🚫 Note: All lines that start with 🚫 are instructions and should be deleted before this is posted to your portfolio. This is intended to be a guideline, feel free to add your own flare to it.

🚫 The numbers 1️⃣ through 5️⃣ next to each item represent the week that part of the docs needs to be completed by. Make sure to delete the numbers by the end of Labs.

🚫 Each student has a required minimum number of meaningful PRs each week per the rubric. Contributing to docs does NOT count as a PR to meet your weekly requirements.

1️⃣ You can find the deployed project at [🚫URL NAME GOES HERE](🚫copy and paste URL here).

🚫Add contributor info below, make sure add images and edit the social links for each member. Add to or delete these place-holders as needed

Student 1	Student 2	Student 3	Student 4	Student 5

🚫 4️⃣ Optional examples of using images with links for your tech stack, make sure to change these to fit your project

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1️⃣ Trello Board

1️⃣ Product Canvas

Our team is developing an interactive map that identifies potential instances of police use of force across the United States of America for Human Rights First, an independent advocacy and action organization.

We're pulling data from similiar APIs(All locations V2 - https://raw.githubusercontent.com/2020PB/police-brutality/data_build/all-locations-v2.json, 846- https://api.846policebrutality.com/api/incidents) and from Twitter and Reddit. We want to identify aggregate these instances.

• feature one
• feature two
• feature three
• feature four
• feature five

🚫 Why did you choose this framework?

• Works well with FastAPI
• Recommended to us
• Wanted to learn an in-demand framework

🚫List the rest of the data science features and libraries in the same format as the framework above.

• Pandas
• scikit-learn
• spacy
• nltk
• PRAW
• Tweepy

• point one
• point two
• point three

🚫 List the rest of the back end end features and libraries in the same format as the framework above

We are sending json objects to the backend with information about instances of police use of force. This information includes location data (city, state, and geocode) and relevant details about the incident, like the type of force that was used.

PRAW, The Python Reddit API Wrapper, makes it easy for users to analyze Reddit data. We used PRAW to scrape Reddit for potential instances of police of force.

Tweepy is a Python library that allows users to access the Twitter API. We used Tweepy to scan Twitter to find instances of police use of force.

In order for the app to function correctly, the user must set up their own environment variables. There should be a .env file containing the following:

🚫These are just examples, replace them with the specifics for your app

*  PRAW_CLIENT_ID  - keys for Reddit API
*  PRAW_CLIENT_SECRET - keys for Reddit API
*  PRAW_USER_AGENT - keys for Reddit API
*  TWEEPY_CONSUMER - keys for Twitter API
*  TWEEPY_SECRET - keys for Twitter API
*  TWEEPY_ACCESS - keys for Twitter API
*  TWEEPY_ACCESS_SECRET - keys for Twitter API

🚫For all content - images, icons, etc, use this table to document permission of use. Remove the two placeholders and add you content to this table

🚫Document what you used for testing and why

🚫explain how to install the required dependencies to get this project up and running with yarn and NPM

🚫replace these examples with your own

* typecheck - runs the TypeScript compiler
* build - creates a build of the application
* start - starts the production server after a build is created
* test - runs tests in **tests** directory \* eject - copy the configuration files and dependencies into the project so you have full control over them

When contributing to this repository, please first discuss the change you wish to make via issue, email, or any other method with the owners of this repository before making a change.

Please note we have a code of conduct. Please follow it in all your interactions with the project.

If you are having an issue with the existing project code, please submit a bug report under the following guidelines:

• Check first to see if your issue has already been reported.
• Check to see if the issue has recently been fixed by attempting to reproduce the issue using the latest master branch in the repository.
• Create a live example of the problem.
• Submit a detailed bug report including your environment & browser, steps to reproduce the issue, actual and expected outcomes, where you believe the issue is originating from, and any potential solutions you have considered.

We would love to hear from you about new features which would improve this app and further the aims of our project. Please provide as much detail and information as possible to show us why you think your new feature should be implemented.

If you have developed a patch, bug fix, or new feature that would improve this app, please submit a pull request. It is best to communicate your ideas with the developers first before investing a great deal of time into a pull request to ensure that it will mesh smoothly with the project.

Remember that this project is licensed under the MIT license, and by submitting a pull request, you agree that your work will be, too.

• Ensure any install or build dependencies are removed before the end of the layer when doing a build.
• Update the README.md with details of changes to the interface, including new plist variables, exposed ports, useful file locations and container parameters.
• Ensure that your code conforms to our existing code conventions and test coverage.
• Include the relevant issue number, if applicable.
• You may merge the Pull Request in once you have the sign-off of two other developers, or if you do not have permission to do that, you may request the second reviewer to merge it for you.

These contribution guidelines have been adapted from this good-Contributing.md-template.

See [Backend Documentation](🚫link to your backend readme here) for details on the backend of our project.