Python 3: Tools, Modules and JSON

Name: Python 3: Tools, Modules and JSON
Rating: 4.4 (39 reviews)

Python 3 Part 2: Tools, Modules, and JSON

Created byStone River eLearning

Last updated 1/2019

English

English [Auto],

What you'll learn

Create working Python scripts following best practices
Use python iterators and generators appropriately
Use regular expressions, lambda functions and decorators
Search and replace text with regular expressions
Work with modules and packages including APIs
Learn metaprogramming
Understand the structure of XML and JSON
Learn XML and JSON parsing

Course content

3 sections • 47 lectures • 3h 51m total length

Topic A: Iterators and Generators - Part 10:24
Explore iterators and generators to traverse collections efficiently, producing cleaner code that decouples data from the algorithm, and learn how generators enable multiple Python constructs including iterators.
Iterators and Generators - Part 215:26
Explore Python 3 programming tools, including iterators and generators, regular expressions, introspection, lambda functions, and decorators, to control data traversal and code clarity.
Iterators and Generators - Part 30:19
Explore the background of iterators and generators and see a practical demonstration on implementing them in Python 3, then preview how regular expressions are used in Python.
Topic B: Regular Expressions - Part 10:23
Explore how Python 3 handles regular expressions and apply common string matching patterns to enhance your projects.
Regular Expressions - Part 217:48
Explore how regular expressions work, their pattern matching power, and key metacharacters, then learn to apply them in Python for searching strings and validating emails.
Regular Expressions - Part 30:25
Explore the foundations of how Python 3 handles regular expressions, covering key concepts and patterns. Prepare for the upcoming, more complex topic: introspection in Python.
Topic C: Introspection and Lambda Functions - Part 10:24
Explore introspection to determine object types at runtime, gain flexibility and control over object structures, and create anonymous functions on the fly, also called lambda functions.
Introspection and Lambda Functions - Part 2A4:05
Explore introspection in Python to determine an object's type at runtime with type and id, and inspect attributes and methods with dir to understand modules, packages, and object structure.
Introspection and Lambda Functions - Part 2B11:14
Explore Python introspection to inspect types at runtime, handle dynamic data with type checks, and leverage metaprogramming to adapt behavior while iterating over strings, lists, and dicts.
Introspection and Lambda Functions - Part 2C5:27
Explore lambda functions as anonymous, name-free blocks of code you can assign to variables and pass into other functions, enabling on-the-fly, elegant functional programming with map and metaprogramming.
Introspection and Lambda Functions - Part 2D6:00
Explore why and how to use lambda functions in Python by building a Celsius to Fahrenheit converter and applying a map with a lambda for concise, readable, functional code.
Introspection and Lambda Functions - Part 30:19
Explore how introspection and lambda functions boost flexibility and knowledge of your own objects, and show how anonymous functions promote more elegant code structure in daily development.
Topic D: Metaclasses and Decorators - Part 10:19
Explore metaclasses and decorators in Python to expand your implementation capabilities. Introduce these advanced concepts at a high level and drill deeper into how to implement them in Python programs.
Metaclasses and Decorators - Part 2A2:45
Explore metaclasses in Python as an advanced tool to control class behavior, enabling rapid creation of similar classes, advanced refactoring, and blueprint-driven class construction.
Metaclasses and Decorators - Part 2B10:51
Explore metaclasses and decorators in Python by comparing plain classes with dynamic attribute creation, using an attribute type metaclass to instantiate submarine and tank objects efficiently.
Metaclasses and Decorators - Part 2C2:49
Decorators in Python update a function's behavior without altering its code, by wrapping it and adding pre- or post-execution steps. They enable safe changes across libraries and support aspect-oriented ideas.
Metaclasses and Decorators - Part 2D6:58
Explore how decorators in Python work by building a decorator class, wrapping functions to run code before and after calls. Learn practical examples showing dynamic function enhancement and runtime behavior.
Metaclasses and Decorators - Part 30:17
Learn how to use metaclasses and decorators to inject function entry and exit points and to construct classes using a metaclass as a template.
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Topic A: Modules and Packages - Part 10:19
Explore how to leverage third party modules and packages in Python applications. Discover and configure Python packages, then try popular packages and learn how to use them in code.
Modules and Packages - Part 2A10:21
Explore how to find, download, and install Python packages via the Python Package Index, import them into your project, and use numpy for matrix creation, concatenation, and multiplication.
Modules and Packages - Part 2B9:03
Compare alternative Python package installation methods for different versions and learn to use the Beautiful Soup package for HTML parsing and the requests package for HTTP requests.
Modules and Packages - Part 2C5:13
Install requests with pip, import requests, fetch the hub events page via requests.get, inspect status codes, and parse text or json with libraries like Beautiful Soup.
Modules and Packages - Part 30:14
Discover how to find useful modules and packages for your applications and configure them correctly within your own implementation.
Topic B: Working with APIs - Part 10:22
Learn how to interact with third-party APIs in your Python applications, unlocking increased functionality and enabling your software to communicate with other systems.
Working with APIs - Part 213:57
Learn to integrate third-party APIs with Python using RESTful interfaces, perform get, put, post, and delete requests, and build a Twilio-based app to send text messages.
Working with APIs - Part 30:15
Learn to work with APIs in your application, boost software functionality, and see basic API integrations demonstrated in code.
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Topic A: Metaprogramming Primer - Part 10:16
Explore metaprogramming fundamentals and its key attributes in Python 3, then see practical implementations for common attributes across Python code.
Metaprogramming Primer - Part 218:26
Master metaprogramming in Python by studying metaclasses, prepare and new, and how class creation is customized. Explore local and global scope to avoid namespace pollution in metaprogramming constructs.
Metaprogramming Primer - Part 30:16
Deepen understanding of metaprogramming by exploring more complex constructs that enable more powerful metaprogramming implementations.
Topic B: Decorators and Monkey Patching - Part 10:19
Explore how decorators boost metaprogramming in Python and see practical monkey patching techniques. Understand the construction of decorators and how monkey patching can be applied in metaprogramming applications.
Decorators and Monkey Patching - Part 2A4:31
Use Python decorators as metaprogramming tool to wrap functions with timing and logging. Build an execution timer with time module and phunk tools library to time methods while preserving metadata.
Decorators and Monkey Patching - Part 2B5:26
Learn to build a custom decorator to time function execution, wrap it with wraps, and print benchmark results to compare methods using a practical example.
Decorators and Monkey Patching - Part 2C2:47
Explore monkey patching, a runtime technique to extend or modify a program by changing methods or functions for a running instance, often used with libraries.
Decorators and Monkey Patching - Part 2D7:54
Learn to apply monkey patching using the types library to modify a class method at runtime, explore the more powerful patching technique, and discuss metaprogramming best practices and potential pitfalls.
Decorators and Monkey Patching - Part 30:15
Master decorators and monkey patching concepts as you complete this metaprogramming-focused lecture. Apply decorators in your metaprogramming modules and understand the ideas behind monkey patching.
Topic C: XML and JSON Structure - Part 10:17
Explore the overall structure of XML and JSON. Build a basic understanding of how each format is arranged.
XML and JSON Structure - Part 29:25
Understand the basic xml structure with a root and nested elements. Build a json structure of rebels as name objects and learn to generate and parse both with python libraries.
XML and JSON Structure - Part 30:12
Compare xml and json structures and explain how data is represented in each format, highlighting differences and practical implications for using them in Python.
Topic: Generating XML and JSON - Part 10:24
Explore iterators and generators to traverse collections efficiently, producing cleaner code and decoupling data from the algorithm; learn how generators create Python constructs including iterators.
Generating XML and JSON - Part 216:41
Generate xml and json automatically in Python 3 using built-in libraries, build xml trees with root and subelements, and serialize json with dumps and pretty print.
Generating XML and JSON - Part 30:14
Generate data in XML or JSON format using Python, and leverage Python libraries to implement more robust solutions.
Topic E: Parsing XML and JSON - Part 10:22
Learn to parse xml and json data in python using built-in libraries, and apply these techniques to parse feeds in your programs.
Parsing XML and JSON - Part 218:24
Explore parsing xml feeds with python 3's expat parser, including start element, end element, and character data handlers. Decode json with json.loads to iterate structured data for database integration.
Parsing XML and JSON - Part 30:15
Learn to parse XML and JSON data in Python and extract the exact information from incoming sources.
Topic F: Implementing Algorithms - Part 10:29
Explore implementing complex algorithms in Python, develop critical thinking to analyze and design solutions, and learn by solving the Towers of Hanoi problem.
Implementing Algorithms - Part 217:58
Explore solving the Tower of Hanoi with a recursive algorithm in Python, analyzing problem structure, big-O growth, and a concise three-line implementation.
Implementing Algorithms - Part 30:24
Explore implementing a popular mathematics and computer science problem, walking through its solution design and implementation. Practice applying programming, critical thinking, and design skills through related exercises.
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Requirements

The Python Tools, Modules and JSON is part of the two-course series on Python.
The candidates wishing to register for this course are required to have completed the Python Fundamentals course.
In addition to this, a basic understanding of the Python language and standard library is also recommended.

Description

The Python Tools, Modules and JSON course will enable the students to learn the more advanced concepts of writing and running Python scripts. The course builds on the Python Fundamentals course and covers the more complex topics such as iterators and generators, regular expressions, introspection and lambda functions, metaclasses and decorators, and using the extensive functionality of Python modules. Extra emphasis is placed on features unique to Python, such as metaprogramming and JSON. After completing this course, the students will immediately be able to use Python to complete tasks in the real world.

The Python Tools, Modules and JSON course will comprehensively cover the more advanced topics related to the Python programming language with primary focus on the several tools, modules and JSON. The course enables the students to code efficient scripts to solve the real-world problems using the advanced features of Python.

Who this course is for:

Advanced level programmers
System administrators who want to use Python to support their server installations
Website administrators who want to use Python to support their web-servers
IT professionals who want to automate or simplify common tasks with the use of Python scripts

Python 3: Tools, Modules and JSON

What you'll learn

Explore related topics

Course content

Chapter 01 - Programming Tools18 lectures • 1hr 26min

Chapter 02 - Modules and Packages8 lectures • 40min

Chapter 03 - Metaprogramming and JSON21 lectures • 1hr 45min

Requirements

Description

Who this course is for: