the_information_nexus/projects/forex_algo_trading.md

To set up a virtual environment for your forex trading analysis project, you'll first need to decide on a folder structure that organizes your work efficiently. I'll guide you through creating this structure, setting up a virtual environment, and providing a basic requirements.txt file.

Project Folder Structure

Here's a suggested structure to keep your project organized:

forex_analysis_project/
│
├── data/                        # Store raw and processed forex data
│   ├── raw/
│   └── processed/
│
├── notebooks/                   # Jupyter notebooks for exploration and analysis
│
├── src/                         # Source code for the project
│   ├── data_retrieval/          # Scripts for fetching and preprocessing data
│   │   ├── __init__.py
│   │   └── fetch_forex_data.py
│   │
│   ├── feature_engineering/     # Generate features from forex data
│   │   ├── __init__.py
│   │   └── features.py
│   │
│   ├── models/                  # Machine learning and deep learning models
│   │   ├── __init__.py
│   │   ├── lstm_model.py        # LSTM for time series prediction
│   │   └── rag_model.py         # RAG model integration
│   │
│   ├── inference/               # Inference logic for making predictions
│   │   ├── __init__.py
│   │   └── predict.py
│   │
│   └── utils/                   # Utility functions and classes
│       ├── __init__.py
│       └── utils.py
│
├── tests/                       # Unit and integration tests
│   ├── __init__.py
│   └── test_fetch_forex_data.py
│
├── requirements.txt             # Project dependencies
│
└── Dockerfile                   # Containerize your project (optional)

Setting Up a Virtual Environment

1. Creating a Virtual Environment:

First, navigate to your project directory in the terminal, then run:

python3 -m venv venv

This command creates a virtual environment named venv within your project directory.

2. Activating the Virtual Environment:

• On Windows:

venv\Scripts\activate

• On macOS and Linux:

source venv/bin/activate

Once activated, you'll see the name of the virtual environment (venv) in your terminal prompt, indicating that any Python or pip commands will use the environments' packages and settings.

3. Deactivating the Virtual Environment:

When you're done working in the virtual environment, you can deactivate it by running:

deactivate

requirements.txt File

Create a requirements.txt file in your project root directory (forex_project/) with the following content to specify the project dependencies:

pandas
numpy
matplotlib
seaborn
requests
oandapyV20
jupyterlab

Installing Dependencies:

With your virtual environment activated, install the project dependencies by running:

pip install -r requirements.txt

This command reads the requirements.txt file and installs the specified versions of the packages into your virtual environment.

Final Steps

• Developing Your Project: Place your Python scripts in the src/ directory, Jupyter notebooks in notebooks/, and any tests in tests/. Use the data/ directory to store fetched data, such as CSV files.
• Using Jupyter Notebook: If you want to use Jupyter Notebook for analysis, start it with jupyter notebook or jupyter lab if you're using JupyterLab, and it will open in your web browser. Ensure you're doing this with your virtual environment activated so that Jupyter can access your project's dependencies.

This setup provides a solid foundation for developing your forex trading analysis project, offering a clear separation of concerns and making it easier to manage dependencies and share your work with others.