Web Scrapping (HTML Parsing and JSON API) using Python Spider-Scrapy

Web scraping is a technique to extract data from a website. Many tools can be used to scrape a website. And now I want to explain how we can extract data from a website using scrapy python.

And now we will scrap data using scrapy from https://www.jobstreet.vn/j?sp=search&q=C%C3%B4ng+ngh%E1%BB%87+th%C3%B4ng+tin&l.

We will take the URL for each job title such as Giang vien…., Nhan vien …, and many more. After that, we could have to extract the data from each page.

Requirements

1. Must understand about scrapy theory (https://docs.scrapy.org/en/latest/index.html).
2. Must understand python programming language (especially the OOP theory).
3. Of course, we need a code editor and python that have been installed on your PC/Laptop.
4. The browser, in this case, is Google Chrome, so the options that will be mentioned in this article are available on Google Chrome.

What you will learn

1. Web crawling technique using spider scrapy.
2. Scraping technique with HTML parsing method.
3. Scraping technique with JSON API.
4. Debugging technique for scrapy in the terminal.

Project’s steps

Here the project‘s steps for scraping it.

• You must finish reading this article first, and then doing the practice technically.
• Scraping the main page and get the URLs for all the job titles in there.
• Scraping all the URLs page.
• Scraping the texts at the page which has the ads post label.
• Scraping the texts at the page which has the non-ads post label.

The job title on the main page is divided into two categories, there are ads-post and non-ads-post. Well, the ads post is the job title that has a sponsor and the sign ad for each of them.

That’s the point! We can scrape the data from the non-ads-post using the HTML parsing method. But it is doesn’t apply to the ads-post because in this case, the data from the ads-post can be gained using the JSON API method only.

In this case, I assume that you have already read or understood the scrapy theory here before.

#python #api #programming #html #json

What is GEEK

Buddha Community

Web Scrapping (HTML Parsing and JSON API) using Python Spider-Scrapy

Web scraping is a technique to extract data from a website. Many tools can be used to scrape a website. And now I want to explain how we can extract data from a website using scrapy python.

And now we will scrap data using scrapy from https://www.jobstreet.vn/j?sp=search&q=C%C3%B4ng+ngh%E1%BB%87+th%C3%B4ng+tin&l.

We will take the URL for each job title such as Giang vien…., Nhan vien …, and many more. After that, we could have to extract the data from each page.

Requirements

1. Must understand about scrapy theory (https://docs.scrapy.org/en/latest/index.html).
2. Must understand python programming language (especially the OOP theory).
3. Of course, we need a code editor and python that have been installed on your PC/Laptop.
4. The browser, in this case, is Google Chrome, so the options that will be mentioned in this article are available on Google Chrome.

What you will learn

1. Web crawling technique using spider scrapy.
2. Scraping technique with HTML parsing method.
3. Scraping technique with JSON API.
4. Debugging technique for scrapy in the terminal.

Project’s steps

Here the project‘s steps for scraping it.

• You must finish reading this article first, and then doing the practice technically.
• Scraping the main page and get the URLs for all the job titles in there.
• Scraping all the URLs page.
• Scraping the texts at the page which has the ads post label.
• Scraping the texts at the page which has the non-ads post label.

The job title on the main page is divided into two categories, there are ads-post and non-ads-post. Well, the ads post is the job title that has a sponsor and the sign ad for each of them.

That’s the point! We can scrape the data from the non-ads-post using the HTML parsing method. But it is doesn’t apply to the ads-post because in this case, the data from the ads-post can be gained using the JSON API method only.

In this case, I assume that you have already read or understood the scrapy theory here before.

#python #api #programming #html #json

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Lambda, Map, Filter functions in python

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:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Web Scraping Using Scrapy and Python

A beginner-friendly guide to scraping web data

Introduction

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

Web Scraping Using Scrapy and Python

A beginner-friendly guide to scraping web data

Introduction

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