Metadata-Version: 2.1
Name: aio-request
Version: 0.1.6
Summary: Various strategies for sending requests
Home-page: UNKNOWN
Author: Yury Pliner
Author-email: yury.pliner@gmail.com
License: MIT
Platform: macOS
Platform: POSIX
Platform: Windows
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: multidict (<7.0,>=4.5)
Requires-Dist: yarl (<2.0,>=1.0)

# aio-request

This library simplifies an interaction between microservices:
1. Allows sending requests using various strategies
1. Propagates a deadline and a priority of requests
1. Exposes client/server metrics

Example:
```python
import aiohttp
import aio_request

async with aiohttp.ClientSession() as client_session:
    client = aio_request.setup(
        transport=aio_request.AioHttpTransport(client_session),
        endpoint="http://endpoint:8080/",
    )
    response_ctx = client.request(
        aio_request.get("thing"),
        deadline=aio_request.Deadline.from_timeout(5)
    )
    async with response_ctx as response:
        pass  # process response here
```

# Request strategies 
The following strategies are supported:
1. Single attempt. Only one attempt is sent.
1. Sequential. Attempts are sent sequentially with delays between them.
1. Parallel. Attempts are sent in parallel one by one with delays between them.

Attempts count and delays are configurable.

Example:
```python
import aiohttp
import aio_request

async with aiohttp.ClientSession() as client_session:
    client = aio_request.setup(
        transport=aio_request.AioHttpTransport(client_session),
        endpoint="http://endpoint:8080/",
    )
    response_ctx = client.request(
        aio_request.get("thing"),
        deadline=aio_request.Deadline.from_timeout(5),
        strategy=aio_request.parallel_strategy(
            attempts_count=3,
            delays_provider=aio_request.linear_delays(min_delay_seconds=0.1, delay_multiplier=0.1)
        )
    )
    async with response_ctx as response:
        pass  # process response here
```

# Deadline & priority propagation

To enable it for the server side a middleware should be configured:
```python
import aiohttp.web
import aio_request

app = aiohttp.web.Application(middlewares=[aio_request.aiohttp_middleware_factory()])
```

# Expose client/server metrics

To enable client metrics a metrics provider should be passed to the transport:
```python
import aiohttp
import aio_request

async with aiohttp.ClientSession() as client_session:
    client = aio_request.setup(
        transport=aio_request.AioHttpTransport(
            client_session,
            metrics_provider=aio_request.PROMETHEUS_METRICS_PROVIDER
        ),
        endpoint="http://endpoint:8080/",
    )
```

It is an example of how it should be done for aiohttp and prometheus.

To enable client metrics a metrics provider should be passed to the middleware:
```python
import aiohttp.web
import aio_request

app = aiohttp.web.Application(
    middlewares=[
        aio_request.aiohttp_middleware_factory(
            metrics_provider=aio_request.PROMETHEUS_METRICS_PROVIDER
        )
    ]
)
```


