ratehttp 0.1.2

ratehttp is fork from octopus-api based on aiohttp, and ratehttp provides ssl-verify setting

About

ratehttp is fork from octopus-api based on aiohttp, but ratehttp provides ssl-verify setting

ratehttp is simple; it combines the asyncio and aiohttp and octopus-api library's functionality and makes sure the requests follows the constraints set by the contract.

Installation

pip install ratehttp

PyPi

https://pypi.org/project/ratehttp/

Get started

To start RateHttp, you first initiate the client, setting your constraints.

client = RateHttp(rate=100, connections=10, retries=5, sll=False)
client = RateHttp(connections=10, retries=3, sll=True)

After that, you will specify what you want to perform on the endpoint response. This is done within a user-defined function.

async def patch_data(session: RateSession, request: Dict):
    async with session.patch(url=request["url"], data=requests["data"], params=request["params"]) as response:
        body = await response.json()
        return body["id"]

As RateHttp RateSession uses aiohttp under the hood, the resulting way to write POST, GET, PUT and PATCH for aiohttp will be the same for RateHttp. The only difference is the added functionality of retries and optional rate limit.

Finally, you finish everything up with the execute call for the RateHttp client, where you provide the list of requests dicts and the user function. The execute call will then return a list of the return values defined in user function. As the requests list is a bounded stream we return the result in order.

result: List = client.execute(requests_list=[
    {
        "url": "http://localhost:3000",
        "data": {"id": "a", "first_name": "filip"},
        "params": {"id": "a"}
    },
    {
        "url": "http://localhost:3000",
        "data": {"id": "b", "first_name": "morris"},
        "params": {"id": "b"} 
    }
    ] , func=patch_data)

Examples

Optimize the request based on max connections constraints:

from ratehttp import RateSession, RateHttp
from typing import Dict, List

if __name__ == '__main__':
    async def fetch_data(session: RateSession, request: Dict):
        async with session.get(url=request["url"], params=request["params"]) as response:
            body = await response.text()
            return body


    client = RateHttp(connections=100)
    result: List = client.execute(requests_list=[{
        "url": "http://google.com",
        "params": {}}] * 100, func=fetch_data)
    print(result)

Optimize the request based on rate limit and connections limit:

from ratehttp import RateSession, RateHttp
from typing import Dict, List

if __name__ == '__main__':
    async def fetch_data(session: RateSession, request: Dict):
        async with session.get(url=request["url"], params=request["params"]) as response:
            body = await response.json()
            return body

    client = RateHttp(rate=50, resolution="sec", connections=6)
    result: List = client.execute(requests_list=[{
        "url": "https://api.pro.coinbase.com/products/ETH-EUR/candles?granularity=900&start=2021-12-04T00:00:00Z&end=2021-12-04T00:00:00Z",
        "params": {}}] * 1000, func=fetch_data)
    print(result)