carlee-tools 1.0.0

Core utilities, types, and plotting for atmospheric science

cloudy-core

Core utilities and type definitions for cloudy ecosystem of atmospheric modeling packages.

Overview

cloudy-core provides shared utilities and type definitions that are used across the cloudy ecosystem of atmospheric modeling and visualization packages. This package serves as a common dependency for other cloudy packages.

Features

• Type Definitions: Common type aliases for paths, configurations, and Blender objects
• Datetime Utilities: Functions for parsing and formatting datetime objects
• File I/O: Convenient file reading/writing functions for common scientific data formats (NetCDF, CSV, pickle, NumPy)
• Data Utilities: Helper functions for working with arrays, key-value pairs, and data structures

Installation

Install from a local copy:

pip install -e /path/to/cloudy-core

Usage

from cloudy_core import PathLike, dt_to_str, read_file, TwoWayDict
from cloudy_core.utils import current_dt_str
from cloudy_core.types_core import ConfigDict

# Use datetime utilities
timestamp = current_dt_str()

# Read scientific data files
data = read_file("data.nc")  # Automatically uses xarray for .nc files

# Work with nested dictionaries
nested = TwoWayDict({'a': {'x': 1, 'y': 2}, 'b': {'x': 3, 'y': 4}})

Type Definitions

• PathLike: Union of str and Path for file paths
• ConfigDict: Dictionary for storing arbitrary configuration data
• BlenderObject: Type alias for Blender objects (gracefully handles non-Blender environments)
• BlenderCollection: Type alias for Blender collections
• NumpyNumeric: Union of NumPy integer and floating types

Key Utilities

Datetime Functions

• dt_to_str(): Convert datetime-like objects to formatted strings
• str_to_dt(): Parse datetime strings with flexible format detection
• current_dt_str(): Get current time as formatted string

File I/O

• read_file(): Automatically detect file type and read with appropriate library
• write_file(): Write data with format detection

Data Structures

• TwoWayDict: Dictionary accessor that allows indexing by outer or inner keys

Dependencies

• typing-extensions (Python < 3.10)

Optional dependencies for full functionality:

• numpy
• xarray (for NetCDF support)
• pandas (for CSV support and enhanced datetime parsing)

License

MIT License