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Refactor README.md to introduce RePrompt repository-context generator
Update README.md to reflect the new purpose of the repository as a context generator for AI coding assistants. Replace previous content about lagged oil and unemployment charting with detailed features, installation instructions, and usage guidelines for the RePrompt tool.
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# Lagged Oil vs. Unemployment Charting
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# RePrompt – Repository-Context Generator
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This repository provides two Python scripts to fetch the latest US Unemployment Rate (UNRATE) and WTI crude oil price (DCOILWTICO) from FRED, apply a configurable lag or lead to the oil series, and generate polished dual‑axis charts.
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**RePrompt** creates a single `repo-context.txt` file that gives AI coding assistants
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(e.g. ChatGPT) a concise, opinionated snapshot of your repository.
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It combines an overview, directory tree, highlighted file contents, and optional static
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sections such as to-do lists—all configurable through a Streamlit UI.
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## Files
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> **Works great with**
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> [mckaywrigley’s XML parser](https://github.com/mckaywrigley/o1-xml-parser/tree/main).
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* **`lagged_oil_unrate_chart.py`**
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---
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A lightweight script that:
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1. Downloads monthly UNRATE and averages daily WTI to monthly.
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## ✨ Features
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2. Shifts the oil series by `N` months (default = 18).
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3. Plots both series on a dual‑axis Matplotlib chart.
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* **`lagged_oil_unrate_chart_styled.py`**
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| Category | What it does |
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A more polished version that adds:
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|----------|--------------|
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| **Streamlit UI** | Choose a target repo, set include/exclude rules, and generate the context file in one screen. |
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| **Context builder** | Produces `repo-context.txt` tailored for AI assistants. |
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| **Configurable tree** | Exclude or include directories/files interactively (defaults skip noisy folders like `node_modules`, `.git`, etc.). |
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| **File highlights** | Embeds syntax-highlighted contents of “important” files you pick. |
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| **Static sections** | Auto-appends `overview.txt`, `to-do_list.txt`, or any custom text snippets. |
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| **Save & load config** | Persist your include/exclude selections for future sessions. |
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* Title, subtitle, footnote with date range and source.
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---
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* Clean dual‑axis styling with percentage and dollar‑format ticks.
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* Customizable date range and extended x‑axis (e.g., 1973–2028).
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* CLI flags for offset, start/end dates, and axis extension.
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* **`requirements.txt`**
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## 🛠 Prerequisites
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Lists all Python dependencies for both scripts.
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## Prerequisites
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* **Python 3.7 +** – [download](https://www.python.org/downloads/)
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* **Git** – [download](https://git-scm.com/downloads)
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* Python 3.7 or later
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---
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* Internet connection (to fetch data from FRED)
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## Setup
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## 🗂 Directory layout
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Clone or download this repository:
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```bash
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git clone https://your-repo-url.git
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cd your-repo-folder
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```
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```
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### Create a Virtual Environment & Install Dependencies
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RePrompt/
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├── src/
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│ ├── app.py # Streamlit entry-point
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│ ├── generate\_repo\_context.py # Core context-builder
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│ ├── config.yaml # Default config (auto-generated if absent)
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│ ├── index.html # Single-page static explanation
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│ └── requirements.txt # Python dependencies
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└── README.md
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#### On Linux / macOS
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````
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---
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## 🚀 Installation
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### 1 Clone the repo
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```bash
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```bash
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# 1. Create a venv
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git clone https://github.com/PR0M3TH3AN/RePrompt.git
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python3 -m venv venv
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cd RePrompt
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````
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# 2. Activate it
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### 2 Create & activate a virtual-environment
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source venv/bin/activate
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# 3. Upgrade pip and install requirements
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<details>
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pip install --upgrade pip
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<summary>Windows (PowerShell)</summary>
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pip install -r requirements.txt
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```
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#### On Windows (PowerShell)
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```powershell
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```powershell
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# 1. Create a venv
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python -m venv venv
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python -m venv venv
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# 2. Activate it
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venv\Scripts\Activate.ps1
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venv\Scripts\Activate.ps1
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```
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# 3. Upgrade pip and install requirements
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</details>
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<details>
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<summary>macOS / Linux</summary>
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```bash
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python3 -m venv venv
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source venv/bin/activate
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```
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</details>
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### 3 Install dependencies
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```bash
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python -m pip install --upgrade pip
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python -m pip install --upgrade pip
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pip install -r requirements.txt
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pip install -r src/requirements.txt
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```
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```
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> **Note:** If you get execution policy errors on Windows, you may need to run:
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`requirements.txt` contains only three packages:
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>
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> ```powershell
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> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
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> ```
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## Usage
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```text
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streamlit
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PyYAML
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pyperclip
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```
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Once the virtual environment is active and dependencies are installed, run either script from the project root.
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---
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### 1. Basic Lag Script
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## ▶️ Running the app
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```bash
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```bash
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# Default: oil lags unemployment by 18 months (~1.5 years)
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streamlit run src/app.py
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python lagged_oil_unrate_chart.py
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# Other offsets (in months)
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python lagged_oil_unrate_chart.py --offset 6 # 6‑month lag
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python lagged_oil_unrate_chart.py --offset -12 # 12‑month lead
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```
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```
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### 2. Styled & Configurable Chart
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The UI opens at **[http://localhost:8501](http://localhost:8501)**.
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---
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## 📝 Usage walk-through
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1. **Config file**
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A starter `config.yaml` is created in `src/`:
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```yaml
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exclude_dirs:
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- node_modules
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- venv
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- __pycache__
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- .git
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- dist
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- build
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- logs
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- .idea
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- .vscode
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important_files: []
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custom_sections: []
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```
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2. **Select repo**
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Click **“Choose Folder”** in the sidebar, navigate to the repository you
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want to summarise, and select it.
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3. **Fine-tune files**
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* Tick directories to *include* in the rendered tree.
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* Exclude noisy or irrelevant files.
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* Review the final list.
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4. **Generate**
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Hit **“Generate Context File”**.
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Download or copy the result; optionally save the configuration for later.
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---
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## 🔧 Customisation tips
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### Change default exclusions
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Edit these constants in `src/app.py`:
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```python
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DEFAULT_EXCLUDED_DIRS = [
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"node_modules", "venv", "__pycache__", ".git",
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"dist", "build", "logs", ".idea", ".vscode"
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]
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DEFAULT_EXCLUDED_FILES = ["repo-context.txt"]
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```
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### Different port
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If port 8501 is busy:
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```bash
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```bash
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python lagged_oil_unrate_chart_styled.py \
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streamlit run src/app.py --server.port 8502
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--offset 18 \
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--start 1973-01-01 \
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--end 2025-05-31 \
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--extend-years 3
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```
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```
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| Flag | Description |
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---
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| ------------------ | -------------------------------------------------------------- |
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| `--offset N` | Lag (positive) or lead (negative) in months (default = 18) |
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| `--start DATE` | Series start date (`YYYY-MM-DD`, default = `1973-01-01`) |
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| `--end DATE` | Series end date (`YYYY-MM-DD`, default = today) |
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| `--extend-years M` | How many years beyond `end` to extend the x‑axis (default = 3) |
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## Customization
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## ❓ Troubleshooting
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* **Normalization**: Insert a normalization step (e.g., percent change from a base date).
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| Problem | Fix |
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* **Export**: Modify the script to save figures with `plt.savefig('chart.png', dpi=300)`.
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| -------------------------------------- | ------------------------------------------------------------- |
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* **Statistics**: Add `ta.correl()` or use Pandas to compute rolling correlations.
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| `Tcl_AsyncDelete` warning | Harmless—ignore it. |
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| “Permission denied” when creating dirs | Run your terminal as admin or check folder write permissions. |
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| Packages won’t install | `python -m pip install --upgrade pip` then reinstall. |
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| Port already in use | Kill other Streamlit processes or use `--server.port`. |
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## Troubleshooting
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---
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* **"ModuleNotFoundError"**: Ensure your venv is activated, then reinstall dependencies.
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## 🤝 Contributing
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* **SSL/DataReader errors**: Upgrade `pandas_datareader` or switch to an alternate data source.
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## License
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1. Fork → create a feature branch
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2. Commit & push your changes
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3. Open a Pull Request
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This project is released under the MIT License.
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---
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## 📄 License
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Distributed under the **MIT License** – see `LICENSE` for details.
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