Postman Collection Tests

This project provides a lightweight environment for running Postman-style test collections using a Python-based automation template. It’s built for developers who want a cheaper, flexible alternative for executing their test suites without relying on heavyweight infrastructure.

     

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Introduction

The Postman Collection Tests tool serves as a starter framework for automating API test execution. It gives you control of how Postman-like tests run inside a Python environment, allowing you to integrate custom logic, add validations, and sync results with other systems.

Why This Template Helps Developers

• Eliminates the overhead of maintaining a full Postman runtime.
• Lets you extend test logic using Python libraries and tooling.
• Supports reusable workflows for API monitoring and validation.
• Designed for cost-efficient, large-scale automated test execution.

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Features

Feature	Description
Python-Based Test Runner	Insert custom test logic directly into the provided async template.
Apify SDK Integration	Use queues, storage, and structured datasets to organize test flows.
Flexible Test Logic	Combine API calls, assertions, and workflows as needed.
Easy Expansion	Ideal foundation for building advanced API test frameworks.
Consistent Dataset Output	Store execution results in structured form for logs or dashboards.

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What Data This Scraper Extracts

Field Name	Field Description
testName	Name of the test collection or individual test.
endpoint	API endpoint under evaluation.
status	Pass/Fail status after execution.
responseTime	Measured latency of the request.
responseCode	The actual HTTP response status.
metadata	Any additional information attached to the test run.

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Example Output

[
  {
    "testName": "User Auth Check",
    "endpoint": "https://api.example.com/login",
    "status": "passed",
    "responseTime": 182,
    "responseCode": 200,
    "metadata": {
      "method": "POST",
      "payload": {"email": "test@example.com"}
    }
  }
]

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Directory Structure Tree

Postman Collection Tests/
├── src/
│   ├── main.py
│   ├── runner/
│   │   ├── test_executor.py
│   │   ├── assertion_engine.py
│   │   └── request_client.py
│   ├── utils/
│   │   ├── logger.py
│   │   ├── dataset_writer.py
│   │   └── config_loader.py
│   └── config/
│       └── settings.example.json
├── tests/
│   ├── sample_collection.json
│   └── templates/
│       └── sample_test_template.py
├── data/
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• API Developers run ongoing validation tests during development cycles.
• QA Engineers automate regression suites and track failures.
• DevOps Teams integrate lightweight test runners in CI/CD pipelines.
• SaaS Platforms monitor API uptime and response consistency.
• Test Automation Engineers build custom frameworks without vendor lock-in.

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FAQs

Is this a full Postman runtime?
No. It’s a flexible template for running Postman-like tests using Python.

Can I import existing Postman collections?
Yes—convert collections into JSON and process them using your custom test executor.

Does it support async workflows?
The template is async-ready and supports concurrent test execution.

Where are the test results stored?
All outputs are saved in structured datasets, ready for export or analysis.

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Performance Benchmarks and Results

Primary Metric:
Runs light to medium API test suites in seconds with minimal compute overhead.

Reliability Metric:
Consistent execution flow using Apify SDK queues and retries.

Efficiency Metric:
Low-cost execution—optimized for batches of 1,000+ test events.

Quality Metric:
Produces clean, structured logs suitable for debugging, dashboards, and compliance reporting.

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