anvai-sdk 1.0.1

A client library for accessing Anvai python sdk

anvai_sdk

A client library for accessing Anvai python sdk

Usage

First, create a client:

from anvai_sdk import Client

client = Client(base_url="https://feedback.nirva-ai-esg.com/")

If the endpoints you're going to hit require authentication, use AuthenticatedClient instead:

from anvai_sdk import AuthenticatedClient

client = AuthenticatedClient(base_url="https://feedback.nirva-ai-esg.com/", token="SuperSecretToken")

Now call your endpoint and use your models:

from anvai_sdk.models.get_token_body import GetTokenBody
from anvai_sdk.api.auth import get_token
from anvai_sdk.types import Response

with client as client:
    body = GetTokenBody.from_dict({"username":"username", "password":"password"})
    my_data:GetTokenBody = get_token.sync(client=client, body=body)
    # or if you need more info (e.g. status_code)
    response: Response[MyDataModel] = get_token.sync_detailed(client=client)

Or do the same thing with an async version:

from anvai_sdk.models.get_token_body import GetTokenBody
from anvai_sdk.api.auth import get_token
from anvai_sdk.types import Response

async with client as client:
    my_data: MyDataModel = await get_token.asyncio(client=client)
    response: Response[MyDataModel] = await get_token.asyncio_detailed(client=client)

By default, when you're calling an HTTPS API it will attempt to verify that SSL is working correctly. Using certificate verification is highly recommended most of the time, but sometimes you may need to authenticate to a server (especially an internal server) using a custom certificate bundle.

client = AuthenticatedClient(
    base_url="https://internal_api.example.com", 
    token="SuperSecretToken",
    verify_ssl="/path/to/certificate_bundle.pem",
)

You can also disable certificate validation altogether, but beware that this is a security risk.

client = AuthenticatedClient(
    base_url="https://internal_api.example.com", 
    token="SuperSecretToken", 
    verify_ssl=False
)

Things to know:

1. Every path/method combo becomes a Python module with four functions:

   1. sync: Blocking request that returns parsed data (if successful) or None
   2. sync_detailed: Blocking request that always returns a Request, optionally with parsed set if the request was successful.
   3. asyncio: Like sync but async instead of blocking
   4. asyncio_detailed: Like sync_detailed but async instead of blocking

2. All path/query params, and bodies become method arguments.

3. If your endpoint had any tags on it, the first tag will be used as a module name for the function (my_tag above)

4. Any endpoint which did not have a tag will be in anvai_sdk.api.default

Advanced customizations

There are more settings on the generated Client class which let you control more runtime behavior, check out the docstring on that class for more info. You can also customize the underlying httpx.Client or httpx.AsyncClient (depending on your use-case):

from anvai_sdk import Client

def log_request(request):
    print(f"Request event hook: {request.method} {request.url} - Waiting for response")

def log_response(response):
    request = response.request
    print(f"Response event hook: {request.method} {request.url} - Status {response.status_code}")

client = Client(
    base_url="https://api.example.com",
    httpx_args={"event_hooks": {"request": [log_request], "response": [log_response]}},
)

# Or get the underlying httpx client to modify directly with client.get_httpx_client() or client.get_async_httpx_client()

You can even set the httpx client directly, but beware that this will override any existing settings (e.g., base_url):

import httpx
from anvai_sdk import Client

client = Client(
    base_url="https://api.example.com",
)
# Note that base_url needs to be re-set, as would any shared cookies, headers, etc.
client.set_httpx_client(httpx.Client(base_url="https://api.example.com", proxies="http://localhost:8030"))