Python Full-Stack Developer

Numeric types: integers, floats, complex numbers and their operations

String manipulation: concatenation, slicing, formatting, and string methods

String operations: upper, lower, strip, split, join, replace, and find methods

List operations: creation, indexing, slicing, appending, extending, and sorting

Tuple operations: creation, packing, unpacking, and immutability benefits

Dictionary operations: creation, key-value access, update, merge, and iteration

Set operations: creation, union, intersection, difference, and uniqueness properties

Generator expressions and yield statements for memory-efficient iteration

Enumerate function for indexed iteration over sequences

Type conversion and casting between different data types

Conditional statements: if, elif, else constructs for decision making

Comparison operators in conditional contexts and boolean evaluation

Loop constructs: for loops for iteration and while loops for conditional repetition

Nested loops and multi-dimensional iteration patterns

Loop control statements: break for early termination, continue for skipping iterations

Range function for generating numeric sequences in loops

List comprehensions for concise data transformation and filtering

Conditional expressions (ternary operator) for inline decision making

Function definition syntax: def keyword, parameters, and return statements

Parameter types: positional, keyword, default, and variable-length arguments

Function scope and local vs global variable access

Lambda functions for anonymous function definitions and inline operations

Higher-order functions: map for transformation, filter for selection, reduce for aggregation

Function decorators for extending functionality and cross-cutting concerns

Recursive functions for self-referential problem solving and mathematical computations

Partial functions for function specialization and currying

Function introspection and dynamic function manipulation

File reading operations: open, read, readline, readlines methods

File writing operations: write, writelines, and append modes

Context managers and with statements for automatic resource management

File handling with exception management for robust file operations

Directory operations: listing, creation, deletion, and navigation

Recursive directory traversal and file system exploration

File renaming, moving, and batch processing operations

Working with file paths, extensions, and metadata

Handling different file encodings and character sets

Exception handling: try-except-finally blocks for error management

Custom exception classes and exception hierarchy design

Assert statements for debugging and development-time checks

Module creation, importing, and package organization

Python path manipulation and module discovery

Namespace concepts: local, global, and built-in scopes

Variable scope resolution and the LEGB rule

Memory management: reference counting and garbage collection

Deep vs shallow copying for complex data structures

Debugging techniques: print debugging, logging, and debugger usage

Class definition and object instantiation fundamentals

Constructor methods (__init__) for object initialization

Instance variables and methods for object state and behavior

Class variables for shared state across instances

Inheritance for code reuse and hierarchical relationships

Method overriding and polymorphism for flexible behavior

Multiple inheritance and method resolution order

Operator overloading with magic methods (__add__, str, etc.)

Static methods and class methods for utility functions

Property decorators for controlled attribute access

JSON parsing: loading, parsing, and generating JSON data

JSON data validation and error handling for malformed data

CSV processing: reading, writing, and manipulating tabular data

CSV dialects and custom delimiters for different file formats

Excel file handling: reading workbooks, sheets, and cell data

Excel automation: creating charts, formatting, and data manipulation

XML parsing: DOM and SAX parsing approaches

XML data extraction and transformation techniques

Regular expressions: pattern matching, search, and replace operations

DateTime manipulation: parsing, formatting, and timezone handling

PostgreSQL connectivity and connection management

SQL query execution and result processing

Database transactions and commit/rollback operations

MongoDB integration and document-based operations

NoSQL query patterns and data modeling

Microsoft SQL Server connectivity and enterprise integration

Database connection pooling and performance optimization

Data migration scripts and ETL (Extract, Transform, Load) processes

Database error handling and connection recovery

ORM concepts and database abstraction layers

Socket programming: TCP and UDP communication protocols

Client-server architecture and network communication patterns

HTTP requests: GET, POST, PUT, DELETE operations

REST API development with FastAPI framework

API authentication and security considerations

JSON data exchange in web services

Email handling: SMTP operations for sending emails

Email attachments and HTML content formatting

Telnet automation for network device testing

SSH automation for remote server management and deployment

Process vs thread concepts and when to use each approach

Threading module: thread creation, management, and synchronization

Multiprocessing module: process creation and inter-process communication

Thread locks and synchronization primitives for shared resources

Race conditions and deadlock prevention strategies

Concurrent execution patterns and performance considerations

Parallel processing for CPU-intensive tasks

Asynchronous programming concepts and async/await patterns

Thread pools and process pools for resource management

Unit testing with unittest framework: test cases and test suites

Test assertions and validation methods for comprehensive testing

PyTest framework: fixtures, parameterization, and advanced features

Test fixtures for setup and teardown operations

Mocking and monkey patching for isolated unit testing

Test-driven development (TDD) practices and methodologies

Code coverage analysis and quality metrics

Integration testing and end-to-end testing strategies

Performance testing and benchmarking techniques

Continuous integration and automated testing pipelines

Logging framework: loggers, handlers, formatters, and log levels

Instrumentation and monitoring for production applications

Decorator patterns for cross-cutting concerns and aspect-oriented programming

Iterator tools and functional programming utilities

Generator functions and memory-efficient data processing

Context managers and resource management patterns

CRON job automation and scheduled task execution

FastAPI web framework: routing, middleware, and dependency injection

API documentation and OpenAPI specification generation

Performance optimization techniques and profiling tools

Helper functions for common programming tasks and utilities

File and directory manipulation utilities for batch operations

Data processing utilities for JSON, CSV, and XML formats

Database connection utilities and query helpers

Testing utilities and custom assertion functions

Networking utilities for API testing and automation

Debugging utilities and development tools

Performance monitoring and profiling utilities

Code style and PEP 8 compliance for readable, maintainable code

Documentation practices and docstring conventions

Error handling patterns and exception management strategies

Performance optimization techniques and memory management

Security considerations in Python applications

Package management and virtual environment best practices

Code organization and project structure guidelines

Version control integration and collaborative development

Setting up Python development environments and IDEs

Package management with pip and virtual environments

Code versioning and collaborative development with Git

Deployment strategies for Python applications

Performance monitoring and optimization in production

Security best practices for enterprise Python applications

Integration with CI/CD pipelines and DevOps practices

Career development and Python certification paths