lambdadb 0.5.1

Python Client SDK Generated by Speakeasy.

LambdaDB Python SDK

Developer-friendly & type-safe Python SDK specifically catered to leverage LambdaDB API.

Summary

LambdaDB API: LambdaDB Open API Spec

Table of Contents

• LambdaDB Python SDK
  • SDK Installation
  • IDE Support
  • SDK Example Usage
  • Authentication
  • Available Resources and Operations
  • Retries
  • Error Handling
  • Server Selection
  • Custom HTTP Client
  • Resource Management
  • Debugging
• Development
  • Maturity
  • Contributions

SDK Installation

[!NOTE] Python version upgrade policy

Once a Python version reaches its official end of life date, a 3-month grace period is provided for users to upgrade. Following this grace period, the minimum python version supported in the SDK will be updated.

The SDK can be installed with either pip or poetry package managers.

PIP

PIP is the default package installer for Python, enabling easy installation and management of packages from PyPI via the command line.

pip install lambdadb

Poetry

Poetry is a modern tool that simplifies dependency management and package publishing by using a single pyproject.toml file to handle project metadata and dependencies.

poetry add lambdadb

Shell and script usage with uv

You can use this SDK in a Python shell with uv and the uvx command that comes with it like so:

uvx --from lambdadb python

It's also possible to write a standalone Python script without needing to set up a whole project like so:

#!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.9"
# dependencies = [
#     "lambdadb",
# ]
# ///

from lambdadb import LambdaDB

sdk = LambdaDB(
  # SDK arguments
)

# Rest of script here...

Once that is saved to a file, you can run it with uv run script.py where script.py can be replaced with the actual file name.

IDE Support

PyCharm

Generally, the SDK will work well with most IDEs out of the box. However, when using PyCharm, you can enjoy much better integration with Pydantic by installing an additional plugin.

• PyCharm Pydantic Plugin

SDK Example Usage

Example

# Synchronous Example
from lambdadb import LambdaDB


with LambdaDB(
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list()

    # Handle response
    print(res)

The same SDK client can also be used to make asychronous requests by importing asyncio.

# Asynchronous Example
import asyncio
from lambdadb import LambdaDB

async def main():

    async with LambdaDB(
        project_api_key="<YOUR_PROJECT_API_KEY>",
    ) as lambda_db:

        res = await lambda_db.collections.list_async()

        # Handle response
        print(res)

asyncio.run(main())

Authentication

Per-Client Security Schemes

This SDK supports the following security scheme globally:

Name	Type	Scheme	Environment Variable
project_api_key	apiKey	API key	LAMBDADB_PROJECT_API_KEY

To authenticate with the API the project_api_key parameter must be set when initializing the SDK client instance. For example:

from lambdadb import LambdaDB


with LambdaDB(
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list()

    # Handle response
    print(res)

Available Resources and Operations

Available methods

collections

• list - List all collections in an existing project.
• create - Create a collection.
• delete - Delete an existing collection.
• get - Get metadata of an existing collection.
• update - Configure a collection.
• query - Search a collection with a query and return the most similar documents.

collections.docs

• upsert - Upsert documents into a collection. Note that the maximum supported payload size is 6MB.
• get_bulk_upsert - Request required info to upload documents.
• bulk_upsert - Bulk upsert documents into a collection. Note that the maximum supported object size is 200MB.
• update - Update documents in a collection. Note that the maximum supported payload size is 6MB.
• delete - Delete documents by document IDs or query filter from a collection.
• fetch - Lookup and return documents by document IDs from a collection.

Retries

Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.

To change the default retry strategy for a single API call, simply provide a RetryConfig object to the call:

from lambdadb import LambdaDB
from lambdadb.utils import BackoffStrategy, RetryConfig


with LambdaDB(
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list(,
        RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False))

    # Handle response
    print(res)

If you'd like to override the default retry strategy for all operations that support retries, you can use the retry_config optional parameter when initializing the SDK:

from lambdadb import LambdaDB
from lambdadb.utils import BackoffStrategy, RetryConfig


with LambdaDB(
    retry_config=RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False),
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list()

    # Handle response
    print(res)

Error Handling

LambdaDBError is the base class for all HTTP error responses. It has the following properties:

Property	Type	Description
err.message	str	Error message
err.status_code	int	HTTP response status code eg 404
err.headers	httpx.Headers	HTTP response headers
err.body	str	HTTP body. Can be empty string if no body is returned.
err.raw_response	httpx.Response	Raw HTTP response
err.data		Optional. Some errors may contain structured data. See Error Classes.

Example

from lambdadb import LambdaDB, errors


with LambdaDB(
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:
    res = None
    try:

        res = lambda_db.collections.list()

        # Handle response
        print(res)


    except errors.LambdaDBError as e:
        # The base class for HTTP error responses
        print(e.message)
        print(e.status_code)
        print(e.body)
        print(e.headers)
        print(e.raw_response)

        # Depending on the method different errors may be thrown
        if isinstance(e, errors.UnauthenticatedError):
            print(e.data.message)  # Optional[str]

Error Classes

Primary errors:

• LambdaDBError: The base class for HTTP error responses.
  • UnauthenticatedError: Unauthenticated. Status code 401.
  • TooManyRequestsError: Too many requests. Status code 429.
  • InternalServerError: Internal server error. Status code 500.
  • ResourceNotFoundError: Resource not found. Status code 404. *

Less common errors (7)

Network errors:

• httpx.RequestError: Base class for request errors.
  • httpx.ConnectError: HTTP client was unable to make a request to a server.
  • httpx.TimeoutException: HTTP request timed out.

Inherit from LambdaDBError:

• BadRequestError: Bad request. Status code 400. Applicable to 8 of 12 methods.*
• ResourceAlreadyExistsError: Resource already exists. Status code 409. Applicable to 1 of 12 methods.*
• ResponseValidationError: Type mismatch between the response data and the expected Pydantic model. Provides access to the Pydantic validation error via the cause attribute.

* Check the method documentation to see if the error is applicable.

Server Selection

Server Variables

The default server https://{baseUrl} contains variables and is set to https://api.lambdadb.com/projects/default by default. To override default values, the following parameters are available when initializing the SDK client instance:

Variable	Parameter	Default	Description
baseUrl	base_url: str	"api.lambdadb.com/projects/default"	The base URL of the API

Example

from lambdadb import LambdaDB


with LambdaDB(
    base_url="https://functional-jury.net/"
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list()

    # Handle response
    print(res)

Override Server URL Per-Client

The default server can be overridden globally by passing a URL to the server_url: str optional parameter when initializing the SDK client instance. For example:

from lambdadb import LambdaDB


with LambdaDB(
    server_url="https://api.lambdadb.com/projects/default",
    project_api_key="<YOUR_PROJECT_API_KEY>",
) as lambda_db:

    res = lambda_db.collections.list()

    # Handle response
    print(res)

Custom HTTP Client

The Python SDK makes API calls using the httpx HTTP library. In order to provide a convenient way to configure timeouts, cookies, proxies, custom headers, and other low-level configuration, you can initialize the SDK client with your own HTTP client instance. Depending on whether you are using the sync or async version of the SDK, you can pass an instance of HttpClient or AsyncHttpClient respectively, which are Protocol's ensuring that the client has the necessary methods to make API calls. This allows you to wrap the client with your own custom logic, such as adding custom headers, logging, or error handling, or you can just pass an instance of httpx.Client or httpx.AsyncClient directly.

For example, you could specify a header for every request that this sdk makes as follows:

from lambdadb import LambdaDB
import httpx

http_client = httpx.Client(headers={"x-custom-header": "someValue"})
s = LambdaDB(client=http_client)

or you could wrap the client with your own custom logic:

from lambdadb import LambdaDB
from lambdadb.httpclient import AsyncHttpClient
import httpx

class CustomClient(AsyncHttpClient):
    client: AsyncHttpClient

    def __init__(self, client: AsyncHttpClient):
        self.client = client

    async def send(
        self,
        request: httpx.Request,
        *,
        stream: bool = False,
        auth: Union[
            httpx._types.AuthTypes, httpx._client.UseClientDefault, None
        ] = httpx.USE_CLIENT_DEFAULT,
        follow_redirects: Union[
            bool, httpx._client.UseClientDefault
        ] = httpx.USE_CLIENT_DEFAULT,
    ) -> httpx.Response:
        request.headers["Client-Level-Header"] = "added by client"

        return await self.client.send(
            request, stream=stream, auth=auth, follow_redirects=follow_redirects
        )

    def build_request(
        self,
        method: str,
        url: httpx._types.URLTypes,
        *,
        content: Optional[httpx._types.RequestContent] = None,
        data: Optional[httpx._types.RequestData] = None,
        files: Optional[httpx._types.RequestFiles] = None,
        json: Optional[Any] = None,
        params: Optional[httpx._types.QueryParamTypes] = None,
        headers: Optional[httpx._types.HeaderTypes] = None,
        cookies: Optional[httpx._types.CookieTypes] = None,
        timeout: Union[
            httpx._types.TimeoutTypes, httpx._client.UseClientDefault
        ] = httpx.USE_CLIENT_DEFAULT,
        extensions: Optional[httpx._types.RequestExtensions] = None,
    ) -> httpx.Request:
        return self.client.build_request(
            method,
            url,
            content=content,
            data=data,
            files=files,
            json=json,
            params=params,
            headers=headers,
            cookies=cookies,
            timeout=timeout,
            extensions=extensions,
        )

s = LambdaDB(async_client=CustomClient(httpx.AsyncClient()))

Resource Management

The LambdaDB class implements the context manager protocol and registers a finalizer function to close the underlying sync and async HTTPX clients it uses under the hood. This will close HTTP connections, release memory and free up other resources held by the SDK. In short-lived Python programs and notebooks that make a few SDK method calls, resource management may not be a concern. However, in longer-lived programs, it is beneficial to create a single SDK instance via a context manager and reuse it across the application.

from lambdadb import LambdaDB
def main():

    with LambdaDB(
        project_api_key="<YOUR_PROJECT_API_KEY>",
    ) as lambda_db:
        # Rest of application here...


# Or when using async:
async def amain():

    async with LambdaDB(
        project_api_key="<YOUR_PROJECT_API_KEY>",
    ) as lambda_db:
        # Rest of application here...

Debugging

You can setup your SDK to emit debug logs for SDK requests and responses.

You can pass your own logger class directly into your SDK.

from lambdadb import LambdaDB
import logging

logging.basicConfig(level=logging.DEBUG)
s = LambdaDB(debug_logger=logging.getLogger("lambdadb"))

You can also enable a default debug logger by setting an environment variable LAMBDADB_DEBUG to true.

Development

Maturity

This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.

Contributions

While we value open-source contributions to this SDK, this library is generated programmatically. Any manual changes added to internal files will be overwritten on the next generation. We look forward to hearing your feedback. Feel free to open a PR or an issue with a proof of concept and we'll do our best to include it in a future release.