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Update app.py
Browse files
app.py
CHANGED
@@ -7,6 +7,8 @@ from datetime import datetime
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from functools import lru_cache
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import time
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st.set_page_config(page_title="HF Contributions", layout="wide")
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api = HfApi()
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@@ -34,28 +36,57 @@ def cached_list_items(username, kind):
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return []
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# Function to fetch trending
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@lru_cache(maxsize=1)
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def get_trending_accounts(limit=100):
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except Exception as e:
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st.error(f"Error fetching trending accounts: {str(e)}")
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# Rate limiting
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@@ -207,51 +238,61 @@ with st.sidebar:
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# Fetch trending accounts with a loading spinner
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with st.spinner("Loading top trending accounts..."):
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trending_accounts = get_trending_accounts(limit=100)
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#
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# Filter accounts based on search
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filtered_accounts = [acc for acc in trending_accounts if search_filter.lower() in acc.lower()] if search_filter else trending_accounts
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# Show account count
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st.caption(f"Showing {len(filtered_accounts)} accounts")
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# Create a scrollable container for the accounts list
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account_container = st.container()
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with account_container:
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selected_trending = st.selectbox(
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"Select trending account",
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options=filtered_accounts,
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index=0 if filtered_accounts else None,
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key="trending_selectbox"
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)
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"Select
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options=
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index=0
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)
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st.markdown("<div style='text-align: center; margin: 10px 0;'>OR</div>", unsafe_allow_html=True)
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custom = st.text_input("", placeholder="Enter custom username/org")
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if custom.strip():
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username = custom.strip()
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elif
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username =
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# Year selection
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st.subheader("🗓️ Time Period")
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year_options = list(range(datetime.now().year, 2017, -1))
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selected_year = st.selectbox("Select Year", options=year_options)
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st.title("🤗 Hugging Face Contributions")
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if username:
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with st.spinner(f"Fetching commit data for {username}..."):
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# Create a dictionary to store commits by type
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commits_by_type = {}
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commit_counts_by_type = {}
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@@ -342,6 +388,13 @@ if username:
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with profile_col2:
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st.metric("Total Commits", total_commits)
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st.markdown(f"[View Profile on Hugging Face](https://huggingface.co/{username})")
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# Create DataFrame for all commits
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from functools import lru_cache
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import time
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import requests
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from collections import Counter
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st.set_page_config(page_title="HF Contributions", layout="wide")
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api = HfApi()
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return []
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# Function to fetch trending accounts and create stats
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@lru_cache(maxsize=1)
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def get_trending_accounts(limit=100):
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try:
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# Get spaces for stats calculation
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spaces_response = requests.get("https://huggingface.co/api/spaces",
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params={"limit": 10000},
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timeout=30)
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if spaces_response.status_code == 200:
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spaces = spaces_response.json()
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# Count spaces by owner
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owner_counts = {}
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for space in spaces:
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if '/' in space.get('id', ''):
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owner, _ = space.get('id', '').split('/', 1)
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else:
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owner = space.get('owner', '')
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if owner != 'None':
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owner_counts[owner] = owner_counts.get(owner, 0) + 1
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# Get top owners by count
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top_owners = sorted(owner_counts.items(), key=lambda x: x[1], reverse=True)[:limit]
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# Extract just the owner names for dropdown
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trending_authors = [owner for owner, count in top_owners]
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return trending_authors, top_owners
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else:
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# Fallback to API method if HTTP request fails
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trending_models = list(api.list_models(sort="trending", limit=limit))
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trending_datasets = list(api.list_datasets(sort="trending", limit=limit))
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trending_spaces = list(api.list_spaces(sort="trending", limit=limit))
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# Extract unique authors
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authors = set()
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for item in trending_models + trending_datasets + trending_spaces:
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if hasattr(item, "author"):
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authors.add(item.author)
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elif hasattr(item, "id") and "/" in item.id:
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authors.add(item.id.split("/")[0])
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# Return sorted list of unique authors and empty stats
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author_list = sorted(list(authors))[:limit]
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return author_list, [(author, 0) for author in author_list[:30]]
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except Exception as e:
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st.error(f"Error fetching trending accounts: {str(e)}")
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fallback_authors = ["ritvik77", "facebook", "google", "stabilityai", "Salesforce", "tiiuae", "bigscience"]
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return fallback_authors, [(author, 0) for author in fallback_authors]
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# Rate limiting
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# Fetch trending accounts with a loading spinner
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with st.spinner("Loading top trending accounts..."):
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trending_accounts, top_owners = get_trending_accounts(limit=100)
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# Show trending accounts list with search filter
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st.subheader("🔥 Top Trending Accounts")
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# Add stats expander
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with st.expander("View Top 30 Contributor Stats"):
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# Create a bar chart for top 30 contributors
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if top_owners:
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chart_data = pd.DataFrame(top_owners[:30], columns=["Owner", "Spaces Count"])
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fig, ax = plt.subplots(figsize=(10, 8))
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bars = ax.barh(chart_data["Owner"], chart_data["Spaces Count"])
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# Add color gradient to bars
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for i, bar in enumerate(bars):
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bar.set_color(plt.cm.viridis(i/len(bars)))
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ax.set_title("Top 30 Contributors by Number of Spaces")
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ax.set_xlabel("Number of Spaces")
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plt.tight_layout()
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st.pyplot(fig)
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# Search filter
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search_filter = st.text_input("Filter accounts", key="trending_filter")
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# Filter accounts based on search
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filtered_accounts = [acc for acc in trending_accounts if search_filter.lower() in acc.lower()] if search_filter else trending_accounts
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# Show account count
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st.caption(f"Showing {len(filtered_accounts)} of {len(trending_accounts)} accounts")
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# Create a scrollable container for the accounts list
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account_container = st.container()
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with account_container:
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selected_trending = st.selectbox(
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"Select trending account",
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options=filtered_accounts,
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index=0 if filtered_accounts else None,
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key="trending_selectbox"
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)
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# Custom account input option
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st.markdown("<div style='text-align: center; margin: 10px 0;'>OR</div>", unsafe_allow_html=True)
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custom = st.text_input("", placeholder="Enter custom username/org")
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# Set username based on selection or custom input
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if custom.strip():
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username = custom.strip()
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elif selected_trending:
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username = selected_trending
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else:
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username = "facebook" # Default fallback
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# Year selection
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st.subheader("🗓️ Time Period")
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year_options = list(range(datetime.now().year, 2017, -1))
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selected_year = st.selectbox("Select Year", options=year_options)
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st.title("🤗 Hugging Face Contributions")
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if username:
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with st.spinner(f"Fetching commit data for {username}..."):
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# Display contributor rank if in top 100
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if username in trending_accounts:
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rank = trending_accounts.index(username) + 1
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st.success(f"🏆 {username} is ranked #{rank} in the top trending contributors!")
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# Create a dictionary to store commits by type
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commits_by_type = {}
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commit_counts_by_type = {}
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with profile_col2:
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st.metric("Total Commits", total_commits)
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# Show contributor rank if in top owners
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for owner, count in top_owners:
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if owner.lower() == username.lower():
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st.metric("Spaces Count", count)
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break
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st.markdown(f"[View Profile on Hugging Face](https://huggingface.co/{username})")
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# Create DataFrame for all commits
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