### Install StripFeed Python SDK

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Installs the StripFeed Python SDK using pip. This is the first step to using the SDK in your Python projects.

```bash
pip install stripfeed
```

--------------------------------

### Quick Start: Fetch URL Content with StripFeed SDK

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Demonstrates the basic usage of the StripFeed Python SDK to fetch content from a URL. It shows how to initialize the SDK with an API key and retrieve the Markdown content along with token usage statistics.

```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

# Full result with metadata
result = sf.fetch("https://news.ycombinator.com")
print(result["markdown"])
print(f"Tokens: {result['tokens']} (saved {result['savingsPercent']}%) ")

# Just the Markdown string
md = sf.fetch_markdown("https://news.ycombinator.com")
```

--------------------------------

### Install StripFeed Python SDK in Development Mode

Source: https://github.com/stripfeed/stripfeed-python/blob/main/CLAUDE.md

Installs the StripFeed Python SDK in development mode, including necessary dependencies for testing and development. This command is typically run from the project's root directory.

```bash
pip install -e ".[dev]"
```

--------------------------------

### Error Handling for StripFeed API Requests

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Provides an example of how to handle potential `StripFeedError` exceptions that may occur during API calls. It demonstrates using a try-except block to catch errors and print the status code and error message.

```python
from stripfeed import StripFeed, StripFeedError

try:
    result = sf.fetch("https://example.com")
except StripFeedError as e:
    print(f"API error {e.status}: {e}")
```

--------------------------------

### fetch_markdown() - Get Only Markdown String

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

A convenience method that fetches a URL and returns only the clean Markdown string, omitting all metadata.

```APIDOC
## fetch_markdown() - Get Only Markdown String

Convenience method that fetches a URL and returns only the clean Markdown string, without metadata. Ideal when you just need the content.

### Method
GET

### Endpoint
`/v1/fetch` (internally uses fetch with format='markdown')

### Parameters
#### Query Parameters
- **url** (string) - Required - The URL to fetch and convert.
- **selector** (string) - Optional - CSS selector to extract specific elements (Pro plan).
- **cache** (boolean) - Optional - Bypass cache for fresh content (default: true).
- **ttl** (integer) - Optional - Custom cache TTL in seconds (max: 86400).
- **max_tokens** (integer) - Optional - Truncate output to fit token budget.

### Request Example
```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

# Get just the Markdown string
md = sf.fetch_markdown("https://news.ycombinator.com")
print(md)  # "# Hacker News\n\n1. [Article Title](https://...)..."

# With options
md = sf.fetch_markdown(
    "https://docs.anthropic.com",
    selector="article",
    max_tokens=3000,
    cache=False,
)
```

### Response
#### Success Response (200)
- **markdown** (string) - Clean Markdown content.

#### Response Example
```
# Hacker News

1. [Article Title](https://...)
...
```
```

--------------------------------

### Batch Fetch URLs with StripFeed SDK (Pro Plan)

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Demonstrates the `sf.batch()` method for fetching multiple URLs concurrently, available on the Pro plan. It shows how to pass a list of URLs or dictionaries with URL and selector options, and how to iterate through the results to access token usage per URL.

```python
result = sf.batch(
    [
        "https://example.com",
        {"url": "https://docs.anthropic.com", "selector": "article"},
    ],
    model="claude-sonnet-4-6",
)

for item in result["results"]:
    print(f"{item['url']}: {item['tokens']} tokens")
```

--------------------------------

### Client Initialization

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Initialize the StripFeed client with your API key. Optional configurations for custom base URL and timeout are also supported.

```APIDOC
## Client Initialization

Initialize the StripFeed client with your API key and optional configuration for custom base URL and timeout settings.

```python
from stripfeed import StripFeed

# Basic initialization
sf = StripFeed("sf_live_your_api_key")

# With custom configuration
sf = StripFeed(
    "sf_live_your_api_key",
    base_url="https://custom.api/v1",  # Optional custom endpoint
    timeout=10,                         # Optional timeout in seconds (default: 30)
)
```
```

--------------------------------

### Configure StripFeed SDK Client

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Demonstrates how to initialize the `StripFeed` client with custom configurations, including an alternative `base_url` for the API endpoint and a custom `timeout` value for requests. The default timeout is 30 seconds.

```python
sf = StripFeed(
    "sf_live_your_api_key",
    base_url="https://custom.api/v1",
    timeout=10,
)
```

--------------------------------

### Configure StripFeed Fetch Options

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Illustrates how to use various options with the `sf.fetch()` method, such as specifying a CSS selector, choosing an output format, tracking model costs, bypassing cache, setting a custom cache TTL, and truncating output to a maximum token count.

```python
result = sf.fetch(
    "https://example.com",
    selector="article",
    format="json",
    model="claude-sonnet-4-6",
    cache=False,
    ttl=7200,
    max_tokens=5000,
)
```

--------------------------------

### Initialize StripFeed Client

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Initializes the StripFeed client with an API key. Optional parameters allow for custom API base URLs and request timeouts.

```python
from stripfeed import StripFeed

# Basic initialization
sf = StripFeed("sf_live_your_api_key")

# With custom configuration
sf = StripFeed(
    "sf_live_your_api_key",
    base_url="https://custom.api/v1",  # Optional custom endpoint
    timeout=10,                         # Optional timeout in seconds (default: 30)
)
```

--------------------------------

### Batch Fetch with String URLs

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Demonstrates how to perform a batch fetch of web content using a list of string URLs and process the results.

```APIDOC
## POST /batch

### Description
Fetches content from multiple URLs in a batch. Supports basic string URLs or objects with custom selectors.

### Method
POST

### Endpoint
/batch

### Parameters
#### Query Parameters
- **model** (string) - Optional - Specifies the model to use for processing, useful for tracking costs.

#### Request Body
- **urls** (array) - Required - A list of URLs to fetch. Each item can be a string URL or an object with `url` and `selector` properties.
  - **url** (string) - Required - The URL to fetch.
  - **selector** (string) - Optional - A CSS selector to extract specific content from the page.

### Request Example
```json
{
  "urls": [
    "https://example.com",
    {"url": "https://docs.anthropic.com", "selector": "article"},
    {"url": "https://openai.com/api", "selector": "main"}
  ],
  "model": "claude-sonnet-4-6"
}
```

### Response
#### Success Response (200)
- **total** (integer) - The total number of URLs processed.
- **success** (integer) - The number of URLs successfully fetched.
- **failed** (integer) - The number of URLs that failed to fetch.
- **results** (array) - A list of results for each URL.
  - **url** (string) - The URL that was processed.
  - **status** (integer) - The HTTP status code of the response.
  - **tokens** (integer) - The number of tokens generated for the content.
  - **savingsPercent** (float) - The percentage of savings achieved.
  - **error** (string) - An error message if the fetch failed.

#### Response Example
```json
{
  "total": 3,
  "success": 2,
  "failed": 1,
  "results": [
    {
      "url": "https://example.com",
      "status": 200,
      "tokens": 1500,
      "savingsPercent": 10.5
    },
    {
      "url": "https://docs.anthropic.com",
      "status": 200,
      "tokens": 3000,
      "savingsPercent": 15.2
    },
    {
      "url": "https://openai.com/api",
      "status": 404,
      "error": "Not Found"
    }
  ]
}
```
```

--------------------------------

### Run Tests for StripFeed Python SDK

Source: https://github.com/stripfeed/stripfeed-python/blob/main/CLAUDE.md

Executes the test suite for the StripFeed Python SDK using pytest. This command verifies the functionality and stability of the SDK.

```bash
pytest
```

--------------------------------

### Fetch URL Content in Different Formats (JSON, Text, HTML)

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Shows how to use the `format` parameter in the `sf.fetch()` method to retrieve content in JSON, plain text, or clean HTML. Each format provides specific data fields, including metadata like token counts and processing times.

```python
# Get structured JSON with all metadata fields
result = sf.fetch("https://news.ycombinator.com", format="json")

print(result["markdown"])
print(result["html"])
print(result["text"])
print(result["title"])
print(result["tokens"])
print(result["originalTokens"])
print(result["savingsPercent"])
print(result["cached"])
print(result["fetchMs"])
print(result["truncated"])

# Get plain text with all Markdown formatting stripped
result = sf.fetch("https://news.ycombinator.com", format="text")
print(result["text"])

# Get clean HTML (after Readability extraction)
result = sf.fetch("https://news.ycombinator.com", format="html")
print(result["html"])
```

--------------------------------

### fetch() - Convert URL to Markdown

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Fetches a URL and converts it to clean Markdown with full metadata. Supports various options including CSS selectors, output formats, and caching controls.

```APIDOC
## fetch() - Convert URL to Markdown

Fetches a URL and converts it to clean Markdown with full metadata including token counts, savings percentage, and caching information. Supports multiple output formats and Pro plan features like CSS selectors.

### Method
GET

### Endpoint
`/v1/fetch`

### Parameters
#### Query Parameters
- **url** (string) - Required - The URL to fetch and convert.
- **selector** (string) - Optional - CSS selector to extract specific elements (Pro plan).
- **format** (string) - Optional - Output format: "markdown", "json", "text", "html" (default: "markdown").
- **model** (string) - Optional - AI model ID for cost tracking.
- **cache** (boolean) - Optional - Bypass cache for fresh content (default: true).
- **ttl** (integer) - Optional - Custom cache TTL in seconds (max: 86400).
- **max_tokens** (integer) - Optional - Truncate output to fit token budget.

### Request Example
```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

# Basic fetch with full result
result = sf.fetch("https://news.ycombinator.com")
print(result["markdown"])
print(result["title"])
print(result["tokens"])
print(result["originalTokens"])
print(result["savingsPercent"])
print(result["cached"])
print(result["fetchMs"])

# With all options (Pro plan features)
result = sf.fetch(
    "https://example.com",
    selector="article",           # CSS selector to extract specific elements
    format="json",                # Output format: "markdown", "json", "text", "html"
    model="claude-sonnet-4-6",    # AI model ID for cost tracking
    cache=False,                  # Bypass cache for fresh content
    ttl=7200,                     # Custom cache TTL in seconds (max: 86400)
    max_tokens=5000,              # Truncate output to fit token budget
)

# Check if content was truncated
if result.get("truncated"):
    print("Content was truncated to fit max_tokens limit")
```

### Response
#### Success Response (200)
- **markdown** (string) - Clean Markdown content.
- **title** (string) - Page title.
- **tokens** (integer) - Token count of clean output.
- **originalTokens** (integer) - Token count of original HTML.
- **savingsPercent** (float) - Percentage of tokens saved.
- **cached** (boolean) - True if served from cache.
- **fetchMs** (integer) - Processing time in milliseconds.
- **truncated** (boolean) - True if content was truncated due to `max_tokens`.
- **html** (string) - Clean HTML content (if format is "html" or "json").
- **text** (string) - Plain text content (if format is "text" or "json").

#### Response Example
```json
{
  "markdown": "# Hacker News\n\n1. [Article Title](https://...)...",
  "title": "Hacker News",
  "tokens": 150,
  "originalTokens": 1500,
  "savingsPercent": 90.0,
  "cached": false,
  "fetchMs": 500,
  "truncated": false
}
```
```

--------------------------------

### Output Formats

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Fetch content in different formats including JSON, plain text, and clean HTML, depending on your use case.

```APIDOC
## Output Formats

Fetch content in different formats depending on your use case. The format parameter controls what fields are populated in the response.

### Method
GET

### Endpoint
`/v1/fetch`

### Parameters
#### Query Parameters
- **url** (string) - Required - The URL to fetch and convert.
- **format** (string) - Required - Output format: "markdown", "json", "text", "html".

### Request Example
```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

# JSON format - returns all metadata fields
result = sf.fetch("https://example.com", format="json")
print(result["markdown"])
print(result["html"])
print(result["text"])
print(result["title"])
print(result["tokens"])

# Plain text format - strips all Markdown formatting
result = sf.fetch("https://example.com", format="text")
print(result["text"])  # No headings, bold, links, etc.

# HTML format - returns clean HTML after Readability extraction
result = sf.fetch("https://example.com", format="html")
print(result["html"])  # Clean <article> HTML
```

### Response
#### Success Response (200)
- **markdown** (string) - Clean Markdown content.
- **html** (string) - Clean HTML content (if format is "html" or "json").
- **text** (string) - Plain text content (if format is "text" or "json").
- **title** (string) - Page title.
- **tokens** (integer) - Token count.
- Other metadata fields may be present depending on the format.

#### Response Example (format='json')
```json
{
  "markdown": "# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ncontent freely.",
  "html": "<article><h1>Example Domain</h1><p>This domain is for use in illustrative examples in documents. You may use this content freely.</p></article>",
  "text": "Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this content freely.",
  "title": "Example Domain",
  "tokens": 50,
  "originalTokens": 200,
  "savingsPercent": 75.0,
  "cached": false,
  "fetchMs": 300
}
```
```

--------------------------------

### Fetch URL to Markdown with Metadata

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Fetches content from a URL, converts it to Markdown, and returns comprehensive metadata. Supports various output formats and advanced options like CSS selectors and cache control.

```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")

# Basic fetch with full result
result = sf.fetch("https://news.ycombinator.com")
print(result["markdown"])
print(result["title"])
print(result["tokens"])
print(result["originalTokens"])
print(result["savingsPercent"])
print(result["cached"])
print(result["fetchMs"])

# With all options (Pro plan features)
result = sf.fetch(
    "https://example.com",
    selector="article",           # CSS selector to extract specific elements
    format="json",                # Output format: "markdown", "json", "text", "html"
    model="claude-sonnet-4-6",    # AI model ID for cost tracking
    cache=False,                  # Bypass cache for fresh content
    ttl=7200,                     # Custom cache TTL in seconds (max: 86400)
    max_tokens=5000,              # Truncate output to fit token budget
)

# Check if content was truncated
if result.get("truncated"):
    print("Content was truncated to fit max_tokens limit")
```

--------------------------------

### usage() - Check API Usage

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Queries your current monthly API usage, plan limits, and when the usage counter resets.

```APIDOC
## GET /usage

### Description
Retrieves information about your current API usage, including plan details, requests used, limits, and reset times.

### Method
GET

### Endpoint
/usage

### Parameters
None

### Request Example
```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")
usage = sf.usage()
```

### Response
#### Success Response (200)
- **plan** (string) - The current subscription plan (e.g., "free", "pro").
- **usage** (integer) - The number of requests used this month.
- **limit** (integer) - The monthly request limit for the current plan.
- **remaining** (integer) - The number of requests remaining for the month.
- **resetsAt** (string) - An ISO 8601 formatted timestamp indicating when the usage counter resets.

#### Response Example
```json
{
  "plan": "pro",
  "usage": 1250,
  "limit": 100000,
  "remaining": 98750,
  "resetsAt": "2026-04-01T00:00:00.000Z"
}
```
```

--------------------------------

### Build StripFeed Python SDK Distribution Packages

Source: https://github.com/stripfeed/stripfeed-python/blob/main/CLAUDE.md

Builds the source distribution (sdist) and wheel package for the StripFeed Python SDK. This command is used to prepare the SDK for distribution.

```bash
python -m build
```

--------------------------------

### Check API Usage with StripFeed SDK

Source: https://github.com/stripfeed/stripfeed-python/blob/main/README.md

Shows how to use the `sf.usage()` method to retrieve information about the current API plan, monthly usage, usage limit, and remaining quota. This is useful for monitoring consumption.

```python
usage = sf.usage()
print(f"Plan: {usage['plan']}")
print(f"Used: {usage['usage']} / {usage['limit']}")
print(f"Remaining: {usage['remaining']}")
```

--------------------------------

### Batch Fetch Web Content with Selectors and Model Tracking

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Fetches content from a list of URLs, allowing specific CSS selectors to target content within pages. It also supports tracking costs by specifying the model used for processing.

```python
result = sf.batch(
    [
        "https://example.com",
        {"url": "https://docs.anthropic.com", "selector": "article"},
        {"url": "https://openai.com/api", "selector": "main"},
    ],
    model="claude-sonnet-4-6",  # Track costs per model
)
```

--------------------------------

### Utilize TypedDict Response Types for Autocompletion

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Shows how to import and use `TypedDict` response types exported by the SDK for enhanced IDE autocompletion and static type checking. This improves code quality and maintainability.

```python
from stripfeed import (
    StripFeed,
    StripFeedError,
    FetchResult,
    BatchResult,
    BatchResultItem,
    UsageResult,
)

sf = StripFeed("sf_live_your_api_key")

# Type hints work with responses
result: FetchResult = sf.fetch("https://example.com")
batch_result: BatchResult = sf.batch(["https://a.com", "https://b.com"])
usage: UsageResult = sf.usage()
```

--------------------------------

### Batch Fetch Web Content with String URLs

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Fetches content from a list of URLs in batches. It returns a summary of total, successful, and failed requests, along with detailed results for each URL including token count and savings percentage for successful fetches.

```python
result = sf.batch([
    "https://example.com",
    "https://docs.anthropic.com",
    "https://openai.com/api",
])

print(f"Total: {result['total']}")
print(f"Success: {result['success']}")
print(f"Failed: {result['failed']}")

for item in result["results"]:
    if item.get("status") == 200:
        print(f"{item['url']}: {item['tokens']} tokens, saved {item['savingsPercent']}%")
    else:
        print(f"{item['url']}: Error - {item.get('error')}")
```

--------------------------------

### Fetch Only Markdown String

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

A convenience method to fetch a URL and return only the clean Markdown content as a string, omitting all metadata. Useful for direct content integration.

```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

# Get just the Markdown string
md = sf.fetch_markdown("https://news.ycombinator.com")
print(md)

# With options
md = sf.fetch_markdown(
    "https://docs.anthropic.com",
    selector="article",
    max_tokens=3000,
    cache=False,
)
```

--------------------------------

### batch() - Process Multiple URLs

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Process up to 10 URLs in parallel with a single API call. This feature requires a Pro plan.

```APIDOC
## batch() - Process Multiple URLs

Process up to 10 URLs in parallel with a single API call. Requires Pro plan. Returns aggregated results with success/failure counts.

### Method
POST

### Endpoint
`/v1/batch`

### Parameters
#### Request Body
- **urls** (array of strings) - Required - An array containing up to 10 URLs to process.
- **selector** (string) - Optional - CSS selector to apply to all URLs.
- **format** (string) - Optional - Output format for all URLs: "markdown", "json", "text", "html" (default: "markdown").
- **cache** (boolean) - Optional - Bypass cache for fresh content (default: true).
- **ttl** (integer) - Optional - Custom cache TTL in seconds (max: 86400).
- **max_tokens** (integer) - Optional - Truncate output to fit token budget for all URLs.

### Request Example
```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")

urls_to_process = [
    "https://news.ycombinator.com",
    "https://example.com",
    "https://docs.anthropic.com"
]

try:
    results = sf.batch(urls_to_process, format="json", max_tokens=2000)
    for url, result in results.items():
        if result.get("error"):
            print(f"Error processing {url}: {result['error']}")
        else:
            print(f"Successfully processed {url}: Title - {result.get('title')}, Tokens - {result.get('tokens')}")
except StripFeedError as e:
    print(f"An API error occurred: {e}")
```

### Response
#### Success Response (200)
- **results** (object) - An object where keys are the input URLs and values are the processing results for each URL. Each result object contains the same fields as the `fetch` method response, or an `error` field if processing failed for that specific URL.

#### Response Example
```json
{
  "results": {
    "https://news.ycombinator.com": {
      "markdown": "# Hacker News...",
      "title": "Hacker News",
      "tokens": 150,
      "originalTokens": 1500,
      "savingsPercent": 90.0,
      "cached": false,
      "fetchMs": 500
    },
    "https://example.com": {
      "markdown": "# Example Domain...",
      "title": "Example Domain",
      "tokens": 50,
      "originalTokens": 200,
      "savingsPercent": 75.0,
      "cached": true,
      "fetchMs": 100
    },
    "https://docs.anthropic.com": {
      "error": "Failed to fetch content. Status code: 404"
    }
  }
}
```
```

--------------------------------

### Batch Process Multiple URLs

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Processes up to 10 URLs concurrently in a single API call, requiring a Pro plan subscription. Returns aggregated results, including counts of successful and failed fetches.

```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")


```

--------------------------------

### TypedDict Response Types

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Explains the availability of exported `TypedDict` response types for enhanced IDE autocompletion and type checking.

```APIDOC
## Typed Response Types

### Description
The StripFeed SDK provides exported `TypedDict` classes for its response objects. These enhance developer experience by enabling IDE autocompletion, static type checking, and improved code clarity.

### Available Types
- **FetchResult**: Represents the response structure for the `fetch()` method.
- **BatchResult**: Represents the overall response structure for the `batch()` method.
- **BatchResultItem**: Represents the structure of an individual item within the `BatchResult.results` list.
- **UsageResult**: Represents the response structure for the `usage()` method.

### Method
All SDK methods that return structured data.

### Parameters
None

### Request Example
```python
from stripfeed import (
    StripFeed,
    StripFeedError,
    FetchResult,      # Result from fetch()
    BatchResult,      # Result from batch()
    BatchResultItem,  # Individual item in BatchResult.results
    UsageResult,      # Result from usage()
)

sf = StripFeed("sf_live_your_api_key")

# Type hints work with responses
result: FetchResult = sf.fetch("https://example.com")
batch_result: BatchResult = sf.batch(["https://a.com", "https://b.com"])
usage: UsageResult = sf.usage()

# Accessing typed data
print(result.markdown)
print(batch_result.results[0].url)
print(usage.plan)
```

### Response
#### Success Response
Responses from methods like `fetch()`, `batch()`, and `usage()` will conform to their respective `TypedDict` structures, allowing for type-safe access to data.
```

--------------------------------

### Handle API Errors with StripFeedError

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Demonstrates how to catch and handle `StripFeedError` exceptions raised by the SDK for API-related issues. It provides specific handling for common HTTP status codes like 401, 429, 403, and 502, offering user-friendly messages.

```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")

try:
    result = sf.fetch("https://example.com")
    print(result["markdown"])
except StripFeedError as e:
    if e.status == 401:
        print("Invalid API key")
    elif e.status == 429:
        print("Rate limit exceeded - try again later")
    elif e.status == 403:
        print("Feature requires Pro plan")
    elif e.status == 502:
        print("Target URL unreachable")
    else:
        print(f"API error {e.status}: {e}")

# Handling batch errors gracefully
try:
    result = sf.batch(["https://a.com", "https://b.com"])
    for item in result["results"]:
        if item.get("status") != 200:
            print(f"Failed: {item['url']} - {item.get('error')}")
except StripFeedError as e:
    print(f"Batch request failed: {e}")
```

--------------------------------

### Error Handling

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Details on how the StripFeed SDK handles API errors using `StripFeedError` and provides guidance for different error scenarios.

```APIDOC
## Error Handling

### Description
The StripFeed SDK raises `StripFeedError` exceptions for API-related errors. This section outlines common error statuses and how to handle them, including specific guidance for batch requests.

### Method
All SDK methods that interact with the API (e.g., `fetch`, `batch`).

### Parameters
None

### Request Example (Single Fetch)
```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")

try:
    result = sf.fetch("https://example.com")
    print(result["markdown"])
except StripFeedError as e:
    if e.status == 401:
        print("Invalid API key")
    elif e.status == 429:
        print("Rate limit exceeded - try again later")
    elif e.status == 403:
        print("Feature requires Pro plan")
    elif e.status == 502:
        print("Target URL unreachable")
    else:
        print(f"API error {e.status}: {e}")
```

### Request Example (Batch Fetch)
```python
from stripfeed import StripFeed, StripFeedError

sf = StripFeed("sf_live_your_api_key")

try:
    result = sf.batch(["https://a.com", "https://b.com"])
    for item in result["results"]:
        if item.get("status") != 200:
            print(f"Failed: {item['url']} - {item.get('error')}")
except StripFeedError as e:
    print(f"Batch request failed: {e}")
```

### Response
#### Error Response (StripFeedError)
- **status** (integer) - The HTTP status code of the error.
- **message** (string) - A descriptive error message.

#### Response Example (within `except` block)
```
# For status 401:
Invalid API key

# For status 429:
Rate limit exceeded - try again later

# For a general API error:
API error 500: Internal Server Error
```
```

--------------------------------

### Check API Usage

Source: https://context7.com/stripfeed/stripfeed-python/llms.txt

Queries the StripFeed API to retrieve current monthly usage statistics, including the plan type, requests used, monthly limit, remaining requests, and the timestamp when the usage counter resets.

```python
from stripfeed import StripFeed

sf = StripFeed("sf_live_your_api_key")

usage = sf.usage()
print(f"Plan: {usage['plan']}")           # "free", "pro", etc.
print(f"Used: {usage['usage']}")          # Requests used this month
print(f"Limit: {usage['limit']}")         # Monthly request limit
print(f"Remaining: {usage['remaining']}") # Requests remaining
print(f"Resets: {usage['resetsAt']}")     # ISO timestamp of reset date
```

--------------------------------

### Commit with Specific Author in Git

Source: https://github.com/stripfeed/stripfeed-python/blob/main/CLAUDE.md

Forces a Git commit to use a specific committer name and email, overriding the global Git configuration. This is used to ensure all commits adhere to the project's authoring policy.

```bash
GIT_COMMITTER_NAME="Claude" GIT_COMMITTER_EMAIL="noreply@anthropic.com" git commit --author="Claude <noreply@anthropic.com>" -m "message"
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.