Dockerized TA-Lib

A pre-built Docker image that bundles TA-Lib with Python.

This setup enables you to quickly get started with TA-Lib and run Python scripts that rely on TA-Lib without manually compiling it.

Overview

Base OS: Ubuntu 24.04
Python Version: Python 3.12
Included Libraries:
- TA-Lib
- TA-Lib (Python bindings) installed in a Python virtual environment located at /venv
- Pandas
- NumPy

Getting Started

1. Prerequisites

Docker and optionally Docker Compose installed on your system.
A local Python script (e.g., script.py) that uses TA-Lib.
- If you need additional Python libraries, you can either:
  1. Install them dynamically inside the container at runtime, for example:
```
docker-compose run --rm python-talib /venv/bin/pip install pandas
```
  2. Or create your own Dockerfile extending this image and install more packages there.

2. Using `docker-compose.yaml`

Below is a sample docker-compose.yaml file (already provided in this repo as docker-compose.yaml):

services:
  python-talib:
    image: ghcr.io/ukewea/python-talib:ubuntu24.04-python3.12-20240915
    container_name: python-talib
    working_dir: /usr/src/app
    volumes:
      - ./:/usr/src/app
    command: /venv/bin/python script.py

Place your script.py (or any other Python scripts) in the same directory as docker-compose.yaml.
Run:
```
docker-compose up
```
Docker Compose will:
- Pull the ghcr.io/ukewea/python-talib image (if not already present).
- Start a container named python-talib-container.
- Mount your current directory into /usr/src/app inside the container.
- Execute script.py using python from the TA-Lib-enabled virtual environment.
Check Console Output: Logs from your script should appear in your terminal.

3. Using docker run (Alternative)

If you prefer a single docker run command, you can do something like:

docker run --rm \
  -v "$(pwd):/usr/src/app" \
  -w /usr/src/app \
  ghcr.io/ukewea/python-talib:ubuntu24.04-python3.12-20240915 \
  /venv/bin/python script.py

-v "$(pwd):/usr/src/app": Mounts your current directory so the script is accessible.
-w /usr/src/app: Sets the working directory where your script.py is located.

Installing Additional Python Packages

Inside the container’s virtual environment (/venv), you can install additional libraries like so:

docker-compose run --rm python-talib /venv/bin/pip install pandas

Or install them permanently in your own derived image by writing a custom Dockerfile:

FROM ghcr.io/ukewea/python-talib:ubuntu24.04-python3.12-20240915
RUN /venv/bin/pip install pandas scikit-learn

Troubleshooting

Container fails to start: Make sure your Docker and Docker Compose versions are up to date. Also verify that you have permissions to mount volumes.
Script not found: Double-check the volumes path and that your script is in the correct directory.
Missing dependencies: Install any additional dependencies (e.g., pandas) within the container environment.

Example Python Script

Here's a simple example (script.py) to demonstrate using TA-Lib within this Docker image:

import random
import talib

# Generate a list of 100 pseudo-random "closing prices" 
random.seed(42)  # For reproducible results
close_prices = [random.random() * 100 for _ in range(100)]

# Compute a 10-period Simple Moving Average using TA-Lib
sma_10 = talib.SMA(close_prices, timeperiod=10)

print("Last 10 closing prices:")
print(close_prices[-10:])

print("\nLast 10 values of the 10-period SMA:")
print(sma_10[-10:])

To run this script using the provided Docker image, save it as script.py in the same directory as docker-compose.yaml and run docker-compose up.

Contributing

If you find any issues or would like to suggest improvements, feel free to open a pull request or create an issue in the GitHub repository.

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