braintrust-api 0.4.0

Description:

braintrustapi 0.4.0

Braintrust Python API library

The Braintrust Python library provides convenient access to the Braintrust 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.
It is generated with Stainless.
Documentation
The REST API documentation can be found on www.braintrustdata.com. The full API of this library can be found in api.md.
Installation
# install from PyPI
pip install braintrust-api

Usage
The full API of this library can be found in api.md.
import os
from braintrust_api import Braintrust

client = Braintrust(
# This is the default and can be omitted
api_key=os.environ.get("BRAINTRUST_API_KEY"),
)

project = client.projects.create(
name="foobar",
)
print(project.id)

While you can provide an api_key keyword argument,
we recommend using python-dotenv
to add BRAINTRUST_API_KEY="My API Key" to your .env file
so that your API Key is not stored in source control.
Async usage
Simply import AsyncBraintrust instead of Braintrust and use await with each API call:
import os
import asyncio
from braintrust_api import AsyncBraintrust

client = AsyncBraintrust(
# This is the default and can be omitted
api_key=os.environ.get("BRAINTRUST_API_KEY"),
)


async def main() -> None:
project = await client.projects.create(
name="foobar",
)
print(project.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 Braintrust API are paginated.
This library provides auto-paginating iterators with each list response, so you do not have to request successive pages manually:
from braintrust_api import Braintrust

client = Braintrust()

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

Or, asynchronously:
import asyncio
from braintrust_api import AsyncBraintrust

client = AsyncBraintrust()


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


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.projects.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.objects)}")

# Remove `await` for non-async usage.

Or just work directly with the returned data:
first_page = await client.projects.list()

print(f"next page cursor: {first_page.starting_after}") # => "next page cursor: ..."
for project in first_page.objects:
print(project.id)

# 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 braintrust_api.APIConnectionError is raised.
When the API returns a non-success status code (that is, 4xx or 5xx
response), a subclass of braintrust_api.APIStatusError is raised, containing status_code and response properties.
All errors inherit from braintrust_api.APIError.
import braintrust_api
from braintrust_api import Braintrust

client = Braintrust()

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

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

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

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 braintrust_api import Braintrust

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

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

# Override per-request:
client.with_options(timeout=5.0).projects.create(
name="foobar",
)

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 BRAINTRUST_LOG to debug.
$ export BRAINTRUST_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 braintrust_api import Braintrust

client = Braintrust()
response = client.projects.with_raw_response.create(
name="foobar",
)
print(response.headers.get('X-My-Header'))

project = response.parse() # get the object that `projects.create()` would have returned
print(project.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.projects.with_streaming_response.create(
name="foobar",
) 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 braintrust_api import Braintrust, DefaultHttpxClient

client = Braintrust(
# Or use the `BRAINTRUST_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"),
),
)

You can also customize the client on a per-request basis by using with_options():
client.with_options(http_client=DefaultHttpxClient(...))

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:

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