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If you‘re involved in web scraping or data mining with Python, you‘ve likely heard of the Requests library. Requests is often hailed as the "gold standard" for making HTTP requests in Python, loved by both beginners and experienced developers alike for its simple, expressive API. But one common question that arises is: is Requests actually part of Python‘s built-in functionality, or is it something you need to install separately?

In this comprehensive article, we‘ll dive deep into the world of Requests and answer that question definitively. Along the way, we‘ll explore what makes Requests so special, how it compares to Python‘s standard HTTP libraries, and why it‘s a must-have tool for any web scraping project.

Understanding HTTP Libraries and Python‘s Standard Library

Before we get into the specifics of Requests, let‘s take a step back and clarify some fundamental concepts. What exactly is an HTTP library, and why is it important for web scraping?

In essence, an HTTP library provides a way for your Python code to communicate with web servers using the HTTP protocol. This allows you to programmatically send requests to web pages and APIs, and receive structured response data that you can then parse and analyze. Some common use cases include:

• Downloading the HTML content of web pages
• Submitting online forms and extracting data from the results
• Interacting with REST APIs to fetch JSON or XML data
• Scraping websites to collect large datasets
• Automating actions like logging into websites or posting content

At a lower level, HTTP libraries handle the nitty-gritty details of establishing TCP connections, constructing properly formatted HTTP requests, handling redirects and errors, and parsing response headers and content. Without an HTTP library, you‘d have to implement all of this functionality from scratch using Python‘s low-level socket module, which would be tedious and error-prone.

Fortunately, Python provides a few built-in libraries in its "standard library" for working with HTTP:

• http.client: A low-level library for making HTTP requests and handling responses
• urllib.request: A higher-level library built on top of http.client that provides a simpler API
• urllib3: A powerful HTTP client that offers thread safety, connection pooling, and more (added in Python 3.x)

The term "standard library" refers to the set of modules and packages that are included with every Python installation by default. These libraries are considered part of the core language and are maintained by the Python development team. Some well-known examples include os for operating system functions, math for mathematical operations, and json for working with JSON data.

While the standard HTTP libraries are quite capable, they can be verbose and confusing to work with, especially for common web scraping tasks. This is where third-party libraries like Requests come in, offering a more user-friendly and Pythonic interface. Third-party libraries are packages that are developed and maintained independently from the core Python language, and must be installed separately.

Introducing Requests: The Beloved Third-Party HTTP Library

Requests is a powerful, feature-rich HTTP library for Python that has taken the world of web scraping and API interaction by storm. Since its initial release in 2011, it has become one of the most downloaded Python packages of all time, with over 1 billion total downloads as of 2023 according to the Python Package Index.

So what makes Requests so special? In short, it offers a dramatically simplified and intuitive API compared to Python‘s built-in HTTP libraries. Requests abstracts away much of the complexity of working with HTTP, allowing you to focus on the high-level logic of your web scraping code.

To illustrate, let‘s compare a basic example of making a GET request and parsing the response using both Requests and Python‘s standard urllib library:

import requests
url = ‘https://api.example.com/data‘
response = requests.get(url)
data = response.json()
print(data)

from urllib import request
import json
url = ‘https://api.example.com/data‘
with request.urlopen(url) as response:
data = json.loads(response.read())
print(data)

As you can see, the Requests code is much more compact and readable. The requests.get() function automatically sends a GET request to the specified URL and returns a Response object. You can then directly access the response content as a string (response.text), bytes (response.content), or even parse it as JSON using response.json().

In contrast, the urllib code is more verbose and requires a few extra steps. You first have to explicitly open a connection to the URL using request.urlopen(), then read the response content as bytes, and finally parse it as JSON using json.loads().

This is just a small taste of the convenience that Requests offers. Some of its key features include:

• Full support for all common HTTP methods (GET, POST, PUT, DELETE, etc.)
• Automatic handling of query parameters, headers, and request bodies
• Built-in JSON and form-encoded data parsing
• Automatic decompression of gzip and deflate responses
• Connection pooling and session persistence via a Session object
• Cookie persistence across requests
• Proxy support for connecting through HTTP and SOCKS proxies
• Automatic handling of redirects
• Timeouts and retry functionality for error handling
• Elegant authentication system supporting Basic Auth, Digest Auth, and more
• Robust SSL/TLS verification to prevent man-in-the-middle attacks

Here‘s an example showcasing some of these features to log in to a website and download data from a protected page:

import requests

session = requests.Session()

login_data = {
‘username‘: ‘my_username‘,
‘password‘: ‘my_password‘
}

login_response = session.post(‘https://example.com/login‘, data=login_data)


data_response = session.get(‘https://example.com/data‘, 
params={‘page‘: 1, ‘per_page‘: 100},
timeout=5)

data = data_response.json()
print(data)

With just a few lines of readable code, Requests allows us to handle authentication, persistent sessions, query parameters, timeouts, and JSON parsing. This is the kind of expressive, high-level API that has endeared Requests to countless developers and made it an indispensable part of the web scraping toolkit.

Installing and Using Requests

As mentioned earlier, Requests is not part of Python‘s standard library – it‘s a third-party package that must be installed separately. However, the installation process is quite straightforward using Python‘s pip package manager.

To install Requests system-wide, you can simply run:

python -m pip install requests

This will download and install the latest version of Requests from the Python Package Index (PyPI), along with any dependencies.

However, it‘s often a good practice to install Requests (and any other project dependencies) in a virtual environment to avoid conflicts with other Python projects on your system. A virtual environment is an isolated Python environment with its own packages and dependencies, separate from your global Python installation.

You can create a new virtual environment and install Requests inside it using the following commands:

python -m venv myproject
source myproject/bin/activate  # On Windows, use `myproject\Scripts\activate`
pip install requests

This creates a new virtual environment named "myproject", activates it, and installs Requests into it. You‘ll need to activate this environment whenever you want to work on your project to ensure the correct version of Requests is available.

Once Requests is installed, using it in your Python code is as simple as importing it:

import requests
response = requests.get(‘https://www.example.com‘)
print(response.text)

This sends a GET request to the specified URL and prints out the HTML content of the response.

Advanced Usage and Ecosystem

Beyond its core functionality, Requests also offers a wealth of advanced features and configurability for more complex use cases. For example, you can:

• Customize your user agent string and other headers to mimic a browser
• Automatically retry failed requests using a custom retry strategy
• Mount custom authentication handlers for APIs that use OAuth or other token-based auth flows
• Streaming large requests and responses for memory efficiency
• Verify SSL/TLS certificates against custom certificate authorities
• Hook into the underlying request/response cycle for logging, monitoring, or modification

One of the most powerful features of Requests is its Session object, which allows you to persist cookies, authentication, and other settings across multiple requests. This is incredibly useful for web scraping scenarios that involve logging into a site and then navigating through multiple pages.

Requests also integrates seamlessly with the broader Python ecosystem, especially in the realm of web scraping and data analysis. Many popular Python libraries and frameworks are built on top of Requests or offer plugins/extensions for it:

• BeautifulSoup: A library for parsing HTML and XML documents that is often used in conjunction with Requests for web scraping.
• Scrapy: A full-featured web crawling and scraping framework that uses Requests under the hood for making HTTP requests.
• Mechanize: A programmable web browsing library that can use Requests as its underlying transport.
• Requests-HTML: An extension library for Requests that provides support for parsing HTML, interacting with dynamic web pages, and even rendering JavaScript.

The Requests ecosystem also includes a number of authentication plugins for integrating with APIs that use various OAuth flows, such as requests_oauthlib and requests-oauth.

Popularity and Community

Requests has seen massive adoption in the Python community and beyond, especially for web scraping and data mining tasks. Its popularity can be attributed to several factors:

• Its clean, expressive API that emphasizes readability and ease of use
• Its comprehensive feature set that covers most common HTTP use cases
• Its strong commitment to backwards compatibility and semantic versioning
• Its excellent documentation and user guides
• Its enthusiastic community of users and contributors

To quantify Requests‘ popularity, let‘s look at some statistics:

• Requests is consistently one of the top 10 most downloaded Python packages, with over 80 million downloads per month as of 2023 (source).
• Requests has over 44,000 stars on GitHub and more than 8,000 forks (source), indicating a high level of developer interest and engagement.
• The Requests documentation has been translated into over 20 languages by the community (source).
• Requests is used by many high-profile companies and organizations including Amazon, Google, Netflix, Twilio, Mozilla, Heroku, and more (source).

This widespread adoption means that Requests has been battle-tested in a wide variety of environments and use cases. It also means that there is a wealth of community resources, tutorials, and Stack Overflow answers available for learning and troubleshooting.

Conclusion

In conclusion, Requests is not part of Python‘s standard library – it‘s a separate third-party library that needs to be installed via pip or other means. However, it has become so ubiquitous and essential in the Python web scraping and data mining ecosystem that it almost feels like a built-in part of the language.

Requests offers a powerful, yet simple, API for making HTTP requests and handling responses, with a strong focus on readability and ease of use. It abstracts away many of the complexities of working with HTTP, allowing you to focus on the high-level logic of your scraping and data extraction tasks.

Whether you‘re a beginner just getting started with web scraping, or an experienced developer looking to streamline your HTTP workflow, Requests is an indispensable tool to have in your Python toolkit. Its extensive feature set, strong community support, and seamless integration with the broader ecosystem make it the go-to choice for most Python HTTP needs.

To learn more about Requests and start using it in your own projects, be sure to check out the following resources:

• Official Requests Documentation
• Requests GitHub Repository
• Real Python: Python‘s Requests Library (Guide)
• DataCamp: Making HTTP Requests in Python with Requests