Python + MongoDB + Charts

🔗 Click this link to see the public version of this Dashboard! 🔗

👋🏽 This is an example repo for working with MongoDB and visualizing testing data with MongoDB Charts.

Currently, there are examples of Unit and UI automated tests in this project, but more types and charts will come 😄

• Setup
  • MongoDB
  • Gitpod
  • Local Machine Requirements
  • Browsers and Drivers
• Run Tests
• Send Data to MongoDB

💡 This project uses Pylenium.io for it's Web Automation.

Setup

This section will help you set things up so you can work with this project.

💡 Using Gitpod is the recommended way to work with QA at the Point repos, but you can clone this locally as well

MongoDB

👀 This repo assumes that you have created a free, MongoDB Atlas account.

• This cloud-based account is where we will create databases, collections, and visual charts for our data!
• You can also install the free MongoDB Compass app for connecting and working with MongoDB locally.

Create a .env file at the Project Root and copy/paste your MongoDB connection string. You can use example.env to see the formatting.

Use this guide to get the connection string

Gitpod

With Gitpod, you just open a workspace and you're done 🎉 You can skip the rest of the setup, but make sure you have a free MongoDB Atlas account!

Machine Requirements

• 🐍 Python 3.8+
• 📦 Poetry as the package manager
• 💻 VS Code recommended

Browsers and Drivers

Gitpod and Pylenium will automatically handle the driver binaries needed to work with Selenium.

• If in Gitpod, point pylenium.json's local_path to either /usr/bin/chromedriver (default) or /usr/bin/geckodriver since the browsers are already installed
• Otherwise, Pylenium will handle downloading the correct driver binaries you need! Just make sure you have the actual browsers installed

Run Tests

• If in Gitpod, open Port 6080 if you'd like to see the tests run in "head" mode
• Otherwise, Pylenium runs tests in "head" mode by default

# Run all tests in the Terminal
poetry run poe test

You will see a .report.json file is created with the test results that we'll send to MongoDB in the next section! Check out the pytest-json-report plugin for more details on what you can do with this JSON report.

Send Data to MongoDB

Once you've executed some tests, a .report.json is created at the Project Root. This report is what we preprocess and send to MongoDB!

# example
python main.py run report send ".report.json" unit functional