Warehouse Management System

This project is a command-line Warehouse Management System implemented in Python. It allows users to manage warehouse entries stored in a CSV file (warehouse.csv) in the current working directory.

Features

• Create: Add new items to the warehouse with comprehensive validation.
• Update: Modify any field of an existing item with field-specific validation.
• Delete: Remove items from the warehouse by ID.
• Enhanced Validation:
  • Item names with sanitization and special character validation
  • Quantity validation (positive integers, configurable maximum)
  • Date validation (YYYY-MM-DD format, minimum date enforcement)
  • Time validation (24-hour HH:MM format)
  • Operation type validation and normalization
  • Operator name validation (letters, spaces, hyphens, apostrophes only)
• Security Features: CSV injection prevention and Unicode normalization
• Duplicate Detection: Warning system for duplicate item names
• Auto-ID Generation: Unique, sequential ID assignment
• Error Handling: Comprehensive error messages for all validation failures

CSV File Structure

The warehouse.csv file contains the following columns:

1. ID: Numeric, unique, autogenerated.
2. Item Name: Text, required.
3. Quantity: Positive integer, required.
4. Date: YYYY-MM-DD, required, autogenerated if not provided.
5. Time: HH:MM (24-hour), required, autogenerated if not provided.
6. Operation: Text, required.
7. Operated By: Text, required.

Usage

Run the program from the command line:

python solution.py <command> [arguments]

Commands

Create

Add a new item (all fields are required):

python solution.py create <item_name> <quantity> <operation> <operated_by> <date> <time>

• All parameters are mandatory - no auto-generation of date/time
• Item names are sanitized and validated for security
• Quantities must be positive integers (1-999999)
• Operations are normalized to uppercase
• Operated by field accepts only valid name formats

Update

Update a field of an item:

python solution.py update <id> <item_name|quantity|operation|operated_by|date|time> <value>

Delete

Delete an item by ID:

python solution.py delete <id>

Validation Rules

• ID: Auto-generated, unique, sequential numeric values
• Item Name:
  • Cannot be empty or whitespace-only
  • Cannot contain only special characters (-, _, .)
  • Sanitized for CSV injection prevention
  • Unicode normalized for consistency
  • Duplicate name warnings provided
• Quantity:
  • Must be positive integer (no decimals)
  • Range: 1 to 999,999
  • Cannot be zero or negative
• Date:
  • Must be in YYYY-MM-DD format
  • Must be a valid calendar date
  • Cannot be earlier than 2020-01-01
  • Handles leap years correctly
• Time:
  • Must be in HH:MM format (24-hour)
  • Valid hours: 00-23, Valid minutes: 00-59
• Operation:
  • Cannot be empty
  • Automatically converted to uppercase
  • Sanitized for security
• Operated By:
  • Cannot be empty
  • Only letters, spaces, hyphens, and apostrophes allowed
  • Sanitized for security

Error Messages

General Commands

• Invalid command: ERROR: Invalid command provided. Use <create>, <update>, or <delete>.

Create Command Errors

• Missing fields: ERROR: Provide all required fields. Use <item_name>, <quantity> <operation> <operated_by> <date> <time>.
• Empty item name: ERROR: Item name cannot be empty.
• Invalid item name: ERROR: Item name cannot contain only special characters.
• Invalid quantity: ERROR: Quantity must be a positive number.
• Decimal quantity: ERROR: Quantity must be a non decimal number.
• Quantity too large: ERROR: Quantity cannot exceed 999999.
• Invalid date: ERROR: Date is not valid. Use the format YYYY-MM-DD.
• Date too early: ERROR: Date cannot be earlier than 2020-01-01.
• Invalid time: ERROR: Time is not valid. Use the format HH:MM (24 hour clock).
• Invalid operation: Field-specific validation messages
• Invalid operator name: ERROR: Operated by can only contain letters, spaces, hyphens, and apostrophes.

Update Command Errors

• Missing fields: ERROR: Provide all required fields. Use <id> <item_name|quantity|operation|operated_by|date|time> <value>
• Invalid ID: ERROR: Invalid ID provided
• Field-specific validation errors (same as create command)

Delete Command Errors

• Invalid ID: ERROR: Invalid ID provided

Warnings

• Duplicate names: WARNING: An item with name '<name>' already exists (ID: <id>).

Success Messages

• Create:

  Item successfully created:
  ID: <id>
  Item name: <item_name>
  Quantity: <quantity>
  Operation: <operation>
  Operated by: <operated_by>
  Date: <date>
  Time: <time>
  

• Update:

  Item with the ID <id> has been updated successfully:
  ID: <id>
  Item name: <item_name>
  Quantity: <quantity>
  Operation: <operation>
  Operated by: <operated_by>
  Date: <date>
  Time: <time>
  

• Delete:

  The following entry has been deleted successfully:
  ID: <id>
  Item name: <item_name>
  Quantity: <quantity>
  Operation: <operation>
  Operated by: <operated_by>
  Date: <date>
  Time: <time>
  

Testing

The project includes comprehensive test coverage with pytest. Run the test suite with:

pytest test.py

Test Coverage

The test suite includes 40+ test cases covering:

Create Operation Tests:

• Successful creation with all valid inputs
• Missing field validation (arguments and empty values)
• Item name validation (empty, whitespace, special characters only)
• Quantity validation (non-numeric, decimals, negative, zero, maximum limits)
• Date validation (invalid formats, leap years, month/day limits, minimum date)
• Time validation (invalid hours/minutes, format validation)
• ID auto-generation and uniqueness

Update Operation Tests:

• Successful updates for all fields (item_name, quantity, operation, operated_by, date, time)
• Missing argument validation
• Invalid field name validation
• Invalid ID handling (non-existent, empty, non-numeric)
• Field-specific validation (same as create tests)

Delete Operation Tests:

• Successful deletion with proper output
• Invalid ID handling (non-existent, empty, missing arguments)
• Proper CSV file updates after deletion

General Command Tests:

• Invalid command handling
• Missing command handling
• Proper error message formatting

Edge Case Tests:

• Boundary value testing (min/max quantities, edge dates)
• Special character handling and sanitization
• Unicode normalization testing
• CSV injection prevention

Test Configuration

• Tests use automatic cleanup fixtures to ensure test isolation
• Each test runs with a fresh warehouse.csv file
• Subprocess execution for realistic CLI testing
• Parameterized tests for efficient validation testing

Requirements

Install dependencies with:

pip install -r requirements.txt

Dependencies include:

• pytest>=8.4.1 - Testing framework
• python-dateutil>=2.9.0 - Enhanced date handling
• Additional validation libraries for robust input sanitization

Python Version: 3.x (tested with Python 3.13)

Configuration

The system includes configurable parameters in solution.py:

CONFIG = {
    'max_quantity': 999999,           # Maximum allowed quantity
    'min_quantity': 1,                # Minimum allowed quantity  
    'duplicate_name_warning': True,   # Enable duplicate name warnings
    'min_date': '2020-01-01',        # Earliest allowed date
}

Security Features

• CSV Injection Prevention: Automatically sanitizes input to prevent formula injection
• Unicode Normalization: Ensures consistent character encoding
• Input Validation: Strict validation prevents malformed data entry
• Safe File Operations: Atomic CSV operations prevent data corruption

Notes

• The CSV file (warehouse.csv) is created automatically if it does not exist
• All operations maintain data integrity through comprehensive validation
• The system is designed for command-line operation with clear error reporting
• IDs are automatically generated and guaranteed to be unique and sequential
• All operations provide detailed success/failure feedback