- Description
- Python 3 Essentials - Course
- Advanced Python - Course
- Python Standard Library Essential Training - Course
- Python Data Structures: Stacks, Queues, and Deques - Course
- Python Generators - Course
- Local setup
- License
Follow a series of courses to train and improve Python skills.
https://www.linkedin.com/learning/python-essential-training-2/
The code for this course lives on the essentials folder.
This course covers the basics of the language syntax and usage, as well as advanced features such as objects, generators, and exceptions. Learn how types and values are related to objects; how to use control statements, loops, and functions; and how to work with generators and decorators.
- Python anatomy
- Types and values
- Conditionals and operators
- Building loops
- Defining functions
- Python data structures: lists, tuples, sets, and more
- Creating classes
- Handling exceptions
- Working with strings
- File input/output (I/O)
- Creating modules
- Integrating a database with Python db-api
https://www.linkedin.com/learning/advanced-python/
The code for this course lives on the advanced folder.
This courses shows shows to leverage Python features such as object-oriented special class methods, using logging to track performance and user activity, how to port code from Python 2 to 3, and how to make the code more efficient and easier to read and maintain. Also shows how to manipulate data, build custom classes and functions, create lists, and write more elegant, optimized code.
- Truth value testing
- Template strings for string formatting
- Generic built-ins: any, all, sum, min, max
- Iterators: next, iter, enumerate, zip, itertools
- Transforms: sorted, filter, map
- Advanced Python functions: docstrings, variable argument lists, lambdas, keyword-only arguments
- Advanced collections: namedtuple, defaultdict, Counter, OrderedDict, deque
- Advanced classes and objects: enums, custom string and bytes representation of objects, computed attributes, support for numerical operations and support for comparisons
- Logging
- Python comprehensions: list, dictionary, and set
https://www.linkedin.com/learning/python-standard-library-essential-training/
The code for this course lives on the standard_library folder.
Understand more about the library of pre-built code — known as the Python standard library — that’s distributed along with the language. See how the library can help to work with numbers, calculate and format dates and times, parse HTML, and more.
- Basic string operations
- Searching strings with str functions
- Manipulating data with str functions, justifications, etc
- Sorting with key parameters, functions from the operator module, etc
- Using efficient arrays for enforcing the type rules of a given data set
- Using the Array bisection algorithm to for maintaining a list in sorted order without having to sort the list after each insertion
- Creating temporary files and directories
- Reading and writing CSV and ZIP files
- Generating unique identifiers
- Calculating dates and times
- Retrieving internet data using the urllib module
- Parsing html
- Working with json using the json module
https://www.linkedin.com/learning/python-data-structures-stacks-queues-and-deques/
The code for this course lives on the data_structures folder.
Learn how to use Python to build the top three linear data structures: stacks, queues, and deques. Learn how to define each class and use Python's built-in methods to accomplish the necessary behaviors, such as push, pop, and peek; enqueue and dequeue; and add_front and remove_rear.
- Abstract types and data structures
- Stacks as a linear abstract data type
- Creating the Stack class and its methods
- Adding items to the top and bottom of a stack
- Creating the Queue class and its methods
- Manipulating items in a queue
- Creating the Dequeue class and its methods
- Adding and removing items from a dequeue
https://www.linkedin.com/learning/learning-python-generators/
The code for this course lives on the generators folder.
Learn about using generators as a way to iterate through large and complex data sets.
- How to build a basic generator function
- Use generator expressions and objects
- How generators work behind the scenes to power context managers and coroutines
Follow the instructions to get the project up and running for local development and testing purposes.
- Install python 3: https://www.python.org/downloads/.
- Configure the IDE Interpreter to use Python 3 and setup the run configuration: https://www.jetbrains.com/help/pycharm/creating-and-editing-run-debug-configurations.html?keymap=secondary_macos.
- Ideally create a dedicated virtual environment for the project and use it as the project interpreter in the IDE.
This project is licensed under the terms of the MIT License. Please see LICENSE for details.