qufe 0.5.1

A comprehensive Python utility library for data processing, file handling, database management, and automation tasks

qufe

A comprehensive Python utility library for data processing, file handling, database management, and automation tasks.

Born from the need to streamline repetitive tasks in Jupyter Lab environments, qufe addresses common pain points encountered during interactive development and data exploration work.

Installation

Quick Start (Core Features Only)

# Install core functionality with no external dependencies
pip install qufe

Feature-Specific Installation

Install only the features you need:

# Database operations (PostgreSQL)
pip install qufe[database]

# Data processing with pandas/numpy  
pip install qufe[data]

# Web browser automation
pip install qufe[web]

# Screen capture and image processing
pip install qufe[vision]

Features Overview

Always Available (Core Features)

Base Utilities (qufe.base)

• Timestamp handling: Convert timestamps with timezone support
• Code comparison: Compare code snippets with multiple diff formats
• Dynamic imports: Import Python modules from file paths
• List flattening: Flatten nested structures with configurable depth
• Dictionary utilities: Advanced nested dictionary operations

Text Processing (qufe.texthandler, qufe.excludebracket)

• Bracket content removal: Validate and remove bracketed content
• DokuWiki formatting: Convert data to DokuWiki table format
• String utilities: Advanced search with context extraction
• Pretty printing: Format nested dictionaries and lists
• Column display: Multi-column text formatting with alignment

File Operations (qufe.filehandler)

• Directory traversal: Recursive file listing with Unicode normalization
• Pattern matching: Find latest files by datetime patterns
• Pickle operations: Simplified Python object persistence
• Path utilities: Safe filename generation and path management
• Content extraction: Text extraction from directory structures

Optional Features (Require Additional Packages)

Database Management (qufe.dbhandler) - [database]

• PostgreSQL integration: Easy connections using SQLAlchemy
• Database exploration: List databases and tables with metadata
• Connection management: Automatic pooling and cleanup
• Environment integration: .env file and environment variable support

Data Analysis (qufe.pdhandler) - [data]

• DataFrame utilities: Type conversion and structure analysis
• Column comparison: Compare schemas across multiple DataFrames
• Missing data detection: Find NA values and empty strings
• Data validation: Comprehensive quality checks

Web Automation (qufe.wbhandler) - [web]

• Selenium-based browser automation: Direct Selenium WebDriver integration
• Network monitoring: Capture fetch/XHR requests
• Element discovery: Interactive element finding utilities
• URL parsing: Extract and manipulate URL parameters
• Multi-browser support: Firefox implementation with profile detection

Screen Interaction (qufe.interactionhandler) - [vision]

• Screen capture: Full screen or region-specific screenshots
• Image processing: Color detection and comparison algorithms
• Mouse automation: Randomized clicking for natural automation
• Progress tracking: Real-time updates in Jupyter notebooks
• Color analysis: Extract and analyze color information

Quick Start Guide

1. Check Installation Status

import qufe

# See what's available
qufe.help()

# Check dependencies programmatically
status = qufe.check_dependencies()
print(status)

# Get installation commands for missing features
missing = qufe.get_missing_dependencies()
for module, command in missing.items():
    print(f"{module}: {command}")

2. Core Features (Always Available)

from qufe import base, texthandler, filehandler

# Timestamp handling with timezone
ts = base.TS('Asia/Seoul')
formatted = ts.get_ts_formatted(1640995200)

# File operations
fh = filehandler.FileHandler()
files = fh.get_tree('/path/to/directory')

# Text processing
data = [['Name', 'Age'], ['Alice', '25'], ['Bob', '30']]
texthandler.list_to_doku_wiki_table(data)

# Directory exploration
pf = filehandler.PathFinder('/starting/path')
root, dirs, files = pf.get_one_depth()

3. Database Operations (Optional)

Configuration Options

Option 1: .env file (Recommended)

# Create .env file in your project root
POSTGRES_USER=your_username
POSTGRES_PASSWORD=your_password
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
POSTGRES_DB=your_database

Option 2: Environment variables

export POSTGRES_USER=your_username
export POSTGRES_PASSWORD=your_password
# ... etc

Option 3: Direct parameters

from qufe.dbhandler import PostgreSQLHandler

# Use .env or environment variables
db = PostgreSQLHandler()

# Or specify directly
db = PostgreSQLHandler(
    user='username',
    password='password', 
    host='localhost',
    port=5432,
    db_name='database'
)

# Usage
databases = db.get_database_list()
tables = db.get_table_list()
results = db.execute_query("SELECT * FROM users LIMIT 5")

4. Data Processing (Optional)

from qufe.pdhandler import PandasHandler
import pandas as pd

# Initialize handler with default settings
handler = PandasHandler()

# Or with default exclude columns for NA/empty checks
handler = PandasHandler(default_exclude_cols=['id', 'created_at'])

# Compare DataFrames
df1 = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
df2 = pd.DataFrame({'B': [5, 6], 'C': [7, 8]})
col_dict, comparison = handler.show_col_names([df1, df2])

# Find missing data
na_subset = handler.show_all_na(df1)

# Find problematic rows (uses default_exclude_cols if set)
problem_rows = handler.show_all_na_or_empty_rows(df1)

# Convert lists to tuples in DataFrame
df_with_lists = pd.DataFrame({'col1': [[1, 2], [3, 4]], 'col2': ['a', 'b']})
df_converted = handler.convert_list_to_tuple_in_df(df_with_lists)

5. Web Automation (Optional)

from qufe.wbhandler import Firefox

# Start browser
browser = Firefox(private_mode=True)
browser.driver.get('https://example.com')

# Network monitoring
browser.inject_network_capture()
# ... perform actions ...
logs = browser.get_network_logs()

# Clean up
browser.quit_driver()

6. Screen Automation (Optional)

from qufe.interactionhandler import get_screenshot, display_image, get_color_boxes

# Capture screen
screenshot = get_screenshot(100, 100, 800, 600)
display_image(screenshot, is_bgra=True)

# Find colored regions
red_boxes = get_color_boxes(screenshot, (255, 0, 0), tolerance=0.1)

Module-Specific Help

Each module provides detailed help information:

# General help
import qufe
qufe.help()

# Module-specific help
from qufe import dbhandler, pdhandler, wbhandler, interactionhandler
dbhandler.help()      # Database operations guide
pdhandler.help()      # pandas utilities guide  
wbhandler.help()      # Browser automation guide
interactionhandler.help()  # Screen interaction guide

Dependency Details

Feature Group	Dependencies	Purpose
database	sqlalchemy≥1.3.0, python-dotenv≥0.15.0	PostgreSQL operations
data	pandas≥1.1.0, numpy≥1.17.0	Data processing
web	selenium≥3.141.0	Browser automation
vision	opencv-python≥4.1.0, matplotlib≥3.1.0, pyautogui≥0.9.48, mss≥4.0.0	Screen interaction
jupyter	ipython≥6.0.0	Notebook integration

All versions are set to compatible minimums to avoid conflicts in existing environments.

Configuration

Database Setup

qufe supports multiple database configuration methods:

1. .env file (Recommended): Works consistently across all environments
2. Environment variables: System-level configuration
3. Direct parameters: Programmatic configuration

The .env approach is recommended because it:

• Works in Jupyter Lab, PyCharm, terminal, and other environments
• Keeps credentials separate from code
• Doesn't require system-level configuration
• Can be easily excluded from version control

Web Automation Setup

Browser automation requires modern Selenium WebDriver:

• Requirements: Selenium 4.0+ for enhanced tab management and modern WebDriver features
• WebDriver Installation:
  • Chrome: ChromeDriver (auto-managed by Selenium 4.0+)
  • Firefox: GeckoDriver (auto-managed by Selenium 4.0+)
• Security: Runs in secure mode by default; insecure mode available for testing only

Documentation

• Online docs: https://qufe.readthedocs.io
• Local help: Use help() functions in each module

License

MIT License

Security & Ethics Guidelines

Database Security

• Store credentials in .env files, never in source code
• Add .env to .gitignore to prevent credential leaks
• Use environment variables in production environments
• Consider using database connection pooling for production

Responsible Usage

When using automation and web interaction features, we encourage:

• Respecting website terms of service and limits
• Being mindful of server resources and privacy considerations
• Following ethical practices in data collection and automation

These are personal choices, but we believe technology works best when used responsibly.

Support and Troubleshooting

Common Issues

ImportError on module load:

# Check what's available
import qufe
qufe.check_dependencies()

# Install missing features
pip install qufe[database]  # or other feature groups

Database connection issues:

# Check configuration
from qufe.dbhandler import help
help()  # Shows configuration options

Browser automation problems:

# Check WebDriver status
from qufe.wbhandler import help  
help()  # Shows WebDriver requirements

Getting Help

1. Check module help: Call help() on any module
2. GitHub Issues: https://github.com/qufe/qufe/issues
3. Documentation: https://qufe.readthedocs.io