sadtech-kit 0.1.0

A collection of useful Python utilities for dict, list, string manipulation, encoding, and data serialization

toolbox-py

A comprehensive collection of Python utilities for everyday programming tasks.

Features

Dictionary Utilities (toolbox.dict)

• DotDict: Dictionary with dot notation access
• flatten_dict: Flatten nested dictionaries with customizable separators
• unflatten_dict: Convert flattened dicts back to nested structure
• merge_dicts: Recursively merge dictionaries
• get_nested/set_nested: Access nested values using dot notation paths
• filter_dict: Filter dictionaries with predicate functions
• invert_dict: Swap keys and values
• deep_copy_dict: Deep copy nested dictionaries

List Utilities (toolbox.list)

• flatten_list: Recursively flatten nested lists
• chunk_list: Split lists into fixed-size chunks
• unique: Remove duplicates while preserving order
• partition: Split lists based on predicate
• group_by: Group items by key function
• dedupe: Advanced deduplication with custom key functions
• interleave: Merge multiple lists element by element
• compact: Remove falsy values (None, '', False, etc.)

String Utilities (toolbox.string)

• Case conversion: camel_to_snake, snake_to_camel, kebab_case, title_case
• Compression: compress_string/decompress_string with base64 encoding
• Formatting: slugify, truncate, wrap_text
• Text processing: remove_accents, strip_html, reverse_string, count_words

Encoding/Decoding (toolbox.encode, toolbox.decode)

• Base64 encoding and decoding
• Support for both str and bytes

Data Serialization (toolbox.dataclass)

• SerializableDataclass: Enhanced dataclass with JSON serialization
• Alias support for field name mapping
• Preprocessors for data transformation
• Nested dataclass handling

Installation

pip install toolbox-py

Or with uv:

uv add toolbox-py

Usage Examples

Dictionary Operations

from toolbox.dict import flatten_dict, get_nested, DotDict

# Flatten nested dictionary
nested = {'user': {'name': 'John', 'address': {'city': 'NYC'}}}
flat = flatten_dict(nested)
# {'user.name': 'John', 'user.address.city': 'NYC'}

# Access nested values safely
city = get_nested(nested, 'user.address.city', default='Unknown')

# Dot notation access
config = DotDict({'database': {'host': 'localhost'}})
print(config.database.host)  # localhost

List Operations

from toolbox.list import chunk_list, group_by, dedupe

# Split into chunks
items = [1, 2, 3, 4, 5, 6, 7]
chunks = chunk_list(items, 3)  # [[1, 2, 3], [4, 5, 6], [7]]

# Group by key
words = ['apple', 'apricot', 'banana', 'blueberry']
by_first = group_by(words, lambda w: w[0])
# {'a': ['apple', 'apricot'], 'b': ['banana', 'blueberry']}

# Deduplicate with custom key
users = [{'id': 1, 'name': 'Alice'}, {'id': 1, 'name': 'Bob'}]
unique_users = dedupe(users, key=lambda u: u['id'])

String Operations

from toolbox.string import slugify, truncate, camel_to_snake

# Create URL-friendly slugs
slug = slugify('Hello World!')  # 'hello-world'

# Truncate with ellipsis
text = truncate('Long text here', 10)  # 'Long te...'

# Convert naming conventions
snake = camel_to_snake('CamelCase')  # 'camel_case'

Development

# Setup environment
uv sync

# Run tests
pytest

# Format code
black toolbox/ tests/
isort toolbox/ tests/

# Type check
mypy toolbox/

# Build docs
cd docs && make html

Requirements

• Python >= 3.11

License

MIT License - see LICENSE file for details