The Finch Python library provides convenient access to the Finch REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.
The REST API documentation can be found in the Finch Documentation Center. The full API of this library can be found in api.md.
# install from PyPI
pip install finch-apiThe full API of this library can be found in api.md.
from finch import Finch
client = Finch(
access_token="My Access Token",
)
page = client.hris.directory.list()
print(page.page)Simply import AsyncFinch instead of Finch and use await with each API call:
import asyncio
from finch import AsyncFinch
client = AsyncFinch(
access_token="My Access Token",
)
async def main() -> None:
page = await client.hris.directory.list()
print(page.page)
asyncio.run(main())Functionality between the synchronous and asynchronous clients is otherwise identical.
Nested request parameters are TypedDicts. Responses are Pydantic models which also provide helper methods for things like:
- Serializing back into JSON,
model.to_json() - Converting to a dictionary,
model.to_dict()
Typed requests and responses provide autocomplete and documentation within your editor. If you would like to see type errors in VS Code to help catch bugs earlier, set python.analysis.typeCheckingMode to basic.
List methods in the Finch API are paginated.
This library provides auto-paginating iterators with each list response, so you do not have to request successive pages manually:
import finch
client = Finch()
all_directories = []
# Automatically fetches more pages as needed.
for directory in client.hris.directory.list():
# Do something with directory here
all_directories.append(directory)
print(all_directories)Or, asynchronously:
import asyncio
import finch
client = AsyncFinch()
async def main() -> None:
all_directories = []
# Iterate through items across all pages, issuing requests as needed.
async for directory in client.hris.directory.list():
all_directories.append(directory)
print(all_directories)
asyncio.run(main())Alternatively, you can use the .has_next_page(), .next_page_info(), or .get_next_page() methods for more granular control working with pages:
first_page = await client.hris.directory.list()
if first_page.has_next_page():
print(f"will fetch next page using these details: {first_page.next_page_info()}")
next_page = await first_page.get_next_page()
print(f"number of items we just fetched: {len(next_page.individuals)}")
# Remove `await` for non-async usage.Or just work directly with the returned data:
first_page = await client.hris.directory.list()
print(
f"the current start offset for this page: {first_page.paging.offset}"
) # => "the current start offset for this page: 1"
for directory in first_page.individuals:
print(directory.id)
# Remove `await` for non-async usage.Nested parameters are dictionaries, typed using TypedDict, for example:
from finch import Finch
client = Finch()
page = client.hris.directory.list()
print(page.page)We provide helper methods for verifying that a webhook request came from Finch, and not a malicious third party.
You can use finch.webhooks.verify_signature(body: string, headers, secret?) -> None or finch.webhooks.unwrap(body: string, headers, secret?) -> Payload,
both of which will raise an error if the signature is invalid.
Note that the "body" parameter must be the raw JSON string sent from the server (do not parse it first).
The .unwrap() method can parse this JSON for you into a Payload object.
For example, in FastAPI:
@app.post('/my-webhook-handler')
async def handler(request: Request):
body = await request.body()
secret = os.environ['FINCH_WEBHOOK_SECRET'] # env var used by default; explicit here.
payload = client.webhooks.unwrap(body, request.headers, secret)
print(payload)
return {'ok': True}When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of finch.APIConnectionError is raised.
When the API returns a non-success status code (that is, 4xx or 5xx
response), a subclass of finch.APIStatusError is raised, containing status_code and response properties.
All errors inherit from finch.APIError.
import finch
from finch import Finch
client = Finch()
try:
client.hris.company.retrieve()
except finch.APIConnectionError as e:
print("The server could not be reached")
print(e.__cause__) # an underlying Exception, likely raised within httpx.
except finch.RateLimitError as e:
print("A 429 status code was received; we should back off a bit.")
except finch.APIStatusError as e:
print("Another non-200-range status code was received")
print(e.status_code)
print(e.response)Error codes are as followed:
| Status Code | Error Type |
|---|---|
| 400 | BadRequestError |
| 401 | AuthenticationError |
| 403 | PermissionDeniedError |
| 404 | NotFoundError |
| 422 | UnprocessableEntityError |
| 429 | RateLimitError |
| >=500 | InternalServerError |
| N/A | APIConnectionError |
Certain errors are automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors are all retried by default.
You can use the max_retries option to configure or disable retry settings:
from finch import Finch
# Configure the default for all requests:
client = Finch(
# default is 2
max_retries=0,
)
# Or, configure per-request:
client.with_options(max_retries=5).hris.directory.list()By default requests time out after 1 minute. You can configure this with a timeout option,
which accepts a float or an httpx.Timeout object:
from finch import Finch
# Configure the default for all requests:
client = Finch(
# 20 seconds (default is 1 minute)
timeout=20.0,
)
# More granular control:
client = Finch(
timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
)
# Override per-request:
client.with_options(timeout=5.0).hris.directory.list()On timeout, an APITimeoutError is thrown.
Note that requests that time out are retried twice by default.
We automatically send the Finch-API-Version header set to 2020-09-17.
If you need to, you can override it by setting default headers per-request or on the client object.
Be aware that doing so may result in incorrect types and other unexpected or undefined behavior in the SDK.
from finch import Finch
client = Finch(
default_headers={"Finch-API-Version": "My-Custom-Value"},
)We use the standard library logging module.
You can enable logging by setting the environment variable FINCH_LOG to debug.
$ export FINCH_LOG=debugIn an API response, a field may be explicitly null, or missing entirely; in either case, its value is None in this library. You can differentiate the two cases with .model_fields_set:
if response.my_field is None:
if 'my_field' not in response.model_fields_set:
print('Got json like {}, without a "my_field" key present at all.')
else:
print('Got json like {"my_field": null}.')The "raw" Response object can be accessed by prefixing .with_raw_response. to any HTTP method call, e.g.,
from finch import Finch
client = Finch()
response = client.hris.directory.with_raw_response.list()
print(response.headers.get('X-My-Header'))
directory = response.parse() # get the object that `hris.directory.list()` would have returned
print(directory.id)These methods return an LegacyAPIResponse object. This is a legacy class as we're changing it slightly in the next major version.
For the sync client this will mostly be the same with the exception
of content & text will be methods instead of properties. In the
async client, all methods will be async.
A migration script will be provided & the migration in general should be smooth.
The above interface eagerly reads the full response body when you make the request, which may not always be what you want.
To stream the response body, use .with_streaming_response instead, which requires a context manager and only reads the response body once you call .read(), .text(), .json(), .iter_bytes(), .iter_text(), .iter_lines() or .parse(). In the async client, these are async methods.
As such, .with_streaming_response methods return a different APIResponse object, and the async client returns an AsyncAPIResponse object.
with client.hris.directory.with_streaming_response.list() as response:
print(response.headers.get("X-My-Header"))
for line in response.iter_lines():
print(line)The context manager is required so that the response will reliably be closed.
This library is typed for convenient access to the documented API.
If you need to access undocumented endpoints, params, or response properties, the library can still be used.
To make requests to undocumented endpoints, you can make requests using client.get, client.post, and other
http verbs. Options on the client will be respected (such as retries) will be respected when making this
request.
import httpx
response = client.post(
"/foo",
cast_to=httpx.Response,
body={"my_param": True},
)
print(response.headers.get("x-foo"))If you want to explicitly send an extra param, you can do so with the extra_query, extra_body, and extra_headers request
options.
To access undocumented response properties, you can access the extra fields like response.unknown_prop. You
can also get all the extra fields on the Pydantic model as a dict with
response.model_extra.
You can directly override the httpx client to customize it for your use case, including:
- Support for proxies
- Custom transports
- Additional advanced functionality
from finch import Finch, DefaultHttpxClient
client = Finch(
# Or use the `FINCH_BASE_URL` env var
base_url="http://my.test.server.example.com:8083",
http_client=DefaultHttpxClient(
proxies="http://my.test.proxy.example.com",
transport=httpx.HTTPTransport(local_address="0.0.0.0"),
),
)By default the library closes underlying HTTP connections whenever the client is garbage collected. You can manually close the client using the .close() method if desired, or with a context manager that closes when exiting.
This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:
- Changes that only affect static types, without breaking runtime behavior.
- Changes to library internals which are technically public but not intended or documented for external use. (Please open a GitHub issue to let us know if you are relying on such internals).
- Changes that we do not expect to impact the vast majority of users in practice.
We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.
We are keen for your feedback; please open an issue with questions, bugs, or suggestions.
Python 3.7 or higher.