORTED_IMG_FORMATS.get(format, None) else: format = img.format.lower() format = SUPPORTED_IMG_FORMATS.get(format, None) width, height = img.size return format, width, height
python
def guessImageMetadataFromData(img_data): """ Identify an image format and size from its first bytes. """ format, width, height = None, None, None img_stream = io.BytesIO(img_data) try: img = PIL.Image.open(img_stream) except IOError: format = imghdr.what(None, h=img_data) format = SUPPORTED_IMG_FORMATS.get(format, None) else: format = img.format.lower() format = SUPPORTED_IMG_FORMATS.get(format, None) width, height = img.size return format, width, height
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Identify an image format and size from its first bytes.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L494-L507
desbma/sacad
sacad/cover.py
CoverSourceResult.guessImageMetadataFromHttpData
async def guessImageMetadataFromHttpData(response): """ Identify an image format and size from the beginning of its HTTP data. """ metadata = None img_data = bytearray() while len(img_data) < CoverSourceResult.MAX_FILE_METADATA_PEEK_SIZE: new_img_data = await response.content.read(__class__.METADATA_PEEK_SIZE_INCREMENT) if not new_img_data: break img_data.extend(new_img_data) metadata = __class__.guessImageMetadataFromData(img_data) if (metadata is not None) and all(metadata): return metadata return metadata
python
async def guessImageMetadataFromHttpData(response): """ Identify an image format and size from the beginning of its HTTP data. """ metadata = None img_data = bytearray() while len(img_data) < CoverSourceResult.MAX_FILE_METADATA_PEEK_SIZE: new_img_data = await response.content.read(__class__.METADATA_PEEK_SIZE_INCREMENT) if not new_img_data: break img_data.extend(new_img_data) metadata = __class__.guessImageMetadataFromData(img_data) if (metadata is not None) and all(metadata): return metadata return metadata
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Identify an image format and size from the beginning of its HTTP data.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L510-L525
desbma/sacad
sacad/cover.py
CoverSourceResult.guessImageFormatFromHttpResponse
def guessImageFormatFromHttpResponse(response): """ Guess file format from HTTP response, return format or None. """ extensions = [] # try to guess extension from response content-type header try: content_type = response.headers["Content-Type"] except KeyError: pass else: ext = mimetypes.guess_extension(content_type, strict=False) if ext is not None: extensions.append(ext) # try to extract extension from URL urls = list(response.history) + [response.url] for url in map(str, urls): ext = os.path.splitext(urllib.parse.urlsplit(url).path)[-1] if (ext is not None) and (ext not in extensions): extensions.append(ext) # now guess from the extensions for ext in extensions: try: return SUPPORTED_IMG_FORMATS[ext[1:]] except KeyError: pass
python
def guessImageFormatFromHttpResponse(response): """ Guess file format from HTTP response, return format or None. """ extensions = [] # try to guess extension from response content-type header try: content_type = response.headers["Content-Type"] except KeyError: pass else: ext = mimetypes.guess_extension(content_type, strict=False) if ext is not None: extensions.append(ext) # try to extract extension from URL urls = list(response.history) + [response.url] for url in map(str, urls): ext = os.path.splitext(urllib.parse.urlsplit(url).path)[-1] if (ext is not None) and (ext not in extensions): extensions.append(ext) # now guess from the extensions for ext in extensions: try: return SUPPORTED_IMG_FORMATS[ext[1:]] except KeyError: pass
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Guess file format from HTTP response, return format or None.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L528-L554
desbma/sacad
sacad/cover.py
CoverSourceResult.preProcessForComparison
async def preProcessForComparison(results, target_size, size_tolerance_prct): """ Process results to prepare them for future comparison and sorting. """ # find reference (=image most likely to match target cover ignoring factors like size and format) reference = None for result in results: if result.source_quality is CoverSourceQuality.REFERENCE: if ((reference is None) or (CoverSourceResult.compare(result, reference, target_size=target_size, size_tolerance_prct=size_tolerance_prct) > 0)): reference = result # remove results that are only refs results = list(itertools.filterfalse(operator.attrgetter("is_only_reference"), results)) # remove duplicates no_dup_results = [] for result in results: is_dup = False for result_comp in results: if ((result_comp is not result) and (result_comp.urls == result.urls) and (__class__.compare(result, result_comp, target_size=target_size, size_tolerance_prct=size_tolerance_prct) < 0)): is_dup = True break if not is_dup: no_dup_results.append(result) dup_count = len(results) - len(no_dup_results) if dup_count > 0: logging.getLogger("Cover").info("Removed %u duplicate results" % (dup_count)) results = no_dup_results if reference is not None: logging.getLogger("Cover").info("Reference is: %s" % (reference)) reference.is_similar_to_reference = True # calculate sigs futures = [] for result in results: coroutine = result.updateSignature() future = asyncio.ensure_future(coroutine) futures.append(future) if reference.is_only_reference: assert(reference not in results) coroutine = reference.updateSignature() future = asyncio.ensure_future(coroutine) futures.append(future) if futures: await asyncio.wait(futures) for future in futures: future.result() # raise pending exception if any # compare other results to reference for result in results: if ((result is not reference) and (result.thumbnail_sig is not None) and (reference.thumbnail_sig is not None)): result.is_similar_to_reference = __class__.areImageSigsSimilar(result.thumbnail_sig, reference.thumbnail_sig) if result.is_similar_to_reference: logging.getLogger("Cover").debug("%s is similar to reference" % (result)) else: logging.getLogger("Cover").debug("%s is NOT similar to reference" % (result)) else: logging.getLogger("Cover").warning("No reference result found") return results
python
async def preProcessForComparison(results, target_size, size_tolerance_prct): """ Process results to prepare them for future comparison and sorting. """ # find reference (=image most likely to match target cover ignoring factors like size and format) reference = None for result in results: if result.source_quality is CoverSourceQuality.REFERENCE: if ((reference is None) or (CoverSourceResult.compare(result, reference, target_size=target_size, size_tolerance_prct=size_tolerance_prct) > 0)): reference = result # remove results that are only refs results = list(itertools.filterfalse(operator.attrgetter("is_only_reference"), results)) # remove duplicates no_dup_results = [] for result in results: is_dup = False for result_comp in results: if ((result_comp is not result) and (result_comp.urls == result.urls) and (__class__.compare(result, result_comp, target_size=target_size, size_tolerance_prct=size_tolerance_prct) < 0)): is_dup = True break if not is_dup: no_dup_results.append(result) dup_count = len(results) - len(no_dup_results) if dup_count > 0: logging.getLogger("Cover").info("Removed %u duplicate results" % (dup_count)) results = no_dup_results if reference is not None: logging.getLogger("Cover").info("Reference is: %s" % (reference)) reference.is_similar_to_reference = True # calculate sigs futures = [] for result in results: coroutine = result.updateSignature() future = asyncio.ensure_future(coroutine) futures.append(future) if reference.is_only_reference: assert(reference not in results) coroutine = reference.updateSignature() future = asyncio.ensure_future(coroutine) futures.append(future) if futures: await asyncio.wait(futures) for future in futures: future.result() # raise pending exception if any # compare other results to reference for result in results: if ((result is not reference) and (result.thumbnail_sig is not None) and (reference.thumbnail_sig is not None)): result.is_similar_to_reference = __class__.areImageSigsSimilar(result.thumbnail_sig, reference.thumbnail_sig) if result.is_similar_to_reference: logging.getLogger("Cover").debug("%s is similar to reference" % (result)) else: logging.getLogger("Cover").debug("%s is NOT similar to reference" % (result)) else: logging.getLogger("Cover").warning("No reference result found") return results
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Process results to prepare them for future comparison and sorting.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L557-L627
desbma/sacad
sacad/cover.py
CoverSourceResult.computeImgSignature
def computeImgSignature(image_data): """ Calculate an image signature. This is similar to ahash but uses 3 colors components See: https://github.com/JohannesBuchner/imagehash/blob/4.0/imagehash/__init__.py#L125 """ parser = PIL.ImageFile.Parser() parser.feed(image_data) img = parser.close() target_size = (__class__.IMG_SIG_SIZE, __class__.IMG_SIG_SIZE) img.thumbnail(target_size, PIL.Image.BICUBIC) if img.size != target_size: logging.getLogger("Cover").debug("Non square thumbnail after resize to %ux%u, unable to compute signature" % target_size) return None img = img.convert(mode="RGB") pixels = img.getdata() pixel_count = target_size[0] * target_size[1] color_count = 3 r = bitarray.bitarray(pixel_count * color_count) r.setall(False) for ic in range(color_count): mean = sum(p[ic] for p in pixels) // pixel_count for ip, p in enumerate(pixels): if p[ic] > mean: r[pixel_count * ic + ip] = True return r
python
def computeImgSignature(image_data): """ Calculate an image signature. This is similar to ahash but uses 3 colors components See: https://github.com/JohannesBuchner/imagehash/blob/4.0/imagehash/__init__.py#L125 """ parser = PIL.ImageFile.Parser() parser.feed(image_data) img = parser.close() target_size = (__class__.IMG_SIG_SIZE, __class__.IMG_SIG_SIZE) img.thumbnail(target_size, PIL.Image.BICUBIC) if img.size != target_size: logging.getLogger("Cover").debug("Non square thumbnail after resize to %ux%u, unable to compute signature" % target_size) return None img = img.convert(mode="RGB") pixels = img.getdata() pixel_count = target_size[0] * target_size[1] color_count = 3 r = bitarray.bitarray(pixel_count * color_count) r.setall(False) for ic in range(color_count): mean = sum(p[ic] for p in pixels) // pixel_count for ip, p in enumerate(pixels): if p[ic] > mean: r[pixel_count * ic + ip] = True return r
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Calculate an image signature. This is similar to ahash but uses 3 colors components See: https://github.com/JohannesBuchner/imagehash/blob/4.0/imagehash/__init__.py#L125
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/cover.py#L630-L657
desbma/sacad
sacad/recurse.py
analyze_lib
def analyze_lib(lib_dir, cover_filename, *, ignore_existing=False): """ Recursively analyze library, and return a dict of path -> (artist, album). """ work = {} stats = collections.OrderedDict(((k, 0) for k in("files", "albums", "missing covers", "errors"))) with tqdm.tqdm(desc="Analyzing library", unit="dir", postfix=stats) as progress, \ tqdm_logging.redirect_logging(progress): for rootpath, rel_dirpaths, rel_filepaths in os.walk(lib_dir): metadata = analyze_dir(stats, rootpath, rel_filepaths, cover_filename, ignore_existing=ignore_existing) progress.set_postfix(stats, refresh=False) progress.update(1) if all(metadata[:-1]): work[rootpath] = metadata[:-1] return work
python
def analyze_lib(lib_dir, cover_filename, *, ignore_existing=False): """ Recursively analyze library, and return a dict of path -> (artist, album). """ work = {} stats = collections.OrderedDict(((k, 0) for k in("files", "albums", "missing covers", "errors"))) with tqdm.tqdm(desc="Analyzing library", unit="dir", postfix=stats) as progress, \ tqdm_logging.redirect_logging(progress): for rootpath, rel_dirpaths, rel_filepaths in os.walk(lib_dir): metadata = analyze_dir(stats, rootpath, rel_filepaths, cover_filename, ignore_existing=ignore_existing) progress.set_postfix(stats, refresh=False) progress.update(1) if all(metadata[:-1]): work[rootpath] = metadata[:-1] return work
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Recursively analyze library, and return a dict of path -> (artist, album).
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L38-L56
desbma/sacad
sacad/recurse.py
get_metadata
def get_metadata(audio_filepaths): """ Return a tuple of album, artist, has_embedded_album_art from a list of audio files. """ artist, album, has_embedded_album_art = None, None, None for audio_filepath in audio_filepaths: try: mf = mutagen.File(audio_filepath) except Exception: continue if mf is None: continue # artist for key in ("albumartist", "artist", # ogg "TPE1", "TPE2", # mp3 "aART", "\xa9ART"): # mp4 try: val = mf.get(key, None) except ValueError: val = None if val is not None: artist = val[-1] break # album for key in ("_album", "album", # ogg "TALB", # mp3 "\xa9alb"): # mp4 try: val = mf.get(key, None) except ValueError: val = None if val is not None: album = val[-1] break if artist and album: # album art if isinstance(mf, mutagen.ogg.OggFileType): has_embedded_album_art = "metadata_block_picture" in mf elif isinstance(mf, mutagen.mp3.MP3): has_embedded_album_art = any(map(operator.methodcaller("startswith", "APIC:"), mf.keys())) elif isinstance(mf, mutagen.mp4.MP4): has_embedded_album_art = "covr" in mf # stop at the first file that succeeds (for performance) break return artist, album, has_embedded_album_art
python
def get_metadata(audio_filepaths): """ Return a tuple of album, artist, has_embedded_album_art from a list of audio files. """ artist, album, has_embedded_album_art = None, None, None for audio_filepath in audio_filepaths: try: mf = mutagen.File(audio_filepath) except Exception: continue if mf is None: continue # artist for key in ("albumartist", "artist", # ogg "TPE1", "TPE2", # mp3 "aART", "\xa9ART"): # mp4 try: val = mf.get(key, None) except ValueError: val = None if val is not None: artist = val[-1] break # album for key in ("_album", "album", # ogg "TALB", # mp3 "\xa9alb"): # mp4 try: val = mf.get(key, None) except ValueError: val = None if val is not None: album = val[-1] break if artist and album: # album art if isinstance(mf, mutagen.ogg.OggFileType): has_embedded_album_art = "metadata_block_picture" in mf elif isinstance(mf, mutagen.mp3.MP3): has_embedded_album_art = any(map(operator.methodcaller("startswith", "APIC:"), mf.keys())) elif isinstance(mf, mutagen.mp4.MP4): has_embedded_album_art = "covr" in mf # stop at the first file that succeeds (for performance) break return artist, album, has_embedded_album_art
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Return a tuple of album, artist, has_embedded_album_art from a list of audio files.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L59-L106
desbma/sacad
sacad/recurse.py
analyze_dir
def analyze_dir(stats, parent_dir, rel_filepaths, cover_filename, *, ignore_existing=False): """ Analyze a directory (non recursively) to get its album metadata if it is one. """ no_metadata = None, None, None metadata = no_metadata audio_filepaths = [] for rel_filepath in rel_filepaths: stats["files"] += 1 try: ext = os.path.splitext(rel_filepath)[1][1:].lower() except IndexError: continue if ext in AUDIO_EXTENSIONS: audio_filepaths.append(os.path.join(parent_dir, rel_filepath)) if audio_filepaths: stats["albums"] += 1 if (cover_filename != EMBEDDED_ALBUM_ART_SYMBOL): missing = (not os.path.isfile(os.path.join(parent_dir, cover_filename))) or ignore_existing if missing: metadata = get_metadata(audio_filepaths) else: metadata = get_metadata(audio_filepaths) missing = (not metadata[2]) or ignore_existing if missing: stats["missing covers"] += 1 if not all(metadata[:-1]): # failed to get metadata for this album stats["errors"] += 1 logging.getLogger("sacad_r").error("Unable to read metadata for album directory '%s'" % (parent_dir)) else: metadata = no_metadata return metadata
python
def analyze_dir(stats, parent_dir, rel_filepaths, cover_filename, *, ignore_existing=False): """ Analyze a directory (non recursively) to get its album metadata if it is one. """ no_metadata = None, None, None metadata = no_metadata audio_filepaths = [] for rel_filepath in rel_filepaths: stats["files"] += 1 try: ext = os.path.splitext(rel_filepath)[1][1:].lower() except IndexError: continue if ext in AUDIO_EXTENSIONS: audio_filepaths.append(os.path.join(parent_dir, rel_filepath)) if audio_filepaths: stats["albums"] += 1 if (cover_filename != EMBEDDED_ALBUM_ART_SYMBOL): missing = (not os.path.isfile(os.path.join(parent_dir, cover_filename))) or ignore_existing if missing: metadata = get_metadata(audio_filepaths) else: metadata = get_metadata(audio_filepaths) missing = (not metadata[2]) or ignore_existing if missing: stats["missing covers"] += 1 if not all(metadata[:-1]): # failed to get metadata for this album stats["errors"] += 1 logging.getLogger("sacad_r").error("Unable to read metadata for album directory '%s'" % (parent_dir)) else: metadata = no_metadata return metadata
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Analyze a directory (non recursively) to get its album metadata if it is one.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L109-L139
desbma/sacad
sacad/recurse.py
embed_album_art
def embed_album_art(cover_filepath, path): """ Embed album art into audio files. """ with open(cover_filepath, "rb") as f: cover_data = f.read() for filename in os.listdir(path): try: ext = os.path.splitext(filename)[1][1:].lower() except IndexError: continue if ext in AUDIO_EXTENSIONS: filepath = os.path.join(path, filename) mf = mutagen.File(filepath) if (isinstance(mf.tags, mutagen._vorbis.VComment) or isinstance(mf, mutagen.ogg.OggFileType)): picture = mutagen.flac.Picture() picture.data = cover_data picture.type = mutagen.id3.PictureType.COVER_FRONT picture.mime = "image/jpeg" encoded_data = base64.b64encode(picture.write()) mf["metadata_block_picture"] = encoded_data.decode("ascii") elif (isinstance(mf.tags, mutagen.id3.ID3) or isinstance(mf, mutagen.id3.ID3FileType)): mf.tags.add(mutagen.id3.APIC(mime="image/jpeg", type=mutagen.id3.PictureType.COVER_FRONT, data=cover_data)) elif (isinstance(mf.tags, mutagen.mp4.MP4Tags) or isinstance(mf, mutagen.mp4.MP4)): mf["covr"] = [mutagen.mp4.MP4Cover(cover_data, imageformat=mutagen.mp4.AtomDataType.JPEG)] mf.save()
python
def embed_album_art(cover_filepath, path): """ Embed album art into audio files. """ with open(cover_filepath, "rb") as f: cover_data = f.read() for filename in os.listdir(path): try: ext = os.path.splitext(filename)[1][1:].lower() except IndexError: continue if ext in AUDIO_EXTENSIONS: filepath = os.path.join(path, filename) mf = mutagen.File(filepath) if (isinstance(mf.tags, mutagen._vorbis.VComment) or isinstance(mf, mutagen.ogg.OggFileType)): picture = mutagen.flac.Picture() picture.data = cover_data picture.type = mutagen.id3.PictureType.COVER_FRONT picture.mime = "image/jpeg" encoded_data = base64.b64encode(picture.write()) mf["metadata_block_picture"] = encoded_data.decode("ascii") elif (isinstance(mf.tags, mutagen.id3.ID3) or isinstance(mf, mutagen.id3.ID3FileType)): mf.tags.add(mutagen.id3.APIC(mime="image/jpeg", type=mutagen.id3.PictureType.COVER_FRONT, data=cover_data)) elif (isinstance(mf.tags, mutagen.mp4.MP4Tags) or isinstance(mf, mutagen.mp4.MP4)): mf["covr"] = [mutagen.mp4.MP4Cover(cover_data, imageformat=mutagen.mp4.AtomDataType.JPEG)] mf.save()
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Embed album art into audio files.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L142-L173
desbma/sacad
sacad/recurse.py
ichunk
def ichunk(iterable, n): """ Split an iterable into n-sized chunks. """ it = iter(iterable) while True: chunk = tuple(itertools.islice(it, n)) if not chunk: return yield chunk
python
def ichunk(iterable, n): """ Split an iterable into n-sized chunks. """ it = iter(iterable) while True: chunk = tuple(itertools.islice(it, n)) if not chunk: return yield chunk
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Split an iterable into n-sized chunks.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L176-L183
desbma/sacad
sacad/recurse.py
get_covers
def get_covers(work, args): """ Get missing covers. """ with contextlib.ExitStack() as cm: if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: tmp_prefix = "%s_" % (os.path.splitext(os.path.basename(inspect.getfile(inspect.currentframe())))[0]) tmp_dir = cm.enter_context(tempfile.TemporaryDirectory(prefix=tmp_prefix)) # setup progress report stats = collections.OrderedDict(((k, 0) for k in("ok", "errors", "no result found"))) progress = cm.enter_context(tqdm.tqdm(total=len(work), miniters=1, desc="Searching covers", unit="cover", postfix=stats)) cm.enter_context(tqdm_logging.redirect_logging(progress)) def update_progress(future): path, cover_filepath, artist, album = futures[future] try: status = future.result() except Exception as exception: stats["errors"] += 1 logging.getLogger("sacad_r").error("Error occured while searching cover for " "'%s' by '%s' from '%s': %s %s" % (album, artist, path, exception.__class__.__qualname__, exception)) else: if status: if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: try: embed_album_art(cover_filepath, path) except Exception as exception: stats["errors"] += 1 logging.getLogger("sacad_r").error("Error occured while embedding cover for " "'%s' by '%s' from '%s': %s %s" % (album, artist, path, exception.__class__.__qualname__, exception)) else: stats["ok"] += 1 finally: os.remove(cover_filepath) else: stats["ok"] += 1 else: stats["no result found"] += 1 logging.getLogger("sacad_r").warning("Unable to find cover for '%s' by '%s' from '%s'" % (album, artist, path)) progress.set_postfix(stats, refresh=False) progress.update(1) # post work async_loop = asyncio.get_event_loop() i = 0 # default event loop on Windows has a 512 fd limit, see https://docs.python.org/3/library/asyncio-eventloops.html#windows # also on Linux default max open fd limit is 1024 (ulimit -n) # so work in smaller chunks to avoid hitting fd limit # this also updates the progress faster (instead of working on all searches, work on finishing the chunk before # getting to the next one) work_chunk_length = 16 for work_chunk in ichunk(work.items(), work_chunk_length): futures = {} for i, (path, (artist, album)) in enumerate(work_chunk, i): if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: cover_filepath = os.path.join(tmp_dir, "%00u.%s" % (i, args.format.name.lower())) else: cover_filepath = os.path.join(path, args.filename) coroutine = sacad.search_and_download(album, artist, args.format, args.size, cover_filepath, size_tolerance_prct=args.size_tolerance_prct, amazon_tlds=args.amazon_tlds, no_lq_sources=args.no_lq_sources, async_loop=async_loop) future = asyncio.ensure_future(coroutine, loop=async_loop) futures[future] = (path, cover_filepath, artist, album) for future in futures: future.add_done_callback(update_progress) # wait for end of work root_future = asyncio.gather(*futures.keys(), loop=async_loop) async_loop.run_until_complete(root_future)
python
def get_covers(work, args): """ Get missing covers. """ with contextlib.ExitStack() as cm: if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: tmp_prefix = "%s_" % (os.path.splitext(os.path.basename(inspect.getfile(inspect.currentframe())))[0]) tmp_dir = cm.enter_context(tempfile.TemporaryDirectory(prefix=tmp_prefix)) # setup progress report stats = collections.OrderedDict(((k, 0) for k in("ok", "errors", "no result found"))) progress = cm.enter_context(tqdm.tqdm(total=len(work), miniters=1, desc="Searching covers", unit="cover", postfix=stats)) cm.enter_context(tqdm_logging.redirect_logging(progress)) def update_progress(future): path, cover_filepath, artist, album = futures[future] try: status = future.result() except Exception as exception: stats["errors"] += 1 logging.getLogger("sacad_r").error("Error occured while searching cover for " "'%s' by '%s' from '%s': %s %s" % (album, artist, path, exception.__class__.__qualname__, exception)) else: if status: if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: try: embed_album_art(cover_filepath, path) except Exception as exception: stats["errors"] += 1 logging.getLogger("sacad_r").error("Error occured while embedding cover for " "'%s' by '%s' from '%s': %s %s" % (album, artist, path, exception.__class__.__qualname__, exception)) else: stats["ok"] += 1 finally: os.remove(cover_filepath) else: stats["ok"] += 1 else: stats["no result found"] += 1 logging.getLogger("sacad_r").warning("Unable to find cover for '%s' by '%s' from '%s'" % (album, artist, path)) progress.set_postfix(stats, refresh=False) progress.update(1) # post work async_loop = asyncio.get_event_loop() i = 0 # default event loop on Windows has a 512 fd limit, see https://docs.python.org/3/library/asyncio-eventloops.html#windows # also on Linux default max open fd limit is 1024 (ulimit -n) # so work in smaller chunks to avoid hitting fd limit # this also updates the progress faster (instead of working on all searches, work on finishing the chunk before # getting to the next one) work_chunk_length = 16 for work_chunk in ichunk(work.items(), work_chunk_length): futures = {} for i, (path, (artist, album)) in enumerate(work_chunk, i): if args.filename == EMBEDDED_ALBUM_ART_SYMBOL: cover_filepath = os.path.join(tmp_dir, "%00u.%s" % (i, args.format.name.lower())) else: cover_filepath = os.path.join(path, args.filename) coroutine = sacad.search_and_download(album, artist, args.format, args.size, cover_filepath, size_tolerance_prct=args.size_tolerance_prct, amazon_tlds=args.amazon_tlds, no_lq_sources=args.no_lq_sources, async_loop=async_loop) future = asyncio.ensure_future(coroutine, loop=async_loop) futures[future] = (path, cover_filepath, artist, album) for future in futures: future.add_done_callback(update_progress) # wait for end of work root_future = asyncio.gather(*futures.keys(), loop=async_loop) async_loop.run_until_complete(root_future)
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Get missing covers.
[ "Get", "missing", "covers", "." ]
train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/recurse.py#L186-L273
desbma/sacad
sacad/mkstemp_ctx.py
mkstemp
def mkstemp(*args, **kwargs): """ Context manager similar to tempfile.NamedTemporaryFile except the file is not deleted on close, and only the filepath is returned .. warnings:: Unlike tempfile.mkstemp, this is not secure """ fd, filename = tempfile.mkstemp(*args, **kwargs) os.close(fd) try: yield filename finally: os.remove(filename)
python
def mkstemp(*args, **kwargs): """ Context manager similar to tempfile.NamedTemporaryFile except the file is not deleted on close, and only the filepath is returned .. warnings:: Unlike tempfile.mkstemp, this is not secure """ fd, filename = tempfile.mkstemp(*args, **kwargs) os.close(fd) try: yield filename finally: os.remove(filename)
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Context manager similar to tempfile.NamedTemporaryFile except the file is not deleted on close, and only the filepath is returned .. warnings:: Unlike tempfile.mkstemp, this is not secure
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/mkstemp_ctx.py#L7-L18
desbma/sacad
sacad/tqdm_logging.py
redirect_logging
def redirect_logging(tqdm_obj, logger=logging.getLogger()): """ Context manager to redirect logging to a TqdmLoggingHandler object and then restore the original. """ # remove current handler assert(len(logger.handlers) == 1) prev_handler = logger.handlers[0] logger.removeHandler(prev_handler) # add tqdm handler tqdm_handler = TqdmLoggingHandler(tqdm_obj) if prev_handler.formatter is not None: tqdm_handler.setFormatter(prev_handler.formatter) logger.addHandler(tqdm_handler) try: yield finally: # restore handler logger.removeHandler(tqdm_handler) logger.addHandler(prev_handler)
python
def redirect_logging(tqdm_obj, logger=logging.getLogger()): """ Context manager to redirect logging to a TqdmLoggingHandler object and then restore the original. """ # remove current handler assert(len(logger.handlers) == 1) prev_handler = logger.handlers[0] logger.removeHandler(prev_handler) # add tqdm handler tqdm_handler = TqdmLoggingHandler(tqdm_obj) if prev_handler.formatter is not None: tqdm_handler.setFormatter(prev_handler.formatter) logger.addHandler(tqdm_handler) try: yield finally: # restore handler logger.removeHandler(tqdm_handler) logger.addHandler(prev_handler)
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Context manager to redirect logging to a TqdmLoggingHandler object and then restore the original.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/tqdm_logging.py#L21-L39
desbma/sacad
sacad/sources/base.py
CoverSource.search
async def search(self, album, artist): """ Search for a given album/artist and return an iterable of CoverSourceResult. """ self.logger.debug("Searching with source '%s'..." % (self.__class__.__name__)) album = self.processAlbumString(album) artist = self.processArtistString(artist) url_data = self.getSearchUrl(album, artist) if isinstance(url_data, tuple): url, post_data = url_data else: url = url_data post_data = None try: store_in_cache_callback, api_data = await self.fetchResults(url, post_data) results = await self.parseResults(api_data) except Exception as e: # raise self.logger.warning("Search with source '%s' failed: %s %s" % (self.__class__.__name__, e.__class__.__qualname__, e)) return () else: if results: # only store in cache if parsing succeeds and we have results await store_in_cache_callback() # get metadata futures = [] for result in filter(operator.methodcaller("needMetadataUpdate"), results): coroutine = result.updateImageMetadata() future = asyncio.ensure_future(coroutine) futures.append(future) if futures: await asyncio.wait(futures) for future in futures: future.result() # raise pending exception if any # filter results_excluded_count = 0 reference_only_count = 0 results_kept = [] for result in results: if ((result.size[0] + (self.size_tolerance_prct * self.target_size / 100) < self.target_size) or # skip too small images (result.size[1] + (self.size_tolerance_prct * self.target_size / 100) < self.target_size) or (result.format is None) or # unknown format result.needMetadataUpdate()): # if still true, it means we failed to grab metadata, so exclude it if result.source_quality is CoverSourceQuality.REFERENCE: # we keep this result just for the reference, it will be excluded from the results result.is_only_reference = True results_kept.append(result) reference_only_count += 1 else: results_excluded_count += 1 else: results_kept.append(result) result_kept_count = len(results_kept) - reference_only_count # log self.logger.info("Got %u relevant (%u excluded) results from source '%s'" % (result_kept_count, results_excluded_count + reference_only_count, self.__class__.__name__)) for result in itertools.filterfalse(operator.attrgetter("is_only_reference"), results_kept): self.logger.debug("%s %s%s %4dx%4d %s%s" % (result.__class__.__name__, ("(%02d) " % (result.rank)) if result.rank is not None else "", result.format.name, result.size[0], result.size[1], result.urls[0], " [x%u]" % (len(result.urls)) if len(result.urls) > 1 else "")) return results_kept
python
async def search(self, album, artist): """ Search for a given album/artist and return an iterable of CoverSourceResult. """ self.logger.debug("Searching with source '%s'..." % (self.__class__.__name__)) album = self.processAlbumString(album) artist = self.processArtistString(artist) url_data = self.getSearchUrl(album, artist) if isinstance(url_data, tuple): url, post_data = url_data else: url = url_data post_data = None try: store_in_cache_callback, api_data = await self.fetchResults(url, post_data) results = await self.parseResults(api_data) except Exception as e: # raise self.logger.warning("Search with source '%s' failed: %s %s" % (self.__class__.__name__, e.__class__.__qualname__, e)) return () else: if results: # only store in cache if parsing succeeds and we have results await store_in_cache_callback() # get metadata futures = [] for result in filter(operator.methodcaller("needMetadataUpdate"), results): coroutine = result.updateImageMetadata() future = asyncio.ensure_future(coroutine) futures.append(future) if futures: await asyncio.wait(futures) for future in futures: future.result() # raise pending exception if any # filter results_excluded_count = 0 reference_only_count = 0 results_kept = [] for result in results: if ((result.size[0] + (self.size_tolerance_prct * self.target_size / 100) < self.target_size) or # skip too small images (result.size[1] + (self.size_tolerance_prct * self.target_size / 100) < self.target_size) or (result.format is None) or # unknown format result.needMetadataUpdate()): # if still true, it means we failed to grab metadata, so exclude it if result.source_quality is CoverSourceQuality.REFERENCE: # we keep this result just for the reference, it will be excluded from the results result.is_only_reference = True results_kept.append(result) reference_only_count += 1 else: results_excluded_count += 1 else: results_kept.append(result) result_kept_count = len(results_kept) - reference_only_count # log self.logger.info("Got %u relevant (%u excluded) results from source '%s'" % (result_kept_count, results_excluded_count + reference_only_count, self.__class__.__name__)) for result in itertools.filterfalse(operator.attrgetter("is_only_reference"), results_kept): self.logger.debug("%s %s%s %4dx%4d %s%s" % (result.__class__.__name__, ("(%02d) " % (result.rank)) if result.rank is not None else "", result.format.name, result.size[0], result.size[1], result.urls[0], " [x%u]" % (len(result.urls)) if len(result.urls) > 1 else "")) return results_kept
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Search for a given album/artist and return an iterable of CoverSourceResult.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/base.py#L60-L128
desbma/sacad
sacad/sources/base.py
CoverSource.fetchResults
async def fetchResults(self, url, post_data=None): """ Get a (store in cache callback, search results) tuple from an URL. """ if post_data is not None: self.logger.debug("Querying URL '%s' %s..." % (url, dict(post_data))) else: self.logger.debug("Querying URL '%s'..." % (url)) headers = {} self.updateHttpHeaders(headers) return await self.http.query(url, post_data=post_data, headers=headers, cache=__class__.api_cache)
python
async def fetchResults(self, url, post_data=None): """ Get a (store in cache callback, search results) tuple from an URL. """ if post_data is not None: self.logger.debug("Querying URL '%s' %s..." % (url, dict(post_data))) else: self.logger.debug("Querying URL '%s'..." % (url)) headers = {} self.updateHttpHeaders(headers) return await self.http.query(url, post_data=post_data, headers=headers, cache=__class__.api_cache)
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Get a (store in cache callback, search results) tuple from an URL.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/base.py#L130-L141
desbma/sacad
sacad/sources/base.py
CoverSource.probeUrl
async def probeUrl(self, url, response_headers=None): """ Probe URL reachability from cache or HEAD request. """ self.logger.debug("Probing URL '%s'..." % (url)) headers = {} self.updateHttpHeaders(headers) resp_headers = {} resp_ok = await self.http.isReachable(url, headers=headers, response_headers=resp_headers, cache=__class__.probe_cache) if response_headers is not None: response_headers.update(resp_headers) return resp_ok
python
async def probeUrl(self, url, response_headers=None): """ Probe URL reachability from cache or HEAD request. """ self.logger.debug("Probing URL '%s'..." % (url)) headers = {} self.updateHttpHeaders(headers) resp_headers = {} resp_ok = await self.http.isReachable(url, headers=headers, response_headers=resp_headers, cache=__class__.probe_cache) if response_headers is not None: response_headers.update(resp_headers) return resp_ok
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Probe URL reachability from cache or HEAD request.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/base.py#L143-L157
desbma/sacad
sacad/sources/base.py
CoverSource.unaccentuate
def unaccentuate(s): """ Replace accentuated chars in string by their non accentuated equivalent. """ return "".join(c for c in unicodedata.normalize("NFKD", s) if not unicodedata.combining(c))
python
def unaccentuate(s): """ Replace accentuated chars in string by their non accentuated equivalent. """ return "".join(c for c in unicodedata.normalize("NFKD", s) if not unicodedata.combining(c))
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Replace accentuated chars in string by their non accentuated equivalent.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/base.py#L165-L167
desbma/sacad
sacad/sources/base.py
CoverSource.unpunctuate
def unpunctuate(s, *, char_blacklist=string.punctuation): """ Remove punctuation from string s. """ # remove punctuation s = "".join(c for c in s if c not in char_blacklist) # remove consecutive spaces return " ".join(filter(None, s.split(" ")))
python
def unpunctuate(s, *, char_blacklist=string.punctuation): """ Remove punctuation from string s. """ # remove punctuation s = "".join(c for c in s if c not in char_blacklist) # remove consecutive spaces return " ".join(filter(None, s.split(" ")))
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Remove punctuation from string s.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/base.py#L170-L175
desbma/sacad
sacad/sources/amazoncd.py
AmazonCdCoverSource.getSearchUrl
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ params = collections.OrderedDict() params["search-alias"] = "popular" params["field-artist"] = artist params["field-title"] = album params["sort"] = "relevancerank" return __class__.assembleUrl(self.base_url, params)
python
def getSearchUrl(self, album, artist): """ See CoverSource.getSearchUrl. """ params = collections.OrderedDict() params["search-alias"] = "popular" params["field-artist"] = artist params["field-title"] = album params["sort"] = "relevancerank" return __class__.assembleUrl(self.base_url, params)
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See CoverSource.getSearchUrl.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/amazoncd.py#L46-L53
desbma/sacad
sacad/sources/amazoncd.py
AmazonCdCoverSource.parseResults
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse page parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("utf-8", "ignore"), parser) for page_struct_version, result_selector in enumerate(__class__.RESULTS_SELECTORS): result_nodes = result_selector(html) if result_nodes: break for rank, result_node in enumerate(result_nodes, 1): try: img_node = __class__.IMG_SELECTORS[page_struct_version](result_node)[0] except IndexError: # no image for that product continue # get thumbnail & full image url thumbnail_url = img_node.get("src") url_parts = thumbnail_url.rsplit(".", 2) img_url = ".".join((url_parts[0], url_parts[2])) # assume size is fixed size = (500, 500) check_metadata = CoverImageMetadata.SIZE # try to get higher res image... if ((self.target_size > size[0]) and # ...only if needed (rank <= 3)): # and only for first 3 results because this is time # consuming (1 more GET request per result) product_url = __class__.PRODUCT_LINK_SELECTORS[page_struct_version](result_node)[0].get("href") product_url_split = urllib.parse.urlsplit(product_url) if not product_url_split.scheme: # relative redirect url product_url_query = urllib.parse.parse_qsl(product_url_split.query) product_url_query = collections.OrderedDict(product_url_query) try: # needed if page_struct_version == 1 product_url = product_url_query["url"] except KeyError: # page_struct_version == 0, make url absolute product_url = urllib.parse.urljoin(self.base_url, product_url) product_url_split = urllib.parse.urlsplit(product_url) product_url_query = urllib.parse.parse_qsl(product_url_split.query) product_url_query = collections.OrderedDict(product_url_query) try: # remove timestamp from url to improve future cache hit rate del product_url_query["qid"] except KeyError: pass product_url_query = urllib.parse.urlencode(product_url_query) product_url_no_ts = urllib.parse.urlunsplit(product_url_split[:3] + (product_url_query,) + product_url_split[4:]) store_in_cache_callback, product_page_data = await self.fetchResults(product_url_no_ts) product_page_html = lxml.etree.XML(product_page_data.decode("latin-1"), parser) try: img_node = __class__.PRODUCT_PAGE_IMG_SELECTOR(product_page_html)[0] except IndexError: # unable to get better image pass else: better_img_url = img_node.get("data-old-hires") # img_node.get("data-a-dynamic-image") contains json with image urls too, but they are not larger than # previous 500px image and are often covered by autorip badges (can be removed by cleaning url though) if better_img_url: img_url = better_img_url size_url_hint = img_url.rsplit(".", 2)[1].strip("_") assert(size_url_hint.startswith("SL")) size_url_hint = int(size_url_hint[2:]) size = (size_url_hint, size_url_hint) check_metadata = CoverImageMetadata.NONE await store_in_cache_callback() # assume format is always jpg format = CoverImageFormat.JPEG # add result results.append(AmazonCdCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=check_metadata)) return results
python
async def parseResults(self, api_data): """ See CoverSource.parseResults. """ results = [] # parse page parser = lxml.etree.HTMLParser() html = lxml.etree.XML(api_data.decode("utf-8", "ignore"), parser) for page_struct_version, result_selector in enumerate(__class__.RESULTS_SELECTORS): result_nodes = result_selector(html) if result_nodes: break for rank, result_node in enumerate(result_nodes, 1): try: img_node = __class__.IMG_SELECTORS[page_struct_version](result_node)[0] except IndexError: # no image for that product continue # get thumbnail & full image url thumbnail_url = img_node.get("src") url_parts = thumbnail_url.rsplit(".", 2) img_url = ".".join((url_parts[0], url_parts[2])) # assume size is fixed size = (500, 500) check_metadata = CoverImageMetadata.SIZE # try to get higher res image... if ((self.target_size > size[0]) and # ...only if needed (rank <= 3)): # and only for first 3 results because this is time # consuming (1 more GET request per result) product_url = __class__.PRODUCT_LINK_SELECTORS[page_struct_version](result_node)[0].get("href") product_url_split = urllib.parse.urlsplit(product_url) if not product_url_split.scheme: # relative redirect url product_url_query = urllib.parse.parse_qsl(product_url_split.query) product_url_query = collections.OrderedDict(product_url_query) try: # needed if page_struct_version == 1 product_url = product_url_query["url"] except KeyError: # page_struct_version == 0, make url absolute product_url = urllib.parse.urljoin(self.base_url, product_url) product_url_split = urllib.parse.urlsplit(product_url) product_url_query = urllib.parse.parse_qsl(product_url_split.query) product_url_query = collections.OrderedDict(product_url_query) try: # remove timestamp from url to improve future cache hit rate del product_url_query["qid"] except KeyError: pass product_url_query = urllib.parse.urlencode(product_url_query) product_url_no_ts = urllib.parse.urlunsplit(product_url_split[:3] + (product_url_query,) + product_url_split[4:]) store_in_cache_callback, product_page_data = await self.fetchResults(product_url_no_ts) product_page_html = lxml.etree.XML(product_page_data.decode("latin-1"), parser) try: img_node = __class__.PRODUCT_PAGE_IMG_SELECTOR(product_page_html)[0] except IndexError: # unable to get better image pass else: better_img_url = img_node.get("data-old-hires") # img_node.get("data-a-dynamic-image") contains json with image urls too, but they are not larger than # previous 500px image and are often covered by autorip badges (can be removed by cleaning url though) if better_img_url: img_url = better_img_url size_url_hint = img_url.rsplit(".", 2)[1].strip("_") assert(size_url_hint.startswith("SL")) size_url_hint = int(size_url_hint[2:]) size = (size_url_hint, size_url_hint) check_metadata = CoverImageMetadata.NONE await store_in_cache_callback() # assume format is always jpg format = CoverImageFormat.JPEG # add result results.append(AmazonCdCoverSourceResult(img_url, size, format, thumbnail_url=thumbnail_url, source=self, rank=rank, check_metadata=check_metadata)) return results
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See CoverSource.parseResults.
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train
https://github.com/desbma/sacad/blob/a7a010c4d9618a0c90927f1acb530101ca05fac4/sacad/sources/amazoncd.py#L59-L142
fogleman/pg
pg/core.py
delete_all
def delete_all(obj): '''Calls `delete()` on all members of `obj` that are recognized as instances of `pg` objects.''' types = tuple([ Shader, Mesh, VertexBuffer, IndexBuffer, Texture, Program, Context, ]) for name in dir(obj): child = getattr(obj, name) if isinstance(child, types): child.delete()
python
def delete_all(obj): '''Calls `delete()` on all members of `obj` that are recognized as instances of `pg` objects.''' types = tuple([ Shader, Mesh, VertexBuffer, IndexBuffer, Texture, Program, Context, ]) for name in dir(obj): child = getattr(obj, name) if isinstance(child, types): child.delete()
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Calls `delete()` on all members of `obj` that are recognized as instances of `pg` objects.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/core.py#L14-L29
fogleman/pg
pg/glfw.py
_glfw_get_version
def _glfw_get_version(filename): ''' Queries and returns the library version tuple or None by using a subprocess. ''' version_checker_source = """ import sys import ctypes def get_version(library_handle): ''' Queries and returns the library version tuple or None. ''' major_value = ctypes.c_int(0) major = ctypes.pointer(major_value) minor_value = ctypes.c_int(0) minor = ctypes.pointer(minor_value) rev_value = ctypes.c_int(0) rev = ctypes.pointer(rev_value) if hasattr(library_handle, 'glfwGetVersion'): library_handle.glfwGetVersion(major, minor, rev) version = (major_value.value, minor_value.value, rev_value.value) return version else: return None try: input_func = raw_input except NameError: input_func = input filename = input_func().strip() try: library_handle = ctypes.CDLL(filename) except OSError: pass else: version = get_version(library_handle) print(version) """ args = [sys.executable, '-c', textwrap.dedent(version_checker_source)] process = subprocess.Popen(args, universal_newlines=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE) out = process.communicate(_to_char_p(filename))[0] out = out.strip() if out: return eval(out) else: return None
python
def _glfw_get_version(filename): ''' Queries and returns the library version tuple or None by using a subprocess. ''' version_checker_source = """ import sys import ctypes def get_version(library_handle): ''' Queries and returns the library version tuple or None. ''' major_value = ctypes.c_int(0) major = ctypes.pointer(major_value) minor_value = ctypes.c_int(0) minor = ctypes.pointer(minor_value) rev_value = ctypes.c_int(0) rev = ctypes.pointer(rev_value) if hasattr(library_handle, 'glfwGetVersion'): library_handle.glfwGetVersion(major, minor, rev) version = (major_value.value, minor_value.value, rev_value.value) return version else: return None try: input_func = raw_input except NameError: input_func = input filename = input_func().strip() try: library_handle = ctypes.CDLL(filename) except OSError: pass else: version = get_version(library_handle) print(version) """ args = [sys.executable, '-c', textwrap.dedent(version_checker_source)] process = subprocess.Popen(args, universal_newlines=True, stdin=subprocess.PIPE, stdout=subprocess.PIPE) out = process.communicate(_to_char_p(filename))[0] out = out.strip() if out: return eval(out) else: return None
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L84-L135
fogleman/pg
pg/glfw.py
set_error_callback
def set_error_callback(cbfun): ''' Sets the error callback. Wrapper for: GLFWerrorfun glfwSetErrorCallback(GLFWerrorfun cbfun); ''' global _error_callback previous_callback = _error_callback if cbfun is None: cbfun = 0 c_cbfun = _GLFWerrorfun(cbfun) _error_callback = (cbfun, c_cbfun) cbfun = c_cbfun _glfw.glfwSetErrorCallback(cbfun) if previous_callback is not None and previous_callback[0] != 0: return previous_callback[0]
python
def set_error_callback(cbfun): ''' Sets the error callback. Wrapper for: GLFWerrorfun glfwSetErrorCallback(GLFWerrorfun cbfun); ''' global _error_callback previous_callback = _error_callback if cbfun is None: cbfun = 0 c_cbfun = _GLFWerrorfun(cbfun) _error_callback = (cbfun, c_cbfun) cbfun = c_cbfun _glfw.glfwSetErrorCallback(cbfun) if previous_callback is not None and previous_callback[0] != 0: return previous_callback[0]
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Sets the error callback. Wrapper for: GLFWerrorfun glfwSetErrorCallback(GLFWerrorfun cbfun);
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L579-L595
fogleman/pg
pg/glfw.py
destroy_window
def destroy_window(window): ''' Destroys the specified window and its context. Wrapper for: void glfwDestroyWindow(GLFWwindow* window); ''' _glfw.glfwDestroyWindow(window) window_addr = ctypes.cast(ctypes.pointer(window), ctypes.POINTER(ctypes.c_ulong)).contents.value for callback_repository in _callback_repositories: if window_addr in callback_repository: del callback_repository[window_addr]
python
def destroy_window(window): ''' Destroys the specified window and its context. Wrapper for: void glfwDestroyWindow(GLFWwindow* window); ''' _glfw.glfwDestroyWindow(window) window_addr = ctypes.cast(ctypes.pointer(window), ctypes.POINTER(ctypes.c_ulong)).contents.value for callback_repository in _callback_repositories: if window_addr in callback_repository: del callback_repository[window_addr]
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Destroys the specified window and its context. Wrapper for: void glfwDestroyWindow(GLFWwindow* window);
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L798-L810
fogleman/pg
pg/glfw.py
_GLFWvidmode.unwrap
def unwrap(self): ''' Returns a nested python sequence. ''' size = self.width, self.height bits = self.red_bits, self.green_bits, self.blue_bits return size, bits, self.refresh_rate
python
def unwrap(self): ''' Returns a nested python sequence. ''' size = self.width, self.height bits = self.red_bits, self.green_bits, self.blue_bits return size, bits, self.refresh_rate
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Returns a nested python sequence.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L190-L196
fogleman/pg
pg/glfw.py
_GLFWgammaramp.wrap
def wrap(self, gammaramp): ''' Wraps a nested python sequence. ''' red, green, blue = gammaramp size = min(len(red), len(green), len(blue)) array_type = ctypes.c_ushort*size self.size = ctypes.c_uint(size) self.red_array = array_type() self.green_array = array_type() self.blue_array = array_type() for i in range(self.size): self.red_array[i] = int(red[i]*65535) self.green_array[i] = int(green[i]*65535) self.blue_array[i] = int(blue[i]*65535) pointer_type = ctypes.POINTER(ctypes.c_ushort) self.red = ctypes.cast(self.red_array, pointer_type) self.green = ctypes.cast(self.green_array, pointer_type) self.blue = ctypes.cast(self.blue_array, pointer_type)
python
def wrap(self, gammaramp): ''' Wraps a nested python sequence. ''' red, green, blue = gammaramp size = min(len(red), len(green), len(blue)) array_type = ctypes.c_ushort*size self.size = ctypes.c_uint(size) self.red_array = array_type() self.green_array = array_type() self.blue_array = array_type() for i in range(self.size): self.red_array[i] = int(red[i]*65535) self.green_array[i] = int(green[i]*65535) self.blue_array[i] = int(blue[i]*65535) pointer_type = ctypes.POINTER(ctypes.c_ushort) self.red = ctypes.cast(self.red_array, pointer_type) self.green = ctypes.cast(self.green_array, pointer_type) self.blue = ctypes.cast(self.blue_array, pointer_type)
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L219-L237
fogleman/pg
pg/glfw.py
_GLFWgammaramp.unwrap
def unwrap(self): ''' Returns a nested python sequence. ''' red = [self.red[i]/65535.0 for i in range(self.size)] green = [self.green[i]/65535.0 for i in range(self.size)] blue = [self.blue[i]/65535.0 for i in range(self.size)] return red, green, blue
python
def unwrap(self): ''' Returns a nested python sequence. ''' red = [self.red[i]/65535.0 for i in range(self.size)] green = [self.green[i]/65535.0 for i in range(self.size)] blue = [self.blue[i]/65535.0 for i in range(self.size)] return red, green, blue
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/glfw.py#L239-L246
fogleman/pg
pg/util.py
hex_color
def hex_color(value): '''Accepts a hexadecimal color `value` in the format ``0xrrggbb`` and returns an (r, g, b) tuple where 0.0 <= r, g, b <= 1.0. ''' r = ((value >> (8 * 2)) & 255) / 255.0 g = ((value >> (8 * 1)) & 255) / 255.0 b = ((value >> (8 * 0)) & 255) / 255.0 return (r, g, b)
python
def hex_color(value): '''Accepts a hexadecimal color `value` in the format ``0xrrggbb`` and returns an (r, g, b) tuple where 0.0 <= r, g, b <= 1.0. ''' r = ((value >> (8 * 2)) & 255) / 255.0 g = ((value >> (8 * 1)) & 255) / 255.0 b = ((value >> (8 * 0)) & 255) / 255.0 return (r, g, b)
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Accepts a hexadecimal color `value` in the format ``0xrrggbb`` and returns an (r, g, b) tuple where 0.0 <= r, g, b <= 1.0.
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train
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fogleman/pg
pg/util.py
normalize
def normalize(vector): '''Normalizes the `vector` so that its length is 1. `vector` can have any number of components. ''' d = sum(x * x for x in vector) ** 0.5 return tuple(x / d for x in vector)
python
def normalize(vector): '''Normalizes the `vector` so that its length is 1. `vector` can have any number of components. ''' d = sum(x * x for x in vector) ** 0.5 return tuple(x / d for x in vector)
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Normalizes the `vector` so that its length is 1. `vector` can have any number of components.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L14-L19
fogleman/pg
pg/util.py
distance
def distance(p1, p2): '''Computes and returns the distance between two points, `p1` and `p2`. The points can have any number of components. ''' return sum((a - b) ** 2 for a, b in zip(p1, p2)) ** 0.5
python
def distance(p1, p2): '''Computes and returns the distance between two points, `p1` and `p2`. The points can have any number of components. ''' return sum((a - b) ** 2 for a, b in zip(p1, p2)) ** 0.5
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Computes and returns the distance between two points, `p1` and `p2`. The points can have any number of components.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L21-L25
fogleman/pg
pg/util.py
cross
def cross(v1, v2): '''Computes the cross product of two vectors. ''' return ( v1[1] * v2[2] - v1[2] * v2[1], v1[2] * v2[0] - v1[0] * v2[2], v1[0] * v2[1] - v1[1] * v2[0], )
python
def cross(v1, v2): '''Computes the cross product of two vectors. ''' return ( v1[1] * v2[2] - v1[2] * v2[1], v1[2] * v2[0] - v1[0] * v2[2], v1[0] * v2[1] - v1[1] * v2[0], )
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Computes the cross product of two vectors.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L27-L34
fogleman/pg
pg/util.py
dot
def dot(v1, v2): '''Computes the dot product of two vectors. ''' x1, y1, z1 = v1 x2, y2, z2 = v2 return x1 * x2 + y1 * y2 + z1 * z2
python
def dot(v1, v2): '''Computes the dot product of two vectors. ''' x1, y1, z1 = v1 x2, y2, z2 = v2 return x1 * x2 + y1 * y2 + z1 * z2
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train
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fogleman/pg
pg/util.py
add
def add(v1, v2): '''Adds two vectors. ''' return tuple(a + b for a, b in zip(v1, v2))
python
def add(v1, v2): '''Adds two vectors. ''' return tuple(a + b for a, b in zip(v1, v2))
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Adds two vectors.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L43-L46
fogleman/pg
pg/util.py
sub
def sub(v1, v2): '''Subtracts two vectors. ''' return tuple(a - b for a, b in zip(v1, v2))
python
def sub(v1, v2): '''Subtracts two vectors. ''' return tuple(a - b for a, b in zip(v1, v2))
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Subtracts two vectors.
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train
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fogleman/pg
pg/util.py
interpolate
def interpolate(v1, v2, t): '''Interpolate from one vector to another. ''' return add(v1, mul(sub(v2, v1), t))
python
def interpolate(v1, v2, t): '''Interpolate from one vector to another. ''' return add(v1, mul(sub(v2, v1), t))
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Interpolate from one vector to another.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L63-L66
fogleman/pg
pg/util.py
normal_from_points
def normal_from_points(a, b, c): '''Computes a normal vector given three points. ''' x1, y1, z1 = a x2, y2, z2 = b x3, y3, z3 = c ab = (x2 - x1, y2 - y1, z2 - z1) ac = (x3 - x1, y3 - y1, z3 - z1) x, y, z = cross(ab, ac) d = (x * x + y * y + z * z) ** 0.5 return (x / d, y / d, z / d)
python
def normal_from_points(a, b, c): '''Computes a normal vector given three points. ''' x1, y1, z1 = a x2, y2, z2 = b x3, y3, z3 = c ab = (x2 - x1, y2 - y1, z2 - z1) ac = (x3 - x1, y3 - y1, z3 - z1) x, y, z = cross(ab, ac) d = (x * x + y * y + z * z) ** 0.5 return (x / d, y / d, z / d)
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Computes a normal vector given three points.
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train
https://github.com/fogleman/pg/blob/124ea3803c788b2c98c4f3a428e5d26842a67b58/pg/util.py#L68-L78
fogleman/pg
pg/util.py
smooth_normals
def smooth_normals(positions, normals): '''Assigns an averaged normal to each position based on all of the normals originally used for the position. ''' lookup = defaultdict(list) for position, normal in zip(positions, normals): lookup[position].append(normal) result = [] for position in positions: tx = ty = tz = 0 for x, y, z in lookup[position]: tx += x ty += y tz += z d = (tx * tx + ty * ty + tz * tz) ** 0.5 result.append((tx / d, ty / d, tz / d)) return result
python
def smooth_normals(positions, normals): '''Assigns an averaged normal to each position based on all of the normals originally used for the position. ''' lookup = defaultdict(list) for position, normal in zip(positions, normals): lookup[position].append(normal) result = [] for position in positions: tx = ty = tz = 0 for x, y, z in lookup[position]: tx += x ty += y tz += z d = (tx * tx + ty * ty + tz * tz) ** 0.5 result.append((tx / d, ty / d, tz / d)) return result
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Assigns an averaged normal to each position based on all of the normals originally used for the position.
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train
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fogleman/pg
pg/util.py
bounding_box
def bounding_box(positions): '''Computes the bounding box for a list of 3-dimensional points. ''' (x0, y0, z0) = (x1, y1, z1) = positions[0] for x, y, z in positions: x0 = min(x0, x) y0 = min(y0, y) z0 = min(z0, z) x1 = max(x1, x) y1 = max(y1, y) z1 = max(z1, z) return (x0, y0, z0), (x1, y1, z1)
python
def bounding_box(positions): '''Computes the bounding box for a list of 3-dimensional points. ''' (x0, y0, z0) = (x1, y1, z1) = positions[0] for x, y, z in positions: x0 = min(x0, x) y0 = min(y0, y) z0 = min(z0, z) x1 = max(x1, x) y1 = max(y1, y) z1 = max(z1, z) return (x0, y0, z0), (x1, y1, z1)
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train
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fogleman/pg
pg/util.py
recenter
def recenter(positions): '''Returns a list of new positions centered around the origin. ''' (x0, y0, z0), (x1, y1, z1) = bounding_box(positions) dx = x1 - (x1 - x0) / 2.0 dy = y1 - (y1 - y0) / 2.0 dz = z1 - (z1 - z0) / 2.0 result = [] for x, y, z in positions: result.append((x - dx, y - dy, z - dz)) return result
python
def recenter(positions): '''Returns a list of new positions centered around the origin. ''' (x0, y0, z0), (x1, y1, z1) = bounding_box(positions) dx = x1 - (x1 - x0) / 2.0 dy = y1 - (y1 - y0) / 2.0 dz = z1 - (z1 - z0) / 2.0 result = [] for x, y, z in positions: result.append((x - dx, y - dy, z - dz)) return result
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train
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fogleman/pg
pg/util.py
interleave
def interleave(*args): '''Interleaves the elements of the provided arrays. >>> a = [(0, 0), (1, 0), (2, 0), (3, 0)] >>> b = [(0, 0), (0, 1), (0, 2), (0, 3)] >>> interleave(a, b) [(0, 0, 0, 0), (1, 0, 0, 1), (2, 0, 0, 2), (3, 0, 0, 3)] This is useful for combining multiple vertex attributes into a single vertex buffer. The shader attributes can be assigned a slice of the vertex buffer. ''' result = [] for array in zip(*args): result.append(tuple(flatten(array))) return result
python
def interleave(*args): '''Interleaves the elements of the provided arrays. >>> a = [(0, 0), (1, 0), (2, 0), (3, 0)] >>> b = [(0, 0), (0, 1), (0, 2), (0, 3)] >>> interleave(a, b) [(0, 0, 0, 0), (1, 0, 0, 1), (2, 0, 0, 2), (3, 0, 0, 3)] This is useful for combining multiple vertex attributes into a single vertex buffer. The shader attributes can be assigned a slice of the vertex buffer. ''' result = [] for array in zip(*args): result.append(tuple(flatten(array))) return result
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Interleaves the elements of the provided arrays. >>> a = [(0, 0), (1, 0), (2, 0), (3, 0)] >>> b = [(0, 0), (0, 1), (0, 2), (0, 3)] >>> interleave(a, b) [(0, 0, 0, 0), (1, 0, 0, 1), (2, 0, 0, 2), (3, 0, 0, 3)] This is useful for combining multiple vertex attributes into a single vertex buffer. The shader attributes can be assigned a slice of the vertex buffer.
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train
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fogleman/pg
pg/util.py
distinct
def distinct(iterable, keyfunc=None): '''Yields distinct items from `iterable` in the order that they appear. ''' seen = set() for item in iterable: key = item if keyfunc is None else keyfunc(item) if key not in seen: seen.add(key) yield item
python
def distinct(iterable, keyfunc=None): '''Yields distinct items from `iterable` in the order that they appear. ''' seen = set() for item in iterable: key = item if keyfunc is None else keyfunc(item) if key not in seen: seen.add(key) yield item
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Yields distinct items from `iterable` in the order that they appear.
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train
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fogleman/pg
pg/util.py
ray_triangle_intersection
def ray_triangle_intersection(v1, v2, v3, o, d): '''Computes the distance from a point to a triangle given a ray. ''' eps = 1e-6 e1 = sub(v2, v1) e2 = sub(v3, v1) p = cross(d, e2) det = dot(e1, p) if abs(det) < eps: return None inv = 1.0 / det t = sub(o, v1) u = dot(t, p) * inv if u < 0 or u > 1: return None q = cross(t, e1) v = dot(d, q) * inv if v < 0 or v > 1: return None t = dot(e2, q) * inv if t > eps: return t return None
python
def ray_triangle_intersection(v1, v2, v3, o, d): '''Computes the distance from a point to a triangle given a ray. ''' eps = 1e-6 e1 = sub(v2, v1) e2 = sub(v3, v1) p = cross(d, e2) det = dot(e1, p) if abs(det) < eps: return None inv = 1.0 / det t = sub(o, v1) u = dot(t, p) * inv if u < 0 or u > 1: return None q = cross(t, e1) v = dot(d, q) * inv if v < 0 or v > 1: return None t = dot(e2, q) * inv if t > eps: return t return None
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Computes the distance from a point to a triangle given a ray.
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train
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fogleman/pg
pg/util.py
pack_list
def pack_list(fmt, data): '''Convert a Python list into a ctypes buffer. This appears to be faster than the typical method of creating a ctypes array, e.g. (c_float * len(data))(*data) ''' func = struct.Struct(fmt).pack return create_string_buffer(''.join([func(x) for x in data]))
python
def pack_list(fmt, data): '''Convert a Python list into a ctypes buffer. This appears to be faster than the typical method of creating a ctypes array, e.g. (c_float * len(data))(*data) ''' func = struct.Struct(fmt).pack return create_string_buffer(''.join([func(x) for x in data]))
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train
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wgnet/webium
webium/controls/click.py
Clickable.click
def click(self, jquery=False): """ Click by WebElement, if not, JQuery click """ if jquery: e = JQuery(self) e.click() else: super(Clickable, self).click()
python
def click(self, jquery=False): """ Click by WebElement, if not, JQuery click """ if jquery: e = JQuery(self) e.click() else: super(Clickable, self).click()
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Click by WebElement, if not, JQuery click
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train
https://github.com/wgnet/webium/blob/ccb09876a201e75f5c5810392d4db7a8708b90cb/webium/controls/click.py#L8-L16
wgnet/webium
webium/cookie.py
convert_cookie_to_dict
def convert_cookie_to_dict(cookie, keys_map=WEB_DRIVER_COOKIE_KEYS_MAP): """ Converts an instance of Cookie class from cookielib to a dict. The names of attributes can be changed according to keys_map:. For example, this method can be used to create a cookie which compatible with WebDriver format. :param cookie: Cookie instance received from requests/sessions using url2lib or requests libraries. :param keys_map: The dict to map cookie attributes for different schemas. By default WebDriver format is used. :return: """ cookie_dict = dict() for k in keys_map.keys(): key = _to_unicode_if_str(keys_map[k]) value = _to_unicode_if_str(getattr(cookie, k)) cookie_dict[key] = value return cookie_dict
python
def convert_cookie_to_dict(cookie, keys_map=WEB_DRIVER_COOKIE_KEYS_MAP): """ Converts an instance of Cookie class from cookielib to a dict. The names of attributes can be changed according to keys_map:. For example, this method can be used to create a cookie which compatible with WebDriver format. :param cookie: Cookie instance received from requests/sessions using url2lib or requests libraries. :param keys_map: The dict to map cookie attributes for different schemas. By default WebDriver format is used. :return: """ cookie_dict = dict() for k in keys_map.keys(): key = _to_unicode_if_str(keys_map[k]) value = _to_unicode_if_str(getattr(cookie, k)) cookie_dict[key] = value return cookie_dict
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train
https://github.com/wgnet/webium/blob/ccb09876a201e75f5c5810392d4db7a8708b90cb/webium/cookie.py#L20-L38