rusty-req 0.3.43

⚡ High-performance async HTTP client in Rust with Python bindings for blazing-fast batch requests.

rusty-req

A high-performance asynchronous request library based on Rust and Python, suitable for scenarios that require high-throughput concurrent HTTP requests. It implements the core concurrent logic in Rust and packages it into a Python module using PyO3 and maturin, combining Rust's performance with Python's ease of use.

🚀 Features

• Dual Request Modes: Supports both batch concurrent requests (fetch_requests) and single asynchronous requests (fetch_single).
• High Performance: Built with Rust, Tokio, and a shared reqwest client for maximum throughput.
• Highly Customizable: Allows custom headers, parameters/body, per-request timeouts, and tags.
• Flexible Concurrency Modes: Choose between SELECT_ALL (default, get results as they complete) and JOIN_ALL (wait for all requests to finish) to fit your use case.
• Smart Response Handling: Automatically decompresses gzip, brotli, and deflate encoded responses.
• Global Timeout Control: Use total_timeout in batch requests to prevent hangs.
• Detailed Results: Each response includes the HTTP status, body, metadata (like processing time), and any exceptions.
• Debug Mode: An optional debug mode (set_debug(True)) prints detailed request/response information.

🔧 Installation

pip install rusty-req

Or build from source:

# This will compile the Rust code and create a .whl file
maturin build --release

# Install from the generated wheel
pip install target/wheels/rusty_req-*.whl

Development & Debugging

cargo watch -s "maturin develop"

📦 Example Usage

1. Fetching a Single Request (fetch_single)

Perfect for making a single asynchronous call and awaiting its result.

import asyncio
import pprint
import rusty_req

async def single_request_example():
    """Demonstrates how to use fetch_single for a POST request."""
    print("🚀 Fetching a single POST request to httpbin.org...")

    # Enable debug mode to see detailed logs in the console
    rusty_req.set_debug(True)

    response = await rusty_req.fetch_single(
        url="https://httpbin.org/post",
        method="POST",
        params={"user_id": 123, "source": "example"},
        headers={"X-Client-Version": "1.0"},
        tag="my-single-post"
    )

    print("\n✅ Request finished. Response:")
    pprint.pprint(response)

if __name__ == "__main__":
    asyncio.run(single_request_example())

2. Fetching Batch Requests (fetch_requests)

The core feature for handling a large number of requests concurrently. This example simulates a simple load test.

import asyncio
import time
import rusty_req
from rusty_req import ConcurrencyMode

async def batch_requests_example():
    """Demonstrates 100 concurrent requests with a global timeout."""
    requests = [
        rusty_req.RequestItem(
            url="https://httpbin.org/delay/2",  # This endpoint waits 2 seconds
            method="GET",
            timeout=2.9,  # Per-request timeout, should succeed
            tag=f"test-req-{i}",
        )
        for i in range(100)
    ]

    # Disable debug logs for cleaner output
    rusty_req.set_debug(False)

    print("🚀 Starting 100 concurrent requests...")
    start_time = time.perf_counter()

    # Set a global timeout of 3.0 seconds. Some requests will be cut off.
    responses = await rusty_req.fetch_requests(
        requests,
        total_timeout=3.0,
        mode=ConcurrencyMode.SELECT_ALL # Explicitly use SELECT_ALL mode
    )

    total_time = time.perf_counter() - start_time

    # --- Process results ---
    success_count = 0
    failed_count = 0
    for r in responses:
        # Check the 'exception' field to see if the request was successful
        if r.get("exception") and r["exception"].get("type"):
            failed_count += 1
        else:
            success_count += 1

    print("\n📊 Load Test Summary:")
    print(f"⏱️  Total time taken: {total_time:.2f}s")
    print(f"✅ Successful requests: {success_count}")
    print(f"⚠️ Failed or timed-out requests: {failed_count}")

if __name__ == "__main__":
    asyncio.run(batch_requests_example())

3. Understanding Concurrency Modes (SELECT_ALL vs JOIN_ALL)

The fetch_requests function supports two powerful concurrency strategies. Choosing the right one is key to building robust applications.

• ConcurrencyMode.SELECT_ALL (Default): Best-Effort Collector This mode operates on a "first come, first served" or "best-effort" basis. It aims to collect as many successful results as possible within the given total_timeout.

  • It returns results as soon as they complete.
  • If the total_timeout is reached, it gracefully returns all the requests that have already succeeded, while marking any still-pending requests as timed out.
  • A failure in one request does not affect others.

• ConcurrencyMode.JOIN_ALL: Transactional (All-or-Nothing) This mode treats the entire batch of requests as a single, atomic transaction. It is much stricter.

  • It waits for all submitted requests to complete first.
  • It then inspects the results.
  • Success Case: Only if every single request was successful will it return the complete list of successful results.
  • Failure Case: If even one request fails for any reason (e.g., its individual timeout, a network error, or a non-2xx status code), this mode will discard all results and return a list where every request is marked as a global failure.

---

Quick Comparison

Aspect	ConcurrencyMode.SELECT_ALL (Default)	ConcurrencyMode.JOIN_ALL
Failure Handling	Tolerant. One failure does not affect other successful requests.	Strict / Atomic. One failure causes the entire batch to fail.
Primary Use Case	Maximizing throughput; getting as much data as possible.	Tasks that must succeed or fail as a single unit (e.g., transactions).
Result Order	By completion time (fastest first).	By original submission order.
"When do I get results?"	As they complete, one by one.	All at once, only after every request has finished and been validated.

---

Code Example

The example below clearly demonstrates the difference in behavior.

import asyncio
import rusty_req
from rusty_req import ConcurrencyMode

async def concurrency_modes_example():
    """Demonstrates the difference between SELECT_ALL and JOIN_ALL modes."""
    # Note: We are using an endpoint that returns 500 to force a failure.
    requests = [
        rusty_req.RequestItem(url="https://httpbin.org/delay/2", tag="should_succeed"),
        rusty_req.RequestItem(url="https://httpbin.org/status/500", tag="will_fail"),
        rusty_req.RequestItem(url="https://httpbin.org/delay/1", tag="should_also_succeed"),
    ]

    # --- 1. Test SELECT_ALL ---
    print("--- 🚀 Testing SELECT_ALL (Best-Effort) ---")
    results_select = await rusty_req.fetch_requests(
        requests,
        mode=ConcurrencyMode.SELECT_ALL,
        total_timeout=3.0
    )

    print("Results:")
    for res in results_select:
        tag = res.get("meta", {}).get("tag")
        status = res.get("http_status")
        err_type = res.get("exception", {}).get("type")
        print(f"  - Tag: {tag}, Status: {status}, Exception: {err_type}")

    print("\n" + "="*50 + "\n")

    # --- 2. Test JOIN_ALL ---
    print("--- 🚀 Testing JOIN_ALL (All-or-Nothing) ---")
    results_join = await rusty_req.fetch_requests(
        requests,
        mode=ConcurrencyMode.JOIN_ALL,
        total_timeout=3.0
    )

    print("Results:")
    for res in results_join:
        tag = res.get("meta", {}).get("tag")
        status = res.get("http_status")
        err_type = res.get("exception", {}).get("type")
        print(f"  - Tag: {tag}, Status: {status}, Exception: {err_type}")

if __name__ == "__main__":
    asyncio.run(concurrency_modes_example())

The expected output from the script above:

--- 🚀 Testing SELECT_ALL (Best-Effort) ---
Results:
  - Tag: should_also_succeed, Status: 200, Exception: None
  - Tag: will_fail, Status: 500, Exception: HttpStatusError
  - Tag: should_succeed, Status: 200, Exception: None

==================================================

--- 🚀 Testing JOIN_ALL (All-or-Nothing) ---
Results:
  - Tag: should_succeed, Status: 0, Exception: GlobalTimeout
  - Tag: will_fail, Status: 0, Exception: GlobalTimeout
  - Tag: should_also_succeed, Status: 0, Exception: GlobalTimeout

🧱 Data Structures

RequestItem Parameters

Field	Type	Required	Description
url	str	✅	The target URL.
method	str	✅	The HTTP method.
params	dict / None	No	For GET/DELETE, converted to URL query parameters. For POST/PUT/PATCH, sent as a JSON body.
headers	dict / None	No	Custom HTTP headers.
timeout	float	✅	Timeout for this individual request in seconds. Defaults to 30s.
tag	str	No	An arbitrary tag to help identify or index the response.

fetch_requests Parameters

Field	Type	Required	Description
requests	List[RequestItem]	✅	A list of RequestItem objects to be executed concurrently.
total_timeout	float	No	A global timeout in seconds for the entire batch operation.
mode	ConcurrencyMode	No	The concurrency strategy. SELECT_ALL (default) for best-effort collection. JOIN_ALL for atomic (all-or-nothing) execution. See Section 3 for a detailed comparison.

Response Dictionary Format

Both fetch_single and fetch_requests return a dictionary (or a list of dictionaries) with a consistent structure.

Example of a successful response:

{
    "http_status": 200,
    "response": "{\"data\": \"...\", \"headers\": {\"...\"}}",
    "meta": {
        "process_time": "0.4531",
        "request_time": "2025-08-08 03:15:01 -> 2025-08-08 03:15:01",
        "tag": "my-single-post"
    },
    "exception": {}
}

Example of a failed response (e.g., timeout):

{
    "http_status": 0,
    "response": "",
    "meta": {
        "process_time": "3.0012",
        "request_time": "2025-08-08 03:15:05 -> 2025-08-08 03:15:08",
        "tag": "test-req-50"
    },
    "exception": {
        "type": "Timeout",
        "message": "Request timeout after 3.00 seconds"
    }
}

📄 License

This project is licensed under the MIT License.