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Cloudflare Python API library

The Cloudflare Python library provides convenient access to the Cloudflare 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.

Documentation

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

Installation

# install from PyPI
pip install cloudflare

Usage

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

import os
from cloudflare import Cloudflare

client = Cloudflare(
    # This is the default and can be omitted
    api_email=os.environ.get("CLOUDFLARE_EMAIL"),
    # This is the default and can be omitted
    api_key=os.environ.get("CLOUDFLARE_API_KEY"),
)

zone = client.zones.create(
    account={"id": "023e105f4ecef8ad9ca31a8372d0c353"},
    name="example.com",
    type="full",
)
print(zone.id)

While you can provide a api_email keyword argument, we recommend using python-dotenv to add CLOUDFLARE_EMAIL="user@example.com" to your .env file so that your API Email is not stored in source control.

Async usage

Simply import AsyncCloudflare instead of Cloudflare and use await with each API call:

import os
import asyncio
from cloudflare import AsyncCloudflare

client = AsyncCloudflare(
    # This is the default and can be omitted
    api_email=os.environ.get("CLOUDFLARE_EMAIL"),
    # This is the default and can be omitted
    api_key=os.environ.get("CLOUDFLARE_API_KEY"),
)


async def main() -> None:
    zone = await client.zones.create(
        account={"id": "023e105f4ecef8ad9ca31a8372d0c353"},
        name="example.com",
        type="full",
    )
    print(zone.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 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.

Pagination

List methods in the Cloudflare API are paginated.

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

import cloudflare

client = Cloudflare()

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 cloudflare

client = AsyncCloudflare()


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.result)}")

# Remove `await` for non-async usage.

Or just work directly with the returned data:

first_page = await client.accounts.list()
for account in first_page.result:
    print(account)

# Remove `await` for non-async usage.

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 cloudflare.APIConnectionError is raised.

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

All errors inherit from cloudflare.APIError.

import cloudflare
from cloudflare import Cloudflare

client = Cloudflare()

try:
    client.zones.get(
        zone_id="023e105f4ecef8ad9ca31a8372d0c353",
    )
except cloudflare.APIConnectionError as e:
    print("The server could not be reached")
    print(e.__cause__)  # an underlying Exception, likely raised within httpx.
except cloudflare.RateLimitError as e:
    print("A 429 status code was received; we should back off a bit.")
except cloudflare.APIStatusError as e:
    print("Another non-200-range status code was received")
    print(e.status_code)
    print(e.response)

Error codes are as followed:

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 cloudflare import Cloudflare

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

# Or, configure per-request:
client.with_options(max_retries=5).zones.get(
    zone_id="023e105f4ecef8ad9ca31a8372d0c353",
)

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 cloudflare import Cloudflare

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

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

# Override per-request:
client.with_options(timeout=5.0).zones.edit(
    zone_id="023e105f4ecef8ad9ca31a8372d0c353",
)

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 CLOUDFLARE_LOG to debug.

$ export CLOUDFLARE_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 cloudflare import Cloudflare

client = Cloudflare()
response = client.zones.with_raw_response.create(
    account={
        "id": "023e105f4ecef8ad9ca31a8372d0c353"
    },
    name="example.com",
    type="full",
)
print(response.headers.get('X-My-Header'))

zone = response.parse()  # get the object that `zones.create()` would have returned
print(zone.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.zones.with_streaming_response.create(
    account={"id": "023e105f4ecef8ad9ca31a8372d0c353"},
    name="example.com",
    type="full",
) 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.

Making custom/undocumented requests

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.

Undocumented endpoints

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"))

Undocumented request params

If you want to explicitly send an extra param, you can do so with the extra_query, extra_body, and extra_headers request options.

Undocumented response properties

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.

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

from cloudflare import Cloudflare, DefaultHttpxClient

client = Cloudflare(
    # Or use the `CLOUDFLARE_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"),
    ),
)

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.

Semantic 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.

[!WARNING] In addition to the above, changes to type names, structure or methods may occur as we stabilise the automated codegen pipeline. This will be removed in the future once we are further along and the service owner OpenAPI schemas have reached a higher maturity level where changes are not as constant. If this isn't suitable for your project, we recommend pinning to a known version or using the previous major version.

Requirements

Python 3.7 or higher.