Cookies allow web scrapers to store and send session data that enables accessing protected resources on websites. With the Python Requests library, you can easily save cookies to reuse in later sessions. This enables mimicking user logins and continuing long-running scrapes without starting over.

In this comprehensive guide, you'll learn the ins and outs of cookie persistence with Requests using practical examples. We'll cover:

And more. Let's get scraping!

Making Requests with Sessions

The Requests Session object automatically persists cookies across all requests made through that Session. This handles the cookie workflow for you:

import requests

session = requests.Session()

response = session.get('<http://example.com>')
# Cookies saved from response

response = session.get('<http://example.com/user-page>')
# Session sends cookies back automatically

To access the cookie data, use session.cookies which returns a RequestsCookieJar:

session_cookies = session.cookies
print(session_cookies.get_dict())

This simplicity makes Sessions ideal for most scraping cases. You get cookie persistence without manually saving and loading files.

Saving Cookies to Disk

For long-running scrapes, you may want to save cookies to disk to resume later. The RequestsCookieJar doesn't support serialization itself, but we can convert to a built-in cookiejar that does:

Serializing the Cookiejar

Use requests.utils.dict_from_cookiejar() to get a dictionary from the cookiejar:

import requests

cookie_dict = requests.utils.dict_from_cookiejar(session.cookies)

We can then serialize this dictionary to JSON and save to a file:

import json

with open('cookies.json', 'w') as f:
    json.dump(cookie_dict, f)

Loading Cookies from Disk

To resume the session, we load the cookies back into a new cookiejar:

with open('cookies.json', 'r') as f:
    cookie_dict = json.load(f)

cookiejar = requests.utils.cookiejar_from_dict(cookie_dict)
session.cookies = cookiejar

This gives us back the original RequestsCookieJar with all of our cookies!

Using Cookiejar Subclasses for Serialization

Requests provides CookieJar subclasses that handle serialization for us automatically:

from requests.cookies import MozillaCookieJar

session = requests.Session()
session.cookies = MozillaCookieJar('cookies.txt')

# Cookies saved to cookies.txt automatically

The built-ins MozillaCookieJar and LWPCookieJar support saving to disk in the Netscape and libwww-perl formats respectively.

We can then call load() on a new cookiejar instance to resume the session:

jar = MozillaCookieJar()
jar.load('cookies.txt', ignore_discard=True)

session.cookies = jar

This is simpler than manual serialization when you don't need to customize the storage format.

Rotating User Agents

Websites can identify scrapers by consistent User Agent strings. To avoid this, we can rotate random User Agents with each request:

import requests, random

user_agents = [
  'Mozilla/5.0 (Windows NT 10.0; Win64; x64)...'
  'Mozilla/5.0 (X11; Ubuntu; Linux x86_64)...'
]

for i in range(10):

  # Pick a random user agent
  user_agent = random.choice(user_agents)

  # Create headers with UA
  headers = {'User-Agent': user_agent}

  # Make request with UA header
  response = requests.get('<http://example.com>', headers=headers)

This makes your scraper appear to use different browsers, avoiding UA blocking.

Inspecting Cookies

Sometimes you need to view cookie metadata like the domain and path.

We can get a list of cookie dicts from the cookiejar:

cookies = []
for c in session.cookies:
    cookies.append({
        'name': c.name,
        'domain': c.domain,
        'path': c.path
    })

print(cookies)

This lets you log or inspect individual cookie attributes as needed.

When to Use Cookie Dicts vs Cookiejars

Both cookie dicts and cookiejars allow you to persist cookies with Requests. When should you use each?

Cookie dicts

Cookiejars

If you need to customize your cookie storage, use a cookie dict. The cookiejar subclasses are best for simple cases without specialized disk formats.

And remember, Sessions provide the simplest persistence without any serialization!

Use expire_after to Limit Cookie Lifetimes

Cookies can last for years if not expired properly. For short-lived scrapes, make cookies expire after the request session:

session = requests.Session()

session.cookies.set('name', 'value', expires_after=3600)
# Expires in 1 hour

This avoids leaving cookies behind that could impact later runs.

Configuring Cookie Policies

The CookiePolicy class handles rules for parsing and returning cookies:

from requests.cookies import CookiePolicy

policy = CookiePolicy(
    blocked_domains=['ads.com'],
    allowed_domains=['example.com']
)

session.cookies.set_policy(policy)

Use this to block or allow certain domains from setting and receiving cookies.

Conclusion

Requests makes it easy to implement complex cookie workflows for web scraping and automation. Key takeaways:

Cookie handling is a scrapers bread and butter. Mastering techniques like those in this guide will level up your scraping abilities.

Frequently Asked Questions

How do you send cookies in Python requests?

Use a requests.Session() object to automatically handle cookies across requests:

session = requests.Session()
response = session.get('<http://example.com>')

How do you use sessions and cookies in Python?

The Session object persists cookies across requests automatically. Access cookies with session.cookies which returns a RequestsCookieJar.

How to create cookies in Python?

Use session.cookies.set(name, value) to set a cookie in the session cookie jar.

How do you automate cookies in Python?

Use the requests.Session() as a persistent cookie jar that handles sending and receiving cookies automatically.

What is the Python library for cookies?

The http.cookiejar module contains CookieJar classes like MozillaCookieJar and LWPCookieJar for saving cookies to disk.

How do I set cookies in API calls?

Pass a cookie dictionary in the cookies parameter of requests:

cookies = {'cookie_name' : 'value'}
response = requests.get(url, cookies=cookies)

What is requests session () in Python?

requests.Session() creates a persistent session that keeps cookies and connections open across multiple requests.

How to store data in cookies in Python?

Serialize the cookie jar to JSON and save to disk. Then load the JSON to resume with the same cookies.

What is the difference between request and session in Python?

request makes a single HTTP request. Session persists cookies and connections across multiple requests.

Can a REST API use cookies?

Yes, REST APIs can send and receive cookies like a normal web application.

Where are cookies stored in request?

Cookies are stored in the session.cookies attribute which contains a RequestsCookieJar instance.

Does flask session use cookies?

Yes, Flask server-side sessions are implemented on top of secure signed cookies by default.

Is Python requests library safe?

Yes, Requests validates SSL certificates and has robust security protections for cookies and authentication.

Why HTTP uses cookies?

Cookies allow stateful sessions with user data to be maintained across multiple HTTP requests.

How are request cookies generated?

Cookies are generated on the server and sent in the Set-Cookie header. The client automatically sends cookies back.

Which is safe session or cookies?

Sessions built on top of HTTP cookies can safely maintain state. Follow best practices like using HTTPS.

What is cookies in Python Flask?

Flask uses secure signed cookies to store session data by default. Flask cookie handling can be customized.

How are cookies set in HTTP request?

The server sets cookies in the response with Set-Cookie headers. The client automatically attaches cookies to future requests.

How to get cookie value from API?

Check the cookies dictionary on the requests.Response object after making a request.

What is cookie authentication?

Some web apps use cookie-based sessions for authentication instead of tokens. The user logs in and gets a session cookie.

Is Python Requests a REST API?

No, Requests is a Python HTTP client library, not a REST API framework. It can call REST APIs by making HTTP requests.

Why use Python Requests?

Requests makes it easy to call REST APIs and web scrapers with a simple interface for HTTP requests, sessions, cookies, etc.

What is request library in Python?

The Requests library provides an elegant HTTP client interface for Python. It abstracts away complexity for calling web APIs and scraping websites.

Does flask session use cookies?

Yes, Flask uses signed cookies to handle session data by default. Server-side sessions are implemented on top of these cookies.

Is Python request an API?

No, Requests is a client library for calling APIs. It provides an API for making HTTP requests and handling responses in Python.

Is session storage same as cookies?

Session storage maintains state on the client side, similar to cookies. But sessionStorage is isolated per browser tab, while cookies are sent with every request.

How do I get data from cookies?

Access the cookies attribute on the Response object after making a request to get a dictionary of cookie names and values.