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README.md

@@ -1,12 +1,6 @@
 ---
-title: Starknet Dev Metrics
-emoji: 🏆
-colorFrom: green
-colorTo: green
+title: Starknet_Dev_Metrics
+app_file: github_metrics/main.py
 sdk: gradio
-sdk_version: 4.19.2
-app_file: app.py
-pinned: false
+sdk_version: 4.7.1
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

github_metrics/main.py

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+import gradio as gr
+import pandas as pd
+import matplotlib.pyplot as plt
+from io import StringIO
+from termcolor import colored
+
+# Load the dataset with debug prints
+def load_dataset():
+    try:
+        print(colored("Loading dataset...", "blue"))
+        df = pd.read_csv("data/source/all_networks_developer_classification.csv")
+        # Ensure the month_year column is in the correct datetime format
+        df['month_year'] = pd.to_datetime(df['month_year'], format='%B_%Y')  # Adjust format if necessary
+        return df
+    except Exception as e:
+        print(colored(f"Error loading dataset: {e}", "red"))
+        raise
+
+# Process input and generate plot and classification with debug prints
+def process_input(input_text, uploaded_file):
+    try:
+        print(colored("Processing input...", "blue"))
+
+        # Read GitHub handles from input text or uploaded file
+        if uploaded_file is not None:
+            print(colored("Reading from uploaded file...", "blue"))
+            input_text = uploaded_file.read().decode("utf-8")
+        github_handles = [handle.strip() for handle in input_text.split(",")]
+        print(colored(f"GitHub handles: {github_handles}", "blue"))
+
+        # Load dataset
+        df = load_dataset()
+
+        # Filter dataset for the provided GitHub handles
+        print(colored("Filtering dataset...", "blue"))
+        filtered_df = df[df['developer'].isin(github_handles)]
+
+        # Generate plot
+        print(colored("Generating plot...", "blue"))
+        fig, ax = plt.subplots()
+        for handle in github_handles:
+            dev_df = filtered_df[filtered_df['developer'] == handle]
+            dev_df = dev_df.sort_values('month_year')
+            ax.plot(dev_df['month_year'], dev_df['total_commits'], label=handle)
+
+        ax.set_xlabel("Month")
+        ax.set_ylabel("Number of Commits")
+        ax.legend()
+        plt.xticks(rotation=45)
+        plt.tight_layout()
+
+        # Generate classification table
+        print(colored("Classifying developers...", "blue"))
+        classification = []
+        for handle in github_handles:
+            dev_df = filtered_df[filtered_df['developer'] == handle]
+            last_3_months = pd.Timestamp.now() - pd.DateOffset(months=3)
+            recent_activity = dev_df[dev_df['month_year'] >= last_3_months]
+            total_recent_commits = recent_activity['total_commits'].sum()
+            
+            if dev_df.empty:
+                status = "Always been inactive"
+            elif recent_activity.empty:
+                status = "Previously active but no longer"
+            elif total_recent_commits < 20:
+                status = "Low-level active"
+            else:
+                status = "Highly involved"
+            
+            classification.append((handle, status))
+        
+        classification_df = pd.DataFrame(classification, columns=["Developer", "Classification"]).sort_values("Classification", ascending=False)
+        print(colored("Classification completed.", "blue"))
+
+        # Return plot and classification table
+        return fig, classification_df
+    except Exception as e:
+        print(colored(f"Error processing input: {e}", "red"))
+        raise
+
+# Gradio interface with descriptions and debug prints
+with gr.Blocks() as app:
+    gr.Markdown("## GitHub Starknet Developer Insights")
+    gr.Markdown("""
+    This tool allows you to analyze the GitHub activity of developers within the Starknet ecosystem. 
+    Enter GitHub handles separated by commas or upload a CSV file with GitHub handles in a single column 
+    to see their monthly commit activity and their current involvement classification.
+    """)
+    
+    with gr.Row():
+        text_input = gr.Textbox(label="Enter GitHub handles separated by commas", placeholder="e.g., user1,user2,user3")
+        file_input = gr.File(label="Or upload a CSV file with GitHub handles in a single column", type="binary")
+    gr.Markdown("""
+    *Note:* When uploading a CSV, ensure it contains a single column of GitHub handles without a header row.
+    """)
+    btn = gr.Button("Analyze")
+    plot_output = gr.Plot(label="Commits per Month")
+    table_output = gr.Dataframe(label="Developer Classification")
+
+    btn.click(process_input, inputs=[text_input, file_input], outputs=[plot_output, table_output])
+
+    print(colored("Gradio app initialized.", "blue"))
+
+if __name__ == "__main__":
+    print(colored("Launching app...", "blue"))
+    app.launch(share=True)
+

pyproject.toml

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+[tool.poetry]
+name = "github-metrics"
+version = "0.1.0"
+description = ""
+authors = ["Omar U. Espejel <espejelomar@gmail.com>"]
+readme = "README.md"
+packages = [{include = "github_metrics"}]
+
+[tool.poetry.dependencies]
+python = "^3.11"
+gradio = "^4.19.2"
+pandas = "^2.2.1"
+matplotlib = "^3.8.3"
+termcolor = "^2.4.0"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

requirements.txt

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+pandas
+gradio
+matplotlib
+termcolor