Github Profile Analysis

Objective

Evaluate the technical skills of the candidate in backend development, reusable code creation, technical documentation interpretation, rate limit handling, and data processing using third-party integrations.

General Instructions

• You can use any backend programming language you are comfortable with (e.g., Node.js, Python, Java, etc.).
• You may use GitHub API integration either via REST or GraphQL, but the output API must be REST.
• Your code needs to be documented and explaines where necessary.
• Include a README.md file with instructions on how to run your solution and any important details.

Challenge Description

Imagine that you are part of a fictional company that is building an advanced analytics platform for developers' GitHub profiles. Your task is to create a system that can extract meaningful insights from a user's GitHub profile. By evaluating their open-source contributions, your system will provide valuable information about their coding practices, preferred languages, and overall activity.

Part 1: RESTful API and Data Processing

You need to create an endpoint that can be queried to get insights into a GitHub profile by passing the GitHub username as a parameter. This endpoint will retrieve detailed insights from a specific GitHub user's profile. The response should include the following information:

• Top 3 most used programming languages: Determine the most common languages used across the user's repositories.
• Repositories with the most merged pull requests: Identify the repositories where the user has had the most pull requests accepted.
• Contributions in the last 6 months: Count the total number of pull requests, issues, and commits the user has made in the last 6 months, and display these numbers month by month in an array.
• Days and time slots of highest activity: Analyze the user's events to determine the days of the week and time slots (morning, afternoon, evening) when the user is most active.

The endpoint should be structured as follows: GET /user-insights/:username

Part 2: Integration and Rate Limit Handling

• Use the GitHub API to implement the operations needed for the insights. Authentication using OAuth or personal tokens may be required.
• Ensure you handle GitHub's rate limits appropriately. Your API should be able to handle rate limit errors and implement a retry logic with exponential backoff.

Part 3: Open/Closed Principle (OCP)

• Structure your code in a way that makes it easy to include new metrics in the future without modifying existing code. This means that if a new metric is required in the future, a new programmer should be able to add it through extension rather than modification.

Part 4: Documentation and Tests

• Use Swagger or a similar tool to document your API.
• Include a brief explanation of each endpoint and the possible response codes.
• Write unit and integration tests for the main endpoints of your API.
• Ensure the tests cover the most important cases, including validations, error handling, and retry logic for rate limits.

Example GitHub Profiles

• Profiles with Many Repositories:

  • torvalds (Linus Torvalds)
  • mojombo (Tom Preston-Werner)

• Profiles with Few Repositories:

  • dhh (David Heinemeier Hansson)
  • tenderlove (Aaron Patterson)

Bonus

Infer developer most user Languages from commits instead of entire repo:

• Additionally, you may infer the languages used in the user’s commits instead of relying on the overall repository languages (since a repository could contain multiple languages, and the user may not have contributed to all of them).
• Analyze the extensions of files modified in the user’s commits to determine the most frequently used languages in their contributions.
• This functionality should be implemented in a way that makes it easy to add more file extensions and corresponding languages in the future.