FalconVis uses Python and Streamlit to host the app. Streamlit is a framework used to create and host data science apps, the documentation for Streamlit can be found here. Before contributing, it's recommended that you play around with Streamlit & read its docs in order to get a feel for it.
In the folder you want to clone the repository in, run git clone https://github.com/team4099/FalconVis.git.
In order to install the dependencies, you must be in the src directory. Then, you can run python -m pip install -r requirements.txt.
The code below shows generally what the style guide is, specifically with writing functions. If you have no parameters or returns, you can remove their corresponding section in the function's docstring. Remember to follow this when following your code (FalconVis uses Sphinx docstrings).
def function_name(parameter: parameter_type) -> return_type:
"""Explanation of what this function does.
:param parameter: Explanation of the parameter.
:return: Explanation of what the function returns.
"""For FalconVis, there are four pages — Teams, Match, Event, and Picklist. Each page has a page manager found in page_managers/[page name]_manager.py, where the page generating happens.
Utility functions like retrieving the current scouting data can be found in utils/functions.py.
Constants like when to delete the cached scouting data, event code, etc. are found in utils/constants.py
Statistics used in the app are calculated in utils/calculated_stats.py.
The pages directory contains the Match, Event and Picklist pages. Teams.py is located outside the directory due to being the entrypoint to the app. Your app should be run with this file, and an entrypoint file means that the app opens on this page and is the "main" page:
In order to run the Streamlit app locally, make sure you're in the src directory, then run python -m streamlit run Teams.py
In calculated_stats.py, if there's ever a missing method that isn't included in calculating statistics, make sure to double check the previous methods. For example, if you ever find yourself wanting to calculate the average mobility %, instead of creating a method for that specific purpose, you could use average_stat in order to calculate said percentage.
In addition, if you ever must create a new method, ensure that you create methods that calculate said statistic by match first. For example, if you want to create a method that calculates the average cubes scored in the Low nodes for a team, you should first create a method that returns a pd.Series containing the amount of cubes scored in Low nodes by match and then create a wrapper around l3_cubes_per_match that calculates the mean of said series.