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Python RTI Example

codecov

This repository demonstrating how to use Codecov's Impact Analysis feature with python. It runs with the Flask framework and leverages the codecov/opentelem-python package to send information to Codecov's Runtime Insights API.

This repository is set up to do to be used as

  1. a working sandbox to explore Impact Analysis
  2. a reference for adding Impact Analysis to your own repositories

Getting Started

The following section details how to get started with Impact Analysis. Before getting started, you will need

  1. python version 3+
  2. An account on Codecov

Step 1: Fork and clone this repository

Fork this repository from GitHub. It is strongly recommended that you fork the repository to your personal GitHub account. Clone your new repository to your local machine.


Step 2: Set the profiling token

Go to Codecov and find the fork in the list of repositories. Note that it may be under Not yet setup in the right-hand section.

In the settings page, grab the Impact analysis token, and set the token locally in a terminal.

export CODECOV_OPENTELEMETRY_TOKEN='***'

Step 3: Install the dependencies

Install all dependencies for this project. It is highly recommended to do this in a virtual environment.

pip install -r requirements.txt

Step 4: Run the server locally and generate profiling data

Run the server from your machine using the command

python example-app/app.py

If the token has been set properly, you should see the server running with the following logs

 * Serving Flask app 'app' (lazy loading)
 * Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: off
 * Running on all addresses (0.0.0.0)
   WARNING: This is a development server. Do not use it in a production deployment.
 * Running on http://127.0.0.1:8080
 * Running on http://192.168.1.184:8080 (Press CTRL+C to quit)

You can view the app by going to http://127.0.0.1:8080. The app has two pages, the main page that has a button to Get the time, while the other page displays the time.


Step 5: Overloading the /time endpoint

In order for us to see what happens when we change a critical (frequently hit) line, we will need to hit the /time endpoint. In a python shell, run the following with the server running

import requests
import time

for i in range(100):
    print(i)
    requests.get('http://127.0.0.1:8080/time')
    time.sleep(0.1)

This should hit our /time endpoint 100 times and upload the telemetry data to Codecov.


Step 6: Making a change to critical code

Let's now make a change in our code to see if what we are changing is critical.

In example-app/utils/time.py, update line 4 from

    return datetime.strftime(time, '%Y-%m-%d %H:%M:%S')

to

    return datetime.strftime(time, '%Y-%m-%d:%H:%M:%S')

You will also need to update the tests. Change line 7 of example-app/utils/tests/test_time.py

    assert(format_time(current_time) == datetime.strftime(current_time, '%Y-%m-%d %H:%M:%S'))

to

    assert(format_time(current_time) == datetime.strftime(current_time, '%Y-%m-%d:%H:%M:%S'))

Save the changes, create a new branch, and push to GitHub.

git checkout -b 'test-codecov'
git add example-app/
git commit -m 'fix: update time display with colon'
git push origin test-codecov

Open a new pull request. Be sure to set the base branch to your fork.


Step 7: Seeing Impact Analysis in the UI

After CI/CD has completed, you should see a comment from Codecov similar to this PR. The comment will now show 2 new elements

  1. Under impacted files, you should see a Critical label next to example-app/utils/time.py. This means that the PR has a change in that file that is frequently hit in production.
  2. Under related entrypoints, you should see /time. This means that the PR has a change that touches that endpoint.

You should now be able to see how Impact Analysis can give crucial information on how a code change can affect critical code in your system.

Using your own repositories

To get started with Impact Analysis on your own repositories, check out our getting started guide.