getting_started.md

Setting Up a Python Virtual Environment and Installing Dependencies

In this guide, we'll walk through the steps to create a Python virtual environment and install the necessary libraries for our financial analysis project. Virtual environments in Python are a tool to keep dependencies required by different projects in separate places. This is achieved by creating isolated python virtual environments for them.

Step 1: Install Virtualenv

First, ensure that you have virtualenv installed. If you don't have virtualenv installed, you can install it using pip:

pip install virtualenv

Step 2: Create a Virtual Environment

Navigate to your project's directory in the terminal and run the following command to create a virtual environment. Replace myenv with your desired environment name.

virtualenv myenv

Step 3: Activate the Virtual Environment

Once the environment is created, you need to activate it. The command to activate the virtual environment varies based on your operating system.

• On Windows:

  .\myenv\Scripts\activate

• On macOS and Linux:

  source myenv/bin/activate

Step 4: Install Dependencies

With your environment activated, you can now install the required libraries. Run the following commands to install numpy, pandas, yfinance, quantstats, and matplotlib:

pip install -r requirements.txt

Step 5: Verify Installation

After installation, you can verify that the packages are installed correctly in your virtual environment by running:

pip list

This will show you a list of all installed packages and their versions in your virtual environment.

Step 6: Deactivating the Virtual Environment

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

deactivate

This command will return you to your global Python environment.

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