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The next best thing after Bloomberg Terminal. #weliketheterminal
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How it started:

Gamestonk Terminal is an awesome stock and crypto market terminal that has been developed for fun, while I saw my GME shares tanking. But hey, I like the stock 💎🙌.

How it's going:

Gamestonk Terminal provides a modern Python-based integrated environment for investment research, that allows the average joe retail trader to leverage state-of-the-art Data Science and Machine Learning technologies.

As a modern Python-based environment, GamestonkTerminal opens access to numerous Python data libraries in Data Science (Pandas, Numpy, Scipy, Jupyter), Machine Learning (Pytorch, Tensorflow, Sklearn, Flair), and Data Acquisition (Beautiful Soup, and numerous third-party APIs).

This project was originally written and tested with Python 3.6.8. It should now support Python 3.6, 3.7, and 3.8.

Our current recommendation is to use this project with Anaconda's Python distribution - either full Anaconda3 Latest or Miniconda3 Latest. Several features in this project utilize Machine Learning. Machine Learning Python dependencies are optional. If you decided to add Machine Learning features at a later point, you will likely have better user experience with Anaconda's Python distribution.

1. Install Anaconda

Confirm that you have it with: conda -V. The output should be something along the lines of: conda 4.9.2

2. Create Environment

You can name the environment whatever you want. Although you could use names such as: welikethestock, thisistheway or diamondhands, we recommend something simple and intuitive like gst. This is because this name will be used from now onwards.

conda create -n gst python=3.6.8

3. Activate the virtual environment

conda activate gst

Note: At the end, you can deactivate it with: conda deactivate

4. Fork the Project

• Via HTTPS: git clone https://github.com/DidierRLopes/GamestonkTerminal.git
• via SSH: git clone [email protected]:DidierRLopes/GamestonkTerminal.git

Navigate into the folder with: cd GamestonkTerminal/

5. Install poetry

conda install poetry

6. Install poetry dependencies

poetry install

This is a library for package management, and ensures a smoother experience than: pip install -r requirements.txt

7. You're ready to Gamestonk it!

python terminal.py

Note that the conda deactivate -> conda activate in the middle is on purpose, this is sometimes required to avoid issues with poetry

conda create -n gst python=3.8.8
conda activate gst
conda install poetry
conda deactivate
conda activate gst
poetry install
conda install -c conda-forge fbprophet numpy=1.19.5 hdf5=1.10.5
poetry install -E prediction

If you are an advanced user and use other Python distributions, we have several requirements.txt documents that you can pick from to download project dependencies.

Note: The libraries specified in the requirements.txt file have been tested and work for the purpose of this project, however, these may be older versions. Hence, it is recommended for the user to set up a virtual python environment prior to installing these. This allows to keep dependencies required by different projects in separate places.

If you would like to use optional Machine Learning features:

• Update your feature_flags.py with:

ENABLE_PREDICT = os.getenv("GTFF_ENABLE_PREDICT") or True

• Install optional ML features dependencies:

poetry install -E prediction

If you run into issues installing or Cannot convert a symbolic Tensor... at runtime, try this:

conda install -c conda-forge fbprophet numpy=1.19.5 hdf5=1.10.5
poetry install
poetry install -E prediction

If you would like to set up a docker image:

• Build the docker: docker build .
• Run it: docker run -it gamestonkterminal:dev

Note: The problem with docker is that it won't output matplotlib figures.

*Commands that may help you in case of an error:

• python -m pip install --upgrade pip
• pip install pystan --upgrade
• poetry update --lock

If you run into trouble with poetry and the advice above did not help, your best bet is to try

1. poetry update --lock

2. conda deactivate -> conda activate gst, then try again

3. Delete the poetry cache, then try again

   Platform	Location
   Linux	"~/.cache/pypoetry"
   Mac	"~/Library/Caches/pypoetry"
   Windows	"%localappdata%/pypoetry/cache"

4. Track down the offensive package and purge it from your anaconda <environment_name> folder, then try again (removing through conda can sometimes leave locks behind)

   Platform	Location
   Linux/Mac	"/anaconda3/envs" or "/opt/anaconda3/envs"
   Windows	"%userprofile%/anaconda3/envs"

5. Completely nuke your conda environment folder and make a new environment from scratch

6. Reboot your computer and try again

7. Submit a ticket on github

In the case when you run into an error of the form ModuleNotFoundError: No module named '_______'. The solution is to install the missing package via pip.

If you get the error that statsmodels is not found, you would run

• pip install statsmodels

Then please submit an issue so that we can address why that was not imported.

The project is build around several different API calls, whether it is to access historical data or financials.

These are the ones where a key is necessary:

• Alpha Vantage: https://www.alphavantage.co
• Quandl: https://www.quandl.com/tools/api
• Reddit: https://www.reddit.com/prefs/apps
• Twitter: https://developer.twitter.com
• Polygon: https://polygon.io
• Financial Modeling Prep: https://financialmodelingprep.com/developer
• FRED: https://fred.stlouisfed.org/docs/api/api_key.html
• News API: https://newsapi.org

When these are obtained, don't forget to update config_terminal.py.

Alternatively, you can also set them to the following environment variables: GT_API_KEY_ALPHAVANTAGE, GT_API_KEY_FINANCIALMODELINGPREP, GT_API_KEY_QUANDL, GT_API_REDDIT_CLIENT_ID, GT_API_REDDIT_CLIENT_SECRET, GT_API_REDDIT_USERNAME, GT_API_REDDIT_USER_AGENT, GT_API_REDDIT_PASSWORD, GT_API_TWITTER_KEY, GT_API_TWITTER_SECRET_KEY, GT_API_TWITTER_BEARER_TOKEN, GT_API_POLYGON_KEY, GT_FRED_API_KEY, GT_API_NEWS_TOKEN.

Example:

export GT_API_REDDIT_USERNAME=SexyYear

Note that it is not necessary to have a valid Alpha Vantage key to get daily OHLC values.

Start by loading a ticker of interest:

load -t GME

The menu will expand to all its menus since a ticker has been loaded.

View the historical data of this stock:

view

Slice the historical data by loading ticker and setting a starting point, e.g.

load -t GME -s 2020-06-04

Enter in technical analysis menu with

ta

and run a SMA with:

sma

However, imagine that you wanted to change the length of the window because you don't want to go long but do a swing, and therefore a smaller window is necessary. Check what settings are available on the SMA command:

sma -h

Once that has been seen, set the parameters that you want after flagging them. In this case, to change length window to 10, we would have to do:

sma -l 10

Example:

There are 3 main ways of contributing to this project.

Become a Contributor 🦍

Recommended if you bought the dip, and the share price keeps dipping. You may as well keep yourself busy while stonks go up.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Appease the linters and commit again if needed
   1. Install and run black for every change you've made
   2. Install and run flake8 for every change you've made. flake8 . --count --ignore=E203,W503 --max-line-length=122 --show-source --statistics
5. Push to your Branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

Become a Karen 🤷

Recommended if you adopted a strategy of buying high and selling low.

We are interested in your view on what sort of features would make you buy even higher and selling even lower.

Also, if somehow you're sitting in several mils due to this terminal, don't forget to report a bug so that the team can fix, and keep the old ways.

Join the 🙌 💎 Gang

If red is your favourite color, and you never sell for a loss.

Welcome to the club, and feel free to support the developers behind this amazing open-source project.

Distributed under the MIT License. See LICENSE for more information.

"A few things I am not. I am not a cat. I am not an institutional investor, nor am I a hedge fund. I do not have clients and I do not provide personalized investment advice for fees or commissions." DFV

Didier Rodrigues Lopes - [email protected]

Artem Veremy - [email protected]

James Maslek - [email protected]

• VICE article
• Daily Fintech article
• HackerNews
• Reddit r/algotrading
• Reddit r/Python