raindrop-query 0.1.5

Official Python SDK for the Raindrop Query API

raindrop-query

Official Python SDK for the Raindrop Query API.

Summary

Raindrop Query API (Beta): API for querying Signals, Events, Users, and Conversations data.

Table of Contents

• raindrop-query
  • 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
  • Support

SDK Installation

The SDK can be installed with pip or uv.

PIP

pip install raindrop-query

uv

uv add raindrop-query

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 raindrop-query 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 = ">=3.10"
# dependencies = [
#     "raindrop-query",
# ]
# ///

from raindrop_query import RaindropQuery

sdk = RaindropQuery(
  # 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 raindrop_query import RaindropQuery


with RaindropQuery(
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:

    res = rq_client.signals.list(limit=50, order_by="-timestamp")

    # Handle response
    print(res)

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

# Asynchronous Example
import asyncio
from raindrop_query import RaindropQuery

async def main():

    async with RaindropQuery(
        api_key="<YOUR_BEARER_TOKEN_HERE>",
    ) as rq_client:

        res = await rq_client.signals.list_async(limit=50, order_by="-timestamp")

        # Handle response
        print(res)

asyncio.run(main())

Authentication

Per-Client Security Schemes

This SDK supports the following security scheme globally:

Name	Type	Scheme
api_key	http	HTTP Bearer

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

from raindrop_query import RaindropQuery


with RaindropQuery(
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:

    res = rq_client.signals.list(limit=50, order_by="-timestamp")

    # Handle response
    print(res)

Available Resources and Operations

Available methods

Conversations

• list - List conversations
• get - Get conversation details

Events

• list - List events
• search - Search events (GET)
• count - Count events
• timeseries - Get event timeseries
• facets - Get event facets
• get - Get event details

SignalGroups

• list - List all signal groups
• get - Get signal group details
• list_signals - List signals in group

Signals

• list - List all signals
• get - Get signal details

Traces

• list - List traces for an event

Users

• list - List users
• get - Get user details

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 raindrop_query import RaindropQuery
from raindrop_query.utils import BackoffStrategy, RetryConfig


with RaindropQuery(
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:

    res = rq_client.signals.list(limit=50, order_by="-timestamp",
        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 raindrop_query import RaindropQuery
from raindrop_query.utils import BackoffStrategy, RetryConfig


with RaindropQuery(
    retry_config=RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False),
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:

    res = rq_client.signals.list(limit=50, order_by="-timestamp")

    # Handle response
    print(res)

Error Handling

RaindropQueryError 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 raindrop_query import RaindropQuery, errors


with RaindropQuery(
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:
    res = None
    try:

        res = rq_client.signals.list(limit=50, order_by="-timestamp")

        # Handle response
        print(res)


    except errors.RaindropQueryError 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.SignalsListUnauthorizedError):
            print(e.data.error)  # models.SignalsListError

Error Classes

Primary error:

• RaindropQueryError: The base class for HTTP error responses.

Less common errors (20)

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 RaindropQueryError:

• EventsSearchBadRequestError: Invalid request (e.g., date range exceeds maximum). Status code 400. Applicable to 1 of 16 methods.*
• EventsFacetsBadRequestError: Invalid field name. Status code 400. Applicable to 1 of 16 methods.*
• TracesListBadRequestError: Bad request (missing event_id). Status code 400. Applicable to 1 of 16 methods.*
• SignalsListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• SignalGroupsListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• EventsListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• UsersListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• ConversationsListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• TracesListUnauthorizedError: Unauthorized. Status code 401. Applicable to 1 of 16 methods.*
• SignalsGetNotFoundError: Signal not found. Status code 404. Applicable to 1 of 16 methods.*
• SignalGroupsGetNotFoundError: Signal group not found. Status code 404. Applicable to 1 of 16 methods.*
• SignalGroupsListSignalsNotFoundError: Signal group not found. Status code 404. Applicable to 1 of 16 methods.*
• EventsGetNotFoundError: Event not found. Status code 404. Applicable to 1 of 16 methods.*
• UsersGetNotFoundError: User not found. Status code 404. Applicable to 1 of 16 methods.*
• ConversationsGetNotFoundError: Conversation not found. Status code 404. Applicable to 1 of 16 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

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 raindrop_query import RaindropQuery


with RaindropQuery(
    server_url="https://query.raindrop.ai",
    api_key="<YOUR_BEARER_TOKEN_HERE>",
) as rq_client:

    res = rq_client.signals.list(limit=50, order_by="-timestamp")

    # 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 raindrop_query import RaindropQuery
import httpx

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

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

from raindrop_query import RaindropQuery
from raindrop_query.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 = RaindropQuery(async_client=CustomClient(httpx.AsyncClient()))

Resource Management

The RaindropQuery 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 raindrop_query import RaindropQuery
def main():

    with RaindropQuery(
        api_key="<YOUR_BEARER_TOKEN_HERE>",
    ) as rq_client:
        # Rest of application here...


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

    async with RaindropQuery(
        api_key="<YOUR_BEARER_TOKEN_HERE>",
    ) as rq_client:
        # 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 raindrop_query import RaindropQuery
import logging

logging.basicConfig(level=logging.DEBUG)
s = RaindropQuery(debug_logger=logging.getLogger("raindrop_query"))

Development

Maturity

This SDK is in beta. We recommend pinning to a specific version.

Support

For questions or issues, contact [e-mail]