gatling 0.3.0.0

A unified I/O management toolkit supporting threads, coroutines, files, databases, and data formats

🧩 Gatling Utility Library

Gatling is a lightweight asynchronous utility library built on aiohttp, asyncio, and threading. It provides concurrent HTTP requests, coroutine-thread orchestration, data pipelines, and handy file utilities.

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📦 Installation

pip install gatling

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📁 Module Overview

Module	Description
http_client.py	Async/sync HTTP request handling
file_utils.py	Common file read/write helpers
taskflow_manager.py	Multi-stage task pipeline system
watch.py	Stopwatch and timing tools

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🧵 1. Process & Coroutine & Thread Manager

A hybrid process + thread + coroutine manager that can run both sync and async tasks concurrently.

Example

from gatling.runtime.taskflow_manager import TaskFlowManager
from gatling.storage.queue.memory_queue import MemoryQueue
from gatling.utility.xprint import check_globals_pickable
from gatling.vtasks.sample_tasks import fake_iter_disk, fake_fctn_disk, async_fake_iter_net, async_fake_fctn_net, fake_fctn_cpu, fake_iter_cpu

if __name__ == '__main__':
    pass

    # ---------- Build and run the pipeline ----------
    check_globals_pickable()
    if True:

        q_wait = MemoryQueue()
        # you can push to quque at here
        for i in range(10):
            q_wait.put(i + 1)

        tfm = TaskFlowManager(q_wait, retry_on_error=False)

        # or you can push to queue at here

        with tfm.execute(log_interval=1):
            tfm.register_process(fake_fctn_cpu, worker=2)
            tfm.register_coroutine(async_fake_fctn_net, worker=5)
            tfm.register_thread(fake_fctn_disk, worker=2)

            tfm.register_process(fake_iter_cpu, worker=2)
            tfm.register_coroutine(async_fake_iter_net, worker=8)
            tfm.register_thread(fake_iter_disk, worker=8)

            # or you can push to queue at here

        q_done = tfm.get_qdone()
        results = list(q_done)
        print(f"\n=== Final Results ({len(results)})===")

🌐 2. HTTP Client Module

File: gatling/utility/http_client.py

Provides unified async/sync HTTP request helpers supporting GET, POST, PUT, and DELETE.

Example

from gatling.utility.http_fetch_fctns import sync_fetch_http, async_fetch_http, fwrap
import asyncio, aiohttp

target_url = "https://httpbin.org/get"
# --- Synchronous request ---
result, status, size = sync_fetch_http(target_url)
print(status, size, result[:80])


# --- Asynchronous request ---
async def main():
    res, status, size = await fwrap(async_fetch_http, target_url=target_url, rtype="json")
    print(res)


asyncio.run(main())

Main functions

• async_fetch_http(...): Generic async HTTP fetcher
• fwrap(...): Safely manages aiohttp session lifecycle
• sync_fetch_http(...): Simple synchronous wrapper (for scripts)

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💾 3. File Utility Module

File: gatling/utility/io_fctns.py

Convenient helpers for reading and writing JSON, JSONL, Pickle, TOML, text, and byte files.

Example

from gatling.utility.io_fctns import *

save_json({"a": 1}, "data.json")
print(read_json("data.json"))
remove_file("data.json")

save_jsonl([{"x": 1}, {"x": 2}], "data.jsonl")
print(read_jsonl("data.jsonl"))

remove_file("data.jsonl")

save_text("Hello world", "msg.txt")
print(read_text("msg.txt"))

remove_file("msg.txt")

Main functions

• save_json / read_json
• save_jsonl / read_jsonl
• save_text / read_text
• save_pickle / read_pickle
• save_bytes / read_bytes
• read_toml
• remove_file

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⏱️ 4. Watch Utility

File: gatling/utility/watch.py

A simple stopwatch for timing operations, plus a decorator for measuring function execution time.

Example

from gatling.utility.watch import Watch, watch_time
import time


@watch_time
def slow_func():
    time.sleep(1)


slow_func()

w = Watch()
time.sleep(0.5)
print("Δt:", w.see_seconds(), "Total:", w.total_seconds())

Main items

• Watch: Manual stopwatch class for measuring intervals
• watch_time: Decorator that prints function execution time

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