<jupyter_start><jupyter_text>Line continuation  do not run.<jupyter_code>>>> a = [
        [1, 2, 3, 4, 5],
        [6, 7, 8, 9, 10],
        [11, 12, 13, 14, 15],
        [16, 17, 18, 19, 20],
        [21, 22, 23, 24, 25]
    ]
a
>>> someone_is_of_working_age = (
...     (person1_age >= 18 and person1_age <= 65)
...     or (person2_age >= 18 and person2_age <= 65)
...     or (person3_age >= 18 and person3_age <= 65)
... )
>>> x = (
...     1 + 2
...     + 3 + 4
...     + 5 + 6
... )
>>> a = [
...     [
...         ['foo', 'bar'],
...         [1, 2, 3]
...     ],
...     {1, 3, 5},
...     {
...         'a': 1,
...         'b': 2
...     }
... ]<jupyter_output><empty_output><jupyter_text>To indicate explicit line continuation, you can specify a backslash (\) character as the final character on the line. In that case, Python ignores the following newline, and the statement is effectively continued on next line:<jupyter_code>>>> s = \
... 'Hello, World!'
>>> s
'Hello, World!'

>>> x = 1 + 2 \
...     + 3 + 4 \
...     + 5 + 6
# must be the last character on the line! Even whitespace gives an error<jupyter_output><empty_output><jupyter_text>Multiple statements per line<jupyter_code>>>> x = 1; y = 2; z = 3
>>> print(x); print(y); print(z)
>>> x, y, z = 1, 2, 3
>>> print(x, y, z, sep='\n')<jupyter_output><empty_output><jupyter_text>Whitespace<jupyter_code># Character	ASCII Code	Literal Expression
# space    	32 (0x20)	' '
# tab   	9 (0x9) 	'\t'
# newline	10(0xa) 	'\n'
>>> x=3;y=12
>>> x+y
15

>>> (x==3)and(x<y)
True

>>> a=['foo','bar','baz']
>>> a
['foo', 'bar', 'baz']

>>> d={'foo':3,'bar':4}
>>> d
{'foo': 3, 'bar': 4}

>>> x,y,z='foo',14,21.1
>>> (x,y,z)
('foo', 14, 21.1)

>>> z='foo'"bar"'baz'#Comment
>>> z
'foobarbaz'<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.23353967360720315, 'fraction_numerical': 0.06527855936972425, 'mean_word_length': 2.5774647887323945, 'pattern_counts': {'":': 0, '<': 21, '<?xml version=': 0, '>': 86, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '400023', 'license': 'MIT', 'n_tokens_mistral': 818, 'n_tokens_neox': 723, 'n_words': 192, 'path': 'w1/d2-day_2/Lexical_structure.ipynb', 'repo_name': 'bmskarate/lighthouseMain', 'size': '1777'}