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| from dash import dcc | |
| def get_intro_markdown(): | |
| return dcc.Markdown(""" | |
| ### 📘 Introduction | |
| This tool analyzes uploaded Python files and visualizes how functions call one another. | |
| --- | |
| #### 🔍 Features | |
| - Upload multiple `.py` files | |
| - Select a top-level function to explore all functions it calls | |
| - Function table shows: | |
| - Arguments and return values with inferred types (e.g. `df: pd.DataFrame`) | |
| - Streamlit `session_state` variables read/written (if applicable) | |
| - Graph shows: | |
| - Call order on edges (`1`, `2`, `3`) | |
| - Thicker lines if a function is called multiple times | |
| --- | |
| #### 📂 How to Use | |
| 1. Switch to the **Graph Explorer** tab | |
| 2. Upload one or more `.py` files | |
| 3. Pick the entry point function | |
| 4. Explore the graph and table dynamically | |
| --- | |
| ### 👋 About the Creator | |
| This tool was built by **Tomas Larsson**, a data scientist and financial modeler with a passion for making complex topics easy to explore and understand. | |
| Tomas is also the creator of [**my.moneytoolbox.com**](https://mymoneytoolbox.com), a blog focused on: | |
| - Tax-efficient investing | |
| - Retirement modeling | |
| - Personal finance analytics | |
| - Tools for DIY investors and early retirees | |
| Whether you're a fellow data enthusiast or someone planning their financial future, Tomas's blog is a resource-rich destination with transparent tools, clear explanations, and practical guidance. | |
| """) | |