python -m pip install bota botasaurus botasaurus-api botasaurus-requests botasaurus-driver bota botasaurus-proxy-authentication botasaurus-server --upgrade.How wonderful that of all the web scraping tools out there, you chose to learn about Botasaurus. Congratulations!
And now that you are here, you are in for an exciting, unusual and rewarding journey that will make your web scraping life a lot, lot easier.
Now, let me tell you in bullet points about Botasaurus. (Because as per the marketing gurus, YOU as a member of Developer Tribe have a VERY short attention span.)
So, what is Botasaurus?
Botasaurus is an all-in-one web scraping framework that enables you to build awesome scrapers in less time, less code, and with more fun.
A Web Scraping Magician has put all his web scraping experience and best practices into Botasaurus to save you hundreds of hours of Development Time!
Now, for the magical powers awaiting you after learning Botasaurus:


Save up to 97%, yes 97% on browser proxy costs by using browser-based fetch requests.
Easily save hours of Development Time with easy parallelization, profiles, extensions, and proxy configuration. Botasaurus makes asynchronous, parallel scraping a child's play.
Use Caching, Sitemap, Data cleaning, and other utilities to save hours of time spent in writing and debugging code.
Easily scale your scraper to multiple machines with Kubernetes, and get your data faster than ever.
And those are just the highlights. I Mean!
There is so much more to Botasaurus, that you will be amazed at how much time you will save with it.
Let's dive right in with a straightforward example to understand Botasaurus.
In this example, we will go through the steps to scrape the heading text from https://www.omkar.cloud/.

First things first, you need to install Botasaurus. Run the following command in your terminal:
python -m pip install botasaurus
Next, let's set up the project:
mkdir my-botasaurus-project cd my-botasaurus-project code . # This will open the project in VSCode if you have it installed
Now, create a Python script named main.py in your project directory and paste the following code:
from botasaurus.browser import browser, Driver @browser def scrape_heading_task(driver: Driver, data): # Visit the Omkar Cloud website driver.get("https://www.omkar.cloud/") # Retrieve the heading element's text heading = driver.get_text("h1") # Save the data as a JSON file in output/scrape_heading_task.json return { "heading": heading } # Initiate the web scraping task scrape_heading_task()
Let's understand this code:
scrape_heading_task, decorated with @browser:@browser def scrape_heading_task(driver: Driver, data):
def scrape_heading_task(driver: Driver, data):
scrape_heading_task.json by Botasaurus:driver.get("https://www.omkar.cloud/") heading = driver.get_text("h1") return {"heading": heading}
# Initiate the web scraping task scrape_heading_task()
Time to run it:
python main.py
After executing the script, it will:
output/scrape_heading_task.json.
Now, let's explore another way to scrape the heading using the request module. Replace the previous code in main.py with the following:
from botasaurus.request import request, Request from botasaurus.soupify import soupify @request def scrape_heading_task(request: Request, data): # Visit the Omkar Cloud website response = request.get("https://www.omkar.cloud/") # Create a BeautifulSoup object soup = soupify(response) # Retrieve the heading element's text heading = soup.find('h1').get_text() # Save the data as a JSON file in output/scrape_heading_task.json return { "heading": heading } # Initiate the web scraping task scrape_heading_task()
In this code:
request, which is specifically designed for making browser-like humane requests.BeautifulSoup object using soupify() and extract the heading.Finally, run it again:
python main.py
This time, you will observe the exact same result as before, but instead of opening a whole Browser, we are making browser-like humane HTTP requests.
Botasaurus Driver is a web automation driver like Selenium, and the single most important reason to use it is because it is truly humane, and you will not, and I repeat NOT, have any issues with accessing any website.
Plus, it is super fast to launch and use, and the API is designed by and for web scrapers, and you will love it.
Cloudflare is the most popular protection system on the web. So, let's see how Botasaurus can help you solve various Cloudflare challenges.
Connection Challenge
This is the single most popular challenge and requires making a browser-like connection with appropriate headers. It's commonly used for:
Example Page: https://www.g2.com/products/github/reviews
from botasaurus.browser import browser, Driver @browser def scrape_heading_task(driver: Driver, data): # Visit the website via Google Referrer driver.google_get("https://www.g2.com/products/github/reviews") driver.prompt() heading = driver.get_text('.product-head__title [itemprop="name"]') return heading scrape_heading_task()
from botasaurus.request import request, Request @request(max_retry=10) def scrape_heading_task(request: Request, data): response = request.get('https://www.g2.com/products/github/reviews') print(response.status_code) response.raise_for_status() return response.text scrape_heading_task()
JS with Captcha Challenge
This challenge requires performing JS computations that differentiate a Chrome controlled by Selenium/Puppeteer/Playwright from a real Chrome. It also involves solving a Captcha. It's used to for pages which are rarely but sometimes visited by people, like:
Example Page: https://www.g2.com/products/github/reviews.html?page=5&product_id=github
Using @request does not work because although it can make browser-like HTTP requests, it cannot run JavaScript to solve the challenge.
Pass the bypass_cloudflare=True argument to the google_get method.
from botasaurus.browser import browser, Driver @browser def scrape_heading_task(driver: Driver, data): driver.google_get("https://www.g2.com/products/github/reviews.html?page=5&product_id=github", bypass_cloudflare=True) driver.prompt() heading = driver.get_text('.product-head__title [itemprop="name"]') return heading scrape_heading_task()
Here are some benefits of creating a scraper with a user interface:
Let's run the Botasaurus Starter Template (the recommended template for greenfield Botasaurus projects), which scrapes the heading of the provided link by following these steps:
Clone the Starter Template:
git clone https://github.com/omkarcloud/botasaurus-starter my-botasaurus-project
cd my-botasaurus-project
Install dependencies (will take a few minutes):
python -m pip install -r requirements.txt
python run.py install
Run the scraper:
python run.py
Your browser will automatically open up at http://localhost:3000/. Then, enter the link you want to scrape (e.g., https://www.omkar.cloud/) and click on the Run Button.

After some seconds, the data will be scraped.

Visit http://localhost:3000/output to see all the tasks you have started.

Go to http://localhost:3000/about to see the rendered README.md file of the project.

Finally, visit http://localhost:3000/api-integration to see how to access the Scraper via API.

The API Documentation is generated dynamically based on your Scraper's Inputs, Sorts, Filters, etc., and is unique to your Scraper.
So, whenever you need to run the Scraper via API, visit this tab and copy the code specific to your Scraper.
Creating a UI Scraper with Botasaurus is a simple 3-step process:
To understand these steps, let's go through the code of the Botasaurus Starter Template that you just ran.
In src/scrape_heading_task.py, we define a scraping function which basically does the following:
data object and extracts the "link".from botasaurus.request import request, Request from botasaurus.soupify import soupify @request def scrape_heading_task(request: Request, data): # Visit the Link response = request.get(data["link"]) # Create a BeautifulSoup object soup = soupify(response) # Retrieve the heading element's text heading = soup.find('h1').get_text() # Save the data as a JSON file in output/scrape_heading_task.json return { "heading": heading }
In backend/scrapers.py, we:
Server.add_scraper() to register the scraperfrom botasaurus_server.server import Server from src.scrape_heading_task import scrape_heading_task # Add the scraper to the server Server.add_scraper(scrape_heading_task)
In backend/inputs/scrape_heading_task.js we:
getInput function that takes the controls parameter/** * @typedef {import('../../frontend/node_modules/botasaurus-controls/dist/index').Controls} Controls */ /** * @param {Controls} controls */ function getInput(controls) { controls // Render a Link Input, which is required, defaults to "https://www.omkar.cloud/". .link('link', { isRequired: true, defaultValue: "https://www.omkar.cloud/" }) }
Above was a simple example; below is a real-world example with multi-text, number, switch, select, section, and other controls.
/** * @typedef {import('../../frontend/node_modules/botasaurus-controls/dist/index').Controls} Controls */ /** * @param {Controls} controls */ function getInput(controls) { controls .listOfTexts('queries', { defaultValue: ["Web Developers in Bangalore"], placeholder: "Web Developers in Bangalore", label: 'Search Queries', isRequired: true }) .section("Email and Social Links Extraction", (section) => { section.text('api_key', { placeholder: "2e5d346ap4db8mce4fj7fc112s9h26s61e1192b6a526af51n9", label: 'Email and Social Links Extraction API Key', helpText: 'Enter your API key to extract email addresses and social media links.', }) }) .section("Reviews Extraction", (section) => { section .switch('enable_reviews_extraction', { label: "Enable Reviews Extraction" }) .numberGreaterThanOrEqualToZero('max_reviews', { label: 'Max Reviews per Place (Leave empty to extract all reviews)', placeholder: 20, isShown: (data) => data['enable_reviews_extraction'], defaultValue: 20, }) .choose('reviews_sort', { label: "Sort Reviews By", isRequired: true, isShown: (data) => data['enable_reviews_extraction'], defaultValue: 'newest', options: [{ value: 'newest', label: 'Newest' }, { value: 'most_relevant', label: 'Most Relevant' }, { value: 'highest_rating', label: 'Highest Rating' }, { value: 'lowest_rating', label: 'Lowest Rating' }] }) }) .section("Language and Max Results", (section) => { section .addLangSelect() .numberGreaterThanOrEqualToOne('max_results', { placeholder: 100, label: 'Max Results per Search Query (Leave empty to extract all places)' }) }) .section("Geo Location", (section) => { section .text('coordinates', { placeholder:


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