Python Programming Training
Learn about Python from Instructors with Real World Expertise.
This 5 day Python Programming training is in-depth instructor-led training (ILT).
Monitoring Training Overview:
This 5 day Python Programming training is in-depth instructor-led training (ILT). It covers all the core features of Python Programming, including basic types, sequence types, I/O Operations, control structures, regular expressions, development tools, object-oriented programming, database API and more.
Target Audience:
- System Administrators
- Developers
- DevOps
- Those wanting to understand and use Perl.
Structure: 50% theory 50% hands on lab exercises
Prerequisites: Proficiency with the Linux CLI. A broad understanding of Linux system administration.
Duration: 5 Days
Course Outline:
Introduction
Overview:
- Why python?
- Executing Python Code
- Implications of PVM
- Execution model variations
- PyPy, Jython, IronPython, frozen binaries
- Running python scripts
- Python CLI features
- Very basic control structures
- If/elif/else
- While/else
- Try/except/finally
- Function syntax
- Vargs,key-value arguments
- Function defaults
- Type enforcements for functions
- Scopes, the LEGB rule
- Debugging python scripts
- Pudb,ipdb
- Modules/packages
- Python search path for modules
- Creating simple modules
- Creating packages
Basic Types
Overview:
- Basic types: numeric
- Int, float, complex
- Python3 changes on number arithmetic
- Basic types: strings
- String vs, Unicode (python2)
- ByteString vs. String (python3)
- Raw strings
- Printing formatted output
- Dealing with user input
- String type
- String manipulation functions
- StringIO
- The unicodedata module
Labs:
- Simple Scripts
Sequence Types
Overview
- Sequence types
- Mutables vs. Inmutables
- Working with list, array, bytearray
- Slice operator
- Interable objects, iterator
- List/sequence functions
- Manipulation elemens (append,extend, pop)
- Sorting
- The range/xrange function
- The dictionary type
- Restrictions
- Getting keys/values/items
- Dictionary iterators
- Defaultdict, Counter
- Using set/frozenset type
- Set type features
- Set operations
- Other sequence types/functions
- Basic aggregations: min, max, sum
- The filter function
- The map function
- The reduce function
- The collections module
- The itertools module
- Differences: python2 vs. python3
I/O Operation
Overview:
- Basic file operations
- Open, io.open, codecs.open
- Iterating file objects
- Fileinput module
- Path operations
- Os module functions
- Os.path
- Os.listdir
- Os.walk
- Glob module functions
- Glob.glob
- Glob.iglob
- Communicate with external processes
- Limitations of os.call, os.popen*
- Subprocess module
- Call
- Popen
- Parsing command line arguments
- Getopt module
- Argparse module
Additional Control Structures
Overview:
- Context manager and with/as
- Comprehensions
- List comprehensions
- Dictionary comprehensions
- Generator comprehensions
- Embedded comprehensions
- Creating Generator Functions
Lab:
- Creating Generator Functions
Regular Expressions in Python
Overview
- Regular expression elements
- Character ranges
- Multipliers
- Anchors
- Re module functions
- Match vs search
- Findall vs finditer
- Split
- Sub
- Compile
- Use cases for flags
- Single vs multi-line match
- Unicode character ranges
- Compile vs flags
- Additional features in regular expressions
- Back-referencing
- Back-referencing in match
- Back-referencing in sub
- Capture groups
- Referencing groups
- Named groups
- Embedded groups
- Back-referencing
- Greediness
Lab: Regular Expressions
Python Development Tools
Overview
- Document your code
- Creating docstrings
- Using Python doc framework Sphinx
- Testing frameworks
- The importance of testing in Python
- Doctest
- Unittest
- Unittest + mock
- Nose
- Logging in python
- Module logging
- Logging configuration format
- Parallel processing
- Threading module
- Multiprocessing module
Advanced Topics
Overview
- Decorator
- Simple decorators
- Decorators with arguments
- Python built-in function/class decorators
- Performance tips
Object-Oriented Programming in Python
Overview
- OOP basics
- Compare OO features of Python and Java/C++
- Python2 vs python3 classes
- New-style vs old-style classes
- __slots__
- Member functions
- Contructors
- Destructors
- Writing member functions
- Member attributes
- General implementation of instance attributes
- Class static attributes
- Getter/setter methods
- Access control solutions
- The property class
- The descriptor model
- Operators
- Operator related functions
- __str__ vs __repr__
- __call__
- Class/function decorators
- @staticmethod, @classmethod
- @abstractmethod, @abstractproperty
- @total ordering
- Python class template
- Inheritance
- Abstract template classes
- Metaclass
Lab:
- Python OO
Python Database API
Overview
- Connecting to DB API compliant Relational Database Management Systems
- Creating and populating tables
- Retrieving data records
- Executing parametrized queries
- Exporting and importing table data with Postgresql
Creating Graphical User Interfaces with Python/Tkinter
Overview
- Tkinter widgets and their standard attributes ◦ Dimensions
- Colors
- Fonts
- Anchors
- Relief styles
- Bitmaps
- Cursors
- Organizing widgets in the parent widget area
- Using pack
- Using grid
- Using place
Introduction to the Python Django WEB Application Framework
Overview
- Architecture
- Creating a Hello world project
- Managing settings
- URL patterns
Lab:
- Using Frameworks