adilytics

Project 1: Perform the advertisement analytics on a platform and visualise the results.

Team 12's submission for Project 1 for CSC-510.

Here is a quick introduction video:

https://user-images.githubusercontent.com/112341004/194640685-1cfeffa0-c33c-4c2f-b2c5-de64d47c637a.mp4

Table Of Contents

• Installation
• License
• Tools
• Team

Installation

Requires Python v3.9+. Clone the repository and move into the project directory and install the project dependencies.

To install the dependencies/packages required for the project install Poetry

shell curl https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py | python3 -

To get started you need Poetry's bin directory (/Users/<username>/Library/Python/python-version/bin) in your PATH environment variable.

Refer here for configuring poetry path correctly.

You can test that everything is set up by executing:

shell poetry --version

Configure Poetry virtual environment by

shell poetry env use python3 poetry install

License

This project is licensed under MIT license available in LICENSE file

Tools

This project makes use of FAST API. You can refer to the link to learn more about its working FAST API .

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints.

Some key features are:

• Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). One of the fastest Python frameworks available.
• Fast to code: Increase the speed to develop features by about 200% to 300%.
• Fewer bugs: Reduce about 40% of human (developer) induced errors.
• Standards-based: Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema.

This project makes use of Locust. You can refer to the link to learn more about its working Locust.

Locust is used to run load tests distributed over multiple machines. It is event-based (using gevent), which makes it possible for a single process to handle many thousands concurrent users. While there alternatives capable of doing more requests per second on a given hardware, the low overhead of each Locust user makes it very suitable for testing highly concurrent workloads.

Run the scripts in the following order:

1. product_creation.py
2. ad_creation.py
3. user_simulation.py

To run productcreation.py: locust -f productcreation.py --headless -H http://127.0.0.1:8000 -u 1 -r 1

Run this script with just one thread to create 50 products (-u 1 -r 1)

To run adcreation.py: locust -f adcreation.py --headless -H http://127.0.0.1:8000 -u 50 -r 50

Run this script with as many number of threads as you want to create ads.

To run usersimulation.py: locust -f usersimulation.py --headless -H http://127.0.0.1:8000 -u 50 -r 50 .

Run this script with as many number of threads as you want to simulate users.

Team

Name | Unity id ------------- | ------------- Aditya Tewari | adtewari Naman Bhagat | nbhagat2 Ritwik Tiwari | rtiwari2 Saksham Thakur | sthakur5 Shubhender Singh | ssingh54

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