Automation and Scripting with Python

Microsoft via Coursera

Go to class Write review

Details

Go to class

Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Paid Certificate Available
Duration & workload

1 day 1 hour 6 minutes
Sessions

On-Demand
Subtitles

English

Found in

Part of

Microsoft Python Development

Overview

Coursera Flash Sale

40% Off Coursera Plus for 3 Months!

Grab it

Description: This course focuses on automating tasks and improving efficiency using Python. You'll learn how to write scripts for file manipulation, data extraction, web scraping, and interacting with APIs. Benefits: Automate repetitive tasks, streamline workflows, and increase productivity in various domains using Python scripting. By the end of this course, you'll be able to: • Write scripts to automate file operations and data extraction. • Perform web scraping using BeautifulSoup and Scrapy. • Interact with REST APIs using the requests library. • Integrate with third-party services like email and cloud storage. • Schedule automated tasks using cron jobs and Task Scheduler. • Optimize and scale automation scripts for increased efficiency. Tools/Software: Python, os, shutil, glob, BeautifulSoup, Scrapy, requests, smtplib, imaplib, cron, Task Scheduler This course is for entry-Level professionals looking to build a foundational understanding and experience with Python, while seeking employment as a Python developer. No prior work experience or degree is required.

Syllabus

Introduction to automation

This module provides a foundational understanding of automation concepts and their relevance in the context of Python programming. Learners will explore the "why" and "how" of automation, its historical evolution, and its impact on modern workplaces. They will learn to identify tasks suitable for automation, analyze their feasibility, and prioritize automation efforts based on impact and business value. The module also covers the essential tools and techniques for setting up a Python development environment for automation, including virtual environments, command line operations, and IDE automation features. By the end of this module, learners will be able to recognize automation opportunities, set up their development environment, and write basic Python scripts executable from the command line.

Basic automation scripts

This module delves into the practical application of Python scripting for automating common tasks, with a focus on file manipulation, data extraction, and web scraping. Learners will gain proficiency in using essential Python modules like os, shutil, and glob to automate file operations, improving efficiency in handling and processing data. They will learn to leverage regular expressions for precise data extraction from unstructured text and explore advanced techniques like NLP and machine learning for more complex data extraction scenarios. Finally, the module introduces web scraping with BeautifulSoup and Scrapy, enabling learners to extract valuable information from websites while adhering to ethical considerations. By the end of this module, learners will be able to write Python scripts to automate file operations, extract data from various sources, and perform basic web scraping tasks.

Advanced automation techniques

This module introduces learners to more sophisticated automation techniques, focusing on API interaction, integration with third-party services, and task scheduling. Learners will explore the world of APIs (Application Programming Interfaces), learning how to use Python's requests library to interact with REST APIs, handle authentication, and manage rate limits. They will gain experience integrating their Python scripts with popular third-party services like email providers (using smtplib and imaplib), cloud storage platforms (like Dropbox and OneDrive), and even social media, further expanding their automation capabilities. Finally, the module covers various methods for scheduling automated tasks, including cron jobs (Linux/macOS), Task Scheduler (Windows), and Python's schedule module, empowering learners to automate tasks efficiently and effectively.

Optimization and scaling

This module focuses on optimizing and scaling automation scripts for improved performance and handling larger, more complex tasks. Learners will explore techniques for ensuring script efficiency, including profiling tools like cProfile and line_profiler to identify bottlenecks and optimize code. They will delve into strategies for scaling automation tasks, such as parallel processing with concurrency and multiprocessing, leveraging Scrapy clusters for efficient web scraping, and utilizing cloud platforms like AWS for scalable infrastructure. The module also emphasizes the importance of monitoring and maintaining automation scripts through logging, error alerts, and best practices for code organization and documentation. Finally, learners will be introduced to testing methodologies like unit testing with pytest, integration testing, and end-to-end testing to ensure script reliability and accuracy.

Git collaboration: Essential skills for a team environment

This module focuses on equipping learners with essential Git skills for effective collaboration in a team environment. Building upon a basic understanding of Git, learners will explore intermediate concepts like branching, merging, and conflict resolution, emphasizing their importance in managing code changes and collaborating on automation projects. The module highlights best practices for teamwork, including communication, code reviews, and utilizing platforms like GitHub, GitLab, and Bitbucket for efficient code sharing and version control. Learners will also gain practical experience in showcasing their skills and projects through a well-structured GitHub portfolio, demonstrating their ability to work collaboratively and contribute to a team's success.