subhosting 0.1.0a2

The official Deno Deploy Subhosting REST API client for Python

Deno Deploy Subhosting REST API client for Python

This library provides convenient access to the Deno Deploy Subhosting REST API, which allows you to programmatically deploy untrusted, third-party code into the cloud, from server-side Python.

The REST API documentation can be found on apidocs.deno.com. The full API of this library can be found in api.md.

To learn more about Subhosting, check out our documentation.

Installation

pip install --pre subhosting

Usage

Before you begin, you'll need to have a Deno Deploy access token and an ID for the Deno Deploy organization you're using for Subhosting.

• You can find or create a personal access token in the dashboard here
• Your org ID can be found near the top of the page on your Deno Deploy dashboard as described here

The code examples below assume your access token is stored in a DEPLOY_ACCESS_TOKEN environment variable and your Deno Deploy org ID is stored in a DEPLOY_ORG_ID environment variable.

import os
from subhosting import Subhosting

client = Subhosting(
    # This is the default and can be omitted
    bearer_token=os.environ.get("DEPLOY_ACCESS_TOKEN"),
)

organization = client.organizations.get(
    "DEPLOY_ORG_ID",
)
print(organization.id)

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

Async usage

Simply import AsyncSubhosting instead of Subhosting and use await with each API call:

import os
import asyncio
from subhosting import AsyncSubhosting

client = AsyncSubhosting(
    # This is the default and can be omitted
    bearer_token=os.environ.get("DEPLOY_ACCESS_TOKEN"),
)


async def main() -> None:
    organization = await client.organizations.get(
        "DEPLOY_ORG_ID",
    )
    print(organization.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, 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.

Handling errors

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

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

All errors inherit from subhosting.APIError.

import subhosting
from subhosting import Subhosting

client = Subhosting()

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

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

# Or, configure per-request:
client.with_options(max_retries=5).organizations.get(
    "DEPLOY_ORG_ID",
)

Timeouts

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 subhosting import Subhosting

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

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

# Override per-request:
client.with_options(timeout=5 * 1000).organizations.get(
    "DEPLOY_ORG_ID",
)

On timeout, an APITimeoutError is thrown.

Note that requests that time out are retried twice by default.

Advanced

Logging

We use the standard library logging module.

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

$ export SUBHOSTING_LOG=debug

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}.')

Accessing raw response data (e.g. headers)

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

from subhosting import Subhosting

client = Subhosting()
response = client.organizations.with_raw_response.get(
    "DEPLOY_ORG_ID",
)
print(response.headers.get('X-My-Header'))

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

These methods return an APIResponse object.

The async client returns an AsyncAPIResponse with the same structure, the only difference being awaitable methods for reading the response content.

.with_streaming_response

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.

with client.organizations.with_streaming_response.get(
    "DEPLOY_ORG_ID",
) 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.

Configuring the HTTP client

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 subhosting import Subhosting

client = Subhosting(
    # Or use the `SUBHOSTING_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"),
    ),
)

Managing HTTP resources

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.

Versioning

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.

Requirements

Python 3.7 or higher.