octopus-api 1.0.0

Octopus-api is a python library for performing client-based optimized concurrent requests and limit rates set by the endpoint contract. Octopus-api is simple; it combines the asyncio and aiohttp library's functionality and makes sure the requests follow the constraints set by the user.

octopus-api

About

Octopus-api is a python library for performing client-based optimized concurrent requests and limit rates set by the endpoint contract.

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

Installation

pip install octopus-api

PyPi

https://pypi.org/project/octopus-api/

Get started

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

client = OctopusApi(rate=30, resolution="minute", retries=10)
client = OctopusApi(rate=5, resolution="sec", retries=3)
client = OctopusApi(concurrency=100, retries=5)

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: TentacleSession, 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 Octopus TentacleSession uses aiohttp under the hood, the resulting way to write POST, GET, PUT and PATCH for aiohttp will be the same for octopus. The only difference is the added functionality of retries and rate limits (if set).

Finally, you finish everything up with the execute call for the octopus client, where you provide the list of requests dicts your defined and the user function. The execute call will then return the waited list of returned values.

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 concurrency constraints:

from octopus_api import TentacleSession, OctopusApi
from typing import Dict, List

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


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

Optimize the request based on rate limit constraints:

from octopus_api import TentacleSession, OctopusApi
from typing import Dict, List

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

    client = OctopusApi(rate=30, resolution="minute")
    result: List = client.execute(requests_list=[{
        "url": "http://api.coingecko.com/api/v3/coins/ethereum?tickers=false&localization=false&market_data=false",
        "params": {}}] * 100, func=get_ethereum_id)
    print(result)

Limitations

1. Returned result from the user defined function comes in out of order.
2. When setting rate-limiting, the api will not utilize the concurrency functionality and only run a single operation in sequence.