A lightweight Python library for safely navigating and manipulating nested data structures (dicts, lists) using simple dot-notation paths. Ideal for JSON APIs, configs, and complex dict/list objects.
Project description
Nested Utils
A lightweight Python library for safely navigating and manipulating nested data structures (dicts, lists) using simple dot-notation paths. Ideal for JSON APIs, configs, and complex dict/list objects.
Why nestedutils?
Working with deeply nested data (like JSON API responses) often leads to verbose, error-prone boilerplate:
# The Standard Way: Verbose and hard to read
user_name = None
if data and "users" in data and len(data["users"]) > 0:
user = data["users"][0]
if "profile" in user:
user_name = user["profile"].get("name")
# With nestedutils: Clean, safe, and readable
from nestedutils import get_path
user_name = get_path(data, "users.0.profile.name")
Features
- Simple Path Syntax: Use dot-notation strings (
"a.b.c") or lists (["a", "b", "c"]) to navigate nested structures - Mixed Data Types: Seamlessly work with dictionaries, lists
- List Index Support: Access list elements using numeric indices, including negative indices
- Auto-creation: Automatically create missing intermediate containers when setting values
- Flexible Fill Strategies: Control how missing containers are created with different fill strategies
- Type Safety: Comprehensive error handling with descriptive error messages and error codes
- Zero Dependencies: Pure Python implementation with no external dependencies
Use Cases
- JSON API Responses: Safely extract values from complex, unpredictable JSON responses without dozens of checks.
- Configuration Management: easily read and modify deeply nested settings in configuration dictionaries.
- Data Transformation: Rapidly remap data from one complex structure to another using
get_pathandset_path.
Installation
pip install nestedutils
Quick Start
from nestedutils import get_path, set_path, del_path
# Create a nested structure
data = {}
# Set values using dot-notation
set_path(data, "user.name", "John")
set_path(data, "user.age", 30)
set_path(data, "user.hobbies.0", "reading")
set_path(data, "user.hobbies.1", "coding")
# Access values
name = get_path(data, "user.name") # "John"
age = get_path(data, "user.age") # 30
first_hobby = get_path(data, "user.hobbies.0") # "reading"
# Delete values
del_path(data, "user.age")
API Reference
get_path(data, path, default=None)
Retrieve a value from a nested data structure.
Parameters:
data: The data structure to navigate (dict, list, tuple, or nested combinations)path: Path to the value (string with dot notation or list of keys/indices)default: Value to return if path doesn't exist (default:None)
Returns: The value at the path, or default if not found
Examples:
data = {"a": {"b": {"c": 5}}}
get_path(data, "a.b.c") # 5
get_path(data, "a.b.d", default=99) # 99
data = {"items": [{"name": "apple"}, {"name": "banana"}]}
get_path(data, "items.1.name") # "banana"
get_path(data, "items.-1.name") # "banana" (negative index)
set_path(data, path, value, fill_strategy="auto")
Set a value in a nested data structure, creating intermediate containers as needed.
Parameters:
data: The data structure to modify (must be mutable: dict or list)path: Path where to set the value (string with dot notation or list of keys/indices)value: The value to setfill_strategy: How to fill missing containers (default:"auto")"auto": Intelligently creates{}for dicts,[]for lists"none": Fills missing list items withNone"dict": Always creates dictionaries"list": Always creates lists
Examples:
data = {}
set_path(data, "user.profile.name", "Alice")
# Creates: {"user": {"profile": {"name": "Alice"}}}
data = {}
set_path(data, "items.0.name", "Item 1")
# Creates: {"items": [{"name": "Item 1"}]}
data = {}
set_path(data, "items.5", "Item 6", fill_strategy="none")
# Creates: {"items": [None, None, None, None, None, "Item 6"]}
del_path(data, path, allow_list_mutation=False)
Delete a value from a nested data structure.
Parameters:
data: The data structure to modifypath: Path to the value to deleteallow_list_mutation: IfTrue, allows deletion from lists (default:False)
Returns: The deleted value
Raises: PathError if the path doesn't exist or deletion is not allowed
Examples:
data = {"a": {"b": 1, "c": 2}}
del_path(data, "a.b") # Returns 1, data becomes {"a": {"c": 2}}
data = {"items": [1, 2, 3]}
del_path(data, "items.1", allow_list_mutation=True) # Returns 2
# data becomes {"items": [1, 3]}
Error Handling
The library uses PathError exceptions with error codes for different failure scenarios:
from nestedutils import PathError, PathErrorCode
try:
set_path(data, "invalid.path", 1)
except PathError as e:
print(e.message) # Error message
print(e.code) # Error code (PathErrorCode enum)
Error Codes:
INVALID_PATH: Invalid path format or typeINVALID_INDEX: Invalid list indexMISSING_KEY: Key doesn't exist in dictionaryEMPTY_PATH: Path is emptyIMMUTABLE_CONTAINER: Attempted to modify a tupleINVALID_FILL_STRATEGY: Invalid fill strategy value
Advanced Usage
Using List Paths
List paths are useful when keys contain dots:
data = {}
set_path(data, ["user.name", "first"], "John")
set_path(data, ["user.name", "last"], "Doe")
# Creates: {"user.name": {"first": "John", "last": "Doe"}}
Negative List Indices
Negative indices work like Python list indexing:
data = {"items": [10, 20, 30]}
get_path(data, "items.-1") # 30 (last item)
set_path(data, "items.-1", 999) # Updates last item
Working with Tuples
Tuples are read-only. You can read from them but cannot modify:
data = {"items": (1, 2, 3)}
get_path(data, "items.0") # 1 (works)
set_path(data, "items.0", 9) # Raises PathError (tuples are immutable)
Handling None Values
The library can navigate through None values when setting:
data = {"a": None}
set_path(data, "a.b.c", 10)
# Replaces None with container: {"a": {"b": {"c": 10}}}
Requirements
- Python 3.8+
Development
For development setup, building, and contributing, see DEVELOPMENT.md.
Changelog
See CHANGELOG.md for a detailed list of changes and version history.
License
MIT License - see LICENSE file for details.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Support
If you find this library useful, please consider:
- ⭐ Starring the repository on GitHub to help others discover it.
- 💖 Sponsoring to support ongoing maintenance and development.
Become a Sponsor on GitHub | Support on Patreon
Links
- PyPI: https://pypi.org/project/nestedutils/
- Homepage: https://github.com/ysskrishna/nestedutils
- Repository: https://github.com/ysskrishna/nestedutils.git
- Issues: https://github.com/ysskrishna/nestedutils/issues
Author
Y. Siva Sai Krishna
- GitHub: @ysskrishna
- LinkedIn: ysskrishna
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