Ontwikkel je van Python Novice naar Pythonista

In this course, you will get started with Python, by installing and getting started with the software, as well as writing your first meaningful program and exploring important language constructs.

Learn to work with lists, tuples, and strings in Python. You will see the similarities and differences between tuples and lists and see how strings are essentially just a list of characters.

Learn about dictionary data type in Python. Dictionaries are associative containers used to store key-value pairs. Given a key, finding the associated value is optimized by Python to be extremely efficient.

Learn about copying operations on containers in Python. You will learn the subtle distinction between shallow and deep copies. Changes made to shallow copies affect the original whereas with deep copies do not.

Conditional Statements & Loops: If-else Control Structures in Python

Explore advanced Python function topics such as recursion, closures, using generator functions to generate sequences, and using decorators to add functionality to code.

• Practice novice Python development tasks such as formatting data types, implementing flow control and conditionals, copying containers and performing loops with list comprehension methods. Then, test your skills by answering assessment questions after converting data types, working with global and local variables within functions, invoking functions with varying parameters and implementing recursive functions and closures.
• This lab provides access to tools typically used when developing with Python, including:
• � Python
• � Anaconda
• � Jupyter Notebook + JupyterHub
• � Pandas, NumPy, SiPy
• � Seaborn Library
• � PyCharm IDE
• � Spyder IDE
• � MongoDB
• � MySQL
• � VS Code
• This lab is part of the Python Novice track of the Skillsoft Aspire Python Novice to Pythonista journey.

Final Exam: Python Novice will test your knowledge and application of the topics presented throughout the Python Novice track of the Skillsoft Aspire Python Novice to Pythonista Journey.

• Python includes functions and modules that simplify working with

• files. In this 11-video course, explore operations for standard
• text files and handling of formatted data such as JSON and CSV by
• using Python modules designed for such data. Learners begin with a
• look at some of the file operations in Python. Use Python's open
• function to open a file for reading, and differentiate between the
• read(), readline(), and readlines() functions. View differences
• between opening a file in write mode and append mode in Python.
• This leads on to distinguishing between the r+ and a+ modes to read
• from and write to a file; using load and loads functions of the
• json module to parse JSON data, and converting Python dictionaries
• and lists into JSON strings and files. Next, learn how to identify
• file formats that can be handled by the CSV module in Python, and
• convert Python dictionaries and lists into CSV files. The final
• tutorial concerns defining a customized file format, creating a CSV
• dialect, and using that to parse and write data.

• In this 11-video course, learners can examine different types of

• exceptions that can be raised in Python and how they can be handled
• with except blocks. Explore execution of Python scripts from the
• command line, including use and parsing of command-line arguments.
• To begin, use a try and except block to handle a Python exception,
• then learn how to handle exceptions that your code may raise.
• Explore how exceptions are defined in a hierarchy and how related
• exceptions are caught and handled. Next, define multiple except
• blocks to handle various exceptions that can be raised by code;
• convert code prototyped in a Jupyter notebook into a Python script
• that can be executed from a shell, and run code from the Python
• shell and execute single-line and multi-line commands. Learn about
• parsing command line arguments, and use the sys and argparse module
• to access command-line arguments to a Python script, then parse and
• use the arguments passed to a Python script from the command line.
• Finally, learn to define command-line arguments by using
• argparse.

Python Classes & Inheritance: Advanced Functionality Using Python Classes

Explore Python data structures and delve into the details of some of the basic data structures, such as linked lists, stacks, and queues.

Begin by examining operations that have different values of time complexity. Then delve into the implementation of some of the basic data structures, such as linked lists, stacks, and queues in Python.

Explore the workings of some of the most widely used sorting algorithms in Python and examine how their performance affects various measures.

Examine the Python implementation of common sorting algorithms such as Selection Sort, Bubble Sort, and Insertion Sort, as well as divide and conquer sorts such as Shell Sort, Merge Sort, and Quicksort.

Examine the theory around graph and tree data structures in Python. Explore binary search trees, different graph representations, and traversal operations on these data structures.

Discover how to implement trees and graphs and examine with the associated functions used to build and maintain these data structures in Python. In addition, explore algorithms for data structure traversal.

• Perform apprentice level Python development tasks such as file handling, implementing polymorphism, implementing special method names, as well as implementing an abstract class and using static methods. Then, test your skills by answering assessment questions after using a Python list as a stack, performing queue operations, implementing a graph as an adjacency matrix, and traversing a Binary Search Tree (BST).
• This lab provides access to tools typically used when developing with Python, including:
• � Python
• � Anaconda
• � Jupyter Notebook + JupyterHub
• � Pandas, NumPy, SiPy
• � Seaborn Library
• � PyCharm IDE
• � Spyder IDE
• � MongoDB
• � MySQL
• � VS Code
• This lab is part of the Python Apprentice track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Final Exam: Python Apprentice will test your knowledge and application of the topics presented throughout the Python Apprentice track of the Skillsoft Aspire Python Novice to Pythonista Journey.

The unittest framework (also known as PyUnit) is modeled on JUnit and simplifies the automation of tests for your Python applications. Discover the basic features of unittest such as the definition and execution of test cases and the selection of specific tests for an execution.

Discover some of the more advanced features of the Python unittest framework such as the use of fixture functions for common operations across tests, the definition and execution of test suites, and the simplification of writing test scripts using the PyCharm IDE.

The pytest module simplifies the definition and execution of unit tests and functional tests for Python code. Discover basic unit testing using asserts as well as the streamlining of tests using fixtures.

Discover how to use the Python Requests package to make different kinds of HTTP requests in order to request and submit data. Explore GET, POST, PUT, and other forms of requests and how to handle the responses.

Flask in Python: User Interactions in Flask Applications

Python Concurrent Programming: Multiprocessing in Python

• Perform journeyman level Python development tasks such as testing with pytest, making HTTP requests, serving HTTP requests with a Flask endpoint and rendering a jinja template. Then, test your skills by answering assessment questions after using multithreading and multiprocessing with Python, processing data in a queue and creating and executing a coroutine with Asyncio.
• This lab provides access to tools typically used when developing with Python, including:
• � Python
• � Anaconda
• � Jupyter Notebook + JupyterHub
• � Pandas, NumPy, SiPy
• � Seaborn Library
• � PyCharm IDE
• � Spyder IDE
• � MongoDB
• � MySQL
• � VS Code
• This lab is part of the Python Journeyman track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

This final exam will test your understanding and application of the skills covered in the Python Journeyman track of the Python Novice to Pythonista Aspire Journey.

PyCharm is one of the most intuitive and feature-rich IDEs available for Python development. Explore some of the important features of this IDE, such as debugging with breakpoints, Python package installation, and even customizing syntax highlighting.

Sockets are a means by which two processes or applications can communicate information. Explore the basics of socket programming and see how small bits of data, ranging from simple text to Python objects, can be transferred between applications via sockets.

• Explore how the SOLID principles can help to make software

• designs easier to understand and maintain. Examine the five SOLID
• principles - Single Responsibility, Open/Closed, Liskov's
• Substitution, Interface Segregation, and Dependency Inversion - as
• well as the creational, structural, and behavioral design
• patterns.

Explore the details and implementation of five commonly used creational design patterns - Singleton, Factory, Abstract Factory, Builder, and Object Pool.

• Explore the design and implementation of five commonly used

• structural design patterns - Adapter, Decorator, Façade, Proxy, and
• Flyweight. Examine how these patterns can be used for tasks like
• working with legacy components, dynamically adding
• responsibilities, offering a simple client interface, controlling
• object access, and efficiently using lightweight resources.

• Explore the design and implementation of five commonly used

• behavioral design patterns - Strategy, Chain of Responsibility,
• Observer, Command, and Iterator. Examine how these patterns can be
• used in Python built-in functions, in simple and complex use cases,
• for performing undo operations, and with Python special
• methods.

• Perform development tasks expected of Pythonistas such as debugging with PyCharm, working with spreadsheet data and creating charts, and writing applications that can communicate using TPC sockets. Then, test your skills by answering assessment questions after working with Singleton, Observer and Factory design patterns and implementing iterators using special methods.
• This lab provides access to tools typically used when developing with Python, including:
• � Python
• � Anaconda
• � Jupyter Notebook + JupyterHub
• � Pandas, NumPy, SiPy
• � Seaborn Library
• � PyCharm IDE
• � Spyder IDE
• � MongoDB
• � MySQL
• � VS Code
• This lab is part of the Pythonista track of the Skillsoft Aspire Python Apprentice to Pythonista journey.

Final Exam: Pythonista will test your knowledge and application of the topics presented throughout the Pythonista track of the Skillsoft Aspire Python Novice to Pythonista Journey.