DictKit

A Python package that provides utility data structures with simple but powerful features, with a focus on flexibility and user experience.

UtilDict

A feature-enriched dictionary.

• Access items with dot notation.
• Flexible subscripting:
  • Get multiple items at once.
  • Set multiple items or the same value to multiple items at once.
• Add items without mutating - return an updated copy
• Drop items without mutating - return a filtered copy
• Accepts a variety of argument types at creation.
• Displays in nested format when printed.
• Easy conversion to json format with .json()

Examples

from dictkit import UtilDict

# Like a dictionary...
ud = UtilDict(a=1, b=2, c=3)
print(ud)  # {'a': 1, 'b': 2, 'c': 3}

# ... but can be initialized from a variety of types
ud = UtilDict({"a": 1}, [("b", 2)], c=3)
print(ud)  # {'a': 1, 'b': 2, 'c': 3}

# Supports dot notation access
print(ud['a'])  # 1
print(ud.a)  # 1

# Get multiple items at once
selected_items = ud[["a", "c"]]
print(selected_items)  # {'a': 1, 'c': 3}

# Set multiple items at once
ud[["a", "c"]] = 10, 30
print(ud)  # {'a': 10, 'b': 2, 'c': 30}

# Set the same value to multiple keys at once
ud[["a", "c"]] = 99
print(ud)  # {'a': 99, 'b': 2, 'c': 99}

# Add items from a variety of types
ud2 = ud.add({"c": 3}, ("d", 4), e=5)
print(ud2)  # {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

# Add items from a 2-column dataframe
import pandas as pd
ud = UtilDict(a=1, b=2)
df = pd.DataFrame({"key": ["c", "d"], "value": [3, 4]})
ud2 = ud.add(df)
print(ud2)  # {'a': 1, 'b': 2, 'c': 3, 'd': 4}

# Drop multiple items at once
>>> ud3 = ud2.drop("a", "c")
>>> print(ud3)  # {'b': 2, 'd': 4}

render()

Somehow, this tool does not yet exist from any popular libraries.

Represents iterables in nested JSON structure, but with Python formatting.

>>> from dictkit.render import render
>>> dct = {'a':1, 'b': {'c':3}, 'list': [int,'b']}
>>> s = render(dct)
>>> s
{
   'a': 1,
   'b': {
      'c': 3
   },
   'list': [
      <class 'int'>,
      'b'
   ]
}

It handles multiline-formatted strings (like dataframes) elegantly, maintaining their original appearance.

>>> from pandas import DataFrame
>>> df = DataFrame([[1, 2, 3], [4, 55, 6]],
...                columns=["ONE", "TWO", "THREE"])
>>> fmt_str = '''|------|
... |      |
... |------|'''
>>> dct = {
...     "key": "value",
...     "formatted string": fmt_str,
...     "nested dct": {
...         "x": "y",
...         "dataframe": df,
...         "a": "b",
...         "formatted string": fmt_str
...     },
...     "lst": ['a', 'b'],
...     "tple": ('a','b')
... }
>>> render(dct, quote=False)
{
   key: value,
   formatted string:
      |------|
      |      |
      |------|,
   nested dct: {
      x: y,
      dataframe:
            ONE  TWO  THREE
         0    1    2      3
         1    4   55      6,
      a: b,
      formatted string:
         |------|
         |      |
         |------|
   },
   lst: [
      a,
      b
   ],
   tple: (
      a,
      b
   )
}