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itamarst/crochet | crochet/_eventloop.py | EventualResult._connect_deferred | def _connect_deferred(self, deferred):
"""
Hook up the Deferred that that this will be the result of.
Should only be run in Twisted thread, and only called once.
"""
self._deferred = deferred
# Because we use __del__, we need to make sure there are no cycles
# involving this object, which is why we use a weakref:
def put(result, eventual=weakref.ref(self)):
eventual = eventual()
if eventual:
eventual._set_result(result)
else:
err(result, "Unhandled error in EventualResult")
deferred.addBoth(put) | python | def _connect_deferred(self, deferred):
"""
Hook up the Deferred that that this will be the result of.
Should only be run in Twisted thread, and only called once.
"""
self._deferred = deferred
# Because we use __del__, we need to make sure there are no cycles
# involving this object, which is why we use a weakref:
def put(result, eventual=weakref.ref(self)):
eventual = eventual()
if eventual:
eventual._set_result(result)
else:
err(result, "Unhandled error in EventualResult")
deferred.addBoth(put) | [
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itamarst/crochet | crochet/_eventloop.py | EventualResult._set_result | def _set_result(self, result):
"""
Set the result of the EventualResult, if not already set.
This can only happen in the reactor thread, either as a result of
Deferred firing, or as a result of ResultRegistry.stop(). So, no need
for thread-safety.
"""
if self._result_set.isSet():
return
self._value = result
self._result_set.set() | python | def _set_result(self, result):
"""
Set the result of the EventualResult, if not already set.
This can only happen in the reactor thread, either as a result of
Deferred firing, or as a result of ResultRegistry.stop(). So, no need
for thread-safety.
"""
if self._result_set.isSet():
return
self._value = result
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itamarst/crochet | crochet/_eventloop.py | EventualResult._result | def _result(self, timeout=None):
"""
Return the result, if available.
It may take an unknown amount of time to return the result, so a
timeout option is provided. If the given number of seconds pass with
no result, a TimeoutError will be thrown.
If a previous call timed out, additional calls to this function will
still wait for a result and return it if available. If a result was
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"""
if timeout is None:
warnings.warn(
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stacklevel=3)
# Queue.get(None) won't get interrupted by Ctrl-C...
timeout = 2**31
self._result_set.wait(timeout)
# In Python 2.6 we can't rely on the return result of wait(), so we
# have to check manually:
if not self._result_set.is_set():
raise TimeoutError()
self._result_retrieved = True
return self._value | python | def _result(self, timeout=None):
"""
Return the result, if available.
It may take an unknown amount of time to return the result, so a
timeout option is provided. If the given number of seconds pass with
no result, a TimeoutError will be thrown.
If a previous call timed out, additional calls to this function will
still wait for a result and return it if available. If a result was
returned on one call, additional calls will return/raise the same
result.
"""
if timeout is None:
warnings.warn(
"Unlimited timeouts are deprecated.",
DeprecationWarning,
stacklevel=3)
# Queue.get(None) won't get interrupted by Ctrl-C...
timeout = 2**31
self._result_set.wait(timeout)
# In Python 2.6 we can't rely on the return result of wait(), so we
# have to check manually:
if not self._result_set.is_set():
raise TimeoutError()
self._result_retrieved = True
return self._value | [
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itamarst/crochet | crochet/_eventloop.py | EventualResult.wait | def wait(self, timeout=None):
"""
Return the result, or throw the exception if result is a failure.
It may take an unknown amount of time to return the result, so a
timeout option is provided. If the given number of seconds pass with
no result, a TimeoutError will be thrown.
If a previous call timed out, additional calls to this function will
still wait for a result and return it if available. If a result was
returned or raised on one call, additional calls will return/raise the
same result.
"""
if threadable.isInIOThread():
raise RuntimeError(
"EventualResult.wait() must not be run in the reactor thread.")
if imp.lock_held():
try:
imp.release_lock()
except RuntimeError:
# The lock is held by some other thread. We should be safe
# to continue.
pass
else:
# If EventualResult.wait() is run during module import, if the
# Twisted code that is being run also imports something the
# result will be a deadlock. Even if that is not an issue it
# would prevent importing in other threads until the call
# returns.
raise RuntimeError(
"EventualResult.wait() must not be run at module "
"import time.")
result = self._result(timeout)
if isinstance(result, Failure):
result.raiseException()
return result | python | def wait(self, timeout=None):
"""
Return the result, or throw the exception if result is a failure.
It may take an unknown amount of time to return the result, so a
timeout option is provided. If the given number of seconds pass with
no result, a TimeoutError will be thrown.
If a previous call timed out, additional calls to this function will
still wait for a result and return it if available. If a result was
returned or raised on one call, additional calls will return/raise the
same result.
"""
if threadable.isInIOThread():
raise RuntimeError(
"EventualResult.wait() must not be run in the reactor thread.")
if imp.lock_held():
try:
imp.release_lock()
except RuntimeError:
# The lock is held by some other thread. We should be safe
# to continue.
pass
else:
# If EventualResult.wait() is run during module import, if the
# Twisted code that is being run also imports something the
# result will be a deadlock. Even if that is not an issue it
# would prevent importing in other threads until the call
# returns.
raise RuntimeError(
"EventualResult.wait() must not be run at module "
"import time.")
result = self._result(timeout)
if isinstance(result, Failure):
result.raiseException()
return result | [
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itamarst/crochet | crochet/_eventloop.py | EventualResult.original_failure | def original_failure(self):
"""
Return the underlying Failure object, if the result is an error.
If no result is yet available, or the result was not an error, None is
returned.
This method is useful if you want to get the original traceback for an
error result.
"""
try:
result = self._result(0.0)
except TimeoutError:
return None
if isinstance(result, Failure):
return result
else:
return None | python | def original_failure(self):
"""
Return the underlying Failure object, if the result is an error.
If no result is yet available, or the result was not an error, None is
returned.
This method is useful if you want to get the original traceback for an
error result.
"""
try:
result = self._result(0.0)
except TimeoutError:
return None
if isinstance(result, Failure):
return result
else:
return None | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop._startReapingProcesses | def _startReapingProcesses(self):
"""
Start a LoopingCall that calls reapAllProcesses.
"""
lc = LoopingCall(self._reapAllProcesses)
lc.clock = self._reactor
lc.start(0.1, False) | python | def _startReapingProcesses(self):
"""
Start a LoopingCall that calls reapAllProcesses.
"""
lc = LoopingCall(self._reapAllProcesses)
lc.clock = self._reactor
lc.start(0.1, False) | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop._common_setup | def _common_setup(self):
"""
The minimal amount of setup done by both setup() and no_setup().
"""
self._started = True
self._reactor = self._reactorFactory()
self._registry = ResultRegistry()
# We want to unblock EventualResult regardless of how the reactor is
# run, so we always register this:
self._reactor.addSystemEventTrigger(
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"""
The minimal amount of setup done by both setup() and no_setup().
"""
self._started = True
self._reactor = self._reactorFactory()
self._registry = ResultRegistry()
# We want to unblock EventualResult regardless of how the reactor is
# run, so we always register this:
self._reactor.addSystemEventTrigger(
"before", "shutdown", self._registry.stop) | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop.setup | def setup(self):
"""
Initialize the crochet library.
This starts the reactor in a thread, and connect's Twisted's logs to
Python's standard library logging module.
This must be called at least once before the library can be used, and
can be called multiple times.
"""
if self._started:
return
self._common_setup()
if platform.type == "posix":
self._reactor.callFromThread(self._startReapingProcesses)
if self._startLoggingWithObserver:
observer = ThreadLogObserver(PythonLoggingObserver().emit)
def start():
# Twisted is going to override warnings.showwarning; let's
# make sure that has no effect:
from twisted.python import log
original = log.showwarning
log.showwarning = warnings.showwarning
self._startLoggingWithObserver(observer, False)
log.showwarning = original
self._reactor.callFromThread(start)
# We only want to stop the logging thread once the reactor has
# shut down:
self._reactor.addSystemEventTrigger(
"after", "shutdown", observer.stop)
t = threading.Thread(
target=lambda: self._reactor.run(installSignalHandlers=False),
name="CrochetReactor")
t.start()
self._atexit_register(self._reactor.callFromThread, self._reactor.stop)
self._atexit_register(_store.log_errors)
if self._watchdog_thread is not None:
self._watchdog_thread.start() | python | def setup(self):
"""
Initialize the crochet library.
This starts the reactor in a thread, and connect's Twisted's logs to
Python's standard library logging module.
This must be called at least once before the library can be used, and
can be called multiple times.
"""
if self._started:
return
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if platform.type == "posix":
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if self._startLoggingWithObserver:
observer = ThreadLogObserver(PythonLoggingObserver().emit)
def start():
# Twisted is going to override warnings.showwarning; let's
# make sure that has no effect:
from twisted.python import log
original = log.showwarning
log.showwarning = warnings.showwarning
self._startLoggingWithObserver(observer, False)
log.showwarning = original
self._reactor.callFromThread(start)
# We only want to stop the logging thread once the reactor has
# shut down:
self._reactor.addSystemEventTrigger(
"after", "shutdown", observer.stop)
t = threading.Thread(
target=lambda: self._reactor.run(installSignalHandlers=False),
name="CrochetReactor")
t.start()
self._atexit_register(self._reactor.callFromThread, self._reactor.stop)
self._atexit_register(_store.log_errors)
if self._watchdog_thread is not None:
self._watchdog_thread.start() | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop._run_in_reactor | def _run_in_reactor(self, function, _, args, kwargs):
"""
Implementation: A decorator that ensures the wrapped function runs in
the reactor thread.
When the wrapped function is called, an EventualResult is returned.
"""
def runs_in_reactor(result, args, kwargs):
d = maybeDeferred(function, *args, **kwargs)
result._connect_deferred(d)
result = EventualResult(None, self._reactor)
self._registry.register(result)
self._reactor.callFromThread(runs_in_reactor, result, args, kwargs)
return result | python | def _run_in_reactor(self, function, _, args, kwargs):
"""
Implementation: A decorator that ensures the wrapped function runs in
the reactor thread.
When the wrapped function is called, an EventualResult is returned.
"""
def runs_in_reactor(result, args, kwargs):
d = maybeDeferred(function, *args, **kwargs)
result._connect_deferred(d)
result = EventualResult(None, self._reactor)
self._registry.register(result)
self._reactor.callFromThread(runs_in_reactor, result, args, kwargs)
return result | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop.run_in_reactor | def run_in_reactor(self, function):
"""
A decorator that ensures the wrapped function runs in the
reactor thread.
When the wrapped function is called, an EventualResult is returned.
"""
result = self._run_in_reactor(function)
# Backwards compatibility; use __wrapped__ instead.
try:
result.wrapped_function = function
except AttributeError:
pass
return result | python | def run_in_reactor(self, function):
"""
A decorator that ensures the wrapped function runs in the
reactor thread.
When the wrapped function is called, an EventualResult is returned.
"""
result = self._run_in_reactor(function)
# Backwards compatibility; use __wrapped__ instead.
try:
result.wrapped_function = function
except AttributeError:
pass
return result | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop.wait_for_reactor | def wait_for_reactor(self, function):
"""
DEPRECATED, use wait_for(timeout) instead.
A decorator that ensures the wrapped function runs in the reactor
thread.
When the wrapped function is called, its result is returned or its
exception raised. Deferreds are handled transparently.
"""
warnings.warn(
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DeprecationWarning,
stacklevel=2)
# This will timeout, in theory. In practice the process will be dead
# long before that.
return self.wait_for(2**31)(function) | python | def wait_for_reactor(self, function):
"""
DEPRECATED, use wait_for(timeout) instead.
A decorator that ensures the wrapped function runs in the reactor
thread.
When the wrapped function is called, its result is returned or its
exception raised. Deferreds are handled transparently.
"""
warnings.warn(
"@wait_for_reactor is deprecated, use @wait_for instead",
DeprecationWarning,
stacklevel=2)
# This will timeout, in theory. In practice the process will be dead
# long before that.
return self.wait_for(2**31)(function) | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop.wait_for | def wait_for(self, timeout):
"""
A decorator factory that ensures the wrapped function runs in the
reactor thread.
When the wrapped function is called, its result is returned or its
exception raised. Deferreds are handled transparently. Calls will
timeout after the given number of seconds (a float), raising a
crochet.TimeoutError, and cancelling the Deferred being waited on.
"""
def decorator(function):
@wrapt.decorator
def wrapper(function, _, args, kwargs):
@self.run_in_reactor
def run():
return function(*args, **kwargs)
eventual_result = run()
try:
return eventual_result.wait(timeout)
except TimeoutError:
eventual_result.cancel()
raise
result = wrapper(function)
# Expose underling function for testing purposes; this attribute is
# deprecated, use __wrapped__ instead:
try:
result.wrapped_function = function
except AttributeError:
pass
return result
return decorator | python | def wait_for(self, timeout):
"""
A decorator factory that ensures the wrapped function runs in the
reactor thread.
When the wrapped function is called, its result is returned or its
exception raised. Deferreds are handled transparently. Calls will
timeout after the given number of seconds (a float), raising a
crochet.TimeoutError, and cancelling the Deferred being waited on.
"""
def decorator(function):
@wrapt.decorator
def wrapper(function, _, args, kwargs):
@self.run_in_reactor
def run():
return function(*args, **kwargs)
eventual_result = run()
try:
return eventual_result.wait(timeout)
except TimeoutError:
eventual_result.cancel()
raise
result = wrapper(function)
# Expose underling function for testing purposes; this attribute is
# deprecated, use __wrapped__ instead:
try:
result.wrapped_function = function
except AttributeError:
pass
return result
return decorator | [
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itamarst/crochet | crochet/_eventloop.py | EventLoop.in_reactor | def in_reactor(self, function):
"""
DEPRECATED, use run_in_reactor.
A decorator that ensures the wrapped function runs in the reactor
thread.
The wrapped function will get the reactor passed in as a first
argument, in addition to any arguments it is called with.
When the wrapped function is called, an EventualResult is returned.
"""
warnings.warn(
"@in_reactor is deprecated, use @run_in_reactor",
DeprecationWarning,
stacklevel=2)
@self.run_in_reactor
@wraps(function)
def add_reactor(*args, **kwargs):
return function(self._reactor, *args, **kwargs)
return add_reactor | python | def in_reactor(self, function):
"""
DEPRECATED, use run_in_reactor.
A decorator that ensures the wrapped function runs in the reactor
thread.
The wrapped function will get the reactor passed in as a first
argument, in addition to any arguments it is called with.
When the wrapped function is called, an EventualResult is returned.
"""
warnings.warn(
"@in_reactor is deprecated, use @run_in_reactor",
DeprecationWarning,
stacklevel=2)
@self.run_in_reactor
@wraps(function)
def add_reactor(*args, **kwargs):
return function(self._reactor, *args, **kwargs)
return add_reactor | [
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itamarst/crochet | examples/mxquery.py | _mx | def _mx(domain):
"""
Return Deferred that fires with a list of (priority, MX domain) tuples for
a given domain.
"""
def got_records(result):
return sorted(
[(int(record.payload.preference), str(record.payload.name))
for record in result[0]])
d = lookupMailExchange(domain)
d.addCallback(got_records)
return d | python | def _mx(domain):
"""
Return Deferred that fires with a list of (priority, MX domain) tuples for
a given domain.
"""
def got_records(result):
return sorted(
[(int(record.payload.preference), str(record.payload.name))
for record in result[0]])
d = lookupMailExchange(domain)
d.addCallback(got_records)
return d | [
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itamarst/crochet | crochet/_resultstore.py | ResultStore.store | def store(self, deferred_result):
"""
Store a EventualResult.
Return an integer, a unique identifier that can be used to retrieve
the object.
"""
self._counter += 1
self._stored[self._counter] = deferred_result
return self._counter | python | def store(self, deferred_result):
"""
Store a EventualResult.
Return an integer, a unique identifier that can be used to retrieve
the object.
"""
self._counter += 1
self._stored[self._counter] = deferred_result
return self._counter | [
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itamarst/crochet | crochet/_resultstore.py | ResultStore.log_errors | def log_errors(self):
"""
Log errors for all stored EventualResults that have error results.
"""
for result in self._stored.values():
failure = result.original_failure()
if failure is not None:
log.err(failure, "Unhandled error in stashed EventualResult:") | python | def log_errors(self):
"""
Log errors for all stored EventualResults that have error results.
"""
for result in self._stored.values():
failure = result.original_failure()
if failure is not None:
log.err(failure, "Unhandled error in stashed EventualResult:") | [
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itamarst/crochet | examples/ssh.py | start_ssh_server | def start_ssh_server(port, username, password, namespace):
"""
Start an SSH server on the given port, exposing a Python prompt with the
given namespace.
"""
# This is a lot of boilerplate, see http://tm.tl/6429 for a ticket to
# provide a utility function that simplifies this.
from twisted.internet import reactor
from twisted.conch.insults import insults
from twisted.conch import manhole, manhole_ssh
from twisted.cred.checkers import (
InMemoryUsernamePasswordDatabaseDontUse as MemoryDB)
from twisted.cred.portal import Portal
sshRealm = manhole_ssh.TerminalRealm()
def chainedProtocolFactory():
return insults.ServerProtocol(manhole.Manhole, namespace)
sshRealm.chainedProtocolFactory = chainedProtocolFactory
sshPortal = Portal(sshRealm, [MemoryDB(**{username: password})])
reactor.listenTCP(port, manhole_ssh.ConchFactory(sshPortal),
interface="127.0.0.1") | python | def start_ssh_server(port, username, password, namespace):
"""
Start an SSH server on the given port, exposing a Python prompt with the
given namespace.
"""
# This is a lot of boilerplate, see http://tm.tl/6429 for a ticket to
# provide a utility function that simplifies this.
from twisted.internet import reactor
from twisted.conch.insults import insults
from twisted.conch import manhole, manhole_ssh
from twisted.cred.checkers import (
InMemoryUsernamePasswordDatabaseDontUse as MemoryDB)
from twisted.cred.portal import Portal
sshRealm = manhole_ssh.TerminalRealm()
def chainedProtocolFactory():
return insults.ServerProtocol(manhole.Manhole, namespace)
sshRealm.chainedProtocolFactory = chainedProtocolFactory
sshPortal = Portal(sshRealm, [MemoryDB(**{username: password})])
reactor.listenTCP(port, manhole_ssh.ConchFactory(sshPortal),
interface="127.0.0.1") | [
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itamarst/crochet | crochet/_util.py | _synced | def _synced(method, self, args, kwargs):
"""Underlying synchronized wrapper."""
with self._lock:
return method(*args, **kwargs) | python | def _synced(method, self, args, kwargs):
"""Underlying synchronized wrapper."""
with self._lock:
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itamarst/crochet | crochet/_shutdown.py | FunctionRegistry.register | def register(self, f, *args, **kwargs):
"""
Register a function and arguments to be called later.
"""
self._functions.append(lambda: f(*args, **kwargs)) | python | def register(self, f, *args, **kwargs):
"""
Register a function and arguments to be called later.
"""
self._functions.append(lambda: f(*args, **kwargs)) | [
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tkf/python-epc | epc/core.py | EPCDispatcher.register_function | def register_function(self, function, name=None):
"""
Register function to be called from EPC client.
:type function: callable
:arg function: Function to publish.
:type name: str
:arg name: Name by which function is published.
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"""
if name is None:
name = function.__name__
self.funcs[name] = function
return function | python | def register_function(self, function, name=None):
"""
Register function to be called from EPC client.
:type function: callable
:arg function: Function to publish.
:type name: str
:arg name: Name by which function is published.
This method returns the given `function` as-is, so that you
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"""
if name is None:
name = function.__name__
self.funcs[name] = function
return function | [
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tkf/python-epc | epc/core.py | EPCDispatcher.get_method | def get_method(self, name):
"""
Get registered method callend `name`.
"""
try:
return self.funcs[name]
except KeyError:
try:
return self.instance._get_method(name)
except AttributeError:
return SimpleXMLRPCServer.resolve_dotted_attribute(
self.instance, name, self.allow_dotted_names) | python | def get_method(self, name):
"""
Get registered method callend `name`.
"""
try:
return self.funcs[name]
except KeyError:
try:
return self.instance._get_method(name)
except AttributeError:
return SimpleXMLRPCServer.resolve_dotted_attribute(
self.instance, name, self.allow_dotted_names) | [
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tkf/python-epc | epc/core.py | EPCCore.set_debugger | def set_debugger(self, debugger):
"""
Set debugger to run when an error occurs in published method.
You can also set debugger by passing `debugger` argument to
the class constructor.
:type debugger: {'pdb', 'ipdb', None}
:arg debugger: type of debugger.
"""
if debugger == 'pdb':
import pdb
self.debugger = pdb
elif debugger == 'ipdb':
import ipdb
self.debugger = ipdb
else:
self.debugger = debugger | python | def set_debugger(self, debugger):
"""
Set debugger to run when an error occurs in published method.
You can also set debugger by passing `debugger` argument to
the class constructor.
:type debugger: {'pdb', 'ipdb', None}
:arg debugger: type of debugger.
"""
if debugger == 'pdb':
import pdb
self.debugger = pdb
elif debugger == 'ipdb':
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else:
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tkf/python-epc | epc/client.py | EPCClient.connect | def connect(self, socket_or_address):
"""
Connect to server and start serving registered functions.
:type socket_or_address: tuple or socket object
:arg socket_or_address: A ``(host, port)`` pair to be passed
to `socket.create_connection`, or
a socket object.
"""
if isinstance(socket_or_address, tuple):
import socket
self.socket = socket.create_connection(socket_or_address)
else:
self.socket = socket_or_address
# This is what BaseServer.finish_request does:
address = None # it is not used, so leave it empty
self.handler = EPCClientHandler(self.socket, address, self)
self.call = self.handler.call
self.call_sync = self.handler.call_sync
self.methods = self.handler.methods
self.methods_sync = self.handler.methods_sync
self.handler_thread = newthread(self, target=self.handler.start)
self.handler_thread.daemon = self.thread_daemon
self.handler_thread.start()
self.handler.wait_until_ready() | python | def connect(self, socket_or_address):
"""
Connect to server and start serving registered functions.
:type socket_or_address: tuple or socket object
:arg socket_or_address: A ``(host, port)`` pair to be passed
to `socket.create_connection`, or
a socket object.
"""
if isinstance(socket_or_address, tuple):
import socket
self.socket = socket.create_connection(socket_or_address)
else:
self.socket = socket_or_address
# This is what BaseServer.finish_request does:
address = None # it is not used, so leave it empty
self.handler = EPCClientHandler(self.socket, address, self)
self.call = self.handler.call
self.call_sync = self.handler.call_sync
self.methods = self.handler.methods
self.methods_sync = self.handler.methods_sync
self.handler_thread = newthread(self, target=self.handler.start)
self.handler_thread.daemon = self.thread_daemon
self.handler_thread.start()
self.handler.wait_until_ready() | [
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tkf/python-epc | epc/server.py | main | def main(args=None):
"""
Quick CLI to serve Python functions in a module.
Example usage::
python -m epc.server --allow-dotted-names os
Note that only the functions which gets and returns simple
built-in types (str, int, float, list, tuple, dict) works.
"""
import argparse
from textwrap import dedent
parser = argparse.ArgumentParser(
formatter_class=type('EPCHelpFormatter',
(argparse.ArgumentDefaultsHelpFormatter,
argparse.RawDescriptionHelpFormatter),
{}),
description=dedent(main.__doc__))
parser.add_argument(
'module', help='Serve python functions in this module.')
parser.add_argument(
'--address', default='localhost',
help='server address')
parser.add_argument(
'--port', default=0, type=int,
help='server port. 0 means to pick up random port.')
parser.add_argument(
'--allow-dotted-names', default=False, action='store_true')
parser.add_argument(
'--pdb', dest='debugger', const='pdb', action='store_const',
help='start pdb when error occurs.')
parser.add_argument(
'--ipdb', dest='debugger', const='ipdb', action='store_const',
help='start ipdb when error occurs.')
parser.add_argument(
'--log-traceback', action='store_true', default=False)
ns = parser.parse_args(args)
server = EPCServer((ns.address, ns.port),
debugger=ns.debugger,
log_traceback=ns.log_traceback)
server.register_instance(
__import__(ns.module),
allow_dotted_names=ns.allow_dotted_names)
server.print_port()
server.serve_forever() | python | def main(args=None):
"""
Quick CLI to serve Python functions in a module.
Example usage::
python -m epc.server --allow-dotted-names os
Note that only the functions which gets and returns simple
built-in types (str, int, float, list, tuple, dict) works.
"""
import argparse
from textwrap import dedent
parser = argparse.ArgumentParser(
formatter_class=type('EPCHelpFormatter',
(argparse.ArgumentDefaultsHelpFormatter,
argparse.RawDescriptionHelpFormatter),
{}),
description=dedent(main.__doc__))
parser.add_argument(
'module', help='Serve python functions in this module.')
parser.add_argument(
'--address', default='localhost',
help='server address')
parser.add_argument(
'--port', default=0, type=int,
help='server port. 0 means to pick up random port.')
parser.add_argument(
'--allow-dotted-names', default=False, action='store_true')
parser.add_argument(
'--pdb', dest='debugger', const='pdb', action='store_const',
help='start pdb when error occurs.')
parser.add_argument(
'--ipdb', dest='debugger', const='ipdb', action='store_const',
help='start ipdb when error occurs.')
parser.add_argument(
'--log-traceback', action='store_true', default=False)
ns = parser.parse_args(args)
server = EPCServer((ns.address, ns.port),
debugger=ns.debugger,
log_traceback=ns.log_traceback)
server.register_instance(
__import__(ns.module),
allow_dotted_names=ns.allow_dotted_names)
server.print_port()
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tkf/python-epc | epc/server.py | EPCServer.print_port | def print_port(self, stream=sys.stdout):
"""
Print port this EPC server runs on.
As Emacs client reads port number from STDOUT, you need to
call this just before calling :meth:`serve_forever`.
:type stream: text stream
:arg stream: A stream object to write port on.
Default is :data:`sys.stdout`.
"""
stream.write(str(self.server_address[1]))
stream.write("\n")
stream.flush() | python | def print_port(self, stream=sys.stdout):
"""
Print port this EPC server runs on.
As Emacs client reads port number from STDOUT, you need to
call this just before calling :meth:`serve_forever`.
:type stream: text stream
:arg stream: A stream object to write port on.
Default is :data:`sys.stdout`.
"""
stream.write(str(self.server_address[1]))
stream.write("\n")
stream.flush() | [
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tkf/python-epc | epc/handler.py | EPCHandler.call | def call(self, name, *args, **kwds):
"""
Call method connected to this handler.
:type name: str
:arg name: Method name to call.
:type args: list
:arg args: Arguments for remote method to call.
:type callback: callable
:arg callback: A function to be called with returned value of
the remote method.
:type errback: callable
:arg errback: A function to be called with an error occurred
in the remote method. It is either an instance
of :class:`ReturnError` or :class:`EPCError`.
"""
self.callmanager.call(self, name, *args, **kwds) | python | def call(self, name, *args, **kwds):
"""
Call method connected to this handler.
:type name: str
:arg name: Method name to call.
:type args: list
:arg args: Arguments for remote method to call.
:type callback: callable
:arg callback: A function to be called with returned value of
the remote method.
:type errback: callable
:arg errback: A function to be called with an error occurred
in the remote method. It is either an instance
of :class:`ReturnError` or :class:`EPCError`.
"""
self.callmanager.call(self, name, *args, **kwds) | [
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tkf/python-epc | epc/handler.py | EPCHandler.methods | def methods(self, *args, **kwds):
"""
Request info of callable remote methods.
Arguments for :meth:`call` except for `name` can be applied to
this function too.
"""
self.callmanager.methods(self, *args, **kwds) | python | def methods(self, *args, **kwds):
"""
Request info of callable remote methods.
Arguments for :meth:`call` except for `name` can be applied to
this function too.
"""
self.callmanager.methods(self, *args, **kwds) | [
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tkf/python-epc | epc/handler.py | EPCHandler.call_sync | def call_sync(self, name, args, timeout=None):
"""
Blocking version of :meth:`call`.
:type name: str
:arg name: Remote function name to call.
:type args: list
:arg args: Arguments passed to the remote function.
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:arg timeout: Timeout in second. None means no timeout.
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"""
return self._blocking_request(self.call, timeout, name, args) | python | def call_sync(self, name, args, timeout=None):
"""
Blocking version of :meth:`call`.
:type name: str
:arg name: Remote function name to call.
:type args: list
:arg args: Arguments passed to the remote function.
:type timeout: int or None
:arg timeout: Timeout in second. None means no timeout.
If the called remote function raise an exception, this method
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"""
return self._blocking_request(self.call, timeout, name, args) | [
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tkf/python-epc | epc/utils.py | func_call_as_str | def func_call_as_str(name, *args, **kwds):
"""
Return arguments and keyword arguments as formatted string
>>> func_call_as_str('f', 1, 2, a=1)
'f(1, 2, a=1)'
"""
return '{0}({1})'.format(
name,
', '.join(itertools.chain(
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map('{0[0]!s}={0[1]!r}'.format, sorted(kwds.items()))))) | python | def func_call_as_str(name, *args, **kwds):
"""
Return arguments and keyword arguments as formatted string
>>> func_call_as_str('f', 1, 2, a=1)
'f(1, 2, a=1)'
"""
return '{0}({1})'.format(
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tkf/python-epc | epc/utils.py | newthread | def newthread(template="EPCThread-{0}", **kwds):
"""
Instantiate :class:`threading.Thread` with an appropriate name.
"""
if not isinstance(template, str):
template = '{0}.{1}-{{0}}'.format(template.__module__,
template.__class__.__name__)
return threading.Thread(
name=newname(template), **kwds) | python | def newthread(template="EPCThread-{0}", **kwds):
"""
Instantiate :class:`threading.Thread` with an appropriate name.
"""
if not isinstance(template, str):
template = '{0}.{1}-{{0}}'.format(template.__module__,
template.__class__.__name__)
return threading.Thread(
name=newname(template), **kwds) | [
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tkf/python-epc | epc/utils.py | callwith | def callwith(context_manager):
"""
A decorator to wrap execution of function with a context manager.
"""
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwds):
with context_manager:
return func(*args, **kwds)
return wrapper
return decorator | python | def callwith(context_manager):
"""
A decorator to wrap execution of function with a context manager.
"""
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kwds):
with context_manager:
return func(*args, **kwds)
return wrapper
return decorator | [
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dgketchum/satellite_image | sat_image/image.py | LandsatImage._scene_centroid | def _scene_centroid(self):
""" Compute image center coordinates
:return: Tuple of image center in lat, lon
"""
ul_lat = self.corner_ul_lat_product
ll_lat = self.corner_ll_lat_product
ul_lon = self.corner_ul_lon_product
ur_lon = self.corner_ur_lon_product
lat = (ul_lat + ll_lat) / 2.
lon = (ul_lon + ur_lon) / 2.
return lat, lon | python | def _scene_centroid(self):
""" Compute image center coordinates
:return: Tuple of image center in lat, lon
"""
ul_lat = self.corner_ul_lat_product
ll_lat = self.corner_ll_lat_product
ul_lon = self.corner_ul_lon_product
ur_lon = self.corner_ur_lon_product
lat = (ul_lat + ll_lat) / 2.
lon = (ul_lon + ur_lon) / 2.
return lat, lon | [
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dgketchum/satellite_image | sat_image/image.py | LandsatImage.earth_sun_d | def earth_sun_d(dtime):
""" Earth-sun distance in AU
:param dtime time, e.g. datetime.datetime(2007, 5, 1)
:type datetime object
:return float(distance from sun to earth in astronomical units)
"""
doy = int(dtime.strftime('%j'))
rad_term = 0.9856 * (doy - 4) * pi / 180
distance_au = 1 - 0.01672 * cos(rad_term)
return distance_au | python | def earth_sun_d(dtime):
""" Earth-sun distance in AU
:param dtime time, e.g. datetime.datetime(2007, 5, 1)
:type datetime object
:return float(distance from sun to earth in astronomical units)
"""
doy = int(dtime.strftime('%j'))
rad_term = 0.9856 * (doy - 4) * pi / 180
distance_au = 1 - 0.01672 * cos(rad_term)
return distance_au | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.reflectance | def reflectance(self, band):
"""
:param band: An optical band, i.e. 1-5, 7
:return: At satellite reflectance, [-]
"""
if band == 6:
raise ValueError('LT5 reflectance must be other than band 6')
rad = self.radiance(band)
esun = self.ex_atm_irrad[band - 1]
toa_reflect = (pi * rad * self.earth_sun_dist ** 2) / (esun * cos(self.solar_zenith_rad))
return toa_reflect | python | def reflectance(self, band):
"""
:param band: An optical band, i.e. 1-5, 7
:return: At satellite reflectance, [-]
"""
if band == 6:
raise ValueError('LT5 reflectance must be other than band 6')
rad = self.radiance(band)
esun = self.ex_atm_irrad[band - 1]
toa_reflect = (pi * rad * self.earth_sun_dist ** 2) / (esun * cos(self.solar_zenith_rad))
return toa_reflect | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.albedo | def albedo(self, model='smith'):
"""Finds broad-band surface reflectance (albedo)
Smith (2010), “The heat budget of the earth’s surface deduced from space”
LT5 toa reflectance bands 1, 3, 4, 5, 7
# normalized i.e. 0.356 + 0.130 + 0.373 + 0.085 + 0.07 = 1.014
Should have option for Liang, 2000;
Tasumi (2008), "At-Surface Reflectance and Albedo from Satellite for
Operational Calculation of Land Surface Energy Balance"
:return albedo array of floats
"""
if model == 'smith':
blue, red, nir, swir1, swir2 = (self.reflectance(1), self.reflectance(3), self.reflectance(4),
self.reflectance(5), self.reflectance(7))
alb = (0.356 * blue + 0.130 * red + 0.373 * nir + 0.085 * swir1 + 0.072 * swir2 - 0.0018) / 1.014
elif model == 'tasumi':
pass
# add tasumi algorithm TODO
return alb | python | def albedo(self, model='smith'):
"""Finds broad-band surface reflectance (albedo)
Smith (2010), “The heat budget of the earth’s surface deduced from space”
LT5 toa reflectance bands 1, 3, 4, 5, 7
# normalized i.e. 0.356 + 0.130 + 0.373 + 0.085 + 0.07 = 1.014
Should have option for Liang, 2000;
Tasumi (2008), "At-Surface Reflectance and Albedo from Satellite for
Operational Calculation of Land Surface Energy Balance"
:return albedo array of floats
"""
if model == 'smith':
blue, red, nir, swir1, swir2 = (self.reflectance(1), self.reflectance(3), self.reflectance(4),
self.reflectance(5), self.reflectance(7))
alb = (0.356 * blue + 0.130 * red + 0.373 * nir + 0.085 * swir1 + 0.072 * swir2 - 0.0018) / 1.014
elif model == 'tasumi':
pass
# add tasumi algorithm TODO
return alb | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.saturation_mask | def saturation_mask(self, band, value=255):
""" Mask saturated pixels, 1 (True) is saturated.
:param band: Image band with dn values, type: array
:param value: Maximum (saturated) value, i.e. 255 for 8-bit data, type: int
:return: boolean array
"""
dn = self._get_band('b{}'.format(band))
mask = self.mask()
mask = where((dn == value) & (mask > 0), True, False)
return mask | python | def saturation_mask(self, band, value=255):
""" Mask saturated pixels, 1 (True) is saturated.
:param band: Image band with dn values, type: array
:param value: Maximum (saturated) value, i.e. 255 for 8-bit data, type: int
:return: boolean array
"""
dn = self._get_band('b{}'.format(band))
mask = self.mask()
mask = where((dn == value) & (mask > 0), True, False)
return mask | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.ndvi | def ndvi(self):
""" Normalized difference vegetation index.
:return: NDVI
"""
red, nir = self.reflectance(3), self.reflectance(4)
ndvi = self._divide_zero((nir - red), (nir + red), nan)
return ndvi | python | def ndvi(self):
""" Normalized difference vegetation index.
:return: NDVI
"""
red, nir = self.reflectance(3), self.reflectance(4)
ndvi = self._divide_zero((nir - red), (nir + red), nan)
return ndvi | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.lai | def lai(self):
"""
Leaf area index (LAI), or the surface area of leaves to surface area ground.
Trezza and Allen, 2014
:param ndvi: normalized difference vegetation index [-]
:return: LAI [-]
"""
ndvi = self.ndvi()
lai = 7.0 * (ndvi ** 3)
lai = where(lai > 6., 6., lai)
return lai | python | def lai(self):
"""
Leaf area index (LAI), or the surface area of leaves to surface area ground.
Trezza and Allen, 2014
:param ndvi: normalized difference vegetation index [-]
:return: LAI [-]
"""
ndvi = self.ndvi()
lai = 7.0 * (ndvi ** 3)
lai = where(lai > 6., 6., lai)
return lai | [
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dgketchum/satellite_image | sat_image/image.py | Landsat5.land_surface_temp | def land_surface_temp(self):
"""
Mean values from Allen (2007)
:return:
"""
rp = 0.91
tau = 0.866
rsky = 1.32
epsilon = self.emissivity(approach='tasumi')
radiance = self.radiance(6)
rc = ((radiance - rp) / tau) - ((1 - epsilon) * rsky)
lst = self.k2 / (log((epsilon * self.k1 / rc) + 1))
return lst | python | def land_surface_temp(self):
"""
Mean values from Allen (2007)
:return:
"""
rp = 0.91
tau = 0.866
rsky = 1.32
epsilon = self.emissivity(approach='tasumi')
radiance = self.radiance(6)
rc = ((radiance - rp) / tau) - ((1 - epsilon) * rsky)
lst = self.k2 / (log((epsilon * self.k1 / rc) + 1))
return lst | [
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dgketchum/satellite_image | sat_image/image.py | Landsat8.brightness_temp | def brightness_temp(self, band, temp_scale='K'):
"""Calculate brightness temperature of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
T = K2 / log((K1 / L) + 1)
and
L = ML * Q + AL
where:
T = At-satellite brightness temperature (degrees kelvin)
L = TOA spectral radiance (Watts / (m2 * srad * mm))
ML = Band-specific multiplicative rescaling factor from the metadata
(RADIANCE_MULT_BAND_x, where x is the band number)
AL = Band-specific additive rescaling factor from the metadata
(RADIANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
(ndarray img)
K1 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
K2 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
if band in self.oli_bands:
raise ValueError('Landsat 8 brightness should be TIRS band (i.e. 10 or 11)')
k1 = getattr(self, 'k1_constant_band_{}'.format(band))
k2 = getattr(self, 'k2_constant_band_{}'.format(band))
rad = self.radiance(band)
brightness = k2 / log((k1 / rad) + 1)
if temp_scale == 'K':
return brightness
elif temp_scale == 'F':
return brightness * (9 / 5.0) - 459.67
elif temp_scale == 'C':
return brightness - 273.15
else:
raise ValueError('{} is not a valid temperature scale'.format(temp_scale)) | python | def brightness_temp(self, band, temp_scale='K'):
"""Calculate brightness temperature of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
T = K2 / log((K1 / L) + 1)
and
L = ML * Q + AL
where:
T = At-satellite brightness temperature (degrees kelvin)
L = TOA spectral radiance (Watts / (m2 * srad * mm))
ML = Band-specific multiplicative rescaling factor from the metadata
(RADIANCE_MULT_BAND_x, where x is the band number)
AL = Band-specific additive rescaling factor from the metadata
(RADIANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
(ndarray img)
K1 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
K2 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
if band in self.oli_bands:
raise ValueError('Landsat 8 brightness should be TIRS band (i.e. 10 or 11)')
k1 = getattr(self, 'k1_constant_band_{}'.format(band))
k2 = getattr(self, 'k2_constant_band_{}'.format(band))
rad = self.radiance(band)
brightness = k2 / log((k1 / rad) + 1)
if temp_scale == 'K':
return brightness
elif temp_scale == 'F':
return brightness * (9 / 5.0) - 459.67
elif temp_scale == 'C':
return brightness - 273.15
else:
raise ValueError('{} is not a valid temperature scale'.format(temp_scale)) | [
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as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
T = K2 / log((K1 / L) + 1)
and
L = ML * Q + AL
where:
T = At-satellite brightness temperature (degrees kelvin)
L = TOA spectral radiance (Watts / (m2 * srad * mm))
ML = Band-specific multiplicative rescaling factor from the metadata
(RADIANCE_MULT_BAND_x, where x is the band number)
AL = Band-specific additive rescaling factor from the metadata
(RADIANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
(ndarray img)
K1 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
K2 = Band-specific thermal conversion constant from the metadata
(K1_CONSTANT_BAND_x, where x is the thermal band number)
Returns
--------
ndarray:
float32 ndarray with shape == input shape | [
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dgketchum/satellite_image | sat_image/image.py | Landsat8.reflectance | def reflectance(self, band):
"""Calculate top of atmosphere reflectance of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
R_raw = MR * Q + AR
R = R_raw / cos(Z) = R_raw / sin(E)
Z = 90 - E (in degrees)
where:
R_raw = TOA planetary reflectance, without correction for solar angle.
R = TOA reflectance with a correction for the sun angle.
MR = Band-specific multiplicative rescaling factor from the metadata
(REFLECTANCE_MULT_BAND_x, where x is the band number)
AR = Band-specific additive rescaling factor from the metadata
(REFLECTANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
E = Local sun elevation angle. The scene center sun elevation angle
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Z = Local solar zenith angle (same angle as E, but measured from the
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Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
if band not in self.oli_bands:
raise ValueError('Landsat 8 reflectance should OLI band (i.e. bands 1-8)')
elev = getattr(self, 'sun_elevation')
dn = self._get_band('b{}'.format(band))
mr = getattr(self, 'reflectance_mult_band_{}'.format(band))
ar = getattr(self, 'reflectance_add_band_{}'.format(band))
if elev < 0.0:
raise ValueError("Sun elevation must be non-negative "
"(sun must be above horizon for entire scene)")
rf = ((mr * dn.astype(float32)) + ar) / sin(deg2rad(elev))
return rf | python | def reflectance(self, band):
"""Calculate top of atmosphere reflectance of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
R_raw = MR * Q + AR
R = R_raw / cos(Z) = R_raw / sin(E)
Z = 90 - E (in degrees)
where:
R_raw = TOA planetary reflectance, without correction for solar angle.
R = TOA reflectance with a correction for the sun angle.
MR = Band-specific multiplicative rescaling factor from the metadata
(REFLECTANCE_MULT_BAND_x, where x is the band number)
AR = Band-specific additive rescaling factor from the metadata
(REFLECTANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
E = Local sun elevation angle. The scene center sun elevation angle
in degrees is provided in the metadata (SUN_ELEVATION).
Z = Local solar zenith angle (same angle as E, but measured from the
zenith instead of from the horizon).
Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
if band not in self.oli_bands:
raise ValueError('Landsat 8 reflectance should OLI band (i.e. bands 1-8)')
elev = getattr(self, 'sun_elevation')
dn = self._get_band('b{}'.format(band))
mr = getattr(self, 'reflectance_mult_band_{}'.format(band))
ar = getattr(self, 'reflectance_add_band_{}'.format(band))
if elev < 0.0:
raise ValueError("Sun elevation must be non-negative "
"(sun must be above horizon for entire scene)")
rf = ((mr * dn.astype(float32)) + ar) / sin(deg2rad(elev))
return rf | [
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--------
ndarray:
float32 ndarray with shape == input shape | [
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dgketchum/satellite_image | sat_image/image.py | Landsat8.radiance | def radiance(self, band):
"""Calculate top of atmosphere radiance of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
L = ML * Q + AL
where:
L = TOA spectral radiance (Watts / (m2 * srad * mm))
ML = Band-specific multiplicative rescaling factor from the metadata
(RADIANCE_MULT_BAND_x, where x is the band number)
AL = Band-specific additive rescaling factor from the metadata
(RADIANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
(ndarray img)
Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
ml = getattr(self, 'radiance_mult_band_{}'.format(band))
al = getattr(self, 'radiance_add_band_{}'.format(band))
dn = self._get_band('b{}'.format(band))
rad = ml * dn.astype(float32) + al
return rad | python | def radiance(self, band):
"""Calculate top of atmosphere radiance of Landsat 8
as outlined here: http://landsat.usgs.gov/Landsat8_Using_Product.php
L = ML * Q + AL
where:
L = TOA spectral radiance (Watts / (m2 * srad * mm))
ML = Band-specific multiplicative rescaling factor from the metadata
(RADIANCE_MULT_BAND_x, where x is the band number)
AL = Band-specific additive rescaling factor from the metadata
(RADIANCE_ADD_BAND_x, where x is the band number)
Q = Quantized and calibrated standard product pixel values (DN)
(ndarray img)
Returns
--------
ndarray:
float32 ndarray with shape == input shape
"""
ml = getattr(self, 'radiance_mult_band_{}'.format(band))
al = getattr(self, 'radiance_add_band_{}'.format(band))
dn = self._get_band('b{}'.format(band))
rad = ml * dn.astype(float32) + al
return rad | [
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dgketchum/satellite_image | sat_image/image.py | Landsat8.ndsi | def ndsi(self):
""" Normalized difference snow index.
:return: NDSI
"""
green, swir1 = self.reflectance(3), self.reflectance(6)
ndsi = self._divide_zero((green - swir1), (green + swir1), nan)
return ndsi | python | def ndsi(self):
""" Normalized difference snow index.
:return: NDSI
"""
green, swir1 = self.reflectance(3), self.reflectance(6)
ndsi = self._divide_zero((green - swir1), (green + swir1), nan)
return ndsi | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.whiteness_index | def whiteness_index(self):
"""Index of "Whiteness" based on visible bands.
Parameters
----------
Output
------
ndarray:
whiteness index
"""
mean_vis = (self.blue + self.green + self.red) / 3
blue_absdiff = np.absolute(self._divide_zero(self.blue - mean_vis, mean_vis))
green_absdiff = np.absolute(self._divide_zero(self.green - mean_vis, mean_vis))
red_absdiff = np.absolute(self._divide_zero(self.red - mean_vis, mean_vis))
return blue_absdiff + green_absdiff + red_absdiff | python | def whiteness_index(self):
"""Index of "Whiteness" based on visible bands.
Parameters
----------
Output
------
ndarray:
whiteness index
"""
mean_vis = (self.blue + self.green + self.red) / 3
blue_absdiff = np.absolute(self._divide_zero(self.blue - mean_vis, mean_vis))
green_absdiff = np.absolute(self._divide_zero(self.green - mean_vis, mean_vis))
red_absdiff = np.absolute(self._divide_zero(self.red - mean_vis, mean_vis))
return blue_absdiff + green_absdiff + red_absdiff | [
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Parameters
----------
Output
------
ndarray:
whiteness index | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.potential_cloud_pixels | def potential_cloud_pixels(self):
"""Determine potential cloud pixels (PCPs)
Combine basic spectral testsr to get a premliminary cloud mask
First pass, section 3.1.1 in Zhu and Woodcock 2012
Equation 6 (Zhu and Woodcock, 2012)
Parameters
----------
ndvi: ndarray
ndsi: ndarray
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
Output
------
ndarray:
potential cloud mask, boolean
"""
eq1 = self.basic_test()
eq2 = self.whiteness_test()
eq3 = self.hot_test()
eq4 = self.nirswir_test()
if self.sat == 'LC8':
cir = self.cirrus_test()
return (eq1 & eq2 & eq3 & eq4) | cir
else:
return eq1 & eq2 & eq3 & eq4 | python | def potential_cloud_pixels(self):
"""Determine potential cloud pixels (PCPs)
Combine basic spectral testsr to get a premliminary cloud mask
First pass, section 3.1.1 in Zhu and Woodcock 2012
Equation 6 (Zhu and Woodcock, 2012)
Parameters
----------
ndvi: ndarray
ndsi: ndarray
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
Output
------
ndarray:
potential cloud mask, boolean
"""
eq1 = self.basic_test()
eq2 = self.whiteness_test()
eq3 = self.hot_test()
eq4 = self.nirswir_test()
if self.sat == 'LC8':
cir = self.cirrus_test()
return (eq1 & eq2 & eq3 & eq4) | cir
else:
return eq1 & eq2 & eq3 & eq4 | [
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Combine basic spectral testsr to get a premliminary cloud mask
First pass, section 3.1.1 in Zhu and Woodcock 2012
Equation 6 (Zhu and Woodcock, 2012)
Parameters
----------
ndvi: ndarray
ndsi: ndarray
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
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ndarray:
potential cloud mask, boolean | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.temp_water | def temp_water(self):
"""Use water to mask tirs and find 82.5 pctile
Equation 7 and 8 (Zhu and Woodcock, 2012)
Parameters
----------
is_water: ndarray, boolean
water mask, water is True, land is False
swir2: ndarray
tirs1: ndarray
Output
------
float:
82.5th percentile temperature over water
"""
# eq7
th_swir2 = 0.03
water = self.water_test()
clear_sky_water = water & (self.swir2 < th_swir2)
# eq8
clear_water_temp = self.tirs1.copy()
clear_water_temp[~clear_sky_water] = np.nan
clear_water_temp[~self.mask] = np.nan
pctl_clwt = np.nanpercentile(clear_water_temp, 82.5)
return pctl_clwt | python | def temp_water(self):
"""Use water to mask tirs and find 82.5 pctile
Equation 7 and 8 (Zhu and Woodcock, 2012)
Parameters
----------
is_water: ndarray, boolean
water mask, water is True, land is False
swir2: ndarray
tirs1: ndarray
Output
------
float:
82.5th percentile temperature over water
"""
# eq7
th_swir2 = 0.03
water = self.water_test()
clear_sky_water = water & (self.swir2 < th_swir2)
# eq8
clear_water_temp = self.tirs1.copy()
clear_water_temp[~clear_sky_water] = np.nan
clear_water_temp[~self.mask] = np.nan
pctl_clwt = np.nanpercentile(clear_water_temp, 82.5)
return pctl_clwt | [
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water mask, water is True, land is False
swir2: ndarray
tirs1: ndarray
Output
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float:
82.5th percentile temperature over water | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.water_temp_prob | def water_temp_prob(self):
"""Temperature probability for water
Equation 9 (Zhu and Woodcock, 2012)
Parameters
----------
water_temp: float
82.5th percentile temperature over water
swir2: ndarray
tirs1: ndarray
Output
------
ndarray:
probability of cloud over water based on temperature
"""
temp_const = 4.0 # degrees C
water_temp = self.temp_water()
return (water_temp - self.tirs1) / temp_const | python | def water_temp_prob(self):
"""Temperature probability for water
Equation 9 (Zhu and Woodcock, 2012)
Parameters
----------
water_temp: float
82.5th percentile temperature over water
swir2: ndarray
tirs1: ndarray
Output
------
ndarray:
probability of cloud over water based on temperature
"""
temp_const = 4.0 # degrees C
water_temp = self.temp_water()
return (water_temp - self.tirs1) / temp_const | [
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Equation 9 (Zhu and Woodcock, 2012)
Parameters
----------
water_temp: float
82.5th percentile temperature over water
swir2: ndarray
tirs1: ndarray
Output
------
ndarray:
probability of cloud over water based on temperature | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.brightness_prob | def brightness_prob(self, clip=True):
"""The brightest water may have Band 5 reflectance
as high as LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF.11
Equation 10 (Zhu and Woodcock, 2012)
Parameters
----------
nir: ndarray
clip: boolean
Output
------
ndarray:
brightness probability, constrained LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF..1
"""
thresh = 0.11
bp = np.minimum(thresh, self.nir) / thresh
if clip:
bp[bp > 1] = 1
bp[bp < 0] = 0
return bp | python | def brightness_prob(self, clip=True):
"""The brightest water may have Band 5 reflectance
as high as LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF.11
Equation 10 (Zhu and Woodcock, 2012)
Parameters
----------
nir: ndarray
clip: boolean
Output
------
ndarray:
brightness probability, constrained LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF..1
"""
thresh = 0.11
bp = np.minimum(thresh, self.nir) / thresh
if clip:
bp[bp > 1] = 1
bp[bp < 0] = 0
return bp | [
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nir: ndarray
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Output
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ndarray:
brightness probability, constrained LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF..1 | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.temp_land | def temp_land(self, pcps, water):
"""Derive high/low percentiles of land temperature
Equations 12 an 13 (Zhu and Woodcock, 2012)
Parameters
----------
pcps: ndarray
potential cloud pixels, boolean
water: ndarray
water mask, boolean
tirs1: ndarray
Output
------
tuple:
17.5 and 82.5 percentile temperature over clearsky land
"""
# eq 12
clearsky_land = ~(pcps | water)
# use clearsky_land to mask tirs1
clear_land_temp = self.tirs1.copy()
clear_land_temp[~clearsky_land] = np.nan
clear_land_temp[~self.mask] = np.nan
# take 17.5 and 82.5 percentile, eq 13
low, high = np.nanpercentile(clear_land_temp, (17.5, 82.5))
return low, high | python | def temp_land(self, pcps, water):
"""Derive high/low percentiles of land temperature
Equations 12 an 13 (Zhu and Woodcock, 2012)
Parameters
----------
pcps: ndarray
potential cloud pixels, boolean
water: ndarray
water mask, boolean
tirs1: ndarray
Output
------
tuple:
17.5 and 82.5 percentile temperature over clearsky land
"""
# eq 12
clearsky_land = ~(pcps | water)
# use clearsky_land to mask tirs1
clear_land_temp = self.tirs1.copy()
clear_land_temp[~clearsky_land] = np.nan
clear_land_temp[~self.mask] = np.nan
# take 17.5 and 82.5 percentile, eq 13
low, high = np.nanpercentile(clear_land_temp, (17.5, 82.5))
return low, high | [
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water: ndarray
water mask, boolean
tirs1: ndarray
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tuple:
17.5 and 82.5 percentile temperature over clearsky land | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.land_temp_prob | def land_temp_prob(self, tlow, thigh):
"""Temperature-based probability of cloud over land
Equation 14 (Zhu and Woodcock, 2012)
Parameters
----------
tirs1: ndarray
tlow: float
Low (17.5 percentile) temperature of land
thigh: float
High (82.5 percentile) temperature of land
Output
------
ndarray :
probability of cloud over land based on temperature
"""
temp_diff = 4 # degrees
return (thigh + temp_diff - self.tirs1) / (thigh + 4 - (tlow - 4)) | python | def land_temp_prob(self, tlow, thigh):
"""Temperature-based probability of cloud over land
Equation 14 (Zhu and Woodcock, 2012)
Parameters
----------
tirs1: ndarray
tlow: float
Low (17.5 percentile) temperature of land
thigh: float
High (82.5 percentile) temperature of land
Output
------
ndarray :
probability of cloud over land based on temperature
"""
temp_diff = 4 # degrees
return (thigh + temp_diff - self.tirs1) / (thigh + 4 - (tlow - 4)) | [
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tlow: float
Low (17.5 percentile) temperature of land
thigh: float
High (82.5 percentile) temperature of land
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ndarray :
probability of cloud over land based on temperature | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.variability_prob | def variability_prob(self, whiteness):
"""Use the probability of the spectral variability
to identify clouds over land.
Equation 15 (Zhu and Woodcock, 2012)
Parameters
----------
ndvi: ndarray
ndsi: ndarray
whiteness: ndarray
Output
------
ndarray :
probability of cloud over land based on variability
"""
if self.sat in ['LT5', 'LE7']:
# check for green and red saturation
# if red is saturated and less than nir, ndvi = LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF
mod_ndvi = np.where(self.red_saturated & (self.nir > self.red), 0, self.ndvi)
# if green is saturated and less than swir1, ndsi = LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF
mod_ndsi = np.where(self.green_saturated & (self.swir1 > self.green), 0, self.ndsi)
ndi_max = np.fmax(np.absolute(mod_ndvi), np.absolute(mod_ndsi))
else:
ndi_max = np.fmax(np.absolute(self.ndvi), np.absolute(self.ndsi))
f_max = 1.0 - np.fmax(ndi_max, whiteness)
return f_max | python | def variability_prob(self, whiteness):
"""Use the probability of the spectral variability
to identify clouds over land.
Equation 15 (Zhu and Woodcock, 2012)
Parameters
----------
ndvi: ndarray
ndsi: ndarray
whiteness: ndarray
Output
------
ndarray :
probability of cloud over land based on variability
"""
if self.sat in ['LT5', 'LE7']:
# check for green and red saturation
# if red is saturated and less than nir, ndvi = LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF
mod_ndvi = np.where(self.red_saturated & (self.nir > self.red), 0, self.ndvi)
# if green is saturated and less than swir1, ndsi = LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF
mod_ndsi = np.where(self.green_saturated & (self.swir1 > self.green), 0, self.ndsi)
ndi_max = np.fmax(np.absolute(mod_ndvi), np.absolute(mod_ndsi))
else:
ndi_max = np.fmax(np.absolute(self.ndvi), np.absolute(self.ndsi))
f_max = 1.0 - np.fmax(ndi_max, whiteness)
return f_max | [
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to identify clouds over land.
Equation 15 (Zhu and Woodcock, 2012)
Parameters
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ndvi: ndarray
ndsi: ndarray
whiteness: ndarray
Output
------
ndarray :
probability of cloud over land based on variability | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.land_threshold | def land_threshold(self, land_cloud_prob, pcps, water):
"""Dynamic threshold for determining cloud cutoff
Equation 17 (Zhu and Woodcock, 2012)
Parameters
----------
land_cloud_prob: ndarray
probability of cloud over land
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
Output
------
float:
land cloud threshold
"""
# eq 12
clearsky_land = ~(pcps | water)
# 82.5th percentile of lCloud_Prob(masked by clearsky_land) + LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF.2
cloud_prob = land_cloud_prob.copy()
cloud_prob[~clearsky_land] = np.nan
cloud_prob[~self.mask] = np.nan
# eq 17
th_const = 0.2
return np.nanpercentile(cloud_prob, 82.5) + th_const | python | def land_threshold(self, land_cloud_prob, pcps, water):
"""Dynamic threshold for determining cloud cutoff
Equation 17 (Zhu and Woodcock, 2012)
Parameters
----------
land_cloud_prob: ndarray
probability of cloud over land
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
Output
------
float:
land cloud threshold
"""
# eq 12
clearsky_land = ~(pcps | water)
# 82.5th percentile of lCloud_Prob(masked by clearsky_land) + LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF.2
cloud_prob = land_cloud_prob.copy()
cloud_prob[~clearsky_land] = np.nan
cloud_prob[~self.mask] = np.nan
# eq 17
th_const = 0.2
return np.nanpercentile(cloud_prob, 82.5) + th_const | [
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Equation 17 (Zhu and Woodcock, 2012)
Parameters
----------
land_cloud_prob: ndarray
probability of cloud over land
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
Output
------
float:
land cloud threshold | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.potential_cloud_layer | def potential_cloud_layer(self, pcp, water, tlow, land_cloud_prob, land_threshold,
water_cloud_prob, water_threshold=0.5):
"""Final step of determining potential cloud layer
Equation 18 (Zhu and Woodcock, 2012)
Saturation (green or red) test is not in the algorithm
Parameters
----------
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
tirs1: ndarray
tlow: float
low percentile of land temperature
land_cloud_prob: ndarray
probability of cloud over land
land_threshold: float
cutoff for cloud over land
water_cloud_prob: ndarray
probability of cloud over water
water_threshold: float
cutoff for cloud over water
Output
------
ndarray:
potential cloud layer, boolean
"""
# Using pcp and water as mask todo
# change water threshold to dynamic, line 132 in Zhu, 2015 todo
part1 = (pcp & water & (water_cloud_prob > water_threshold))
part2 = (pcp & ~water & (land_cloud_prob > land_threshold))
temptest = self.tirs1 < (tlow - 35) # 35degrees C colder
if self.sat in ['LT5', 'LE7']:
saturation = self.blue_saturated | self.green_saturated | self.red_saturated
return part1 | part2 | temptest | saturation
else:
return part1 | part2 | temptest | python | def potential_cloud_layer(self, pcp, water, tlow, land_cloud_prob, land_threshold,
water_cloud_prob, water_threshold=0.5):
"""Final step of determining potential cloud layer
Equation 18 (Zhu and Woodcock, 2012)
Saturation (green or red) test is not in the algorithm
Parameters
----------
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
tirs1: ndarray
tlow: float
low percentile of land temperature
land_cloud_prob: ndarray
probability of cloud over land
land_threshold: float
cutoff for cloud over land
water_cloud_prob: ndarray
probability of cloud over water
water_threshold: float
cutoff for cloud over water
Output
------
ndarray:
potential cloud layer, boolean
"""
# Using pcp and water as mask todo
# change water threshold to dynamic, line 132 in Zhu, 2015 todo
part1 = (pcp & water & (water_cloud_prob > water_threshold))
part2 = (pcp & ~water & (land_cloud_prob > land_threshold))
temptest = self.tirs1 < (tlow - 35) # 35degrees C colder
if self.sat in ['LT5', 'LE7']:
saturation = self.blue_saturated | self.green_saturated | self.red_saturated
return part1 | part2 | temptest | saturation
else:
return part1 | part2 | temptest | [
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Equation 18 (Zhu and Woodcock, 2012)
Saturation (green or red) test is not in the algorithm
Parameters
----------
pcps: ndarray
potential cloud pixels
water: ndarray
water mask
tirs1: ndarray
tlow: float
low percentile of land temperature
land_cloud_prob: ndarray
probability of cloud over land
land_threshold: float
cutoff for cloud over land
water_cloud_prob: ndarray
probability of cloud over water
water_threshold: float
cutoff for cloud over water
Output
------
ndarray:
potential cloud layer, boolean | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.potential_snow_layer | def potential_snow_layer(self):
"""Spectral test to determine potential snow
Uses the 9.85C (283K) threshold defined in Zhu, Woodcock 2015
Parameters
----------
ndsi: ndarray
green: ndarray
nir: ndarray
tirs1: ndarray
Output
------
ndarray:
boolean, True is potential snow
"""
return (self.ndsi > 0.15) & (self.tirs1 < 9.85) & (self.nir > 0.11) & (self.green > 0.1) | python | def potential_snow_layer(self):
"""Spectral test to determine potential snow
Uses the 9.85C (283K) threshold defined in Zhu, Woodcock 2015
Parameters
----------
ndsi: ndarray
green: ndarray
nir: ndarray
tirs1: ndarray
Output
------
ndarray:
boolean, True is potential snow
"""
return (self.ndsi > 0.15) & (self.tirs1 < 9.85) & (self.nir > 0.11) & (self.green > 0.1) | [
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Parameters
----------
ndsi: ndarray
green: ndarray
nir: ndarray
tirs1: ndarray
Output
------
ndarray:
boolean, True is potential snow | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.cloud_mask | def cloud_mask(self, min_filter=(3, 3), max_filter=(10, 10), combined=False, cloud_and_shadow=False):
"""Calculate the potential cloud layer from source data
*This is the high level function which ties together all
the equations for generating potential clouds*
Parameters
----------
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
min_filter: 2-element tuple, default=(3,3)
Defines the window for the minimum_filter, for removing outliers
max_filter: 2-element tuple, default=(21, 21)
Defines the window for the maximum_filter, for "buffering" the edges
combined: make a boolean array masking all (cloud, shadow, water)
Output
------
ndarray, boolean:
potential cloud layer; True = cloud
ndarray, boolean
potential cloud shadow layer; True = cloud shadow
:param cloud_and_shadow:
"""
# logger.info("Running initial testsr")
whiteness = self.whiteness_index()
water = self.water_test()
# First pass, potential clouds
pcps = self.potential_cloud_pixels()
if self.sat == 'LC8':
cirrus_prob = self.cirrus / 0.04
else:
cirrus_prob = 0.0
# Clouds over water
wtp = self.water_temp_prob()
bp = self.brightness_prob()
water_cloud_prob = (wtp * bp) + cirrus_prob
wthreshold = 0.5
# Clouds over land
tlow, thigh = self.temp_land(pcps, water)
ltp = self.land_temp_prob(tlow, thigh)
vp = self.variability_prob(whiteness)
land_cloud_prob = (ltp * vp) + cirrus_prob
lthreshold = self.land_threshold(land_cloud_prob, pcps, water)
# logger.info("Calculate potential clouds")
pcloud = self.potential_cloud_layer(
pcps, water, tlow,
land_cloud_prob, lthreshold,
water_cloud_prob, wthreshold)
# Ignoring snow for now as it exhibits many false positives and negatives
# when used as a binary mask
# psnow = potential_snow_layer(ndsi, green, nir, tirs1)
# pcloud = pcloud & ~psnow
# logger.info("Calculate potential cloud shadows")
pshadow = self.potential_cloud_shadow_layer(water)
# The remainder of the algorithm differs significantly from Fmask
# In an attempt to make a more visually appealling cloud mask
# with fewer inclusions and more broad shapes
if min_filter:
# Remove outliers
# logger.info("Remove outliers with minimum filter")
from scipy.ndimage.filters import minimum_filter
from scipy.ndimage.morphology import distance_transform_edt
# remove cloud outliers by nibbling the edges
pcloud = minimum_filter(pcloud, size=min_filter)
# crude, just look x pixels away for potential cloud pixels
dist = distance_transform_edt(~pcloud)
pixel_radius = 100.0
pshadow = (dist < pixel_radius) & pshadow
# remove cloud shadow outliers
pshadow = minimum_filter(pshadow, size=min_filter)
if max_filter:
# grow around the edges
# logger.info("Buffer edges with maximum filter")
from scipy.ndimage.filters import maximum_filter
pcloud = maximum_filter(pcloud, size=max_filter)
pshadow = maximum_filter(pshadow, size=max_filter)
# mystery, save pcloud here, shows no nan in qgis, save later, shows nan
# outfile = '/data01/images/sandbox/pcloud.tif'
# georeference = self.sat_image.rasterio_geometry
# array = pcloud
# array = array.reshape(1, array.shape[LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF], array.shape[1])
# array = np.array(array, dtype=georeference['dtype'])
# with rasterio.open(outfile, 'w', **georeference) as dst:
# dst.write(array)
# mystery test
if combined:
return pcloud | pshadow | water
if cloud_and_shadow:
return pcloud | pshadow
return pcloud, pshadow, water | python | def cloud_mask(self, min_filter=(3, 3), max_filter=(10, 10), combined=False, cloud_and_shadow=False):
"""Calculate the potential cloud layer from source data
*This is the high level function which ties together all
the equations for generating potential clouds*
Parameters
----------
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
min_filter: 2-element tuple, default=(3,3)
Defines the window for the minimum_filter, for removing outliers
max_filter: 2-element tuple, default=(21, 21)
Defines the window for the maximum_filter, for "buffering" the edges
combined: make a boolean array masking all (cloud, shadow, water)
Output
------
ndarray, boolean:
potential cloud layer; True = cloud
ndarray, boolean
potential cloud shadow layer; True = cloud shadow
:param cloud_and_shadow:
"""
# logger.info("Running initial testsr")
whiteness = self.whiteness_index()
water = self.water_test()
# First pass, potential clouds
pcps = self.potential_cloud_pixels()
if self.sat == 'LC8':
cirrus_prob = self.cirrus / 0.04
else:
cirrus_prob = 0.0
# Clouds over water
wtp = self.water_temp_prob()
bp = self.brightness_prob()
water_cloud_prob = (wtp * bp) + cirrus_prob
wthreshold = 0.5
# Clouds over land
tlow, thigh = self.temp_land(pcps, water)
ltp = self.land_temp_prob(tlow, thigh)
vp = self.variability_prob(whiteness)
land_cloud_prob = (ltp * vp) + cirrus_prob
lthreshold = self.land_threshold(land_cloud_prob, pcps, water)
# logger.info("Calculate potential clouds")
pcloud = self.potential_cloud_layer(
pcps, water, tlow,
land_cloud_prob, lthreshold,
water_cloud_prob, wthreshold)
# Ignoring snow for now as it exhibits many false positives and negatives
# when used as a binary mask
# psnow = potential_snow_layer(ndsi, green, nir, tirs1)
# pcloud = pcloud & ~psnow
# logger.info("Calculate potential cloud shadows")
pshadow = self.potential_cloud_shadow_layer(water)
# The remainder of the algorithm differs significantly from Fmask
# In an attempt to make a more visually appealling cloud mask
# with fewer inclusions and more broad shapes
if min_filter:
# Remove outliers
# logger.info("Remove outliers with minimum filter")
from scipy.ndimage.filters import minimum_filter
from scipy.ndimage.morphology import distance_transform_edt
# remove cloud outliers by nibbling the edges
pcloud = minimum_filter(pcloud, size=min_filter)
# crude, just look x pixels away for potential cloud pixels
dist = distance_transform_edt(~pcloud)
pixel_radius = 100.0
pshadow = (dist < pixel_radius) & pshadow
# remove cloud shadow outliers
pshadow = minimum_filter(pshadow, size=min_filter)
if max_filter:
# grow around the edges
# logger.info("Buffer edges with maximum filter")
from scipy.ndimage.filters import maximum_filter
pcloud = maximum_filter(pcloud, size=max_filter)
pshadow = maximum_filter(pshadow, size=max_filter)
# mystery, save pcloud here, shows no nan in qgis, save later, shows nan
# outfile = '/data01/images/sandbox/pcloud.tif'
# georeference = self.sat_image.rasterio_geometry
# array = pcloud
# array = array.reshape(1, array.shape[LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF], array.shape[1])
# array = np.array(array, dtype=georeference['dtype'])
# with rasterio.open(outfile, 'w', **georeference) as dst:
# dst.write(array)
# mystery test
if combined:
return pcloud | pshadow | water
if cloud_and_shadow:
return pcloud | pshadow
return pcloud, pshadow, water | [
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*This is the high level function which ties together all
the equations for generating potential clouds*
Parameters
----------
blue: ndarray
green: ndarray
red: ndarray
nir: ndarray
swir1: ndarray
swir2: ndarray
cirrus: ndarray
tirs1: ndarray
min_filter: 2-element tuple, default=(3,3)
Defines the window for the minimum_filter, for removing outliers
max_filter: 2-element tuple, default=(21, 21)
Defines the window for the maximum_filter, for "buffering" the edges
combined: make a boolean array masking all (cloud, shadow, water)
Output
------
ndarray, boolean:
potential cloud layer; True = cloud
ndarray, boolean
potential cloud shadow layer; True = cloud shadow
:param cloud_and_shadow: | [
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dgketchum/satellite_image | sat_image/fmask.py | Fmask.gdal_nodata_mask | def gdal_nodata_mask(pcl, pcsl, tirs_arr):
"""
Given a boolean potential cloud layer,
a potential cloud shadow layer and a thermal band
Calculate the GDAL-style uint8 mask
"""
tirs_mask = np.isnan(tirs_arr) | (tirs_arr == 0)
return ((~(pcl | pcsl | tirs_mask)) * 255).astype('uint8') | python | def gdal_nodata_mask(pcl, pcsl, tirs_arr):
"""
Given a boolean potential cloud layer,
a potential cloud shadow layer and a thermal band
Calculate the GDAL-style uint8 mask
"""
tirs_mask = np.isnan(tirs_arr) | (tirs_arr == 0)
return ((~(pcl | pcsl | tirs_mask)) * 255).astype('uint8') | [
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dgketchum/satellite_image | sat_image/mtl.py | parsemeta | def parsemeta(metadataloc):
"""Parses the metadata from a Landsat image bundle.
Arguments:
metadataloc: a filename or a directory.
Returns metadata dictionary
"""
# filename or directory? if several fit, use first one and warn
if os.path.isdir(metadataloc):
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if not metalist:
raise MTLParseError(
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elif len(metalist) > 0:
metadatafn = metalist[0]
filehandle = open(metadatafn, 'r')
if len(metalist) > 1:
logging.warning(
"More than one file in directory match metadata "
+ "file pattern. Using %s." % metadatafn)
elif os.path.isfile(metadataloc):
metadatafn = metadataloc
filehandle = open(metadatafn, 'r')
logging.info("Using file %s." % metadatafn)
elif 'L1_METADATA_FILE' in metadataloc:
filehandle = StringIO(metadataloc)
else:
raise MTLParseError(
"File location %s is unavailable " % metadataloc
+ "or doesn't contain a suitable metadata file.")
# Reading file line by line and inserting data into metadata dictionary
status = 0
metadata = {}
grouppath = []
dictpath = [metadata]
for line in filehandle:
if status == 4:
# we reached the end in the previous iteration,
# but are still reading lines
logging.warning(
"Metadata file %s appears to " % metadatafn
+ "have extra lines after the end of the metadata. "
+ "This is probably, but not necessarily, harmless.")
status = _checkstatus(status, line)
grouppath, dictpath = _transstat(status, grouppath, dictpath, line)
return metadata | python | def parsemeta(metadataloc):
"""Parses the metadata from a Landsat image bundle.
Arguments:
metadataloc: a filename or a directory.
Returns metadata dictionary
"""
# filename or directory? if several fit, use first one and warn
if os.path.isdir(metadataloc):
metalist = glob.glob(os.path.join(metadataloc, METAPATTERN))
if not metalist:
raise MTLParseError(
"No files matching metadata file pattern in directory %s."
% metadataloc)
elif len(metalist) > 0:
metadatafn = metalist[0]
filehandle = open(metadatafn, 'r')
if len(metalist) > 1:
logging.warning(
"More than one file in directory match metadata "
+ "file pattern. Using %s." % metadatafn)
elif os.path.isfile(metadataloc):
metadatafn = metadataloc
filehandle = open(metadatafn, 'r')
logging.info("Using file %s." % metadatafn)
elif 'L1_METADATA_FILE' in metadataloc:
filehandle = StringIO(metadataloc)
else:
raise MTLParseError(
"File location %s is unavailable " % metadataloc
+ "or doesn't contain a suitable metadata file.")
# Reading file line by line and inserting data into metadata dictionary
status = 0
metadata = {}
grouppath = []
dictpath = [metadata]
for line in filehandle:
if status == 4:
# we reached the end in the previous iteration,
# but are still reading lines
logging.warning(
"Metadata file %s appears to " % metadatafn
+ "have extra lines after the end of the metadata. "
+ "This is probably, but not necessarily, harmless.")
status = _checkstatus(status, line)
grouppath, dictpath = _transstat(status, grouppath, dictpath, line)
return metadata | [
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dgketchum/satellite_image | sat_image/mtl.py | _checkstatus | def _checkstatus(status, line):
"""Returns state/status after reading the next line.
The status codes are::
LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF - BEGIN parsing; 1 - ENTER METADATA GROUP, 2 - READ METADATA LINE,
3 - END METDADATA GROUP, 4 - END PARSING
Permitted Transitions::
LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 1, LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 4
1 --> 1, 1 --> 2, 1 --> 3
2 --> 2, 2 --> 3
3 --> 1, 1 --> 3, 3 --> 4
"""
newstatus = 0
if status == 0:
# begin --> enter metadata group OR end
if _islinetype(line, GRPSTART):
newstatus = 1
elif _isfinal(line):
newstatus = 4
elif status == 1:
# enter metadata group --> enter metadata group
# OR add metadata item OR leave metadata group
if _islinetype(line, GRPSTART):
newstatus = 1
elif _islinetype(line, GRPEND):
newstatus = 3
elif _isassignment(line):
# test AFTER start and end, as both are also assignments
newstatus = 2
elif status == 2:
if _islinetype(line, GRPEND):
newstatus = 3
elif _isassignment(line):
# test AFTER start and end, as both are also assignments
newstatus = 2
elif status == 3:
if _islinetype(line, GRPSTART):
newstatus = 1
elif _islinetype(line, GRPEND):
newstatus = 3
elif _isfinal(line):
newstatus = 4
if newstatus != 0:
return newstatus
elif status != 4:
raise MTLParseError(
"Cannot parse the following line after status "
+ "'%s':\n%s" % (STATUSCODE[status], line)) | python | def _checkstatus(status, line):
"""Returns state/status after reading the next line.
The status codes are::
LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF - BEGIN parsing; 1 - ENTER METADATA GROUP, 2 - READ METADATA LINE,
3 - END METDADATA GROUP, 4 - END PARSING
Permitted Transitions::
LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 1, LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 4
1 --> 1, 1 --> 2, 1 --> 3
2 --> 2, 2 --> 3
3 --> 1, 1 --> 3, 3 --> 4
"""
newstatus = 0
if status == 0:
# begin --> enter metadata group OR end
if _islinetype(line, GRPSTART):
newstatus = 1
elif _isfinal(line):
newstatus = 4
elif status == 1:
# enter metadata group --> enter metadata group
# OR add metadata item OR leave metadata group
if _islinetype(line, GRPSTART):
newstatus = 1
elif _islinetype(line, GRPEND):
newstatus = 3
elif _isassignment(line):
# test AFTER start and end, as both are also assignments
newstatus = 2
elif status == 2:
if _islinetype(line, GRPEND):
newstatus = 3
elif _isassignment(line):
# test AFTER start and end, as both are also assignments
newstatus = 2
elif status == 3:
if _islinetype(line, GRPSTART):
newstatus = 1
elif _islinetype(line, GRPEND):
newstatus = 3
elif _isfinal(line):
newstatus = 4
if newstatus != 0:
return newstatus
elif status != 4:
raise MTLParseError(
"Cannot parse the following line after status "
+ "'%s':\n%s" % (STATUSCODE[status], line)) | [
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Permitted Transitions::
LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 1, LE07_clip_L1TP_039027_20150529_20160902_01_T1_B1.TIF --> 4
1 --> 1, 1 --> 2, 1 --> 3
2 --> 2, 2 --> 3
3 --> 1, 1 --> 3, 3 --> 4 | [
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dgketchum/satellite_image | sat_image/mtl.py | _transstat | def _transstat(status, grouppath, dictpath, line):
"""Executes processing steps when reading a line"""
if status == 0:
raise MTLParseError(
"Status should not be '%s' after reading line:\n%s"
% (STATUSCODE[status], line))
elif status == 1:
currentdict = dictpath[-1]
currentgroup = _getgroupname(line)
grouppath.append(currentgroup)
currentdict[currentgroup] = {}
dictpath.append(currentdict[currentgroup])
elif status == 2:
currentdict = dictpath[-1]
newkey, newval = _getmetadataitem(line)
# USGS has started quoting the scene center time. If this
# happens strip quotes before post processing.
if newkey == 'SCENE_CENTER_TIME' and newval.startswith('"') \
and newval.endswith('"'):
# logging.warning('Strip quotes off SCENE_CENTER_TIME.')
newval = newval[1:-1]
currentdict[newkey] = _postprocess(newval)
elif status == 3:
oldgroup = _getendgroupname(line)
if oldgroup != grouppath[-1]:
raise MTLParseError(
"Reached line '%s' while reading group '%s'."
% (line.strip(), grouppath[-1]))
del grouppath[-1]
del dictpath[-1]
try:
currentgroup = grouppath[-1]
except IndexError:
currentgroup = None
elif status == 4:
if grouppath:
raise MTLParseError(
"Reached end before end of group '%s'" % grouppath[-1])
return grouppath, dictpath | python | def _transstat(status, grouppath, dictpath, line):
"""Executes processing steps when reading a line"""
if status == 0:
raise MTLParseError(
"Status should not be '%s' after reading line:\n%s"
% (STATUSCODE[status], line))
elif status == 1:
currentdict = dictpath[-1]
currentgroup = _getgroupname(line)
grouppath.append(currentgroup)
currentdict[currentgroup] = {}
dictpath.append(currentdict[currentgroup])
elif status == 2:
currentdict = dictpath[-1]
newkey, newval = _getmetadataitem(line)
# USGS has started quoting the scene center time. If this
# happens strip quotes before post processing.
if newkey == 'SCENE_CENTER_TIME' and newval.startswith('"') \
and newval.endswith('"'):
# logging.warning('Strip quotes off SCENE_CENTER_TIME.')
newval = newval[1:-1]
currentdict[newkey] = _postprocess(newval)
elif status == 3:
oldgroup = _getendgroupname(line)
if oldgroup != grouppath[-1]:
raise MTLParseError(
"Reached line '%s' while reading group '%s'."
% (line.strip(), grouppath[-1]))
del grouppath[-1]
del dictpath[-1]
try:
currentgroup = grouppath[-1]
except IndexError:
currentgroup = None
elif status == 4:
if grouppath:
raise MTLParseError(
"Reached end before end of group '%s'" % grouppath[-1])
return grouppath, dictpath | [
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dgketchum/satellite_image | sat_image/mtl.py | _postprocess | def _postprocess(valuestr):
"""
Takes value as str, returns str, int, float, date, datetime, or time
"""
# USGS has started quoting time sometimes. Grr, strip quotes in this case
intpattern = re.compile(r'^\-?\d+$')
floatpattern = re.compile(r'^\-?\d+\.\d+(E[+-]?\d\d+)?$')
datedtpattern = '%Y-%m-%d'
datedttimepattern = '%Y-%m-%dT%H:%M:%SZ'
timedtpattern = '%H:%M:%S.%f'
timepattern = re.compile(r'^\d{2}:\d{2}:\d{2}(\.\d{6})?')
if valuestr.startswith('"') and valuestr.endswith('"'):
# it's a string
return valuestr[1:-1]
elif re.match(intpattern, valuestr):
# it's an integer
return int(valuestr)
elif re.match(floatpattern, valuestr):
# floating point number
return float(valuestr)
# now let's try the datetime objects; throws exception if it doesn't match
try:
return datetime.datetime.strptime(valuestr, datedtpattern).date()
except ValueError:
pass
try:
return datetime.datetime.strptime(valuestr, datedttimepattern)
except ValueError:
pass
# time parsing is complicated: Python's datetime module only accepts
# fractions of a second only up to 6 digits
mat = re.match(timepattern, valuestr)
if mat:
test = mat.group(0)
try:
return datetime.datetime.strptime(test, timedtpattern).time()
except ValueError:
pass
# If we get here, we still haven't returned anything.
logging.info(
"The value %s couldn't be parsed as " % valuestr
+ "int, float, date, time, datetime. Returning it as string.")
return valuestr | python | def _postprocess(valuestr):
"""
Takes value as str, returns str, int, float, date, datetime, or time
"""
# USGS has started quoting time sometimes. Grr, strip quotes in this case
intpattern = re.compile(r'^\-?\d+$')
floatpattern = re.compile(r'^\-?\d+\.\d+(E[+-]?\d\d+)?$')
datedtpattern = '%Y-%m-%d'
datedttimepattern = '%Y-%m-%dT%H:%M:%SZ'
timedtpattern = '%H:%M:%S.%f'
timepattern = re.compile(r'^\d{2}:\d{2}:\d{2}(\.\d{6})?')
if valuestr.startswith('"') and valuestr.endswith('"'):
# it's a string
return valuestr[1:-1]
elif re.match(intpattern, valuestr):
# it's an integer
return int(valuestr)
elif re.match(floatpattern, valuestr):
# floating point number
return float(valuestr)
# now let's try the datetime objects; throws exception if it doesn't match
try:
return datetime.datetime.strptime(valuestr, datedtpattern).date()
except ValueError:
pass
try:
return datetime.datetime.strptime(valuestr, datedttimepattern)
except ValueError:
pass
# time parsing is complicated: Python's datetime module only accepts
# fractions of a second only up to 6 digits
mat = re.match(timepattern, valuestr)
if mat:
test = mat.group(0)
try:
return datetime.datetime.strptime(test, timedtpattern).time()
except ValueError:
pass
# If we get here, we still haven't returned anything.
logging.info(
"The value %s couldn't be parsed as " % valuestr
+ "int, float, date, time, datetime. Returning it as string.")
return valuestr | [
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dgketchum/satellite_image | sat_image/warped_vrt.py | warp_vrt | def warp_vrt(directory, delete_extra=False, use_band_map=False,
overwrite=False, remove_bqa=True, return_profile=False):
""" Read in image geometry, resample subsequent images to same grid.
The purpose of this function is to snap many Landsat images to one geometry. Use Landsat578
to download and unzip them, then run them through this to get identical geometries for analysis.
Files
:param use_band_map:
:param delete_extra:
:param directory: A directory containing sub-directories of Landsat images.
:return: None
"""
if 'resample_meta.txt' in os.listdir(directory) and not overwrite:
print('{} has already had component images warped'.format(directory))
return None
mapping = {'LC8': Landsat8, 'LE7': Landsat7, 'LT5': Landsat5}
vrt_options = {}
list_dir = [x[0] for x in os.walk(directory) if os.path.basename(x[0])[:3] in mapping.keys()]
extras = [os.path.join(directory, x) for x in os.listdir(directory) if x.endswith('.tif')]
first = True
for d in list_dir:
sat = LandsatImage(d).satellite
paths = extras
root = os.path.join(directory, d)
if os.path.isdir(root):
for x in os.listdir(root):
if remove_bqa and x.endswith('BQA.TIF'):
try:
os.remove(x)
except FileNotFoundError:
pass
elif use_band_map:
bands = BandMap().selected
for y in bands[sat]:
if x.endswith('B{}.TIF'.format(y)):
paths.append(os.path.join(directory, d, x))
else:
if x.endswith('.TIF') or x.endswith('.tif'):
paths.append(os.path.join(directory, d, x))
if x.endswith('MTL.txt'):
mtl = os.path.join(directory, d, x)
if first:
landsat = mapping[sat](os.path.join(directory, d))
dst = landsat.rasterio_geometry
vrt_options = {'resampling': Resampling.nearest,
'dst_crs': dst['crs'],
'dst_transform': dst['transform'],
'dst_height': dst['height'],
'dst_width': dst['width']}
message = """
This directory has been resampled to same grid.
Master grid is {}.
{}
""".format(d, datetime.now())
with open(os.path.join(directory, 'resample_meta.txt'), 'w') as f:
f.write(message)
first = False
for tif_path in paths:
print('warping {}'.format(os.path.basename(tif_path)))
with rasopen(tif_path, 'r') as src:
with WarpedVRT(src, **vrt_options) as vrt:
data = vrt.read()
dst_dir, name = os.path.split(tif_path)
outfile = os.path.join(dst_dir, name)
meta = vrt.meta.copy()
meta['driver'] = 'GTiff'
with rasopen(outfile, 'w', **meta) as dst:
dst.write(data)
if delete_extra:
for x in os.listdir(os.path.join(directory, d)):
x_file = os.path.join(directory, d, x)
if x_file not in paths:
if x[-7:] not in ['ask.tif', 'MTL.txt']:
print('removing {}'.format(x_file))
os.remove(x_file)
if return_profile:
return dst | python | def warp_vrt(directory, delete_extra=False, use_band_map=False,
overwrite=False, remove_bqa=True, return_profile=False):
""" Read in image geometry, resample subsequent images to same grid.
The purpose of this function is to snap many Landsat images to one geometry. Use Landsat578
to download and unzip them, then run them through this to get identical geometries for analysis.
Files
:param use_band_map:
:param delete_extra:
:param directory: A directory containing sub-directories of Landsat images.
:return: None
"""
if 'resample_meta.txt' in os.listdir(directory) and not overwrite:
print('{} has already had component images warped'.format(directory))
return None
mapping = {'LC8': Landsat8, 'LE7': Landsat7, 'LT5': Landsat5}
vrt_options = {}
list_dir = [x[0] for x in os.walk(directory) if os.path.basename(x[0])[:3] in mapping.keys()]
extras = [os.path.join(directory, x) for x in os.listdir(directory) if x.endswith('.tif')]
first = True
for d in list_dir:
sat = LandsatImage(d).satellite
paths = extras
root = os.path.join(directory, d)
if os.path.isdir(root):
for x in os.listdir(root):
if remove_bqa and x.endswith('BQA.TIF'):
try:
os.remove(x)
except FileNotFoundError:
pass
elif use_band_map:
bands = BandMap().selected
for y in bands[sat]:
if x.endswith('B{}.TIF'.format(y)):
paths.append(os.path.join(directory, d, x))
else:
if x.endswith('.TIF') or x.endswith('.tif'):
paths.append(os.path.join(directory, d, x))
if x.endswith('MTL.txt'):
mtl = os.path.join(directory, d, x)
if first:
landsat = mapping[sat](os.path.join(directory, d))
dst = landsat.rasterio_geometry
vrt_options = {'resampling': Resampling.nearest,
'dst_crs': dst['crs'],
'dst_transform': dst['transform'],
'dst_height': dst['height'],
'dst_width': dst['width']}
message = """
This directory has been resampled to same grid.
Master grid is {}.
{}
""".format(d, datetime.now())
with open(os.path.join(directory, 'resample_meta.txt'), 'w') as f:
f.write(message)
first = False
for tif_path in paths:
print('warping {}'.format(os.path.basename(tif_path)))
with rasopen(tif_path, 'r') as src:
with WarpedVRT(src, **vrt_options) as vrt:
data = vrt.read()
dst_dir, name = os.path.split(tif_path)
outfile = os.path.join(dst_dir, name)
meta = vrt.meta.copy()
meta['driver'] = 'GTiff'
with rasopen(outfile, 'w', **meta) as dst:
dst.write(data)
if delete_extra:
for x in os.listdir(os.path.join(directory, d)):
x_file = os.path.join(directory, d, x)
if x_file not in paths:
if x[-7:] not in ['ask.tif', 'MTL.txt']:
print('removing {}'.format(x_file))
os.remove(x_file)
if return_profile:
return dst | [
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samstav/tox-pyenv | tox_pyenv.py | tox_get_python_executable | def tox_get_python_executable(envconfig):
"""Return a python executable for the given python base name.
The first plugin/hook which returns an executable path will determine it.
``envconfig`` is the testenv configuration which contains
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stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
universal_newlines=True
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out, err = pipe.communicate()
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LOG.warning(
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)
else:
if pipe.poll() == 0:
return out.strip()
else:
if not envconfig.tox_pyenv_fallback:
raise PyenvWhichFailed(err)
LOG.debug("`%s` failed thru tox-pyenv plugin, falling back. "
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"""Return a python executable for the given python base name.
The first plugin/hook which returns an executable path will determine it.
``envconfig`` is the testenv configuration which contains
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"""
try:
# pylint: disable=no-member
pyenv = (getattr(py.path.local.sysfind('pyenv'), 'strpath', 'pyenv')
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cmd = [pyenv, 'which', envconfig.basepython]
pipe = subprocess.Popen(
cmd,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
universal_newlines=True
)
out, err = pipe.communicate()
except OSError:
err = '\'pyenv\': command not found'
LOG.warning(
"pyenv doesn't seem to be installed, you probably "
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)
else:
if pipe.poll() == 0:
return out.strip()
else:
if not envconfig.tox_pyenv_fallback:
raise PyenvWhichFailed(err)
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samstav/tox-pyenv | tox_pyenv.py | _setup_no_fallback | def _setup_no_fallback(parser):
"""Add the option, --tox-pyenv-no-fallback.
If this option is set, do not allow fallback to tox's built-in
strategy for looking up python executables if the call to `pyenv which`
by this plugin fails. This will allow the error to raise instead
of falling back to tox's default behavior.
"""
cli_dest = 'tox_pyenv_fallback'
halp = ('If `pyenv which {basepython}` exits non-zero when looking '
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# Add a command-line option.
tox_pyenv_group = parser.argparser.add_argument_group(
title='{0} plugin options'.format(__title__),
)
tox_pyenv_group.add_argument(
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action='store_false',
help=halp
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def _pyenv_fallback(testenv_config, value):
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"""Add the option, --tox-pyenv-no-fallback.
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strategy for looking up python executables if the call to `pyenv which`
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alanjcastonguay/pyforce | src/pyforce/xmlclient.py | Client.sendEmail | def sendEmail(self, emails, massType='SingleEmailMessage'):
"""
Send one or more emails from Salesforce.
Parameters:
emails - a dictionary or list of dictionaries, each representing a
single email as described by https://www.salesforce.com/us
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massType - 'SingleEmailMessage' or 'MassEmailMessage'.
MassEmailMessage is used for mailmerge of up to 250
recepients in a single pass.
Note:
Newly created Salesforce Sandboxes default to System email only. In
this situation, sendEmail() will fail with NO_MASS_MAIL_PERMISSION.
"""
return SendEmailRequest(
self.__serverUrl,
self.sessionId,
emails,
massType
).post(self.__conn) | python | def sendEmail(self, emails, massType='SingleEmailMessage'):
"""
Send one or more emails from Salesforce.
Parameters:
emails - a dictionary or list of dictionaries, each representing a
single email as described by https://www.salesforce.com/us
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massType - 'SingleEmailMessage' or 'MassEmailMessage'.
MassEmailMessage is used for mailmerge of up to 250
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Note:
Newly created Salesforce Sandboxes default to System email only. In
this situation, sendEmail() will fail with NO_MASS_MAIL_PERMISSION.
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return SendEmailRequest(
self.__serverUrl,
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massType
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alanjcastonguay/pyforce | src/pyforce/xmltramp.py | quote | def quote(myitem, elt=True):
'''URL encode string'''
if elt and '<' in myitem and len(myitem) > 24 and myitem.find(']]>') == -1:
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else:
myitem = myitem.replace('&', '&').\
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if not elt:
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return myitem | python | def quote(myitem, elt=True):
'''URL encode string'''
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alanjcastonguay/pyforce | src/pyforce/pyforce.py | _doPrep | def _doPrep(field_dict):
"""
_doPrep is makes changes in-place.
Do some prep work converting python types into formats that
Salesforce will accept.
This includes converting lists of strings to "apple;orange;pear".
Dicts will be converted to embedded objects
None or empty list values will be Null-ed
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fieldsToNull = []
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field_dict[key] = ";".join(value)
if 'fieldsToNull' in field_dict:
raise ValueError(
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field_dict['fieldsToNull'] = fieldsToNull | python | def _doPrep(field_dict):
"""
_doPrep is makes changes in-place.
Do some prep work converting python types into formats that
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This includes converting lists of strings to "apple;orange;pear".
Dicts will be converted to embedded objects
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fieldsToNull = []
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fieldsToNull.append(key)
field_dict[key] = []
if hasattr(value, '__iter__'):
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field_dict[key] = innerCopy
else:
field_dict[key] = ";".join(value)
if 'fieldsToNull' in field_dict:
raise ValueError(
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field_dict['fieldsToNull'] = fieldsToNull | [
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Dicts will be converted to embedded objects
None or empty list values will be Null-ed | [
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alanjcastonguay/pyforce | src/pyforce/pyforce.py | _prepareSObjects | def _prepareSObjects(sObjects):
'''Prepare a SObject'''
sObjectsCopy = copy.deepcopy(sObjects)
if isinstance(sObjectsCopy, dict):
# If root element is a dict, then this is a single object not an array
_doPrep(sObjectsCopy)
else:
# else this is an array, and each elelment should be prepped.
for listitems in sObjectsCopy:
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return sObjectsCopy | python | def _prepareSObjects(sObjects):
'''Prepare a SObject'''
sObjectsCopy = copy.deepcopy(sObjects)
if isinstance(sObjectsCopy, dict):
# If root element is a dict, then this is a single object not an array
_doPrep(sObjectsCopy)
else:
# else this is an array, and each elelment should be prepped.
for listitems in sObjectsCopy:
_doPrep(listitems)
return sObjectsCopy | [
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alanjcastonguay/pyforce | src/pyforce/pyforce.py | Client.sendEmail | def sendEmail(self, emails, mass_type='SingleEmailMessage'):
"""
Send one or more emails from Salesforce.
Parameters:
emails - a dictionary or list of dictionaries, each representing
a single email as described by https://www.salesforce.com
/us/developer/docs/api/Content/sforce_api_calls_sendemail
.htm
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Note:
Newly created Salesforce Sandboxes default to System email only.
In this situation, sendEmail() will fail with
NO_MASS_MAIL_PERMISSION.
"""
preparedEmails = _prepareSObjects(emails)
if isinstance(preparedEmails, dict):
# If root element is a dict, then this is a single object not an
# array
del preparedEmails['fieldsToNull']
else:
# else this is an array, and each elelment should be prepped.
for listitems in preparedEmails:
del listitems['fieldsToNull']
res = BaseClient.sendEmail(self, preparedEmails, mass_type)
if type(res) not in (TupleType, ListType):
res = [res]
data = list()
for resu in res:
d = dict()
data.append(d)
d['success'] = success = _bool(resu[_tPartnerNS.success])
if not success:
d['errors'] = [_extractError(e)
for e in resu[_tPartnerNS.errors,]]
else:
d['errors'] = list()
return data | python | def sendEmail(self, emails, mass_type='SingleEmailMessage'):
"""
Send one or more emails from Salesforce.
Parameters:
emails - a dictionary or list of dictionaries, each representing
a single email as described by https://www.salesforce.com
/us/developer/docs/api/Content/sforce_api_calls_sendemail
.htm
massType - 'SingleEmailMessage' or 'MassEmailMessage'.
MassEmailMessage is used for mailmerge of up to 250
recepients in a single pass.
Note:
Newly created Salesforce Sandboxes default to System email only.
In this situation, sendEmail() will fail with
NO_MASS_MAIL_PERMISSION.
"""
preparedEmails = _prepareSObjects(emails)
if isinstance(preparedEmails, dict):
# If root element is a dict, then this is a single object not an
# array
del preparedEmails['fieldsToNull']
else:
# else this is an array, and each elelment should be prepped.
for listitems in preparedEmails:
del listitems['fieldsToNull']
res = BaseClient.sendEmail(self, preparedEmails, mass_type)
if type(res) not in (TupleType, ListType):
res = [res]
data = list()
for resu in res:
d = dict()
data.append(d)
d['success'] = success = _bool(resu[_tPartnerNS.success])
if not success:
d['errors'] = [_extractError(e)
for e in resu[_tPartnerNS.errors,]]
else:
d['errors'] = list()
return data | [
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.htm
massType - 'SingleEmailMessage' or 'MassEmailMessage'.
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alanjcastonguay/pyforce | src/pyforce/pyforce.py | Client.queryTypesDescriptions | def queryTypesDescriptions(self, types):
"""
Given a list of types, construct a dictionary such that
each key is a type, and each value is the corresponding sObject
for that type.
"""
types = list(types)
if types:
types_descs = self.describeSObjects(types)
else:
types_descs = []
return dict(map(lambda t, d: (t, d), types, types_descs)) | python | def queryTypesDescriptions(self, types):
"""
Given a list of types, construct a dictionary such that
each key is a type, and each value is the corresponding sObject
for that type.
"""
types = list(types)
if types:
types_descs = self.describeSObjects(types)
else:
types_descs = []
return dict(map(lambda t, d: (t, d), types, types_descs)) | [
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miguelgrinberg/flask-paranoid | flask_paranoid/paranoid.py | Paranoid.create_token | def create_token(self):
"""Create a session protection token for this client.
This method generates a session protection token for the cilent, which
consists in a hash of the user agent and the IP address. This method
can be overriden by subclasses to implement different token generation
algorithms.
"""
user_agent = request.headers.get('User-Agent')
if user_agent is None: # pragma: no cover
user_agent = 'no user agent'
user_agent = user_agent.encode('utf-8')
base = self._get_remote_addr() + b'|' + user_agent
h = sha256()
h.update(base)
return h.hexdigest() | python | def create_token(self):
"""Create a session protection token for this client.
This method generates a session protection token for the cilent, which
consists in a hash of the user agent and the IP address. This method
can be overriden by subclasses to implement different token generation
algorithms.
"""
user_agent = request.headers.get('User-Agent')
if user_agent is None: # pragma: no cover
user_agent = 'no user agent'
user_agent = user_agent.encode('utf-8')
base = self._get_remote_addr() + b'|' + user_agent
h = sha256()
h.update(base)
return h.hexdigest() | [
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miguelgrinberg/flask-paranoid | flask_paranoid/paranoid.py | Paranoid.clear_session | def clear_session(self, response):
"""Clear the session.
This method is invoked when the session is found to be invalid.
Subclasses can override this method to implement a custom session
reset.
"""
session.clear()
# if flask-login is installed, we try to clear the
# "remember me" cookie, just in case it is set
if 'flask_login' in sys.modules:
remember_cookie = current_app.config.get('REMEMBER_COOKIE',
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response.set_cookie(remember_cookie, '', expires=0, max_age=0) | python | def clear_session(self, response):
"""Clear the session.
This method is invoked when the session is found to be invalid.
Subclasses can override this method to implement a custom session
reset.
"""
session.clear()
# if flask-login is installed, we try to clear the
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if 'flask_login' in sys.modules:
remember_cookie = current_app.config.get('REMEMBER_COOKIE',
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Atrox/haikunatorpy | haikunator/haikunator.py | Haikunator.haikunate | def haikunate(self, delimiter='-', token_length=4, token_hex=False, token_chars='0123456789'):
"""
Generate heroku-like random names to use in your python applications
:param delimiter: Delimiter
:param token_length: TokenLength
:param token_hex: TokenHex
:param token_chars: TokenChars
:type delimiter: str
:type token_length: int
:type token_hex: bool
:type token_chars: str
:return: heroku-like random string
:rtype: str
"""
if token_hex:
token_chars = '0123456789abcdef'
adjective = self._random_element(self._adjectives)
noun = self._random_element(self._nouns)
token = ''.join(self._random_element(token_chars) for _ in range(token_length))
sections = [adjective, noun, token]
return delimiter.join(filter(None, sections)) | python | def haikunate(self, delimiter='-', token_length=4, token_hex=False, token_chars='0123456789'):
"""
Generate heroku-like random names to use in your python applications
:param delimiter: Delimiter
:param token_length: TokenLength
:param token_hex: TokenHex
:param token_chars: TokenChars
:type delimiter: str
:type token_length: int
:type token_hex: bool
:type token_chars: str
:return: heroku-like random string
:rtype: str
"""
if token_hex:
token_chars = '0123456789abcdef'
adjective = self._random_element(self._adjectives)
noun = self._random_element(self._nouns)
token = ''.join(self._random_element(token_chars) for _ in range(token_length))
sections = [adjective, noun, token]
return delimiter.join(filter(None, sections)) | [
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ftao/python-ifcfg | src/ifcfg/__init__.py | get_parser_class | def get_parser_class():
"""
Returns the parser according to the system platform
"""
global distro
if distro == 'Linux':
Parser = parser.LinuxParser
if not os.path.exists(Parser.get_command()[0]):
Parser = parser.UnixIPParser
elif distro in ['Darwin', 'MacOSX']:
Parser = parser.MacOSXParser
elif distro == 'Windows':
# For some strange reason, Windows will always be win32, see:
# https://stackoverflow.com/a/2145582/405682
Parser = parser.WindowsParser
else:
Parser = parser.NullParser
Log.error("Unknown distro type '%s'." % distro)
Log.debug("Distro detected as '%s'" % distro)
Log.debug("Using '%s'" % Parser)
return Parser | python | def get_parser_class():
"""
Returns the parser according to the system platform
"""
global distro
if distro == 'Linux':
Parser = parser.LinuxParser
if not os.path.exists(Parser.get_command()[0]):
Parser = parser.UnixIPParser
elif distro in ['Darwin', 'MacOSX']:
Parser = parser.MacOSXParser
elif distro == 'Windows':
# For some strange reason, Windows will always be win32, see:
# https://stackoverflow.com/a/2145582/405682
Parser = parser.WindowsParser
else:
Parser = parser.NullParser
Log.error("Unknown distro type '%s'." % distro)
Log.debug("Distro detected as '%s'" % distro)
Log.debug("Using '%s'" % Parser)
return Parser | [
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ftao/python-ifcfg | src/ifcfg/__init__.py | default_interface | def default_interface(ifconfig=None, route_output=None):
"""
Return just the default interface device dictionary.
:param ifconfig: For mocking actual command output
:param route_output: For mocking actual command output
"""
global Parser
return Parser(ifconfig=ifconfig)._default_interface(route_output=route_output) | python | def default_interface(ifconfig=None, route_output=None):
"""
Return just the default interface device dictionary.
:param ifconfig: For mocking actual command output
:param route_output: For mocking actual command output
"""
global Parser
return Parser(ifconfig=ifconfig)._default_interface(route_output=route_output) | [
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ftao/python-ifcfg | src/ifcfg/parser.py | Parser.parse | def parse(self, ifconfig=None): # noqa: max-complexity=12
"""
Parse ifconfig output into self._interfaces.
Optional Arguments:
ifconfig
The data (stdout) from the ifconfig command. Default is to
call exec_cmd(self.get_command()).
"""
if not ifconfig:
ifconfig, __, __ = exec_cmd(self.get_command())
self.ifconfig_data = ifconfig
cur = None
patterns = self.get_patterns()
for line in self.ifconfig_data.splitlines():
for pattern in patterns:
m = re.match(pattern, line)
if not m:
continue
groupdict = m.groupdict()
# Special treatment to trigger which interface we're
# setting for if 'device' is in the line. Presumably the
# device of the interface is within the first line of the
# device block.
if 'device' in groupdict:
cur = groupdict['device']
self.add_device(cur)
elif cur is None:
raise RuntimeError(
"Got results that don't belong to a device"
)
for k, v in groupdict.items():
if k in self._interfaces[cur]:
if self._interfaces[cur][k] is None:
self._interfaces[cur][k] = v
elif hasattr(self._interfaces[cur][k], 'append'):
self._interfaces[cur][k].append(v)
elif self._interfaces[cur][k] == v:
# Silently ignore if the it's the same value as last. Example: Multiple
# inet4 addresses, result in multiple netmasks. Cardinality mismatch
continue
else:
raise RuntimeError(
"Tried to add {}={} multiple times to {}, it was already: {}".format(
k,
v,
cur,
self._interfaces[cur][k]
)
)
else:
self._interfaces[cur][k] = v
# Copy the first 'inet4' ip address to 'inet' for backwards compatibility
for device, device_dict in self._interfaces.items():
if len(device_dict['inet4']) > 0:
device_dict['inet'] = device_dict['inet4'][0]
# fix it up
self._interfaces = self.alter(self._interfaces) | python | def parse(self, ifconfig=None): # noqa: max-complexity=12
"""
Parse ifconfig output into self._interfaces.
Optional Arguments:
ifconfig
The data (stdout) from the ifconfig command. Default is to
call exec_cmd(self.get_command()).
"""
if not ifconfig:
ifconfig, __, __ = exec_cmd(self.get_command())
self.ifconfig_data = ifconfig
cur = None
patterns = self.get_patterns()
for line in self.ifconfig_data.splitlines():
for pattern in patterns:
m = re.match(pattern, line)
if not m:
continue
groupdict = m.groupdict()
# Special treatment to trigger which interface we're
# setting for if 'device' is in the line. Presumably the
# device of the interface is within the first line of the
# device block.
if 'device' in groupdict:
cur = groupdict['device']
self.add_device(cur)
elif cur is None:
raise RuntimeError(
"Got results that don't belong to a device"
)
for k, v in groupdict.items():
if k in self._interfaces[cur]:
if self._interfaces[cur][k] is None:
self._interfaces[cur][k] = v
elif hasattr(self._interfaces[cur][k], 'append'):
self._interfaces[cur][k].append(v)
elif self._interfaces[cur][k] == v:
# Silently ignore if the it's the same value as last. Example: Multiple
# inet4 addresses, result in multiple netmasks. Cardinality mismatch
continue
else:
raise RuntimeError(
"Tried to add {}={} multiple times to {}, it was already: {}".format(
k,
v,
cur,
self._interfaces[cur][k]
)
)
else:
self._interfaces[cur][k] = v
# Copy the first 'inet4' ip address to 'inet' for backwards compatibility
for device, device_dict in self._interfaces.items():
if len(device_dict['inet4']) > 0:
device_dict['inet'] = device_dict['inet4'][0]
# fix it up
self._interfaces = self.alter(self._interfaces) | [
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The data (stdout) from the ifconfig command. Default is to
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ftao/python-ifcfg | src/ifcfg/parser.py | Parser.alter | def alter(self, interfaces):
"""
Used to provide the ability to alter the interfaces dictionary before
it is returned from self.parse().
Required Arguments:
interfaces
The interfaces dictionary.
Returns: interfaces dict
"""
# fixup some things
for device, device_dict in interfaces.items():
if len(device_dict['inet4']) > 0:
device_dict['inet'] = device_dict['inet4'][0]
if 'inet' in device_dict and not device_dict['inet'] is None:
try:
host = socket.gethostbyaddr(device_dict['inet'])[0]
interfaces[device]['hostname'] = host
except (socket.herror, socket.gaierror):
interfaces[device]['hostname'] = None
# To be sure that hex values and similar are always consistent, we
# return everything in lowercase. For instance, Windows writes
# MACs in upper-case.
for key, device_item in device_dict.items():
if hasattr(device_item, 'lower'):
interfaces[device][key] = device_dict[key].lower()
return interfaces | python | def alter(self, interfaces):
"""
Used to provide the ability to alter the interfaces dictionary before
it is returned from self.parse().
Required Arguments:
interfaces
The interfaces dictionary.
Returns: interfaces dict
"""
# fixup some things
for device, device_dict in interfaces.items():
if len(device_dict['inet4']) > 0:
device_dict['inet'] = device_dict['inet4'][0]
if 'inet' in device_dict and not device_dict['inet'] is None:
try:
host = socket.gethostbyaddr(device_dict['inet'])[0]
interfaces[device]['hostname'] = host
except (socket.herror, socket.gaierror):
interfaces[device]['hostname'] = None
# To be sure that hex values and similar are always consistent, we
# return everything in lowercase. For instance, Windows writes
# MACs in upper-case.
for key, device_item in device_dict.items():
if hasattr(device_item, 'lower'):
interfaces[device][key] = device_dict[key].lower()
return interfaces | [
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The interfaces dictionary.
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ftao/python-ifcfg | src/ifcfg/parser.py | UnixIPParser._default_interface | def _default_interface(self, route_output=None):
"""
:param route_output: For mocking actual output
"""
if not route_output:
out, __, __ = exec_cmd('/sbin/ip route')
lines = out.splitlines()
else:
lines = route_output.split("\n")
for line in lines:
line = line.split()
if 'default' in line:
iface = line[4]
return self.interfaces.get(iface, None) | python | def _default_interface(self, route_output=None):
"""
:param route_output: For mocking actual output
"""
if not route_output:
out, __, __ = exec_cmd('/sbin/ip route')
lines = out.splitlines()
else:
lines = route_output.split("\n")
for line in lines:
line = line.split()
if 'default' in line:
iface = line[4]
return self.interfaces.get(iface, None) | [
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fossasia/AYABInterface | AYABInterface/communication/cache.py | NeedlePositionCache.get | def get(self, line_number):
"""Return the needle positions or None.
:param int line_number: the number of the line
:rtype: list
:return: the needle positions for a specific line specified by
:paramref:`line_number` or :obj:`None` if no were given
"""
if line_number not in self._get_cache:
self._get_cache[line_number] = self._get(line_number)
return self._get_cache[line_number] | python | def get(self, line_number):
"""Return the needle positions or None.
:param int line_number: the number of the line
:rtype: list
:return: the needle positions for a specific line specified by
:paramref:`line_number` or :obj:`None` if no were given
"""
if line_number not in self._get_cache:
self._get_cache[line_number] = self._get(line_number)
return self._get_cache[line_number] | [
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fossasia/AYABInterface | AYABInterface/communication/cache.py | NeedlePositionCache.get_bytes | def get_bytes(self, line_number):
"""Get the bytes representing needle positions or None.
:param int line_number: the line number to take the bytes from
:rtype: bytes
:return: the bytes that represent the message or :obj:`None` if no
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Depending on the :attr:`machine`, the length and result may vary.
"""
if line_number not in self._needle_position_bytes_cache:
line = self._get(line_number)
if line is None:
line_bytes = None
else:
line_bytes = self._machine.needle_positions_to_bytes(line)
self._needle_position_bytes_cache[line_number] = line_bytes
return self._needle_position_bytes_cache[line_number] | python | def get_bytes(self, line_number):
"""Get the bytes representing needle positions or None.
:param int line_number: the line number to take the bytes from
:rtype: bytes
:return: the bytes that represent the message or :obj:`None` if no
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Depending on the :attr:`machine`, the length and result may vary.
"""
if line_number not in self._needle_position_bytes_cache:
line = self._get(line_number)
if line is None:
line_bytes = None
else:
line_bytes = self._machine.needle_positions_to_bytes(line)
self._needle_position_bytes_cache[line_number] = line_bytes
return self._needle_position_bytes_cache[line_number] | [
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fossasia/AYABInterface | AYABInterface/communication/cache.py | NeedlePositionCache.get_line_configuration_message | def get_line_configuration_message(self, line_number):
"""Return the cnfLine content without id for the line.
:param int line_number: the number of the line
:rtype: bytes
:return: a cnfLine message without id as defined in :ref:`cnfLine`
"""
if line_number not in self._line_configuration_message_cache:
line_bytes = self.get_bytes(line_number)
if line_bytes is not None:
line_bytes = bytes([line_number & 255]) + line_bytes
line_bytes += bytes([self.is_last(line_number)])
line_bytes += crc8(line_bytes).digest()
self._line_configuration_message_cache[line_number] = line_bytes
del line_bytes
line = self._line_configuration_message_cache[line_number]
if line is None:
# no need to cache a lot of empty lines
line = (bytes([line_number & 255]) +
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' +
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01')
line += crc8(line).digest()
return line | python | def get_line_configuration_message(self, line_number):
"""Return the cnfLine content without id for the line.
:param int line_number: the number of the line
:rtype: bytes
:return: a cnfLine message without id as defined in :ref:`cnfLine`
"""
if line_number not in self._line_configuration_message_cache:
line_bytes = self.get_bytes(line_number)
if line_bytes is not None:
line_bytes = bytes([line_number & 255]) + line_bytes
line_bytes += bytes([self.is_last(line_number)])
line_bytes += crc8(line_bytes).digest()
self._line_configuration_message_cache[line_number] = line_bytes
del line_bytes
line = self._line_configuration_message_cache[line_number]
if line is None:
# no need to cache a lot of empty lines
line = (bytes([line_number & 255]) +
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' +
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01')
line += crc8(line).digest()
return line | [
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fossasia/AYABInterface | AYABInterface/communication/hardware_messages.py | read_message_type | def read_message_type(file):
"""Read the message type from a file."""
message_byte = file.read(1)
if message_byte == b'':
return ConnectionClosed
message_number = message_byte[0]
return _message_types.get(message_number, UnknownMessage) | python | def read_message_type(file):
"""Read the message type from a file."""
message_byte = file.read(1)
if message_byte == b'':
return ConnectionClosed
message_number = message_byte[0]
return _message_types.get(message_number, UnknownMessage) | [
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"""Read the b"\\r\\n" at the end of the message."""
read = self._file.read
last = read(1)
current = read(1)
while last != b'' and current != b'' and not \
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current = read(1) | [
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fossasia/AYABInterface | AYABInterface/communication/hardware_messages.py | InformationConfirmation._init | def _init(self):
"""Read the success byte."""
self._api_version = self._file.read(1)[0]
self._firmware_version = FirmwareVersion(*self._file.read(2)) | python | def _init(self):
"""Read the success byte."""
self._api_version = self._file.read(1)[0]
self._firmware_version = FirmwareVersion(*self._file.read(2)) | [
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fossasia/AYABInterface | AYABInterface/communication/hardware_messages.py | LineRequest._init | def _init(self):
"""Read the line number."""
self._line_number = next_line(
self._communication.last_requested_line_number,
self._file.read(1)[0]) | python | def _init(self):
"""Read the line number."""
self._line_number = next_line(
self._communication.last_requested_line_number,
self._file.read(1)[0]) | [
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fossasia/AYABInterface | AYABInterface/communication/hardware_messages.py | StateIndication._init | def _init(self):
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fossasia/AYABInterface | AYABInterface/communication/hardware_messages.py | Debug._init | def _init(self):
"""Read the b"\\r\\n" at the end of the message."""
read_values = []
read = self._file.read
last = read(1)
current = read(1)
while last != b'' and current != b'' and not \
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read_values.append(last)
last = current
current = read(1)
if current == b'' and last != b'\r':
read_values.append(last)
self._bytes = b''.join(read_values) | python | def _init(self):
"""Read the b"\\r\\n" at the end of the message."""
read_values = []
read = self._file.read
last = read(1)
current = read(1)
while last != b'' and current != b'' and not \
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read_values.append(last)
last = current
current = read(1)
if current == b'' and last != b'\r':
read_values.append(last)
self._bytes = b''.join(read_values) | [
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fossasia/AYABInterface | AYABInterface/communication/host_messages.py | Message.send | def send(self):
"""Send this message to the controller."""
self._file.write(self.as_bytes())
self._file.write(b'\r\n') | python | def send(self):
"""Send this message to the controller."""
self._file.write(self.as_bytes())
self._file.write(b'\r\n') | [
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fossasia/AYABInterface | AYABInterface/communication/host_messages.py | StartRequest.init | def init(self, left_end_needle, right_end_needle):
"""Initialize the StartRequest with start and stop needle.
:raises TypeError: if the arguments are not integers
:raises ValueError: if the values do not match the
:ref:`specification <m4-01>`
"""
if not isinstance(left_end_needle, int):
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if left_end_needle < 0 or left_end_needle > 198:
raise ValueError(_left_end_needle_error_message(left_end_needle))
if not isinstance(right_end_needle, int):
raise TypeError(_right_end_needle_error_message(right_end_needle))
if right_end_needle < 1 or right_end_needle > 199:
raise ValueError(_right_end_needle_error_message(right_end_needle))
self._left_end_needle = left_end_needle
self._right_end_needle = right_end_needle | python | def init(self, left_end_needle, right_end_needle):
"""Initialize the StartRequest with start and stop needle.
:raises TypeError: if the arguments are not integers
:raises ValueError: if the values do not match the
:ref:`specification <m4-01>`
"""
if not isinstance(left_end_needle, int):
raise TypeError(_left_end_needle_error_message(left_end_needle))
if left_end_needle < 0 or left_end_needle > 198:
raise ValueError(_left_end_needle_error_message(left_end_needle))
if not isinstance(right_end_needle, int):
raise TypeError(_right_end_needle_error_message(right_end_needle))
if right_end_needle < 1 or right_end_needle > 199:
raise ValueError(_right_end_needle_error_message(right_end_needle))
self._left_end_needle = left_end_needle
self._right_end_needle = right_end_needle | [
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fossasia/AYABInterface | AYABInterface/communication/host_messages.py | LineConfirmation.content_bytes | def content_bytes(self):
"""Return the start and stop needle."""
get_message = \
self._communication.needle_positions.get_line_configuration_message
return get_message(self._line_number) | python | def content_bytes(self):
"""Return the start and stop needle."""
get_message = \
self._communication.needle_positions.get_line_configuration_message
return get_message(self._line_number) | [
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fossasia/AYABInterface | AYABInterface/utils.py | sum_all | def sum_all(iterable, start):
"""Sum up an iterable starting with a start value.
In contrast to :func:`sum`, this also works on other types like
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"""
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start |= value
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"""Sum up an iterable starting with a start value.
In contrast to :func:`sum`, this also works on other types like
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"""
if hasattr(start, "__add__"):
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start += value
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for value in iterable:
start |= value
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fossasia/AYABInterface | AYABInterface/utils.py | next_line | def next_line(last_line, next_line_8bit):
"""Compute the next line based on the last line and a 8bit next line.
The behaviour of the function is specified in :ref:`reqline`.
:param int last_line: the last line that was processed
:param int next_line_8bit: the lower 8 bits of the next line
:return: the next line closest to :paramref:`last_line`
.. seealso:: :ref:`reqline`
"""
# compute the line without the lowest byte
base_line = last_line - (last_line & 255)
# compute the three different lines
line = base_line + next_line_8bit
lower_line = line - 256
upper_line = line + 256
# compute the next line
if last_line - lower_line <= line - last_line:
return lower_line
if upper_line - last_line < last_line - line:
return upper_line
return line | python | def next_line(last_line, next_line_8bit):
"""Compute the next line based on the last line and a 8bit next line.
The behaviour of the function is specified in :ref:`reqline`.
:param int last_line: the last line that was processed
:param int next_line_8bit: the lower 8 bits of the next line
:return: the next line closest to :paramref:`last_line`
.. seealso:: :ref:`reqline`
"""
# compute the line without the lowest byte
base_line = last_line - (last_line & 255)
# compute the three different lines
line = base_line + next_line_8bit
lower_line = line - 256
upper_line = line + 256
# compute the next line
if last_line - lower_line <= line - last_line:
return lower_line
if upper_line - last_line < last_line - line:
return upper_line
return line | [
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fossasia/AYABInterface | AYABInterface/utils.py | camel_case_to_under_score | def camel_case_to_under_score(camel_case_name):
"""Return the underscore name of a camel case name.
:param str camel_case_name: a name in camel case such as
``"ACamelCaseName"``
:return: the name using underscores, e.g. ``"a_camel_case_name"``
:rtype: str
"""
result = []
for letter in camel_case_name:
if letter.lower() != letter:
result.append("_" + letter.lower())
else:
result.append(letter.lower())
if result[0].startswith("_"):
result[0] = result[0][1:]
return "".join(result) | python | def camel_case_to_under_score(camel_case_name):
"""Return the underscore name of a camel case name.
:param str camel_case_name: a name in camel case such as
``"ACamelCaseName"``
:return: the name using underscores, e.g. ``"a_camel_case_name"``
:rtype: str
"""
result = []
for letter in camel_case_name:
if letter.lower() != letter:
result.append("_" + letter.lower())
else:
result.append(letter.lower())
if result[0].startswith("_"):
result[0] = result[0][1:]
return "".join(result) | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication._message_received | def _message_received(self, message):
"""Notify the observers about the received message."""
with self.lock:
self._state.receive_message(message)
for callable in chain(self._on_message_received, self._on_message):
callable(message) | python | def _message_received(self, message):
"""Notify the observers about the received message."""
with self.lock:
self._state.receive_message(message)
for callable in chain(self._on_message_received, self._on_message):
callable(message) | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.receive_message | def receive_message(self):
"""Receive a message from the file."""
with self.lock:
assert self.can_receive_messages()
message_type = self._read_message_type(self._file)
message = message_type(self._file, self)
self._message_received(message) | python | def receive_message(self):
"""Receive a message from the file."""
with self.lock:
assert self.can_receive_messages()
message_type = self._read_message_type(self._file)
message = message_type(self._file, self)
self._message_received(message) | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.can_receive_messages | def can_receive_messages(self):
"""Whether tihs communication is ready to receive messages.]
:rtype: bool
.. code:: python
assert not communication.can_receive_messages()
communication.start()
assert communication.can_receive_messages()
communication.stop()
assert not communication.can_receive_messages()
"""
with self.lock:
return not self._state.is_waiting_for_start() and \
not self._state.is_connection_closed() | python | def can_receive_messages(self):
"""Whether tihs communication is ready to receive messages.]
:rtype: bool
.. code:: python
assert not communication.can_receive_messages()
communication.start()
assert communication.can_receive_messages()
communication.stop()
assert not communication.can_receive_messages()
"""
with self.lock:
return not self._state.is_waiting_for_start() and \
not self._state.is_connection_closed() | [
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.. code:: python
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assert not communication.can_receive_messages() | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.stop | def stop(self):
"""Stop the communication with the shield."""
with self.lock:
self._message_received(ConnectionClosed(self._file, self)) | python | def stop(self):
"""Stop the communication with the shield."""
with self.lock:
self._message_received(ConnectionClosed(self._file, self)) | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.send | def send(self, host_message_class, *args):
"""Send a host message.
:param type host_message_class: a subclass of
:class:`AYABImterface.communication.host_messages.Message`
:param args: additional arguments that shall be passed to the
:paramref:`host_message_class` as arguments
"""
message = host_message_class(self._file, self, *args)
with self.lock:
message.send()
for callable in self._on_message:
callable(message) | python | def send(self, host_message_class, *args):
"""Send a host message.
:param type host_message_class: a subclass of
:class:`AYABImterface.communication.host_messages.Message`
:param args: additional arguments that shall be passed to the
:paramref:`host_message_class` as arguments
"""
message = host_message_class(self._file, self, *args)
with self.lock:
message.send()
for callable in self._on_message:
callable(message) | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.state | def state(self, new_state):
"""Set the state."""
with self.lock:
self._state.exit()
self._state = new_state
self._state.enter() | python | def state(self, new_state):
"""Set the state."""
with self.lock:
self._state.exit()
self._state = new_state
self._state.enter() | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication.parallelize | def parallelize(self, seconds_to_wait=2):
"""Start a parallel thread for receiving messages.
If :meth:`start` was no called before, start will be called in the
thread.
The thread calls :meth:`receive_message` until the :attr:`state`
:meth:`~AYABInterface.communication.states.State.is_connection_closed`.
:param float seconds_to_wait: A time in seconds to wait with the
parallel execution. This is useful to allow the controller time to
initialize.
.. seealso:: :attr:`lock`, :meth:`runs_in_parallel`
"""
with self.lock:
thread = Thread(target=self._parallel_receive_loop,
args=(seconds_to_wait,))
thread.deamon = True
thread.start()
self._thread = thread | python | def parallelize(self, seconds_to_wait=2):
"""Start a parallel thread for receiving messages.
If :meth:`start` was no called before, start will be called in the
thread.
The thread calls :meth:`receive_message` until the :attr:`state`
:meth:`~AYABInterface.communication.states.State.is_connection_closed`.
:param float seconds_to_wait: A time in seconds to wait with the
parallel execution. This is useful to allow the controller time to
initialize.
.. seealso:: :attr:`lock`, :meth:`runs_in_parallel`
"""
with self.lock:
thread = Thread(target=self._parallel_receive_loop,
args=(seconds_to_wait,))
thread.deamon = True
thread.start()
self._thread = thread | [
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fossasia/AYABInterface | AYABInterface/communication/__init__.py | Communication._parallel_receive_loop | def _parallel_receive_loop(self, seconds_to_wait):
"""Run the receiving in parallel."""
sleep(seconds_to_wait)
with self._lock:
self._number_of_threads_receiving_messages += 1
try:
with self._lock:
if self.state.is_waiting_for_start():
self.start()
while True:
with self.lock:
if self.state.is_connection_closed():
return
self.receive_message()
finally:
with self._lock:
self._number_of_threads_receiving_messages -= 1 | python | def _parallel_receive_loop(self, seconds_to_wait):
"""Run the receiving in parallel."""
sleep(seconds_to_wait)
with self._lock:
self._number_of_threads_receiving_messages += 1
try:
with self._lock:
if self.state.is_waiting_for_start():
self.start()
while True:
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return
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finally:
with self._lock:
self._number_of_threads_receiving_messages -= 1 | [
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