Design & Build Test Framework with Python Pytest | API Tests

Install python on Windows via Python.org, choose the appropriate release, run the Windows installer, add Python to path, and verify the version in command prompt.

Learn to design a modular, data-driven test framework with pytest in Python for rest api testing. See how simple syntax, fixtures, and ci integration streamline test development and reporting.

Learn how to write a pytest test from scratch, name test files and functions correctly, and run arithmetic tests in Python using clear conventions and verbose output.

Discover how pytest discovers tests by default test naming conventions and how to run them from the command line across directories, files, and individual functions.

Discover how __init__.py turns folders into Python packages for pytest test discovery across subdirectories, even with identical module names.

Explore pytest command line options, including -V verbose, -K and -M selectors, --collect-only, -x exit, --maxfail, -s for print output, and junitxml reporting for Jenkins.

Learn to use pytest parameterization to perform data-driven testing with multiple username and password combinations, using pytest.mark.parametrize to run a single test across a list of values.

Explore essential Python file operations for your test framework, including open and file modes (r, w, a), and reading methods (read, readline, readlines) with safe closing.

Discover how JSON serves as a lightweight, language-independent data interchange format for client-server communication. Understand JSON objects, key-value pairs, types, serialization, and using Python's JSON module with API responses.

Learn to serialize Python dictionaries into JSON strings using the json.dumps method, and print formatted output to debug API responses and understand JSON structures.

Explore json operations in Python, converting json strings to data with loads and reading json files with load, then traverse dictionaries to access keys and values for api testing.

Validate json strings by using json loads and json load to parse from strings or files, handle value errors, and perform preliminary validation for API tests.

Explore free API URLs like httpbin.org and Swagger Pet Store to practice API testing with curl, covering GET, POST, PUT, DELETE, and JSON responses in Python pytest.

Explore the Python requests library to send HTTP requests and obtain a response object with data, status, headers, and encoding. Learn to use get and post methods, URL, and optional args like params and timeout, and inspect r.text, r.headers, r.status_code, and r.json for API testing.

Learn how to use Python's requests module to build API tests by passing URL query strings with key-value parameters using the params option, and parse the JSON response.

Learn to set custom headers in Python requests for API testing, including content-type, accept headers, and JSON payloads with json.dumps.

Explore using Python's csv module to drive data-driven tests, reading CSV data with reader and DictReader and handling headers and rows.

Explore rest APIs and http fundamentals, defining terms like url endpoints and status codes, and verbs such as get, post, put, and delete for API testing within a test framework.

Explore rest apis as a lightweight, stateless web architecture that uses http methods to manipulate resources identified by urls, returns json representations, and enables interoperable, scalable api design.

Explore rest api request and response compositions, including endpoints, urls, http methods, headers, body, and parameters, and learn how to test these with a pet store example.

Create a reusable utils module for get API calls with headers, return data, status, and time taken. Then implement a pets API test validating the response ID.

Update a pet on the server with a put request, implement a put data utility, build tests with a payload, and validate id, name, and status.

Learn how to use curl, a cross-platform command line tool for testing REST APIs, performing get and delete requests, with options like -X and -H before automated Python pytest tests.

Master curl basics by sending headers with -H, timing out with -M, saving output with -O, and using -V for verbose testing of the get all user count endpoint.

Design and implement api tests with pytest by building api utils, configuring a local server, and validating payloads, headers, and basic performance. Organize test files and naming for clarity.

Learn to add pytest tests for the all user count API, organize into modules, and validate status codes, headers, and payloads with a mix of API-name and test-type approaches.

Learn to write api tests with pytest, including adding a get all user count test, validating response data and status, and measuring response time with fixtures.

Explore scenario parameterization in pytest to feed multiple inputs into the same test, enabling data-driven API tests, varied headers and status checks with a single test function.

Learn to post to the register API by reading the request body from a JSON file, update API utils, and test with valid.json in the test data folder, expecting 201.

explore data driven testing by reading csv data files to test multiple login credentials, and build a csv reader that returns dicts for easy json payloads.

Learn how to implement a data driven test for a register API using a CSV data file, building payloads, posting to the API, and asserting created IDs.

Apply pytest parameterization to run multiple API data sets as separate tests, covering empty, valid, invalid, and boundary cases with data files and a utils function for reading data.

Create a data file for api tests and implement a utils function to read csv data as a list, then transform to tuples for parameterized pytest tests validating status codes.

Use data driven testing with parameterized pytest to generate separate tests from a csv data file for api registration, building a request dict via zip, and asserting status codes.