Kraken-Websockets-API-1.9.0

Summary

This is a repository of example on how to use the Python and Pytest framework for validating Kraken Websockets API 1.9.0.
It covers the folloiwng:

1. Connection to Kraken Websockets API.
2. Assert details on Public Channel messages (Request and Reponse).
3. Run Test in parallel mode.
4. Provide Docker endpoints for ease of installations and execution via container.
5. Generate HTML and XML reports of Test run results.

Test Scenarios:

Public Channel Name	Test Scenario	Status
Book	1. Validate Publication Payload elements	Completed
	2. Validate whether Book publication has Ask price updates in the last t seconds (configurable)	Completed
	3. Validate whether Book publication has Bid price updates in the last t seconds (configurable)	Completed
	4. Validate Response Schema- subscriptionStatus	Completed
	5. Validate Response Schema- book publication snapshot	Completed
	6. Validate Response Schema- book publication update	Completed
	7. Validate Invalid Request	Completed
	8. Validate Server heartbeat sent more than once within the last 2 seconds	Completed
ohlc	1. Validate Response Schema- publication	In Progress, Connection Timeout to be resolved
trade	1. Validate Response Schema- publication	Completed
spread	1. Validate Response Schema- publication	Completed
General Message	1. Validate payload elements of Status sent on connection or system status changes.	Completed
	2. Validate system status Response Schema	Completed
	3. Validate server Ping Response with or without optional request fields	Completed
	4. Validate server Ping Response Schema	Completed
	5. Validate server Ping for various Invalid Requests	Completed, see Notes 1 below

Notes 1: Requires further evaluation for an unexpected observation. Details are noted in test_kraken_websocket_api.py: test_ping_response_error_reqid

Docker endpoints:

Pre-requisite:

1. Install Docker for the end user Operating System.
2. Clone this repository.
3. Launch the terminal/command prompt and navigate to the folder for this repository.

After that, follow these steps:

1. Image: Template for running Containers. Run the following on the terminal to build image:

    docker build -t pytest-kraken-ws .
   

2. Container: Actual running process where we have our package. Run the following on the terminal to start the container:

    docker run pytest-kraken-ws
   

Parallel run using xdist

Configured in pytest.ini
The folloiwng options can be used:

1. Let Pytest decide the number of Parallel runs using the following command line flag
   This option is built into the Docker Image by default.

    -n auto
   

2. Specify number of Parallel runs, e.g. use the following command line flag:
   To use this option, make changes in the pytest.ini file.

    -n 10  
   

Note: Docker image would require to be re-built if parallel run change are made.

Test Run Reports:

JUnit style XML Report: Test_Run_Report.xml
Pytest HTML Report: Test_Run_Report.html
Example:

Command to generate: python -m pytest

Test Framework organization:

tests folder has:

1. conftest.py has basic Pytest Fixture for Websockets connection.
2. helper_function.py has functions that provide abstraction of simple actions for the test cases.
3. schema.py is a schema store to be used durign the validations.
4. test_kraken_websocket_api.py has Test Cases related to Websockets Connection and Ping.
5. test_kraken_websocket_api_Public_Book_Channel.py has Test Cases related to Public Channel 'Book'.
6. test_kraken_websocket_api_Public_Channel_schema_validations.py has test cases related to Publication schema validation for other Public Channels.

Other than that:

1. Dockerfile has Docker Blueprint for building images.
2. pytest.ini has properties related to Commandline options, Markers, and Testpath.
3. requirements.txt has Python environment package versions for Docker Image creation.