Metadata-Version: 2.1
Name: nifty-nesting
Version: 0.2
Summary: Python utilities for arbitrarily nested data structures.
Home-page: https://github.com/aetiusflavius/nifty-nesting/
Author: Aetius Flavius
Author-email: aetius.flavius.390@gmail.com
License: UNKNOWN
Keywords: nested,data,structure,arbitrary,utilities,manipulation
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown

# Nifty Nesting

### Python utilities for manipulating arbitrarily nested data structures.

Includes: `flatten`, `map`, `pack_into`, `filter`, `reduce`, `assert_same_structure`

Heavily inspired by the [internal nesting utilities in TensorFlow.](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/util/nest.py)

Supports `collections.Sequence` (`list`, `tuple`, etc.), `collections.Mapping` (`dict`, etc.), `set`, `namedtuple`, and `attr` data classes as part of the nesting structure.

Allows users to specify what elements should be considered part of the nesting structure and which elements should be considered "atomic" data elements via an `is_atomic` argument to all functions.

Examples:

### flatten

Returns a list containing every atomic element of a nested structure. Elements are returned in a determinstic order.

```python
import nifty_nesting as nest

structure = [1, (2, {'a': 3}, 4]
flat = nest.flatten(structure)
assert flat == [1, 2, 3, 4]

structure = ([1, 2], {'a': [3, 4], 'b': [5, 6]})
flat = nest.flatten(structure, is_atomic=lambda x: isinstance(x, list))
assert flat == [[1, 2], [3, 4], [5, 6]] 
```

### map

Maps every atomic element of a nested structure.

```python
import nifty_nesting as nest

structure = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
mapped = nest.map(lambda x: 2*x, structure)
assert mapped == {'a': [2, 4], 'b': (6, 8, {'c': 10})}

structure = ([1, 2], {'a': [3, 4], 'b': [5, 6]})
mapped = nest.map(lambda x: max(x), structure, is_atomic=lambda x: isinstance(x, list))
assert mapped == (2, {'a': 4, 'b': 6})
```

### pack_list_into

Packs a flat list into any arbitrary structure with the same number of atomic elements. Elements are packed in a deterministic order that is compatible with flat lists created by `flatten`.

```python
import nifty_nesting as nest

structure = (1, {'key': [2, {3, 4}, 5]}, [6, 7])
flat_list = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
packed = nest.pack_list_into(structure, flat_list)
assert packed == ('a', {'key': ['b', {'c', 'd'}, 'e']}, ['f', 'g'])
```

## Documentation

### Main functions

#### flatten(structure, is_atomic=is_scalar)

    Returns a flattened list containing the atomic elements of `structure`.

    The elements of `structure` are flattened in a deterministic order.

    ```
    import nifty_nesting as nest
    flat = nest.flatten([1, (2, {'a': 3}, 4])
    assert flat == [1, 2, 3, 4]
    ```

    Arguments:
        structure: An arbitrarily nested structure of elements.
        is_atomic: A function that returns `True` if a certain element
          of `structure` ought to be treated as an atomic element, i.e.
          not as part of the nesting structure.

    Returns:
        A list containing every atomic element of `structure`.

#### map(func, structure, is_atomic=is_scalar)
    Maps the atomic elements of `structure`.

    ```
    import nifty_nesting as nest
    structure = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
    mapped = nest.map(lambda x: 2*x, structure)
    assert mapped == {'a': [2, 4], 'b': (6, 8, {'c': 10})}
    ```

    Arguments:
      func: The function to use to map atomic elements of `structure`.
      structure: An arbitrarily nested structure of elements.
      is_atomic: A function that returns `True` if a certain element
        of `structure` ought to be treated as an atomic element, i.e.
        not as part of the nesting structure.

    Returns:
      A structure with the same structure as `structure`, with the atomic elements
        mapped according to `func`.

#### reduce(func, structure, is_atomic=is_scalar):
    Reduces the atomic elements of `structure`.

    ```
    import nifty_nesting as nest
    structure = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
    reduced = nest.reduce(lambda x, y: x+y, structure)
    assert reduced == 15
    ```

    Arguments:
      func: The function to use to reduce atomic elements of `structure`.
      structure: An arbitrarily nested structure of elements.
      is_atomic: A function that returns `True` if a certain element
        of `structure` ought to be treated as an atomic element, i.e.
        not as part of the nesting structure.

    Returns:
      The reduced value.

 #### filter(func, structure, keep_structure=True, is_atomic=is_scalar)
    Filters the atomic elements of `structure`.

    ```
    import nifty_nesting as nest
    structure = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
    filtered = nest.filter(lambda x: x > 2, structure)
    assert filtered == {'a': [], 'b': (3, 4, {'c': 5})}

    filtered = nest.filter(lambda x: x > 2, structure, keep_structure=False)
    assert filtered == {'b': (3, 4, {'c': 5})}
    ```

    Arguments:
      func: The function to use to filter atomic elements of `structure`.
      structure: An arbitrarily nested structure of elements.
      keep_structure: Whether or not to preserve empty substructures. If
        `True`, these structures will be kept. If `False`, they will be
        entirely filtered out.
      is_atomic: A function that returns `True` if a certain element
        of `structure` ought to be treated as an atomic element, i.e.
        not as part of the nesting structure.

    Returns:
      The filtered elements of `structure` in the same structure as `structure`.

 #### assert_same_structure(structure1, structure2, is_atomic=is_scalar)
    Asserts that `structure1` and `structure2` have the same nested structure.

    ```
    import nifty_nesting as nest
    structure1 = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
    structure1 = {'a': ['a', 'b'], 'b': ('c', 'd', {'c': 'e'})}
    nest.assert_same_structure(structure1, structure2)
    ```

    Arguments:
      structure1: An arbitrarily nested structure of elements.
      structure2: An arbitrarily nested structure of elements.
      is_atomic: A function that returns `True` if a certain element
        of `structure` ought to be treated as an atomic element, i.e.
        not as part of the nesting structure.

    Raises:
      `AssertionError` if the structures are not the same.

#### pack_list_into(structure, flat_list, is_atomic=is_scalar)
    Packs the atomic elements of `flat_list` into the same structure as `structure`.

    ``
    import nifty_nesting as nest
    structure = {'a': [1, 2], 'b': (3, 4, {'c': 5})}
    flat_list = [2, 4, 6, 7, 10]
    packed = nest.pack_list_into(structure, flat_list)
    assert packed == {'a': [2, 4], 'b': (6, 8, {'c': 10})}
    ```

    Arguments:
      structure: An arbitrarily nested structure of elements.
      flat_list: A flat list with the same number of atomic elements as
        `structure`.
      is_atomic: A function that returns `True` if a certain element
        of `structure` ought to be treated as an atomic element, i.e.
        not as part of the nesting structure.

    Returns:
      A structure with the atomic elements of `flat_list` packed into the same
        structure as `structure`.

### Helper functions for `is_atomic` 

 #### is_scalar(element)
    An `is_atomic` criterion. Returns `True` for scalar elements.

    Scalar elements are : strings and any object that is not one of:
      collections.Sequence, collections.Mapping, set, or attrs object.

    ```
    import nifty_nesting as nest
    flat = nest.flatten([1, [2, 3]], is_atomic=is_scalar)
    assert flat == [1, 2, 3]
    ```

    Arguments:
      element: The element to check.

    Returns:
      `True` if the element is a scalar, else `False`.

#### has_max_depth(depth, is_atomic=is_scalar)
    Returns an `is_atomic` criterion that checks the depth of a structure.

    This function returns a function that can be passed to `is_atomic` to
    preserve all structures up to a given depth.

    ```
    import nifty_nesting as nest
    flat = nest.flatten([[1, 2], [3, [4, 5]]], is_atomic=has_max_depth(1))
    assert flat == [[1, 2], [3], [4, 5]]
    ```

    Arguments:
      depth: The maximum depth a structure can have in order to be considered
        as an atomic element. For instance, `[1, 2, {'a': 3}]` has a depth of 2.
        is_atomic: A function that returns `True` if a certain element
          of `structure` ought to be treated as an atomic element, i.e.
          not as part of the nesting structure.

    Returns:
       A function that can be passed to `is_atomic` to check for elements
       with a depth of `depth` or less.

#### is_sequence(element)

Returns `True` for instances of `collections.Sequence`.

#### is_mapping(element)

Returns `True` for instances of `collections.Mapping`.

#### is_set(element)

 Returns `True` for instances of `set`.

 #### is_namedtuple(element)

 Returns `True` for instances of `namedtuple`.

 #### is_attrs_object(element)

 Returns `True` for instances of `attr`-decorated classes.













