Social Network REST API

This project is a simple REST API for a social networking application using Flask. It demonstrates basic CRUD operations for user management and post interactions within the network.

Features

• User Registration: Sign up with an email and password.
• User Authentication: Secure login with JWT token authentication.
• Post Creation: Authenticated users can create posts.
• Post Like/Unlike: Users can like or unlike posts.
• Analytics: View count of likes aggregated by day within a date range with flexible query parameters.
• User Activity: Check the last login time and last request made by a user.

Installation

To set up the project for development or testing:

1. Clone the repository git clone <url>.
2. Install the dependencies using pip install -r requirements.txt.
3. Run the Flask application with python run.py.

Configuration

• The application reads from a config.json for bot activities, structured as follows:

{
    "number_of_users": "Number of users to simulate",
    "max_posts_per_user": "Maximum number of posts per user",
    "max_likes_per_user": "Maximum number of likes per user"
}

Testing

The API functionalities can be tested using the following methods:

• Automated Bot: Run bot.py to simulate user activity on the network after configuring config.json file.

• Postman: Manual testing can be done also by using Postman for each endpoint as I did.

  

Endpoints

The API provides the following endpoints:

• POST localhost/api/signup: Register a new user.
• POST localhost/api/login: Login for existing users and retrieve a token.
• POST localhost/api/token/refresh: Refresh the access token using the refresh token.
• POST localhost/api/post: Create a new post.
• POST localhost/api/post/<post_id>/like: Like a post.
• POST localhost/api/post/<post_id>/unlike: Unlike a post.
• GET localhost/api/analytics/?date_from=YYYY-MM-DD&date_to=YYYY-MM-DD: Get like analytics with the flexibility of specifying either start date, end date, or both.
• GET localhost/api/activity: Get user's last login and request activity.

Design Decisions

• Flask was chosen due to its simplicity and extensibility for small to medium-sized applications.
• JWT was used for authentication to provide a stateless authentication mechanism. A refresh token feature was implemented to allow users to remain logged in securely without re-entering credentials.
• The analytics endpoint was designed with flexibility in mind, allowing users to retrieve data by specifying either a date_from, date_to, or both to accommodate various user needs.

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To run autopep8 on a file:

autopep8 --in-place --aggressive --aggressive <filename>

Contributor

• Andriy Sheredko