[Part 7]File I/O and Data Persistence in Python for QA Automation

Introduction

Reading and writing data is a key part of test automation. Whether it’s parsing logs, storing test results, or using CSV and JSON files, this module will help you master Python’s file-handling features.

Lesson 1: Reading and Writing Text Files

Concept:
Text files help store logs, config values, and test data persistently.

Key Topics:

• open(), read(), write(): Basic file operations.
• File Modes: "r", "w", "a", "r+"
• Context Manager: Using with to manage file resources.

Example:

with open("results.txt", "w") as file:
    file.write("Login Test: Passed\n")

Pro Tip: Always use with for safer file handling.

Lesson 2: Working with CSV Files

Concept:
CSV files are widely used in data-driven testing to store and read test cases and results.

Key Topics:

• csv.reader and csv.writer: Standard Python CSV tools.
• DictReader and DictWriter: Work with CSV rows as dictionaries.
• Reading Multiple Rows: Looping through test datasets.

Example:

import csv
with open("test_data.csv") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["test_name"], row["status"])

Pro Tip: Use CSV files for quick and readable input data during test case execution.

Lesson 3: Parsing JSON Data

Concept:
JSON is a flexible format used in API automation and configuration files.

Key Topics:

• json.load() / json.dump(): Reading and writing JSON files.
• json.loads() / json.dumps(): Parsing strings in-memory.
• Use Cases in QA: Validating API responses, storing test data.

Example:

import json
with open("config.json") as f:
    config = json.load(f)
    print(config["username"])

Pro Tip: Keep your JSON schemas clean and predictable for easy debugging.

Lesson 4: Introduction to File System Operations

Concept:
Python’s os and shutil modules help manage test directories and files.

Key Topics:

• Checking File Existence: os.path.exists()
• Creating/Deleting Folders: os.mkdir(), os.remove(), shutil.rmtree()
• Listing Files: os.listdir()

Example:

import os
if not os.path.exists("logs"):
    os.mkdir("logs")

Pro Tip: Use tempfile for safe temporary file storage during test runs.

Lesson 5: Best Practices for Handling Large Test Data Files

Concept:
Efficient file I/O becomes important when dealing with large datasets.

Key Topics:

• Reading in Chunks: Avoid memory overload.
• File Compression: Using gzip.
• Moving to Databases: When files become unwieldy.

Example:

with open("large_file.txt") as f:
    for line in f:
        process(line)

Pro Tip: Always close large files or use with to manage memory efficiently.

Conclusion

Python provides powerful tools to handle file I/O, making it easy to store, retrieve, and manipulate test data.

Key Takeaways:

• Use text files for logs and results.
• Use CSV for readable, structured data inputs.
• Use JSON for config and API test data.
• Use os and shutil to organize automation directories and output.

What’s Next?
In the final module, we’ll explore Python for Selenium: Preparation for UI Automation, where you’ll get hands-on with browser automation using Python.

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