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API Call Analysis Using Time Series

This project aims to analyze API calls using time series data. It involves collecting API call data, processing it, and visualizing it to extract insights. The analysis can help in understanding patterns, detecting anomalies, and improving the performance of APIs.

Features

  • User Input: Allows users to enter the number of top APIs to analyze.
  • Data Processing: Time series data is used to track API calls over time.
  • Visualizations: Graphical representation of API call frequencies and trends.
  • Responsive Design: The interface adapts to various screen sizes.

Project Structure

The project includes the following files:

  • index.html: The main HTML file that contains the structure and layout of the page.
  • template/: Folder containing the HTML file and other related assets.
  • styles.css: CSS file for styling the HTML page and ensuring a responsive design.
  • api_analysis.py: Python script to process the time series data and generate analysis reports (if applicable).

Web Preview

Homepage

Homepage

Form Submission

Form Submission

API Options

API Options

API Calls

API Calls

Analysis Results

Analysis Results

Installation

  1. Clone the repository to your local machine:

    git clone https://github.com/yourusername/API-call-Analysis-using-time-series.git

  2. Navigate to the project directory:

    cd API-call-Analysis-using-time-series

  3. Install any necessary dependencies (if any, e.g., Python libraries for analysis):

    pip install -r requirements.txt

  4. Open index.html in your browser to start the application.

Usage

  1. Open the index.html file in a web browser.

  2. Enter the number of top APIs you want to analyze.

  3. Click "Submit" to process the request.

  4. View the results of the analysis and visualizations.

Contributing

If you'd like to contribute to this project, feel free to fork the repository, make your changes, and submit a pull request.

Made with ❤️ by Shaurya Bhatia