Visão Geral

Curso Advanced Python Programming. Este curso explora tópicos e habilidades avançadas do Python com foco no desenvolvimento empresarial. Você aprenderá como aproveitar serviços do SO, codificar interfaces de aplicativos gráficos, criar módulos e executar testes de unidade, definir classes, interagir com séries de rede, consultar bancos de dados e processar dados XML. Este Curso Advanced Python Programming abrangente fornece uma exploração aprofundada do trabalho com a linguagem de programação para desenvolvimento empresarial. Na conclusão, você será capaz de usar o Python para concluir tarefas avançadas no mundo real.

Objetivo

Após realizar este Curso Advanced Python Programming você será capaz de:

• Aproveitando os serviços do SO
• Melhorias nas classes
• Codifique interfaces gráficas para aplicações
• Conceitos avançados de metaprogramação em Python
• Módulos e pacotes fáceis de usar e manter
• Implementando e executando testes unitários
• Criação de aplicações multithread e multiprocesso
• Interagindo com serviços de rede
• Projetando scripts profissionais
• Consultando bancos de dados
• Processando dados XML, CSV e JSON

Publico Alvo

• Desenvolvedores, engenheiros,
• Administradores experientes
• Qualquer pessoa focada em habilidades avançadas para desenvolvimento empresarial.

Pre-Requisitos

• Experiência em escrever scripts Python
• Conhecimento prático de Unix/Linux, Mac ou Windows

Materiais

Conteúdo Programatico

Python refresher

1. Built-in data types
2. Lists and tuples
3. Dictionaries and sets
4. Program structure
5. Files and console I/O
6. If statement
7. for and while loops

OS Services

1. The os and os.path modules
2. Environment variables
3. Launching external commands with subprocess
4. Walking directory trees
5. Paths, directories, and filenames
6. Working with file systems

Dates and times

1. Basic date and time classes
2. Different time formats
3. Converting between formats
4. Formatting dates and times
5. Parsing date/time information
6. Binary data
7. What is Binary Data?
8. Binary vs text
9. Using the Struct module

Pythonic programming

1. The Zen of Python
2. Tuples
3. Advanced unpacking
4. Sorting
5. Lambda functions
6. List comprehensions
7. Generator expressions
8. String formatting

Functions, modules, and packages

1. Four types of function parameters
2. Four levels of name scoping
3. Single/multi dispatch
4. Relative imports
5. Using __init__ effectively
6. Documentation best practices

Intermediate classes

1. Class/static data and methods
2. Inheritance (or composition)
3. Abstract base classes
4. Implementing protocols (context, iterator, etc.) with special methods

Metaprogramming

1. Implicit properties
2. globals() and locals()
3. Working with object attributes
4. The inspect module
5. Callable classes
6. Decorators
7. Monkey patching

Developer tools

1. Analyzing programs with Pylint
2. Using the debugger
3. Profiling code
4. Testing speed with benchmarking

Unit testing with Pytest

1. What is a unit test?
2. Writing tests
3. Working with fixtures
4. Test runners
5. Mocking resources

Database access

1. The DB API
2. Available Interfaces
3. Connecting to a server
4. Creating and executing a cursor
5. Fetching data
6. Parameterized statements
7. Using Metadata
8. Transaction control
9. ORMs and NoSQL overview

PyQt

1. Overview
2. Qt Architecture
3. Using designer
4. Standard widgets
5. Event handling
6. Extras

Network Programming

1. Built-in classes
2. Using requests
3. Grabbing web pages
4. Sending email
5. Working with binary data
6. Consuming RESTful services
7. Remote access (SSH)

Multiprogramming

1. The threading module
2. Sharing variables
3. The queue module
4. The multiprocessing module
5. Creating pools
6. About async programming

Scripting for System Administration

1. Running external programs
2. Parsing arguments
3. Creating filters to read text files
4. Logging

Serializing data – XML and JSON

1. Working with XML
2. XML modules in Python
3. Getting started with ElementTree
4. Parsing XML
5. Updating an XML tree
6. Creating a new document
7. About JSON
8. Reading JSON
9. Writing JSON
10. Reading/writing CSV files
11. YAML, other formats as time permits

Advanced data handling

1. Discover the collections module
2. Use defaultdict, Counter, and namedtuple
3. Create dataclasses
4. Store data offline with pickle

Type hinting

1. Annotate variables
2. Learn what type hinting does NOT do
3. Use the typing module for detailed type hints
4. Understand union and optional types
5. Write stub interfaces