This module covers Python tools and techniques for engineering applications. Topics progress from advanced data structures and functions through practical file processing, text parsing, and command-line scripting.

liststuplesdictionaries.py

Comprehensive coverage of Python's core data structures:

• Lists: creation, operations, slicing, iteration
• Tuples: immutable sequences, unpacking, use as dictionary keys
• Dictionaries: key-value pairs, methods, nested structures
• Practical examples: shopping carts, student grades, word frequency counting

recursion.py

Demonstrates recursive function design:

• Naive and optimized (tail-recursive) implementations
• Fibonacci sequence calculation
• Array searching with recursion
• Understanding base cases and recursive calls

advancedfunctions.py

Function parameter techniques:

• Positional-only parameters (/)
• Keyword arguments with defaults
• Variable-length argument lists (*args)
• Keyword-only parameters (*)
• Practical examples with statistical functions

comprehensionsintro.py

VIDEO (8:56): Concise syntax for creating collections:

• List comprehensions for transforming sequences
• Set comprehensions for unique elements
• Dictionary comprehensions for key-value pairs
• Filtering with conditional expressions
• Nested comprehensions for complex operations

strings_advanced.py

Essential string methods for engineering scripts:

• String methods: strip(), upper(), lower(), replace()
• Checking content: startswith(), endswith(), isdigit()
• Splitting and joining: split(), join()
• String formatting: f-strings, .format(), alignment
• Extracting data from structured text
• Finding and locating substrings

regex.py

Pattern matching and text extraction:

• Basic pattern matching with re.search()
• Extracting numbers and codes from text
• Email validation patterns
• Finding all matches with re.findall()
• Replacing with patterns using re.sub()
• Splitting text on patterns
• Pattern syntax: \d, \w, [a-z], +, *, ?, {n,m}

csv_files.py

Reading and writing comma-separated data:

• Reading CSV with csv.reader()
• Dictionary access with csv.DictReader()
• Filtering and extracting specific columns
• Writing CSV files with csv.DictWriter()
• Handling different delimiters (semicolon, tab)
• Aggregating and summarizing CSV data

fileio_engineering.py

File operations for engineering workflows:

• Writing files with open() and write()
• Reading entire files and line-by-line processing
• Appending to existing files
• Filtering file contents
• Processing structured data from files
• Working with file metadata and directories

error_handling.py

Writing robust scripts with exception handling:

• try/except for handling specific exceptions
• ValueError, FileNotFoundError, TypeError
• Multiple exception types in one script
• Else and finally clauses
• Raising custom exceptions
• Exception chaining with "from"
• Handling bad data in loops gracefully

commandline_engineering.py

Making scripts flexible with arguments:

• Accessing command-line arguments (sys.argv)
• Processing required and optional arguments
• Common patterns for argument handling
• Usage messages and error checking
• Examples: file analyzer, unit converter
• Introduction to argparse for complex scripts

Each file can be run directly:

python liststuplesdictionaries.py
python recursion.py
python advancedfunctions.py
python comprehensionsintro.py
python strings_advanced.py
python regex.py
python csv_files.py
python fileio_engineering.py
python error_handling.py
python commandline_engineering.py

Some examples create temporary files during execution and clean them up automatically.

1. Read the file (fileio_engineering.py)
2. Parse each line (strings_advanced.py)
3. Handle errors gracefully (error_handling.py)
4. Aggregate results (liststuplesdictionaries.py)

1. Use regex patterns (regex.py)
2. Process with comprehensions (comprehensionsintro.py)
3. Store in dictionaries (liststuplesdictionaries.py)
4. Write results to CSV (csv_files.py)

1. Accept arguments (commandline_engineering.py)
2. Validate input (error_handling.py)
3. Process files (fileio_engineering.py)
4. Handle exceptions gracefully (error_handling.py)