# TypeScript and Python SDKs: News Search API

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OFFICIAL SDKs · v0.1

# TypeScript and Python SDKs

Typed clients that handle authentication, retries, paging and polling for you. Both are MIT-licensed.

**Publishing soon**

The packages aren't on npm and PyPI yet. Until they are, call the REST API directly: every example in the [quickstart](/docs/quickstart) and [API reference](/docs/reference/searchArticles) works without an SDK.

## Install

TypeScript needs Node 18+ (or Deno, Bun or an edge runtime) and has no runtime dependencies. Python needs 3.9+ and uses httpx and Pydantic v2.

```
npm install @newssearchapi/sdk
```

```
pip install newssearchapi
```

## First request

Read the key from an environment variable, never from source code.

```
import { NewsSearchAPI } from "@newssearchapi/sdk";

const news = new NewsSearchAPI({ apiKey: process.env.NEWSSEARCHAPI_API_KEY! });

const { data, meta } = await news.articles.search({ q: "climate summit", page_size: 10 });
for (const article of data.articles) console.log(article.title);
console.log("Requests left this period:", meta.quota.remaining);

const { data: one } = await news.articles.get(data.articles[0].id);
```

```
import os
from newssearchapi import NewsSearchAPI

with NewsSearchAPI(api_key=os.environ["NEWSSEARCHAPI_API_KEY"]) as news:
    result = news.articles.search({"q": "climate summit", "page_size": 10})
    for article in result.data.articles:
        print(article.title)
    print("Requests left this period:", result.meta.quota_remaining)

    one = news.articles.get(result.data.articles[0].id).data.article
```

Article `content` is plain text. Every plan returns metadata, a safe excerpt of about 200 characters with `contentTruncated: true`, and a link to the original article.

You can set `baseUrl`, `timeoutMs`, `maxRetries` or a custom `fetch` in the TypeScript constructor. Python also has `AsyncNewsSearchAPI` with the same methods as awaitables.

## Errors and retries

Failed requests raise `NewsSearchAPIError` with the HTTP status, API [error code](/docs/errors), message and request ID. Network errors, `429` and `5xx` responses are retried automatically with exponential backoff and jitter, honouring `Retry-After`. Other `4xx` errors are never retried.

```
import { NewsSearchAPI, NewsSearchAPIError } from "@newssearchapi/sdk";

try {
  await news.articles.search({ q: "elections", page_size: 500 });
} catch (error) {
  if (error instanceof NewsSearchAPIError) {
    console.error(error.status, error.code, error.message, error.requestId);
  } else throw error;
}
```

```
from newssearchapi import NewsSearchAPIError

try:
    news.articles.search({"q": "elections", "page_size": 500})
except NewsSearchAPIError as error:
    print(error.status, error.code, error.message, error.request_id)
```

## Paging

`iterate` walks every page for you, up to the API's [10,000-result window](/docs/pagination).

```
for await (const article of news.articles.iterate({ q: "semiconductors", page_size: 50 })) {
  console.log(article.publishedAt, article.title);
}
```

```
for article in news.articles.iterate({"q": "semiconductors", "page_size": 50}):
    print(article.publishedAt, article.title)
```

## Polling for new articles

The poller uses `indexed_from` with `sort=indexed_desc` and yields each article as it's indexed. `indexedAt` is the time that article version was last indexed; persist the latest value and restart from it with a small overlap. See [Keep a RAG index fresh](/docs/guides/rag).

```
const stop = new AbortController();
for await (const article of news.articles.pollIndexed({ since: lastIndexedAt, q: "climate", intervalMs: 60_000, signal: stop.signal })) {
  await vectorStore.upsert(article.id, article.content, { indexedAt: article.indexedAt });
}
```

```
for article in news.articles.poll_indexed(since=last_indexed_at, q="climate", interval_seconds=60):
    vector_store.upsert(article.id, article.content, indexed_at=article.indexedAt)
```

## AI tool helpers

Ready-made tool definitions for OpenAI (Chat Completions and Responses) and Anthropic, plus a dispatcher that runs the model's tool calls against the API. Python also offers optional LangChain and LlamaIndex wrappers (`pip install "newssearchapi[langchain]"`).

```
import { openAITools, anthropicTools, handleToolCall } from "@newssearchapi/sdk/tools";

// Pass openAITools / anthropicTools to your model, then execute its tool calls:
const result = await handleToolCall(call.name, call.arguments, news);
```

```
from newssearchapi.tools import openai_tools, anthropic_tools, handle_tool_call

# Pass openai_tools / anthropic_tools to your model, then execute its tool calls:
result = handle_tool_call(call.name, call.arguments, news)
```