Building Automated Data Extraction Pipelines with Python

سرفصل های دوره

Data Extraction and Scraping Techniques Using Python

1. Introduction to Automated Data Extraction

1. Introduction

2. Understanding the importance of automated data extraction.html

3. Identifying use cases for automated data extraction.html

4. Web Scraping Overview.html

5. Introduction to Python libraries for data extraction.html

2. Setting up Your Data Extraction Environment

1. Installing Python on Windows

2. Installing Python on Mac OS

3. Updating Pip

4. Create and activate a virtual environment

5. Install Scrapy

6. Install Beautiful Soup

7. Note on Text Editors.html

8. Installing Visual Studio Code Text Editor

9. Best practices for data extraction pipelines.html

3. Building Basic Data Extraction Pipeline using BeautifulSoup

1. What we will extract

2. Writing Python script for basic data extraction - Part 1

3. Writing Python script for basic data extraction -Part 2

4. Prototyping the script - Part 1

5. Prototyping the script - Part 2

6. Prototyping the script - Part 3

7. Prototyping the script - Part 4

8. Prototyping the script - Part 5

9. Extracting data with the script

4. Building Basic Data Extraction Pipeline using Scrapy

1. Creating a Scrapy project

2. Components of a scrapy project

3. Scrapy architecture

4. Creating a spider Part 1

5. Creating a spider Part 2

6. Extracting data with scrapy shell Part 1

7. Extracting data with scrapy shell Part 2

8. Running the spider to extract data

5. Building Basic Data Extraction Pipeline for e-commerce

1. Create and activate a virtual environment.html

2. Install Python Packages

3. Creating a Python file

4. Creating Variables

5. Enabling Gmail Security

6. Creating Functions Part 1

7. Creating Functions Part 2

8. Creating Functions Part 3

9. Extracting data with the Python Script

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تولید کننده: Udemy-Training