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Duplicate from bigcode/clean-issues-visualization
Browse files- .gitattributes +34 -0
- README.md +14 -0
- app.py +26 -0
.gitattributes
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README.md
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---
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title: Clean Issues Visualization
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emoji: 🐨
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colorFrom: red
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colorTo: purple
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sdk: streamlit
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sdk_version: 1.17.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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duplicated_from: bigcode/clean-issues-visualization
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import streamlit as st
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import json
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from datasets import load_dataset
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st.set_page_config(page_title="Clean GitHub Issues", layout="wide")
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st.title("GitHub Issues visualization after filtering")
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@st.cache()
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def load_data():
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ds = load_dataset("loubnabnl/preprocessed-issues", split="train")
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return ds
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def print_issue(events):
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for event in events:
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st.markdown("""---""")
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masked_author = f"masked as {event['masked_author']}" if "masked_author" in event else ""
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st.markdown(f"**Author:** {event['author']} {masked_author}, {event['action']} {event['type']} with title: {event['title']}")
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st.code(f"{event['text']}", language="html")
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samples = load_data()
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col1, _ = st.columns([2, 4])
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with col1:
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index_example = st.number_input(f"Index of the chosen conversation from the existing {len(samples)}", min_value=0, max_value=len(samples)-1, value=0, step=1)
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st.write(f"Issue size: {samples[index_example]['text_size_no_bots']}\n\n")
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print_issue(samples[index_example]["events"])
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