HOT

Python 3: Deep Dive (Part 3 – Dictionaries, Sets, JSON)

Development

Python 3: Deep Dive (Part 3 – Dictionaries, Sets, JSON), available at $124.99, has an average rating of 4.84, with 85 lectures, based on 1704 reviews, and has 28128 subscribers.

Rating4.8
Enroll Now

You will learn about Associative Arrays Hash Tables and Hash Functions Python's implementation of hash tables Dictionaries and Sets Defining hash functions for our custom classes and why that is useful Creating customized dictionaries using the UserDict class defaultdict OrderedDict and Python3.6+ equivalences Counter (multi-sets) ChainMap Serialization and Deserialization JSON serialization/deserialization Intro to JSONSchema, Marshmallow, PyYaml and Serpy 3rd party libraries This course is ideal for individuals who are Python developers who want a deeper understanding of Python dictionaries and related topics It is particularly useful for Python developers who want a deeper understanding of Python dictionaries and related topics.

Enroll now: Python 3: Deep Dive (Part 3 – Dictionaries, Sets, JSON)

Summary

Title: Python 3: Deep Dive (Part 3 – Dictionaries, Sets, JSON)

Price: $124.99

Average Rating: 4.84

Number of Lectures: 85

Number of Published Lectures: 85

Number of Curriculum Items: 85

Number of Published Curriculum Objects: 85

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Associative Arrays
  • Hash Tables and Hash Functions
  • Python's implementation of hash tables
  • Dictionaries and Sets
  • Defining hash functions for our custom classes and why that is useful
  • Creating customized dictionaries using the UserDict class
  • defaultdict
  • OrderedDict and Python3.6+ equivalences
  • Counter (multi-sets)
  • ChainMap
  • Serialization and Deserialization
  • JSON serialization/deserialization
  • Intro to JSONSchema, Marshmallow, PyYaml and Serpy 3rd party libraries

Who Should Attend

  • Python developers who want a deeper understanding of Python dictionaries and related topics

Target Audiences

  • Python developers who want a deeper understanding of Python dictionaries and related topics

This course is an in-depth look at Python dictionaries.

Dictionaries are ubiquitous in Python. Classes are essentially dictionaries, modules are dictionaries, namespaces are dictionaries, sets are dictionaries and many more.

In this course we’ll take an in-depth look at:

  • associative arrays and how they can be implemented using hash maps

  • hash functions and how we can leverage them for our own custom classes

  • Python dictionaries and sets and the various operations we can perform with them

  • specialized dictionary structures such  as OrderedDict and how it relates to the built-in Python3.6+ dict

  • Python’s implementation of multi-sets, the Counter class

  • the ChainMap class

  • how to create custom dictionaries by inheriting from the UserDict class

  • how to serialize and deserialize dictionaries to JSON

  • the use of schemas in custom JSON deserialization

  • a brief introduction to some useful libraries such as JSONSchema, PyYaml and Serpy

***** Prerequisites *****

Please note that this is a relatively advanced Python course, and a strong knowledge of some topics in Python is required. 

Beyond the basics of Python (loops, conditional statements, exception handling, built-in data types, creating classes, etc), you should also have an in-depth understanding of the following topics:

  • functions and functional programming (recursion, *args, **kwargs, zip, map, sorted, any, all, etc)

  • lambdas, closures and decorators (including standard decorators such as @singledispatch, @wraps, etc)

  • iterables, iterators, generators and context managers

  • named tuples

  • variable scopes and namespaces (globals, locals, etc)

For this course you will also need to install some 3rd party libraries, so you need to be comfortable with doing this using the tool of your choice (e.g. pip, conda, etc)

Finally, most of the code in this course is illustrated using the freely available  Jupyter Notebooks, so you will need that as well.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Overview

Lecture 2: Prerequisites

Lecture 3: Course Slides

Chapter 2: Associative Arrays – Theory!

Lecture 1: Introduction

Lecture 2: Associative Arrays

Lecture 3: Hash Maps

Lecture 4: Python Dictionaries

Lecture 5: Python's hash() Function

Chapter 3: Dictionaries

Lecture 1: Introduction

Lecture 2: Creating Dictionaries – Lecture

Lecture 3: Creating Dictionaries – Coding

Lecture 4: Common Operations – Lecture

Lecture 5: Common Operations – Coding

Lecture 6: Dictionary Views – Lecture

Lecture 7: Dictionary Views – Coding

Lecture 8: Updating, Merging, and Copying – Lecture

Lecture 9: Updating, Merging, and Copying – Coding

Lecture 10: Custom Classes and Hashing – Lecture

Lecture 11: Custom Classes and Hashing – Coding

Chapter 4: Coding Exercises

Lecture 1: Exercises

Lecture 2: Solution 1

Lecture 3: Solution 2

Lecture 4: Solution 3

Lecture 5: Solution 4

Chapter 5: Sets

Lecture 1: Introduction

Lecture 2: Basic Set Theory

Lecture 3: Python Sets

Lecture 4: Creating Sets – Lecture

Lecture 5: Creating Sets – Coding

Lecture 6: Common Operations – Lecture

Lecture 7: Common Operations – Coding

Lecture 8: Set Operations – Lecture

Lecture 9: Set Operations – Coding

Lecture 10: Update Operations – Lecture

Lecture 11: Update Operations – Coding

Lecture 12: Copying Sets – Lecture

Lecture 13: Copying Sets – Coding

Lecture 14: Frozen Sets – Lecture

Lecture 15: Frozen Sets – Coding

Lecture 16: Dictionary Views – Lecture

Lecture 17: Dictionary Views – Coding

Chapter 6: Project 1

Lecture 1: Project 1 – Goals

Lecture 2: Project 1 – Solution

Chapter 7: Serialization and Deserialization

Lecture 1: Introduction

Lecture 2: Pickling – Lecture

Lecture 3: Pickling – Coding

Lecture 4: JSON Serialization – Lecture

Lecture 5: JSON Serialization – Coding

Lecture 6: Custom JSON Encoding – Lecture

Lecture 7: Custom JSON Encoding – Coding

Lecture 8: Using JSONEncoder – Lecture

Lecture 9: Using JSONEncoder – Coding

Lecture 10: Custom JSON Decoding – Lecture

Lecture 11: Custom JSON Decoding – Coding

Lecture 12: Using JSONDecoder – Lecture

Lecture 13: Using JSONDecoder – Coding

Lecture 14: JSON Schema

Lecture 15: Marshmallow –> Archived

Lecture 16: PyYaml

Lecture 17: Serpy

Chapter 8: Coding Exercises

Lecture 1: Exercises

Lecture 2: Solution 1

Lecture 3: Solution 2

Lecture 4: Solution 3

Chapter 9: Specialized Dictionaries

Lecture 1: Introduction

Lecture 2: DefaultDict – Lecture

Lecture 3: DefaultDict – Coding

Lecture 4: OrderedDict – Lecture

Lecture 5: OrderedDict – Coding

Lecture 6: OrderedDict and Python 3.6 Dicts

Lecture 7: Counter – Lecture

Lecture 8: Counter – Coding

Lecture 9: ChainMap – Lecture

Lecture 10: ChainMap – Coding

Lecture 11: UserDict – Lecture

Lecture 12: UserDict – Coding

Chapter 10: Coding Exercises

Lecture 1: Exercises

Lecture 2: Solution 1

Lecture 3: Solution 2

Lecture 4: Solution 3

Chapter 11: Python Updates

Lecture 1: Python 3.10

Lecture 2: Python 3.9

Lecture 3: Python 3.8 / 3.7

Chapter 12: Extras

Lecture 1: The MappingProxy Type

Lecture 2: Marshmallow

Instructors

Rating Distribution

  • 1 stars: 1 votes
  • 2 stars: 2 votes
  • 3 stars: 31 votes
  • 4 stars: 312 votes
  • 5 stars: 1358 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

You may also like

Fundamentals of Analyzing Real Estate Investments

Scrum Master I Prep & Mock Exams With AI update (Agile SM 1)

Leadership: Practical Leadership Skills