Undetected web-scraping & seamless HTML parsing in Python!
Project description
The Easiest Way to Scrape the Web
Features
- Realistic HTTP Requests:
- Mimics Chrome browser for undetected scraping using curl_cffi
- Automatically rotates User Agents between requests
- Tracks and updates the
Refererheader to simulate realistic request chains - Built-in retry logic for failed requests (e.g. 429, 503, 522)
- Faster and Easier Parsing:
- Extract emails, phone numbers, images, and links from responses
- Automatically extract metadata (title, description, author, etc.) from HTML-based responses
- Seamlessly convert responses into Lxml and BeautifulSoup objects for more parsing
- Easily convert full or specific sections of HTML to Markdown
Install
$ pip install stealth_requests
Table of Contents
- Sending Requests
- Sending Requests With Asyncio
- Accessing Page Metadata
- Extracting Emails, Phone Numbers, Images, and Links
- Extracting HTML Tables
- More Parsing Options
- Converting Responses to Markdown
- Using Proxies
Sending Requests
Stealth-Requests mimics the API of the requests package, allowing you to use it in nearly the same way.
You can send one-off requests like this:
import stealth_requests as requests
resp = requests.get('https://link-here.com')
Or you can use a StealthSession object which will keep track of certain headers for you between requests such as the Referer header.
from stealth_requests import StealthSession
with StealthSession() as session:
resp = session.get('https://link-here.com')
Stealth-Requests has a built-in retry feature that automatically waits 2 seconds and retries the request if it fails due to certain status codes (like 429, 503, etc.).
To enable retries, just pass the number of retry attempts using the retry argument:
import stealth_requests as requests
resp = requests.get('https://link-here.com', retry=3)
Sending Requests With Asyncio
Stealth-Requests supports Asyncio in the same way as the requests package:
from stealth_requests import AsyncStealthSession
async with AsyncStealthSession() as session:
resp = await session.get('https://link-here.com')
Accessing Page Metadata
The response returned from this package is a StealthResponse, which has all of the same methods and attributes as a standard requests response object, with a few added features. One of these extra features is automatic parsing of header metadata from HTML-based responses. The metadata can be accessed from the meta property, which gives you access to the following metadata:
- title:
str | None - author:
str | None - description:
str | None - thumbnail:
str | None - canonical:
str | None - twitter_handle:
str | None - keywords:
tuple[str] | None - robots:
tuple[str] | None
Here's an example of how to get the title of a page:
import stealth_requests as requests
resp = requests.get('https://link-here.com')
print(resp.meta.title)
Extracting Emails, Phone Numbers, Images, and Links
The StealthResponse object includes some helpful properties for extracting common data:
import stealth_requests as requests
resp = requests.get('https://link-here.com')
print(resp.emails)
# Output: ('info@example.com', 'support@example.com')
print(resp.phone_numbers)
# Output: ('+1 (800) 123-4567', '212-555-7890')
print(resp.images)
# Output: ('https://example.com/logo.png', 'https://cdn.example.com/banner.jpg')
print(resp.links)
# Output: ('https://example.com/about', 'https://example.com/contact')
Extracting HTML Tables
The StealthResponse object can parse HTML tables into dictionaries, where each key is a column header and the value is a list of that column's cell values.
For example, given a page with this table:
| Name | Age |
|---|---|
| Jacob | 30 |
| Jake | 25 |
You can extract it like this:
import stealth_requests as requests
resp = requests.get('https://link-here.com')
# Each table becomes a dict: {column_name: [values]}
for table in resp.tables:
print(table)
# Output: {'Name': ['Jacob', 'Jake'], 'Age': ['30', '25']}
Tables without recognizable headers are automatically skipped.
More Parsing Options
To make parsing HTML faster, I've also added two popular parsing packages to Stealth-Requests: Lxml and BeautifulSoup4. To use these add-ons, you need to install the parsers extra:
$ pip install 'stealth_requests[parsers]'
To easily get an Lxml tree, you can use resp.tree() and to get a BeautifulSoup object, use the resp.soup() method.
For simple parsing, I've also added the following convenience methods, from the Lxml package, right into the StealthResponse object:
text_content(): Get all text content in a responsexpath(): Go right to using XPath expressions instead of getting your own Lxml tree.
Converting Responses to Markdown
In some cases, it’s easier to work with a webpage in Markdown format rather than HTML. After making a GET request that returns HTML, you can use the resp.markdown() method to convert the response into a Markdown string, providing a simplified and readable version of the page content!
markdown() has two optional parameters:
content_xpathAn XPath expression, in the form of a string, which can be used to narrow down what text is converted to Markdown. This can be useful if you don't want the header and footer of a webpage to be turned into Markdown.ignore_linksA boolean value that tellsHtml2Textwhether to include links in the Markdown output.
Using Proxies
Stealth-Requests supports proxy usage through a proxies dictionary argument, similar to the standard requests package.
You can pass both HTTP and HTTPS proxy URLs when making a request:
import stealth_requests as requests
proxies = {
"http": "http://username:password@proxyhost:port",
"https": "http://username:password@proxyhost:port",
}
resp = requests.get('https://link-here.com', proxies=proxies)
Contributing
Contributions are welcome! Feel free to open issues or submit pull requests.
Before submitting a pull request, please format your code with Ruff: uvx ruff format stealth_requests/
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file stealth_requests-2.0.5.tar.gz.
File metadata
- Download URL: stealth_requests-2.0.5.tar.gz
- Upload date:
- Size: 15.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e1393cd888be154dca2927e12ea82d23cab5f74fee2362c1a7a9a80e61075e87
|
|
| MD5 |
ec67a916ceb43e65f47aafb7f68bf472
|
|
| BLAKE2b-256 |
e8d2bb0244ba90a9ba931434e49f8f70f7cd626113ee301468589829d1285e83
|
File details
Details for the file stealth_requests-2.0.5-py3-none-any.whl.
File metadata
- Download URL: stealth_requests-2.0.5-py3-none-any.whl
- Upload date:
- Size: 9.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
24a27a21105cb1d01e52995165912b3ed2ed44af6cf5ce599950e538a309fd18
|
|
| MD5 |
ddf3375eef8a19617b8cd934aa0fe18f
|
|
| BLAKE2b-256 |
578e2253e387c56c197cbb47f88e8617b1c4bd9b08181bfb938bd6515eb23982
|