6.4. Type Nested¶
Iterable is an object
Iterable element is an object too
Therefore an element of a Iterable could be another Iterable
There is no limit how nested it could be
>>> obj = 1
>>>
>>> data = [obj, obj, obj]
>>> data
[1, 1, 1]
>>> obj = [1, 2, 3]
>>>
>>> data = [obj, obj, obj]
>>> data
[[1, 2, 3],
[1, 2, 3],
[1, 2, 3]]
6.4.1. What is an Object?¶
Basic types are objects
Iterable are objects too
Everything is an object
>>> int.mro()
[<class 'int'>, <class 'object'>]
>>> float.mro()
[<class 'float'>, <class 'object'>]
>>> bool.mro()
[<class 'bool'>, <class 'int'>, <class 'object'>]
>>> type(None).mro()
[<class 'NoneType'>, <class 'object'>]
>>> tuple.mro()
[<class 'tuple'>, <class 'object'>]
>>> list.mro()
[<class 'list'>, <class 'object'>]
>>> set.mro()
[<class 'set'>, <class 'object'>]
6.4.2. List of Lists¶
Also known as multidimensional lists or matrix.
Readability differs depending on whitespaces:
>>> a = [[1,2,3],[4,5,6],[7,8,9]]
>>> b = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
>>> c = [[1,2,3], [4,5,6], [7,8,9]]
>>> d = [
... [1, 2, 3],
... [4, 5, 6],
... [7, 8, 9],
... ]
>>> e = [
... [1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]]
>>> f = [[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9],
... ]
>>> g = [[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]]
6.4.3. List of Tuples¶
Readability differs depending on whitespaces:
>>> data = [(4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica')]
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica')]
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
6.4.4. List of Dicts¶
>>> data = [
... {'sepal_length': 5.1, 'sepal_width': 3.5, 'species': 'setosa'},
... {'petal_length': 4.1, 'petal_width': 1.3, 'species': 'versicolor'},
... {'sepal_length': 6.3, 'petal_width': 1.8, 'species': 'virginica'},
... {'sepal_length': 5.0, 'petal_width': 0.2, 'species': 'setosa'},
... {'sepal_width': 2.8, 'petal_length': 4.1, 'species': 'versicolor'},
... {'sepal_width': 2.9, 'petal_width': 1.8, 'species': 'virginica'},
... ]
>>> data = [
... {'measurements': [4.7, 3.2, 1.3, 0.2], 'species': 'setosa'},
... {'measurements': [7.0, 3.2, 4.7, 1.4], 'species': 'versicolor'},
... {'measurements': [7.6, 3.0, 6.6, 2.1], 'species': 'virginica'},
... ]
>>> data = [
... {'sepal_length': 5.4, 'sepal_width': 3.9, 'petal_length': 1.3, 'petal_width': 0.4, 'species': 'setosa'},
... {'sepal_length': 5.9, 'sepal_width': 3.0, 'petal_length': 5.1, 'petal_width': 1.8, 'species': 'virginica'},
... {'sepal_length': 6.0, 'sepal_width': 3.4, 'petal_length': 4.5, 'petal_width': 1.6, 'species': 'versicolor'},
... ]
6.4.5. Many Types¶
Readability differs depending on whitespaces:
>>> data = [[1, 2],
... (3, 4, 5, 6),
... {7, 8, 9, 10, 11}]
>>> data = [
... [1, 2],
... (3, 4, 5, 6),
... {7, 8, 9, 10, 11}]
>>> data = [
... [1, 2],
... (3, 4, 5, 6),
... {7, 8, 9, 10, 11},
... ]
Content could be both basic types and sequences:
>>> data = [
... 1,
... 1.5,
... True,
... None,
... [1, 2],
... (3, 4, 5, 6),
... {7, 8, 9, 10, 11},
... ]
>>> data = {
... 'date': '1969-07-21',
... 'age': 42,
... 'astronaut': {'name': 'Mark Watney', 'medals': {'Medal of Honor', 'Purple Heart'}},
... 'agency': ['NASA', 'ESA', 'POLSA'],
... 'location': ('Baikonur', 'Johnson Space Center'),
... }
6.4.6. Length¶
list[list]:
>>> data = [[1, 2, 3],
... [4, 5, 6],
... [7, 8, 9]]
>>>
>>> len(data)
3
>>> len(data[0])
3
list[tuple]:
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
>>>
>>> len(data)
3
>>> len(data[0])
5
list[dict]:
>>> data = [
... {'measurements': [4.7, 3.2, 1.3, 0.2], 'species': 'setosa'},
... {'measurements': [7.0, 3.2, 4.7, 1.4], 'species': 'versicolor'},
... {'measurements': [7.6, 3.0, 6.6, 2.1], 'species': 'virginica'},
... ]
>>>
>>>
>>> len(data)
3
>>>
>>> len(data[0])
2
>>>
>>> len(data[1])
2
>>>
>>> len(data[1]['species'])
10
>>>
>>> len(data[1]['measurements'])
4
6.4.7. Append vs Extend¶
>>> data = [1,2,3]
>>> data.extend([4,5,6])
>>>
>>> data
[1, 2, 3, 4, 5, 6]
>>> data = [1,2,3]
>>> data.append([4,5,6])
>>>
>>> data
[1, 2, 3, [4, 5, 6]]
Append elements using list.append():
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
>>>
>>> row = (4.9, 2.5, 4.5, 1.7, 'virginica')
>>>
>>> data.append(row)
>>> data
[(4.7, 3.2, 1.3, 0.2, 'setosa'),
(7.0, 3.2, 4.7, 1.4, 'versicolor'),
(7.6, 3.0, 6.6, 2.1, 'virginica'),
(4.9, 2.5, 4.5, 1.7, 'virginica')]
Append elements using list.extend():
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
>>>
>>> row = (4.9, 2.5, 4.5, 1.7, 'virginica')
>>>
>>> data.extend(row)
>>> data
[(4.7, 3.2, 1.3, 0.2, 'setosa'),
(7.0, 3.2, 4.7, 1.4, 'versicolor'),
(7.6, 3.0, 6.6, 2.1, 'virginica'),
4.9,
2.5,
4.5,
1.7,
'virginica']
Extend with many rows:
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
>>>
>>> rows = [
... (4.9, 2.5, 4.5, 1.7, 'virginica'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor')
... ]
>>>
>>> data.extend(rows)
>>> data
[(4.7, 3.2, 1.3, 0.2, 'setosa'),
(7.0, 3.2, 4.7, 1.4, 'versicolor'),
(7.6, 3.0, 6.6, 2.1, 'virginica'),
(4.9, 2.5, 4.5, 1.7, 'virginica'),
(7.0, 3.2, 4.7, 1.4, 'versicolor')]
Append with many rows:
>>> data = [
... (4.7, 3.2, 1.3, 0.2, 'setosa'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor'),
... (7.6, 3.0, 6.6, 2.1, 'virginica'),
... ]
>>>
>>> rows = [
... (4.9, 2.5, 4.5, 1.7, 'virginica'),
... (7.0, 3.2, 4.7, 1.4, 'versicolor')
... ]
>>>
>>> data.append(rows)
>>> data
[(4.7, 3.2, 1.3, 0.2, 'setosa'),
(7.0, 3.2, 4.7, 1.4, 'versicolor'),
(7.6, 3.0, 6.6, 2.1, 'virginica'),
[(4.9, 2.5, 4.5, 1.7, 'virginica'), (7.0, 3.2, 4.7, 1.4, 'versicolor')]]
6.4.8. Use Case - 0x01¶
One dimensional (1D) structure - vector:
>>> from pprint import pprint
>>> obj1 = 1
>>> obj2 = 2
>>> obj3 = 3
>>>
>>> data = [obj1, obj2, obj3]
>>>
>>> pprint(data, width=20)
[1, 2, 3]
Two dimensional (2D) structure - matrix:
>>> obj1 = [1, 2, 3]
>>> obj2 = [4, 5, 6]
>>> obj3 = [7, 8, 9]
>>>
>>> data = [obj1, obj2, obj3]
>>>
>>> pprint(data, width=20)
[[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
Three dimensional (3D) structure - tensor:
>>> obj1 = [[1,2,3], [4,5,6], [7,8,9]]
>>> obj2 = [[10,20,30], [40,50,60], [70,80,90]]
>>> obj3 = [[100,200,300], [400,500,600], [700,800,900]]
>>>
>>> data = [obj1, obj2, obj3]
>>>
>>> pprint(data, width=20)
[[[1, 2, 3],
[4, 5, 6],
[7, 8, 9]],
[[10, 20, 30],
[40, 50, 60],
[70, 80, 90]],
[[100, 200, 300],
[400, 500, 600],
[700, 800, 900]]]
6.4.9. Assignments¶
"""
* Assignment: Iterable Nested Create
* Type: class assignment
* Complexity: easy
* Lines of code: 4 lines
* Time: 3 min
English:
1. Create nested list `result` with elements:
a. tuple: 1, 2, 3
b. list: 1.1, 2.2, 3.3
c. set: 'red', 'green', 'blue'
2. Run doctests - all must succeed
Polish:
1. Stwórz zagnieżdżoną listę `result` z elementami:
a. tuple: 1, 2, 3
b. list: 1.1, 2.2, 3.3
c. set: 'red', 'green', 'blue'
2. Uruchom doctesty - wszystkie muszą się powieść
Tests:
>>> import sys; sys.tracebacklimit = 0
>>> assert result is not Ellipsis, \
'Assign your result to variable `result`'
>>> assert type(result) is list, \
'Variable `result` has invalid type, should be list'
>>> assert len(result) == 3, \
'Variable `result` length should be 3'
>>> assert (1, 2, 3) in result
>>> assert [1.1, 2.2, 3.3] in result
>>> assert {'red', 'green', 'blue'} in result
"""
# Result should contain:
# - tuple: 1, 2, 3
# - list: 1.1, 2.2, 3.3
# - set: 'red', 'green', 'blue'
# type: list[tuple|list|set]
result = ...