README.md

metadata

license: mit
title: python_to_streamlit_convertor
sdk: streamlit
emoji: 📊
colorFrom: green
colorTo: gray
sdk_version: 1.51.0

PyStreamlit Converter Pro

Transform Jupyter Notebooks and Python scripts into polished, interactive Streamlit apps — in seconds.

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✨ Features

Feature	Description
Hybrid Conversion Engine	Three-pass AST + regex pipeline for accurate, reliable conversion
Deep Code Analysis	Complexity metrics, library detection, function/class inventory
Widget Suggester	Scans hard-coded literals and proposes sidebar sliders, checkboxes, inputs
Diff Viewer	Unified-diff comparison with configurable context lines
Auto @st.cache_data	Automatically decorates data-loading functions
Auto Error Handling	Wraps app body in try/except with st.error() + traceback expander
Batch ZIP Processing	Convert an entire folder; download all results as one ZIP
Session History	Timestamped timeline of all conversions this session
Light / Dark Theme	Toggle from the sidebar
Two Built-in Samples	Notebook and script for instant testing

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🔄 Transformation Map

Original Python	Streamlit Equivalent
print(x)	st.write(x)
display(df)	st.dataframe(df)
df.head()	st.dataframe(df.head())
df.describe()	st.dataframe(df.describe())
plt.show()	st.pyplot(plt.gcf())
fig.show()	st.plotly_chart(fig)
show(bokeh_fig)	st.bokeh_chart(fig)
Notebook markdown cells	st.markdown(...)
%magic / !shell commands	(removed)
load_*() / fetch_*() functions	@st.cache_data applied

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🚀 Quick Start

1. Clone and install

git clone https://github.com/your-username/pystreamlit-converter.git
cd pystreamlit-converter
pip install -r requirements.txt

2. Run

streamlit run app.py

3. Convert your first file

1. Upload a .py or .ipynb file via the sidebar
2. Adjust settings (or keep the defaults)
3. Preview the output side-by-side
4. Download the generated *_streamlit.py

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🧠 Conversion Strategies

Strategy	Best For
Hybrid (default)	Any file — AST + regex fallback
AST Precise	Clean Python 3.9+ with valid syntax
Regex Fast	Large files or syntax-heavy / magic-heavy code

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📁 Project Structure

pystreamlit-converter/
├── app.py              # Single-file Streamlit application
├── requirements.txt    # Python dependencies
└── README.md           # Documentation

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⚙️ Configuration Options

All options are accessible from the sidebar:

Option	Description	Default
Strategy	Conversion engine	Hybrid
Chart Library	Preferred target chart lib	Auto-Detect
App Layout	wide or centered	wide
@st.cache_data	Auto-cache data-loading fns	On
Error Handling	try/except wrapper	On
Auto Sidebar Widgets	Expose literals as controls	On
Download Button Stub	CSV export template	On
Session State Init	Add session_state init block	Off
if name guard	Wrap in main guard	Off
Preserve Comments	Keep docstrings / comments	On
Large File Threshold	Strategy switch threshold	200 KB

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🔍 Analyze Tab

Gives a full breakdown before you convert:

• Complexity — total/code/comment/blank lines, cyclomatic complexity
• Library Detection — chart, ML, and data libraries
• Function Inventory — name, args, line count, async flag
• Widget Suggestions — literals that could become interactive controls

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📦 Batch ZIP Processing

Upload a ZIP containing .py / .ipynb files. The app converts each one and packages all outputs into a downloadable ZIP.

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💡 Tips

1. Run Analyze first to understand what will change
2. Enable Auto Sidebar Widgets to make parameters interactive
3. Use the Diff Viewer to review changes before deploying
4. Hybrid mode handles 99% of files reliably

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🗺️ images of app

🗺️ image 2

🗺️ image 3