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Client library for the increase API

Project description

Increase Python API Library

PyPI version

The Increase Python library provides convenient access to the Increase REST API from any Python 3.7+ application. It includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.

Documentation

The API documentation can be found here.

Installation

pip install increase

Usage

The full API of this library can be found in api.md.

from increase import Increase

client = Increase(
    # defaults to os.environ.get("INCREASE_API_KEY")
    api_key="my api key",
    # defaults to "production".
    environment="sandbox",
)

account = client.accounts.create(
    name="My First Increase Account",
)
print(account.id)

While you can provide an api_key keyword argument, we recommend using python-dotenv and adding INCREASE_API_KEY="my api key" to your .env file so that your API Key is not stored in source control.

Async Usage

Simply import AsyncIncrease instead of Increase and use await with each API call:

from increase import AsyncIncrease

client = AsyncIncrease(
    # defaults to os.environ.get("INCREASE_API_KEY")
    api_key="my api key",
    # defaults to "production".
    environment="sandbox",
)


async def main():
    account = await client.accounts.create(
        name="My First Increase Account",
    )
    print(account.id)


asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.

Using Types

Nested request parameters are TypedDicts. Responses are Pydantic models, which provide helper methods for things like serializing back into json (v1, v2). To get a dictionary, you can call dict(model).

This helps 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".

Pagination

List methods in the Increase API are paginated.

This library provides auto-paginating iterators with each list response, so you do not have to request successive pages manually:

import increase

client = Increase()

all_accounts = []
# Automatically fetches more pages as needed.
for account in client.accounts.list():
    # Do something with account here
    all_accounts.append(account)
print(all_accounts)

Or, asynchronously:

import asyncio
import increase

client = AsyncIncrease()


async def main() -> None:
    all_accounts = []
    # Iterate through items across all pages, issuing requests as needed.
    async for account in client.accounts.list():
        all_accounts.append(account)
    print(all_accounts)


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.accounts.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.data)}")

# Remove `await` for non-async usage.

Or just work directly with the returned data:

first_page = await client.accounts.list()

print(f"next page cursor: {first_page.next_cursor}")  # => "next page cursor: ..."
for account in first_page.data:
    print(account.id)

# Remove `await` for non-async usage.

Nested params

Nested parameters are dictionaries, typed using TypedDict, for example:

from increase import Increase

client = Increase()

client.accounts.create(
    foo={
        "bar": True,
    },
)

File Uploads

Request parameters that correspond to file uploads can be passed as bytes or a tuple of (filename, contents, media type).

from pathlib import Path
from increase import Increase

client = Increase()

contents = Path("my/file.txt").read_bytes()
client.files.create(
    file=contents,
    purpose="other",
)

The async client uses the exact same interface. This example uses aiofiles to asynchronously read the file contents but you can use whatever method you would like.

import aiofiles
from increase import Increase

client = Increase()

async with aiofiles.open("my/file.txt", mode="rb") as f:
    contents = await f.read()

await client.files.create(
    file=contents,
    purpose="other",
)

Handling errors

When the library is unable to connect to the API (e.g., due to network connection problems or a timeout), a subclass of increase.APIConnectionError is raised.

When the API returns a non-success status code (i.e., 4xx or 5xx response), a subclass of increase.APIStatusError will be raised, containing status_code and response properties.

All errors inherit from increase.APIError.

import increase
from increase import Increase

client = Increase()

try:
    client.accounts.create(
        naem="Oops",
    )
except increase.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except increase.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except increase.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

Retries

Certain errors will be 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 will all be retried by default.

You can use the max_retries option to configure or disable this:

from increase import Increase

# Configure the default for all requests:
client = Increase(
    # default is 2
    max_retries=0,
)

# Or, configure per-request:
client.with_options(max_retries=5).accounts.create(
    name="Jack",
)

Timeouts

Requests time out after 1 minute by default. You can configure this with a timeout option, which accepts a float or an httpx.Timeout:

from increase import Increase

# Configure the default for all requests:
client = Increase(
    # default is 60s
    timeout=20.0,
)

# More granular control:
client = Increase(
    timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
)

# Override per-request:
client.with_options(timeout=5 * 1000).accounts.list(
    status="open",
)

On timeout, an APITimeoutError is thrown.

Note that requests which time out will be retried twice by default.

Advanced

How to tell whether None means null or missing

In 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}.')

Configuring custom URLs, proxies, and transports

You can configure the following keyword arguments when instantiating the client:

import httpx
from increase import Increase

client = Increase(
    # Use a custom base URL
    base_url="http://my.test.server.example.com:8083",
    proxies="http://my.test.proxy.example.com",
    transport=httpx.HTTPTransport(local_address="0.0.0.0"),
)

See the httpx documentation for information about the proxies and transport keyword arguments.

Managing HTTP resources

By default we will close the underlying HTTP connections whenever the client is garbage collected is called but you can also manually close the client using the .close() method if desired, or with a context manager that closes when exiting.

Versioning

This package generally attempts to follow SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

  1. Changes that only affect static types, without breaking runtime behavior.
  2. 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).
  3. 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.

Requirements

Python 3.7 or higher.

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