Learning Path: Django Unlocked

Course

Online

£ 40 + VAT

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Build robust production-ready web applications in PythonUnleash Django and build real-world web applications with your existing Python skills in this cutting-edge Learning Path. With some advanced coverage of core Python to start off, you’ll be building live examples that you can modify and extend right away.About the AuthorDaniel Arbuckle holds a Doctorate in Computer Science from the University of Southern California, where he specialized in robotics and was a member of the nanotechnology lab. He now has more than ten years behind him as a consultant, during which time he’s been using Python to help an assortment of businesses, from clothing manufacturers to crowdsourcing platforms. Python has been his primary development language since he was in High School. He’s also an award-winning teacher of programming and computer science.
Matthew Nuzum has been developing web applications since 1999 and has worked for several start-ups including Canonical, the makers of Ubuntu, as well as Fortune 500 companies. He has a passion for helping others learn new technologies and has written numerous tutorials and help documents as well as running a web-focused user group based in his hometown of Des Moines.
Kevin Veroneau is a very active Python and Django developer who has worked for many start-ups, has an active Python blog, and has worked on a magnitude of Python projects over the years.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Become proficient at creating tools and utility programs in Python
Take your first step towards creating efficient apps by installing Django quickly
Build a powerful database to store your app data in an organized way
Explore Django’s automated admin interface to manage your app’s content
Secure your app data by validating users using login and authentication
Explore Django’s automated admin interface to manage your app’s content
Utilize free debugging tools to identify and resolve potential problems
Use complex class-based views to implement a variety of functionalities in Django
Create and use your own custom middleware for a Django app
Learn how to manage and maintainyour apps

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Install
  • Writing
  • Web
  • Layout
  • Benefits
  • Access

Course programme

Mastering Python 37 lectures 02:55:17 Mastering Python - The Course Overview Get a high-level view of what this course will do for you.
  • A quick overview of each section
  • A preview of the results
Downloading and Installing Python Get a functional Python development environment.
  • Picking up a suitable version for working
  • Setting up the environment variables
  • Making sure everything works as expected
Using the Command Line and the Interactive Shell Learn how to perform quick experiments and access documentation.
  • Getting to know the operating system prompt
  • Accessing the Python prompt
  • Accessing the documentation with the help function
Installing Packages with pip Learn how to easily download and install third-party packages.
  • Running through the basic usage of packages
  • Installing packages in the home directory
  • Managing and removing installed packages
Finding Packages in the Python Package Index Discover available resources so that you don't have to reinvent the wheel.
  • Using the web interface
  • Using pip's search command
  • About licenses and legalities
Creating an Empty Package Learn the filesystem structure that defines a Python package.
  • Creating the package folder
  • Creating the __init__.py file
  • Importing the new package
Adding Modules to the Package Add code files to the package.
  • Selecting filenames
  • The namespace packages
  • Package structure versus package API
Importing One of the Package's Modules from Another Combine code from multiple modules.
  • Importing the syntax
  • Dealing with import cycles
  • Differences between Python 2 and Python 3
Adding Data Files to the Package Include data alongside the modules in your package.
  • Where to store the files
  • Using the pkgutil.get_data command
  • Transforming the data into text
PEP 8 and Writing Readable Code Make your code more readable for yourself and others using Python's communal coding standard.
  • Spaces versus tabs
  • Understanding the code layout
  • Using naming conventions to perfection
Using Version Control Manage changes, versions, and branches in your source code.
  • Undoing changes you've made to the code
  • Working with branches
  • Understanding merging
Using venv to Create a Stable and Isolated Work Area Create a development area that remains stable for the duration of your development process.
  • Advantages of development in a virtual environment
  • Setting up a virtual environment
  • Activating and using a virtual environment
Getting the Most Out of docstrings Part 1 – PEP 257 and Sphinx Format your docstrings to maximize their usefulness.
  • Understanding the basic layout
  • Using the reStructuredText command
  • Exporting documentation to HTML
Getting the Most Out of docstrings Part 2 – doctest Run the examples in your docstrings as tests.
  • Benefits of executing examples from docstrings
  • How to write the examples
  • How to run the examples
Making a Package Executable via python – m Create a package entry point to make the package executable.
  • Using __main__.py
  • Using if __name__ == '__main__'
  • An interactive software pipeline – the first step
Handling Command-line Arguments with argparse Create full-featured command-line parsers.
  • Understanding the basic usage of the command line arguments
  • Adding command line switches and arguments
  • An interactive software pipeline – the second step
Text-mode Interactivity Get the input and provide the output while the program is running.
  • Using the print(), input(), getpass, and pprint commands
  • Using the cmd module
  • An interactive software pipeline – the third step
Executing Other Programs Execute and interact with other programs.
  • Using the call(), check_call(), and check_output() functions
  • Understanding the Popen class
  • An interactive software pipeline – the fourth step
Using Shell Scripts or Batch Files to Launch Programs Reduce the effort needed to run executable packages.
  • Launching via shell script
  • Launching via a batch file
  • An interactive software pipeline – the last step
Using concurrent.futures Use a high-level interface to distribute computational tasks to worker processes and collect the results.
  • Understanding the strengths and weaknesses of multiprocess computation in Python
  • Using the ProcessPoolExecutor and Future objects
  • Using the wait and as_completed functions
Using Multiprocessing Use a mid-level interface to create cooperative parallel processes.
  • Launching processes
  • Sending data between processes
  • Keeping processes synchronized
Understanding Why Asynchronous I/O Isn't Like Parallel Processing The API looks a lot like concurrent.futures, but it's doing something very different.
  • What cooperative multitasking is
  • What yield from means
  • What all this means for I/O bound programs
Using the asyncio Event Loop and Coroutine Scheduler How to get the asyncio scheduler running and add asynchronous tasks.
  • Creating coroutines
  • Creating an event loop, adding tasks, running the loop, and shutting it down
  • Checking out an example skeleton by running several tasks until you decides to end the program
Futures How asyncio futures behave and what to do with them.
  • Learning the normal usage pattern
  • Understanding iteration, coroutines, and Futures
  • Coroutines versus functions that return Futures
Making Asynchronous Tasks Interoperate How to use synchronization, waiting, and communication channels.
  • What Lock and Semaphore is
  • Using the as_completed, gather, wait, and wait_for functions
  • Learning the use of Queue, LifoQueue, PriorityQueue, and JoinableQueue
Communicating across the Network Easily use stream sockets to communicate.
  • Creating a client-side connection
  • Creating a server-side connection
  • Running an example ping-pong client and server
Using Function Decorators Automatically post-process functions.
  • Adding attributes to a function
  • Wrapping a function
  • Knowing more about decorators that accept parameters
Using Function Annotations Add new semantics to functions.
  • Adding annotations to a function
  • How to access the annotations
  • Using annotations in decorators
Using Class Decorators Automatically post-process classes.
  • Manipulating a class
  • Wrapping a class
  • Using a class as declarative data
Using Metaclasses Change what it means to be a class.
  • Classes that are not instances of “type”
  • Altering the class's namespace
  • Inheritable special behavior
Using Context Managers Set up special rules for regions of code.
  • Running code when execution enters and leaves a block
  • Using the @contextlib.contextmanager decorator
  • Writing context managers as classes
Using Descriptors Control what happens when attributes are accessed.
  • Running code when an attribute is accessed
  • Using @property
  • Writing descriptors as classes
Understanding the Principles of Unit Testing Get more benefits out of testing with less work.
  • Letting the computer do the work
  • Keeping tests localized
  • Letting the tests tell us what we need to work on
Using unittest Write tests, run them, and understand the results.
  • Running some basic tests
  • Using the assertion methods
  • Checking out the test fixtures
Using unittest.mock Use mock objects to keep tests local.
  • Simple mock objects
  • Checking for proper behavior
  • Using patch
Using unittest's Test Discovery Run tests even more easily with test discovery.
  • Letting unittest find the tests
  • Controlling how tests are found
  • Modules are imported when they are searched for tests
Using Nose for Unified Test Discovery and Reporting Take advantage of more complete test discovery and integrated reporting.
  • Letting Nose find even more tests
  • Code coverage
  • Running tests in multiple processes
Mastering Python. 37 lectures 02:55:17 Mastering Python - The Course Overview Get a high-level view of what this course will do for you.
  • A quick overview of each section
  • A preview of the results
Downloading and Installing Python Get a functional Python development environment.
  • Picking up a suitable version for working
  • Setting up the environment variables
  • Making sure everything works as expected
Using the Command Line and the Interactive Shell Learn how to perform quick experiments and access documentation.
  • Getting to know the operating system prompt
  • Accessing the Python prompt
  • Accessing the documentation with the help function
Installing Packages with pip Learn how to easily download and install third-party packages.
  • Running through the basic usage of packages
  • Installing packages in the home directory
  • Managing and removing installed packages
Finding Packages in the Python Package Index Discover available resources so that you don't have to reinvent the wheel.
  • Using the web interface
  • Using pip's search command
  • About licenses and legalities
Creating an Empty Package Learn the filesystem structure that defines a Python package.
  • Creating the package folder
  • Creating the __init__.py file
  • Importing the new package
Adding Modules to the Package Add code files to the package.
  • Selecting filenames
  • The namespace packages
  • Package structure versus package API
Importing One of the Package's Modules from Another Combine code from multiple modules.
  • Importing the syntax
  • Dealing with import cycles
  • Differences between Python 2 and Python 3
Adding Data Files to the Package Include data alongside the modules in your package.
  • Where to store the files
  • Using the pkgutil.get_data command
  • Transforming the data into text
PEP 8 and Writing Readable Code Make your code more readable for yourself and others using Python's communal coding standard.
  • Spaces versus tabs
  • Understanding the code layout
  • Using naming conventions to perfection
Using Version Control Manage changes, versions, and branches in your source code.
  • Undoing changes you've made to the code
  • Working with branches
  • Understanding merging
Using venv to Create a Stable and Isolated Work Area Create a development area that remains stable for the duration of your development process.
  • Advantages of development in a virtual environment
  • Setting up a virtual environment
  • Activating and using a virtual environment
Getting the Most Out of docstrings Part 1 – PEP 257 and Sphinx Format your docstrings to maximize their usefulness.
  • Understanding the basic layout
  • Using the reStructuredText command
  • Exporting documentation to HTML
Getting the Most Out of docstrings Part 2 – doctest Run the examples in your docstrings as tests.
  • Benefits of executing examples from docstrings
  • How to write the examples
  • How to run the examples
Making a Package Executable via python – m Create a package entry point to make the package executable.
  • Using __main__.py
  • Using if __name__ == '__main__'
  • An interactive software pipeline – the first step
Handling Command-line Arguments with argparse Create full-featured command-line parsers.
  • Understanding the basic usage of the command line arguments
  • Adding command line switches and arguments
  • An interactive software pipeline – the second step
Text-mode Interactivity Get the input and provide the output while the program is running.
  • Using the print(), input(), getpass, and pprint commands
  • Using the cmd module
  • An interactive software pipeline – the third step
Executing Other Programs Execute and interact with other programs.
  • Using the call(), check_call(), and check_output() functions
  • Understanding the Popen class
  • An interactive software pipeline – the fourth step
Using Shell Scripts or Batch Files to Launch Programs Reduce the effort needed to run executable packages.
  • Launching via shell script
  • Launching via a batch file
  • An interactive software pipeline – the last step
Using concurrent.futures Use a high-level interface to distribute computational tasks to worker processes and collect the results d and install third-party...

Additional information

A working knowledge of Python

Learning Path: Django Unlocked

£ 40 + VAT