The Intercom Python library provides convenient access to the Intercom 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 API documentation can be found here.

pip install intercom

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

import os
from intercom import Intercom

client = Intercom(
    # This is the default and can be omitted
    bearer_token=os.environ.get("INTERCOM_TEST_1_BEARER_TOKEN"),
    # or 'production' | 'environment_2'; defaults to "production".
    environment="environment_1",
)

admin_with_app = client.me.retrieve()
print(admin_with_app.id)

While you can provide a bearer_token keyword argument, we recommend using python-dotenv to add INTERCOM_TEST_1_BEARER_TOKEN="My Bearer Token" to your .env file so that your Bearer Token is not stored in source control.

Simply import AsyncIntercom instead of Intercom and use await with each API call:

import os
import asyncio
from intercom import AsyncIntercom

client = AsyncIntercom(
    # This is the default and can be omitted
    bearer_token=os.environ.get("INTERCOM_TEST_1_BEARER_TOKEN"),
    # or 'production' | 'environment_2'; defaults to "production".
    environment="environment_1",
)


async def main() -> None:
    admin_with_app = await client.me.retrieve()
    print(admin_with_app.id)


asyncio.run(main())

Functionality between the synchronous and asynchronous clients is otherwise identical.

Nested request parameters are TypedDicts. Responses are Pydantic models, which provide helper methods for things like:

• Serializing back into JSON, model.model_dump_json(indent=2, exclude_unset=True)
• Converting to a dictionary, model.model_dump(exclude_unset=True)

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.

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

When the API returns a non-success status code (that is, 4xx or 5xx response), a subclass of intercom.APIStatusError is raised, containing status_code and response properties.

All errors inherit from intercom.APIError.

import intercom
from intercom import Intercom

client = Intercom()

try:
    client.me.retrieve()
except intercom.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except intercom.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except intercom.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 intercom import Intercom

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

# Or, configure per-request:
client.with_options(max_retries=5).me.retrieve()

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 intercom import Intercom

# Configure the default for all requests:
client = Intercom(
    # 20 seconds (default is 1 minute)
    timeout=20.0,
)

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

# Override per-request:
client.with_options(timeout=5 * 1000).me.retrieve()

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 INTERCOM_LOG to debug.

$ export INTERCOM_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.

from intercom import Intercom

client = Intercom()
response = client.me.with_raw_response.retrieve()
print(response.headers.get('X-My-Header'))

me = response.parse()  # get the object that `me.retrieve()` would have returned
print(me.id)

These methods return an APIResponse object.

You can directly override the httpx client to customize it for your use case, including:

• Support for proxies
• Custom transports
• Additional advanced functionality

import httpx
from intercom import Intercom

client = Intercom(
    # Or use the `INTERCOM_BASE_URL` env var
    base_url="http://my.test.server.example.com:8083",
    http_client=httpx.Client(
        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.