This guide will help you get started with basic Git version control and Python dependency management using uv for the TA_Analyzer project.
Follow the steps on Git installation page to install Git on your system.
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Clone the repository:
git clone <repository-url>
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Check status:
git status
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Add changes:
git add <file>
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Commit changes:
git commit -m "Describe your changes" -
Push to GitHub:
git push
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Pull latest changes:
git pull
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Fetch latest changes:
git fetch
There is Git built in to VSCode, so you can also use the Source Control tab in the sidebar to manage your repository.
If you haven't already, clone the repository from GitHub:
git clone https://github.com/Alchemist-Aloha/TA_Analyzer.gitThis command creates a local copy of the repository on your machine.
If you plan to modify the code and contribute, consider forking the repository first:
- Go to the repository on GitHub.
- Click the "Fork" button in the top right corner.
- Clone your forked repository:
Then navigate into the cloned directory:
git clone <your-fork-url.git>
cd TA_Analyzeruv is a fast Python package manager. You can use it as a drop-in replacement for pip.
If you don't have uv installed, you can install it with following commands in terminal:
macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | shWindows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"Or with pip if you have python installed already:
pip install uvIt's recommended to use a virtual environment for Python projects:
uv venv --python 3.13This command creates a virtual environment in the .venv directory.
source .venv/bin/activate # macOS/Linux
.venv\Scripts\activate # WindowsThis command activates the virtual environment. You should see the environment name in your terminal prompt.
Note that VSCode will automatically detect the virtual environment if you open the project folder in it.
To deactivate the virtual environment, simply run:
deactivateInstall all required dependencies from requirements.txt:
uv pip install -r requirements.txtTo update all packages to the latest compatible versions:
uv pip install -r requirements.txt --upgradeYou can run the Jupyter notebooks .ipynb files directly in VSCode. Make sure you have IPYkernel installed in your virtual environment:
uv pip install ipykernel # If not already installedThen, you can open the Jupyter notebook in VSCode.
Or run Python scripts directly, for example:
uv run correction_line.pyFor more details, see the API documentation or the example notebook ta_analyzer.ipynb.