This advanced bootcamp transforms Python scripters into tool builders. Moving beyond simple loops, this course focuses on the "dirty work" of professional automation: handling messy file systems, parsing complex text patterns, manipulating Excel and PDF documents, and writing "crash-proof" code. You will learn to apply engineering principles—like Object-Oriented Programming (OOP) and automated testing—to build reliable tools that can run without supervision.

Learning Outcomes

By completing this bootcamp, you will be able to:

1. Programmatically manage files and folders across operating systems
2. Extract complex data patterns (emails, dates, IDs) using Regular Expressions (Regex).
3. Automate Excel reports by reading, writing, and formatting spreadsheets with code.
4. Process PDF documents, including merging files and extracting text.
5. Design modular software using Classes and Objects (OOP).
6. Ensure reliability by implementing professional Logging instead of print statements.
7. Verify code quality using automated unit tests (pytest).
8. Build end-to-end automation pipelines that require zero human intervention.

Day 1: The "Office" Stack (Text & Files)

Theme: Conquering the Messy Real World

Morning Session (9:00 AM - 12:30 PM)

9:00-10:30 | Review & System Mastery (OS & Paths)

• Topics:
  • Refresher: Key concepts from Bootcamp 1 (Functions & Logic).
  • OS Control: Using os and shutil to interact with the computer.
  • Paths: Working with pathlib across Windows/Mac/Linux.
  • Bulk Actions: Listing, moving, copying, and renaming files programmatically.
• Hands-On Activities:
  • "The Bulk Renamer": Write a script that adds timestamps to 100 files instantly.
  • Create a script that detects and deletes empty folders.
  • "The File Organizer": Build a tool that scans a "Downloads" folder and automatically moves files into "Images," "Docs," and "Spreadsheets" folders based on extension.
• You'll be able to: Write scripts that manage thousands of files in seconds.

10:30-11:00 | Morning Break

11:00-12:30 | Pattern Matching with Regular Expressions

• Topics:
  • Why .replace() isn't enough: Introduction to Regex (re).
  • Defining patterns: Digits \d, Words \w, and Whitespace \s.
  • Quantifiers: Finding specific formats (e.g., Phone Numbers \d{3}-\d{3}-\d{4}).
  • Capturing Groups: Extracting just the username from an email.
• Hands-On Activities:
  • "The Data Miner": Parse a messy text block to extract all unique email addresses.
  • "The Invoice Scraper": Find and extract "Order IDs" (e.g., INV-2023-X) from unstructured log text.
  • Validate user inputs to ensure they match specific formats.
• You'll be able to: Find needle-in-a-haystack data within messy text files.

12:30-1:30 PM | Lunch Break

Afternoon Session (1:30 PM - 5:00 PM)

1:30-3:00 | Excel Automation

• Topics:
  • Beyond CSVs: Using openpyxl to work with real Excel files (.xlsx).
  • Reading specific cells, rows, and sheets.
  • Writing data, formulas, and styles (colors/fonts) programmatically.
  • Creating new sheets and workbooks.
• Hands-On Activities:
  • "The Report Formatter": Take a raw data dump and auto-format the headers (Bold, Blue Background).
  • Write a script that splits one Master Excel sheet into 10 separate files by department.
  • Read data from multiple Excel files and combine them into one Summary Report.
• You'll be able to: Automate tedious Excel reporting and formatting tasks.

3:00-3:30 | Afternoon Break

3:30-5:00 | Day 1 Mini-Project: "The Report Assembler"

• The Challenge:
  • You have 3 messy Excel files and a folder of PDF invoices.
• Project Requirements:
  • Use os to locate all .xlsx files in a folder.
  • Use openpyxl to extract the "Total" cell from each sheet.
  • Use re to find the Date in the filename.
  • Create a new "Master Report" Excel file that lists Date, Filename, and Total Amount.
• You'll deliver: A script that turns scattered files into a single, clean report.

Day 2: Engineering Robust Tools

Theme: Building Code That Lasts

Morning Session (9:00 AM - 12:30 PM)

9:00-10:30 | Object-Oriented Programming (OOP)

• Topics:
  • Moving beyond Functions: The Blueprint concept (Class).
  • Attributes (Data) vs. Methods (Actions).
  • The __init__ constructor function.
  • Why OOP makes big automation tools easier to manage.
• Hands-On Activities:
  • "The Employee System": Create an Employee class that tracks Name, ID, and Salary.
  • Add methods to "Give Raise" or "Update Department."
  • "The Ticket Manager": Build a SupportTicket class that changes status from "Open" to "Closed."
• You'll be able to: Model real-world entities in code for better organization.

10:30-11:00 | Morning Break

11:00-12:30 | Advanced Robustness: Logging & Exceptions

• Topics:
  • Logging vs. Print: Why print() is bad for automation (The logging library).
  • Setting Log Levels: DEBUG, INFO, WARNING, ERROR.
  • Writing logs to a file for audit trails.
  • Creating custom Exceptions (e.g., InvalidInvoiceError).
• Hands-On Activities:
  • Refactor yesterday's "File Organizer" to write a log file of every move.
  • Create a script that alerts you (via log) if a critical file is missing, but keeps running.
  • Practice debugging a script using only its log file.
• You'll be able to: Create invisible "black boxes" that track their own health and history.

12:30-1:30 PM | Lunch Break

Afternoon Session (1:30 PM - 5:00 PM)

1:30-3:00 | Quality Assurance: Automated Testing

• Topics:
  • "It works on my machine" vs. "It works everywhere."
  • Introduction to Unit Testing with pytest (or unittest).
  • Writing assertions (assert x == y).
  • Testing for failure: Ensuring your code fails gracefully when it should.
• Hands-On Activities:
  • Write a test for your "Tax Calculator" function to ensure it never returns negative numbers.
  • Test your Regex patterns against tricky edge cases.
  • "The Safety Net": Build a test suite that runs before your automation starts.
• You'll be able to: Trust your code to handle critical business data without corruption.

3:00-3:30 | Afternoon Break

3:30-5:00 | Capstone Project: "The Manager Bot"

• The Challenge:
  • You are the "Manager Bot." You need to process a batch of incoming invoice files (Text & Excel), validate them, and generate a payment schedule.
• Project Steps:
  • Class Design: Create an Invoice class that holds data (ID, Amount, Vendor).
  • Ingest: Use os to loop through a folder of mixed files.
  • Parse: Use Regex to extract IDs from filenames and openpyxl to get amounts.
  • Validate: Raise a custom error if an Amount is negative or ID is missing.
  • Audit: Log every successful process and every error to log.
  • Output: Generate a final clean Excel sheet of "Approved Payments."
• Required Deliverables:
  • A Python script using Classes and Logging.
  • A set of unit tests verifying the logic.
  • The generated Log and Excel files.
• You'll deliver: A professional-grade software tool that is robust, auditable, and automated.