https://github.com/darienmt/py-for-algo-trading
Python for Algorithmic Trading book playground.
https://github.com/darienmt/py-for-algo-trading
pandas python python3 trading trading-algorithm trading-algorithms
Last synced: about 2 months ago
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Python for Algorithmic Trading book playground.
- Host: GitHub
- URL: https://github.com/darienmt/py-for-algo-trading
- Owner: darienmt
- License: mit
- Created: 2021-11-10T03:03:14.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-11-10T05:31:38.000Z (over 3 years ago)
- Last Synced: 2025-02-08T21:46:17.005Z (3 months ago)
- Topics: pandas, python, python3, trading, trading-algorithm, trading-algorithms
- Language: Jupyter Notebook
- Homepage:
- Size: 5.86 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Python for Algorithmic Trading book playground
Here you can find the parts of the book [Python for Algorithmic Trading](https://www.amazon.ca/Python-Algorithmic-Trading-Cloud-Deployment/dp/149205335X) I tried. This book has a repo with most of the code but, I like to do it myself as well.
I put each chapter on its own directory to have independent from eachother, but the virtual environment will be at the root. Yes, instead of [Conda/Miniconda](https://docs.conda.io/en/latest/miniconda.html) I will use [virtualenv](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
## Environment setup
```bash
python3 -m venv venv
. ./venv/bin/activate
pip3 install -r requirements.txt
jupyter notebook
```
*Note*: There are a few configuration keys needed to run the code. Examples of the configuration needed could be found [./config.cfg.example](./config.cfg.example). Make a copy of this file and rename it to `config.cfg` and add your keys. This file will be ignored by Git to make sure it is not accidentally part of a commit.
## Updating the requirement.txt
```bash
pip freeze > requierement.txt
```
## Chapters
### Chapter 3 - Working with Financial Data
- [Accessing Quandl Data](./chapter-3/Accessing_Quandl_Data.ipynb)