📦 PyAPIq

PyAPIq is a modern Python toolkit for building both synchronous and asynchronous API clients with clean, minimal code and full type safety.

Define endpoints using decorators like @sync_endpoint or @async_endpoint, structure logic with optional namespaces, and leverage Pydantic models for strict request/response validation — all with built-in rate limiting and retries.

Installation

pip install pyapiq

Quickstart

1. Define your models

Use Pydantic to define request and response schemas with full type safety:

from typing import List
from pydantic import BaseModel


class BulkAccountsRequest(BaseModel):
    account_ids: List[str]


class AccountInfoResponse(BaseModel):
    address: str
    balance: int
    status: str


class BulkAccountsResponse(BaseModel):
    accounts: List[AccountInfoResponse]

2. Define your client

Declare your API client by subclassing AsyncClientAPI and annotating endpoints with @async_endpoint:

from pyapiq import AsyncClientAPI, async_endpoint
from pyapiq.types import HTTPMethod


class AsyncTONAPI(AsyncClientAPI):
    base_url = "https://tonapi.io"
    headers = {"Authorization": "Bearer <YOUR_API_KEY>"}
    version = "v2"
    rps = 1
    max_retries = 2

    @async_endpoint(HTTPMethod.GET)
    async def status(self) -> dict:
        """Check API status (GET /status)"""

    @async_endpoint(HTTPMethod.GET)
    async def rates(self, tokens: str, currencies: str) -> dict:
        """Get token rates (GET /rates?tokens={tokens}&currencies={currencies})"""

Notes:

• If you prefer synchronous clients, simply use SyncClientAPI with @sync_endpoint instead.
• For synchronous clients, use SyncClientAPI and @sync_endpoint — interface is fully symmetrical.
• Method arguments are automatically mapped to path and query parameters. The return value is parsed from JSON and returned as a dict, unless a return_as=Model is specified.

3. Group endpoints with namespaces (optional)

Use AsyncAPINamespace to logically organize endpoints under a common prefix (e.g., /accounts):

from pyapiq import AsyncAPINamespace, async_endpoint
from pyapiq.types import HTTPMethod


class Accounts(AsyncAPINamespace):
    namespace = "accounts"

    @async_endpoint(HTTPMethod.GET, path="/{account_id}", return_as=AccountInfoResponse)
    async def info(self, account_id: str) -> AccountInfoResponse:
        """Retrieve account information by account_id (GET /accounts/{account_id})"""

    @async_endpoint(HTTPMethod.POST, path="/_bulk", return_as=BulkAccountsResponse)
    async def bulk_info(self, payload: BulkAccountsRequest) -> BulkAccountsResponse:
        """Retrieve info for multiple accounts with a Pydantic model (POST /accounts/_bulk)"""

    @async_endpoint(HTTPMethod.POST, path="/_bulk")
    async def bulk_info_dict(self, payload: dict) -> dict:
        """Retrieve info for multiple accounts with a dict payload (POST /accounts/_bulk)"""

Then include the namespace in your main client:

class AsyncTONAPI(AsyncClientAPI):
    base_url = "https://tonapi.io"
    headers = {"Authorization": "Bearer <YOUR_API_KEY>"}
    version = "v2"
    rps = 1
    max_retries = 2

    # ... endpoints above ...

    @property
    def accounts(self) -> Accounts:
        return Accounts(self)

Note: The namespace can be defined with or without a leading slash. It will be joined correctly with endpoint paths. Each namespace instance receives the parent client instance automatically.

4. Usage

async def main():
    tonapi = AsyncTONAPI()

    async with tonapi:
        # GET /status
        status = await tonapi.status()
        print(status)

Note: Always use async with to open and close the session properly. All retries, throttling, and connection reuse are handled under the hood.

API Configuration

All settings are defined as class attributes on your client class:

Note: The version field is automatically prefixed to all endpoint paths (e.g. /v2/accounts/...). Rate limiting and retries are handled transparently and apply only per-client instance.

Endpoints

• Use @async_endpoint(method, path=..., return_as=...) to declare each endpoint.

• All method arguments are automatically mapped:

  • Scalars → query/path parameters
  • dict or Pydantic models → request body

• return_as=Model lets you parse responses into Pydantic models.

• If omitted, response is returned as dict.

Note: If path is omitted, the method name becomes the endpoint path (e.g. rates → /rates). You can define both flat and namespaced methods together.

Notes

• Fully asynchronous: all clients and endpoints require async with.
• Zero boilerplate: request building, error handling, retries, and throttling are automatic.
• Namespaces help organize large APIs, but are optional.
• Both dicts and Pydantic models are supported in request payloads.
• Great for building typed SDKs or internal tools.

Contribution

We welcome your contributions! If you find a bug or have an idea, please open an issue or submit a pull request.

License

Distributed under the MIT License. Use freely for commercial or personal projects.