The Increase Python library provides convenient access to the Increase 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 on increase.com. The full API of this library can be found in api.md.

# install from PyPI
pip install increase

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

import os
from increase import Increase

client = Increase(
    # This is the default and can be omitted
    api_key=os.environ.get("INCREASE_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 to add INCREASE_API_KEY="My API Key" to your .env file so that your API Key is not stored in source control.

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

import os
import asyncio
from increase import AsyncIncrease

client = AsyncIncrease(
    # This is the default and can be omitted
    api_key=os.environ.get("INCREASE_API_KEY"),
    # defaults to "production".
    environment="sandbox",
)


async def main() -> None:
    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.

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 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 parameters are dictionaries, typed using TypedDict, for example:

from increase import Increase

client = Increase()

account = client.accounts.create(
    name="New Account!",
)
print(account.id)

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

from pathlib import Path
from increase import Increase

client = Increase()

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

The async client uses the exact same interface. If you pass a PathLike instance, the file contents will be read asynchronously automatically.

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

When the API returns a non-success status code (that is, 4xx or 5xx response), a subclass of increase.APIStatusError is 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(
        name="New Account!",
    )
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:

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 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",
)

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 increase import Increase

# Configure the default for all requests:
client = Increase(
    # 20 seconds (default is 1 minute)
    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 that time out are retried twice by default.

We use the standard library logging module.

You can enable logging by setting the environment variable INCREASE_LOG to debug.

$ export INCREASE_LOG=debug

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}.')

The "raw" Response object can be accessed by prefixing .with_raw_response. to any HTTP method call, e.g.,

from increase import Increase

client = Increase()
response = client.accounts.with_raw_response.create(
    name="My First Increase Account",
)
print(response.headers.get('X-My-Header'))

account = response.parse()  # get the object that `accounts.create()` would have returned
print(account.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.accounts.with_streaming_response.create(
    name="My First Increase Account",
) 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 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 increase import Increase, DefaultHttpxClient

client = Increase(
    # Or use the `INCREASE_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:

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.

Python 3.7 or higher.