Let’s say your boss at work gave you a task where he wants you to extract about 1000 product from a website, structure the data and save it to a database, would you copy paste manually all the product details from the product name, url and price ? I can imagine you would work days and nights and you wont finish the task, so this is where web scraping shines. So web scraping, or web harvesting or web data extraction is like writing a script that will automate data extraction from websites in a matter of minutes !.
Whether you’re a data analyst, a web developer or even someone who wants to work as a freelancer you should learn web scraping.
For a data analyst building a dataset is extremely important, so without web scraping you simply can’t generate it in addition to that adding web scraping in your resume is a plus for you.
Web scraping can be used in a variety of fields, so let me give you some examples on what you can do with it:
LXML is a lightweight HTML parser even the most popular web scraping framework (Scrapy) is built on the top of LXML, BeautifulSoup is a little bit overloaded with the number of functions exposed to us, it has more functions to use, yes that’s right ! however in Web Scraping most of the time we use XPath and CSS Selectors to navigate and select what to scrape from the HTML web page (tree) so there is no need to learn about new functions and wasting all that time to familiarize yourself with the BeautifulSoup API and the internal architecture, in addition to all of that LXML in terms of performance is way better than BeautifulSoup.
When scraping a website with Python, it’s common to use the
Requestslibraries to send
GETrequests to the server in order to receive its information.
However, you’ll eventually need to send some information to the website yourself before receiving the data you want, maybe because it’s necessary to perform a log-in or to interact somehow with the page.
To execute such interactions, Selenium is a frequently used tool. However, it also comes with some downsides as it’s a bit slow and can also be quite unstable sometimes. The alternative is to send a
POSTrequest containing the information the website needs using the request library.
In fact, when compared to Requests, Selenium becomes a very slow approach since it does the entire work of actually opening your browser to navigate through the websites you’ll collect data from. Of course, depending on the problem, you’ll eventually need to use it, but for some other situations, a
POSTrequest may be your best option, which makes it an important tool for your web scraping toolbox.
In this article, we’ll see a brief introduction to the
POSTmethod and how it can be implemented to improve your web scraping routines.
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The Beautiful Soup module is used for web scraping in Python. Learn how to use the Beautiful Soup and Requests modules in this tutorial. After watching, you will be able to start scraping the web on your own.
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=87Gx3U0BDlo&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=12
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Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
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No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
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Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
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Web data is one of the most readily accessible sources of data out there. For this reason, being able to extract and utilize the plethora of data that exists on the web is a necessary skill for every data scientist. And if this skill is not in your skillset just yet, needless to worry because this tutorial has got you covered. By the end of this tutorial, you’ll have learned the fundamentals of web scraping using Scrapy and will have a fully functional Python web scraper that extracts Covid-19 data from Worldometers.info.
#scrapy #web-scraping #data #python #covid19 #web scraping using scrapy and python