1. Entry Test

Entry Test

• 1.1. Entry Exam
  • 1.1.1. List[tuple] to List[dict]
  • 1.1.2. Get elements from nested data structure
  • 1.1.3. /etc/hosts - parsing to List[dict]

2. Functions

Functions

• 2.1. Generators
  • 2.1.1. Generator expressions vs. Comprehensions
  • 2.1.2. Lazy evaluation
    • 2.1.2.1. Declaring generators
    • 2.1.2.2. Evaluating generator instantly
    • 2.1.2.3. Evaluate generator iteratively
    • 2.1.2.4. Halting iteration
    • 2.1.2.5. Halting and resuming iteration
    • 2.1.2.6. What is the difference?
    • 2.1.2.7. Which one is better?
  • 2.1.3. yield Operator
  • 2.1.4. Built-in generators
    • 2.1.4.1. zip()
    • 2.1.4.2. map()
    • 2.1.4.3. filter()
  • 2.1.5. Assignments
    • 2.1.5.1. Generators vs. Comprehensions - iris
    • 2.1.5.2. Generators vs. Comprehensions - passwd
• 2.2. Defining function with arbitrary number of arguments
  • 2.2.1. Recap information about function parameters
  • 2.2.2. Arbitrary number of positional arguments
  • 2.2.3. Arbitrary number of keyword arguments
  • 2.2.4. Arbitrary number of positional and named arguments
  • 2.2.5. Keyword only
  • 2.2.6. Use cases
  • 2.2.7. Assignments
    • 2.2.7.1. Average
    • 2.2.7.2. args
    • 2.2.7.3. args and kwargs
• 2.3. Passing many arguments
  • 2.3.1. Arbitrary number of positional arguments
  • 2.3.2. Arbitrary number of keyword arguments
  • 2.3.3. Arbitrary number of positional and keyword arguments
  • 2.3.4. Examples
    • 2.3.4.1. Creating complex numbers
    • 2.3.4.2. Vectors
    • 2.3.4.3. Print formatting
    • 2.3.4.4. Common configuration
    • 2.3.4.5. Calling function with all variables from higher order function
    • 2.3.4.6. Proxy functions
    • 2.3.4.7. Decorators
  • 2.3.5. Assignments
    • 2.3.5.1. Iris
• 2.4. Callable
  • 2.4.1. First-class Function
  • 2.4.2. Aliases
  • 2.4.3. Callable
  • 2.4.4. Assignments
• 2.5. Closures
  • 2.5.1. Nested Function
  • 2.5.2. What is closure?
• 2.6. Decorator
  • 2.6.1. What is decorator
  • 2.6.2. Definition
    • 2.6.2.1. Decorating functions
    • 2.6.2.2. Decorating classes
    • 2.6.2.3. Method decorator
    • 2.6.2.4. Decorator with arguments
  • 2.6.3. Example
    • 2.6.3.1. Debug
    • 2.6.3.2. Cache
    • 2.6.3.3. File exists
    • 2.6.3.4. Deprecated
    • 2.6.3.5. Timeout
    • 2.6.3.6. Cache
  • 2.6.4. functools
    • 2.6.4.1. @functools.wraps(fn)
    • 2.6.4.2. @functools.cached_property(fn)
    • 2.6.4.3. LRU (least recently used) cache
    • 2.6.4.4. memoize
  • 2.6.5. Przykład
    • 2.6.5.1. Example 1
    • 2.6.5.2. Example 2
    • 2.6.5.3. Example 3
    • 2.6.5.4. Use cases
  • 2.6.6. Decorator library
  • 2.6.7. Assignments
    • 2.6.7.1. Memoization
    • 2.6.7.2. Prosty dekorator
    • 2.6.7.3. Type Checking Decorator

3. Performance

Performance

• 3.1. Performance Optimization
  • 3.1.1. PyPy
  • 3.1.2. Seven strategies
    • 3.1.2.1. Line Profiling
    • 3.1.2.2. Numpy vectorization
    • 3.1.2.3. Specialized data structures
    • 3.1.2.4. Cython
    • 3.1.2.5. Numba
    • 3.1.2.6. Dask
    • 3.1.2.7. Find existing implementation
  • 3.1.3. Contains
    • 3.1.3.1. Use set instead of list
  • 3.1.4. Use list.append() instead of str + str
  • 3.1.5. Range between two float
  • 3.1.6. Inne
  • 3.1.7. Further Reading
  • 3.1.8. Assignments
    • 3.1.8.1. Memoization
• 3.2. Micro-benchmarking
  • 3.2.1. Evaluation
  • 3.2.2. timeit
    • 3.2.2.1. Programmatic use
    • 3.2.2.2. Console use
  • 3.2.3. Case Studies - Unique Keys
    • 3.2.3.1. Append if object not in the list
    • 3.2.3.2. Append to list and deduplicate at the end
    • 3.2.3.3. Add to set
    • 3.2.3.4. Update set
    • 3.2.3.5. Set Comprehension
    • 3.2.3.6. Add to Set Comprehension
    • 3.2.3.7. Update Set Comprehension
  • 3.2.4. Case Study - Fibonacci
    • 3.2.4.1. Without cache
    • 3.2.4.2. Cache contains
    • 3.2.4.3. Cache get
    • 3.2.4.4. Cache contains with exceptions
    • 3.2.4.5. Adding cache layer
    • 3.2.4.6. Get from cache
  • 3.2.5. References
• 3.3. Profiling
  • 3.3.1. What's that?
  • 3.3.2. What to measure?
  • 3.3.3. Profiling with IDE
  • 3.3.4. Profiling with cProfile
• 3.4. Compilers and interpreters
  • 3.4.1. Interpreters
    • 3.4.1.1. cPython
    • 3.4.1.2. Cython
    • 3.4.1.3. PyPy
    • 3.4.1.4. IronPython
    • 3.4.1.5. Jython
    • 3.4.1.6. Micropython
    • 3.4.1.7. Inne
  • 3.4.2. Compiling
• 3.5. Collections
  • 3.5.1. OrderedDict
  • 3.5.2. namedtuple
  • 3.5.3. collections.Counter
• 3.6. C Types
  • 3.6.1. Workflow
    • 3.6.1.1. Code
    • 3.6.1.2. Build
    • 3.6.1.3. Run
  • 3.6.2. Arguments
  • 3.6.3. Use cases
    • 3.6.3.1. Example 1
    • 3.6.3.2. Example 2
    • 3.6.3.3. Example 3
    • 3.6.3.4. Example 4
    • 3.6.3.5. Multi OS code
    • 3.6.3.6. Overflow
  • 3.6.4. Assignments
    • 3.6.4.1. C Types
• 3.7. C Modules
  • 3.7.1. Code
  • 3.7.2. Compile
    • 3.7.2.1. setup.py
    • 3.7.2.2. Execute
  • 3.7.3. Run
  • 3.7.4. Assignments
    • 3.7.4.1. C Modules

4. OOP Paradigm

OOP Paradigm

• 4.1. Static and Dynamic Fields
  • 4.1.1. Static Fields
  • 4.1.2. Dynamic Fields
  • 4.1.3. Static vs. Dynamic Fields
• 4.2. Inheritance vs. Composition
  • 4.2.1. Problem with inheritance
  • 4.2.2. Multi level inheritance problem
  • 4.2.3. Composition using Mixin classes
• 4.3. Method Resolution Order
  • 4.3.1. Inheritance Method Resolution
  • 4.3.2. Inheritance Diamond
• 4.4. Relations
  • 4.4.1. Relations
  • 4.4.2. Assignments
    • 4.4.2.1. Defining Classes
    • 4.4.2.2. Basic Address Book
• 4.5. Polymorphism
  • 4.5.1. Switch
  • 4.5.2. Polymorphism on Function
  • 4.5.3. Polymorphism on Classes
• 4.6. Dynamic Typing
  • 4.6.1. Duck typing
  • 4.6.2. Everything is an object
    • 4.6.2.1. Object properties
    • 4.6.2.2. Object methods
    • 4.6.2.3. Injecting properties
    • 4.6.2.4. Injecting methods
  • 4.6.3. Monkey Patching
    • 4.6.3.1. Recap information about classes and objects
    • 4.6.3.2. Injecting fields
    • 4.6.3.3. Injecting methods
    • 4.6.3.4. Use case
• 4.7. New and Old style classes
  • 4.7.1. Rationale
    • 4.7.1.1. New Style Class
    • 4.7.1.2. Old Style classes
    • 4.7.1.3. Python 2 vs 3
• 4.8. Interface
  • 4.8.1. What it is?
  • 4.8.2. When use it?
  • 4.8.3. Example
• 4.9. Abstract classes
  • 4.9.1. What it is?
  • 4.9.2. When use it?
  • 4.9.3. Abstract classes and methods
• 4.10. Good Engineering Practises
  • 4.10.1. Tell - don't ask
  • 4.10.2. Objects and instances
  • 4.10.3. S.O.L.I.D.
    • 4.10.3.1. Single responsibility principle
    • 4.10.3.2. Open/closed principle
    • 4.10.3.3. Liskov substitution principle
    • 4.10.3.4. Interface segregation principle
    • 4.10.3.5. Dependency inversion principle
  • 4.10.4. GRASP
• 4.11. Exam
  • 4.11.1. Dragon (version beta)

5. OOP Protocols

OOP Protocols

• 5.1. Iterators
  • 5.1.1. Protocol
  • 5.1.2. Mechanism
    • 5.1.2.1. For loop
    • 5.1.2.2. Intuitive implementation of the for loop
  • 5.1.3. Iterating over objects
    • 5.1.3.1. Iterating sequences
    • 5.1.3.2. Iterating over dict
    • 5.1.3.3. Iterating over str
  • 5.1.4. Own Implementation
  • 5.1.5. itertools
    • 5.1.5.1. chain()
    • 5.1.5.2. cycle()
  • 5.1.6. Assignments
    • 5.1.6.1. Range
    • 5.1.6.2. Own implementation
• 5.2. Context Managers
  • 5.2.1. Protocol
  • 5.2.2. Application
  • 5.2.3. Implementation
  • 5.2.4. Examples
    • 5.2.4.1. Files
    • 5.2.4.2. Database
    • 5.2.4.3. Lock
  • 5.2.5. Contextmanager decorator
    • 5.2.5.1. contextmanager decorator
    • 5.2.5.2. ContextDecorator class
    • 5.2.5.3. Use Case
  • 5.2.6. Assignments
    • 5.2.6.1. Buffered file
• 5.3. staticmethod
  • 5.3.1. Rationale
  • 5.3.2. Application
  • 5.3.3. Implementation
  • 5.3.4. Use case
  • 5.3.5. Example
• 5.4. classmethod
  • 5.4.1. What it is?
  • 5.4.2. When use it?
  • 5.4.3. Example
  • 5.4.4. Assignments
    • 5.4.4.1. Pickle
• 5.5. Properties
  • 5.5.1. Accessing fields
    • 5.5.1.1. Setter and Getter methods
    • 5.5.1.2. Rationale for setter and getter methods
    • 5.5.1.3. Direct attribute access
  • 5.5.2. Properties
    • 5.5.2.1. Rationale
    • 5.5.2.2. Property class
    • 5.5.2.3. Property decorator
    • 5.5.2.4. Creating properties with property class
    • 5.5.2.5. Creating properties with @property decorator
  • 5.5.3. Use Cases
    • 5.5.3.1. Getter
    • 5.5.3.2. Setter
    • 5.5.3.3. Deleter
  • 5.5.4. Assignments
    • 5.5.4.1. Immutable classes
• 5.6. Setattr, Getattr
  • 5.6.1. Built-in Functions
  • 5.6.2. Protocol
  • 5.6.3. __setattr__()
  • 5.6.4. __delattr__()
  • 5.6.5. __getattribute__()
  • 5.6.6. __getattr__()
  • 5.6.7. hasattr()
  • 5.6.8. Assignments
    • 5.6.8.1. Immutable classes
• 5.7. Descriptor
  • 5.7.1. Protocol
  • 5.7.2. Rationale
  • 5.7.3. Builtin Descriptor Object Examples
  • 5.7.4. Example
    • 5.7.4.1. Outside class
    • 5.7.4.2. Inside class
  • 5.7.5. Case Study
    • 5.7.5.1. Temperature Conversion
    • 5.7.5.2. Timezone Conversion
  • 5.7.6. Assignments
    • 5.7.6.1. Temperature
    • 5.7.6.2. Geographic Coordinates

6. Object Oriented Programming

OOP Advanced

• 6.1. Object initialization
  • 6.1.1. __call__()
  • 6.1.2. __new__()
  • 6.1.3. __init__()
  • 6.1.4. Example usage
  • 6.1.5. Returning values
    • 6.1.5.1. Missing return from constructor
    • 6.1.5.2. Return invalid from constructor
    • 6.1.5.3. Return invalid from initializer
  • 6.1.6. Examples
  • 6.1.7. Initial arguments mutability and shared state
    • 6.1.7.1. Bad
    • 6.1.7.2. Good
  • 6.1.8. Do not run methods in __init__()
• 6.2. Placeholder class
  • 6.2.1. Proxy methods
  • 6.2.2. Flat Problem
  • 6.2.3. Nested Problem
  • 6.2.4. Placeholder class
• 6.3. Object Identity
  • 6.3.1. id()
  • 6.3.2. hash()
  • 6.3.3. String interning
  • 6.3.4. is
    • 6.3.4.1. Test if empty
    • 6.3.4.2. Test if value is equal
    • 6.3.4.3. Using is in script
    • 6.3.4.4. Using is in REPL (evaluated line by line)
    • 6.3.4.5. Using is in REPL (evaluated at once)
• 6.4. Slots
  • 6.4.1. Using
  • 6.4.2. __slots__ and __dict__
  • 6.4.3. Inheritance
• 6.5. Metaclass
  • 6.5.1. Metaclass mechanism
    • 6.5.1.1. What are Metaclasses?
    • 6.5.1.2. How Metaclasses works?
    • 6.5.1.3. Example use of Metaclasses
  • 6.5.2. Type and objects
    • 6.5.2.1. Types
    • 6.5.2.2. Objects
  • 6.5.3. Example
  • 6.5.4. Factories
    • 6.5.4.1. Object factory
    • 6.5.4.2. Class Factory
  • 6.5.5. Metaclass replacements
    • 6.5.5.1. Inheritance
    • 6.5.5.2. Class Decorator
• 6.6. OOP Advanced Exam
  • 6.6.1. Dragon (version release candidate)

7. Design Patterns

Design Patterns

• 7.1. Dependency injection
• 7.2. Singleton
• 7.3. Factory
• 7.4. Gateway
• 7.5. Callback
• 7.6. State Machine
• 7.7. Gang of Four
  • 7.7.1. Examples
  • 7.7.2. Structural Design Patterns
  • 7.7.3. Creational Design Patterns
  • 7.7.4. Behavioral Design Patterns
  • 7.7.5. Idiomy języka programowania

8. Paradigms

Paradigms

• 8.1. Functional Programming
  • 8.1.1. Lambda - Anonymous functions
    • 8.1.1.1. Example 1
    • 8.1.1.2. Example 2
    • 8.1.1.3. Monkey patching
  • 8.1.2. Built-in functions
    • 8.1.2.1. map()
    • 8.1.2.2. zip()
    • 8.1.2.3. filter()
    • 8.1.2.4. all()
    • 8.1.2.5. any()
  • 8.1.3. functools
    • 8.1.3.1. lru_cache
    • 8.1.3.2. memoize
  • 8.1.4. Callback
  • 8.1.5. Assignments
    • 8.1.5.1. map(), filter() i lambda
    • 8.1.5.2. Zbalansowanie nawiasów
• 8.2. Event Programming
  • 8.2.1. Implementation
  • 8.2.2. Przykład użycia
  • 8.2.3. Użycie

9. Concurrency

Concurrency

• 9.1. Queues
  • 9.1.1. Queue
    • 9.1.1.1. FIFO
    • 9.1.1.2. LIFO (stack)
    • 9.1.1.3. Priority Queue
    • 9.1.1.4. Network Queue
  • 9.1.2. queue
• 9.2. Threads
  • 9.2.1. Threads vs processes
    • 9.2.1.1. Process
    • 9.2.1.2. Thread
    • 9.2.1.3. Threads vs processes
  • 9.2.2. Problemy z wątkami
  • 9.2.3. threading
    • 9.2.3.1. daemon flag
    • 9.2.3.2. Delay execution
    • 9.2.3.3. Recurrent timer
  • 9.2.4. Tworzenie wątków
  • 9.2.5. Synchronizacja wątków
  • 9.2.6. Zamykanie wątków
  • 9.2.7. Workery
  • 9.2.8. Assignments
    • 9.2.8.1. Wielowątkowość
• 9.3. Multiprocessing
  • 9.3.1. Problems
  • 9.3.2. Cykl życia procesów
  • 9.3.3. IPC - Inter-Process Communication
    • 9.3.3.1. Define payload
    • 9.3.3.2. Client
    • 9.3.3.3. Listener
• 9.4. Concurrency
  • 9.4.1. High-Level Concurrency
  • 9.4.2. Coroutine
  • 9.4.3. Asyncio
    • 9.4.3.1. Protocol
    • 9.4.3.2. Low-level API
    • 9.4.3.3. async/await
    • 9.4.3.4. Mainstream
    • 9.4.3.5. Pluggable event loop
  • 9.4.4. Przykłady praktyczne
    • 9.4.4.1. Hello World coroutine
    • 9.4.4.2. Coroutine displaying the current date
    • 9.4.4.3. Chain coroutines
    • 9.4.4.4. Future with run_until_complete()
    • 9.4.4.5. Parallel execution of tasks
  • 9.4.5. Trio
    • 9.4.5.1. Client
    • 9.4.5.2. Server
  • 9.4.6. References

10. Exit Test

Exit Test

• 10.1. Exit Exam