![Sequence Types
1. Tuple: (‘john’, 32, [CMSC])
A simple immutable ordered sequence of items
Items can be of mixed types, including collection types
2. Strings: “John Smith”
◦ Immutable
◦ Conceptually very much like a tuple
3. List: [1, 2, ‘john’, (‘up’, ‘down’)]
Mutable ordered sequence of items of mixed types](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-2-320.jpg)
![Sequence Types 1
Define tuples using parentheses and commas
>>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’)
Define lists are using square brackets and commas
>>> li = [“abc”, 34, 4.34, 23]
Define strings using quotes (“, ‘, or “““).
>>> st = “Hello World”
>>> st = ‘Hello World’
>>> st = “““This is a multi-line
string that uses triple quotes.”””](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-4-320.jpg)
![Sequence Types 2
Access individual members of a tuple, list, or string using square bracket “array” notation
Note that all are 0 based…
>>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’)
>>> tu[1] # Second item in the tuple.
‘abc’
>>> li = [“abc”, 34, 4.34, 23]
>>> li[1] # Second item in the list.
34
>>> st = “Hello World”
>>> st[1] # Second character in string.
‘e’](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-5-320.jpg)
![Positive and negative indices
>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
Positive index: count from the left, starting with 0
>>> t[1]
‘abc’
Negative index: count from right, starting with –1
>>> t[-3]
4.56](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-6-320.jpg)
![Slicing: return copy of a subset
>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
Return a copy of the container with a subset of the original members. Start copying at
the first index, and stop copying before second.
>>> t[1:4]
(‘abc’, 4.56, (2,3))
Negative indices count from end
>>> t[1:-1]
(‘abc’, 4.56, (2,3))](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-7-320.jpg)
![Slicing: return copy of a =subset
>>> t = (23, ‘abc’, 4.56, (2,3), ‘def’)
Omit first index to make copy starting from beginning of the container
>>> t[:2]
(23, ‘abc’)
Omit second index to make copy starting at first index and going to end
>>> t[2:]
(4.56, (2,3), ‘def’)](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-8-320.jpg)
![Copying the Whole Sequence
[ : ] makes a copy of an entire sequence
>>> t[:]
(23, ‘abc’, 4.56, (2,3), ‘def’)
Note the difference between these two lines for mutable sequences
>>> l2 = l1 # Both refer to 1 ref,
# changing one affects both
>>> l2 = l1[:] # Independent copies, two refs](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-9-320.jpg)
![The ‘in’ Operator
Boolean test whether a value is inside a container:
>>> t = [1, 2, 4, 5]
>>> 3 in t
False
>>> 4 in t
True
>>> 4 not in t
False
For strings, tests for substrings
>>> a = 'abcde'
>>> 'c' in a
True
>>> 'cd' in a
True
>>> 'ac' in a
False
Be careful: the in keyword is also used in the syntax of for loops and list comprehensions](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-10-320.jpg)
![The + Operator
The + operator produces a new tuple, list, or string whose value is the concatenation of its arguments.
>>> (1, 2, 3) + (4, 5, 6)
(1, 2, 3, 4, 5, 6)
>>> [1, 2, 3] + [4, 5, 6]
[1, 2, 3, 4, 5, 6]
>>> “Hello” + “ ” + “World”
‘Hello World’](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-11-320.jpg)
![The * Operator
The * operator produces a new tuple, list, or string that “repeats” the original content.
>>> (1, 2, 3) * 3
(1, 2, 3, 1, 2, 3, 1, 2, 3)
>>> [1, 2, 3] * 3
[1, 2, 3, 1, 2, 3, 1, 2, 3]
>>> “Hello” * 3
‘HelloHelloHello’](https://image.slidesharecdn.com/python-operators-211006175557/85/Sequence-Types-in-Python-Programming-12-320.jpg)
Sequence Types in Python Programming
- 1. Sequence types: Tuples, Lists, and Strings M.BOBBY ASSISTANT PROFESSOR & HEAD, DEPARTMENT OF COMPUTER SCIENCE SRI ADI CHUNCHANAGIRI WOMEN’S COLLEGE, CUMBUM
- 2. Sequence Types 1. Tuple: (‘john’, 32, [CMSC]) A simple immutable ordered sequence of items Items can be of mixed types, including collection types 2. Strings: “John Smith” ◦ Immutable ◦ Conceptually very much like a tuple 3. List: [1, 2, ‘john’, (‘up’, ‘down’)] Mutable ordered sequence of items of mixed types
- 3. Similar Syntax All three sequence types (tuples, strings, and lists) share much of the same syntax and functionality. Key difference: ◦Tuples and strings are immutable ◦ Lists are mutable The operations shown in this section can be applied to all sequence types ◦most examples will just show the operation performed on one
- 4. Sequence Types 1 Define tuples using parentheses and commas >>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’) Define lists are using square brackets and commas >>> li = [“abc”, 34, 4.34, 23] Define strings using quotes (“, ‘, or “““). >>> st = “Hello World” >>> st = ‘Hello World’ >>> st = “““This is a multi-line string that uses triple quotes.”””
- 5. Sequence Types 2 Access individual members of a tuple, list, or string using square bracket “array” notation Note that all are 0 based… >>> tu = (23, ‘abc’, 4.56, (2,3), ‘def’) >>> tu[1] # Second item in the tuple. ‘abc’ >>> li = [“abc”, 34, 4.34, 23] >>> li[1] # Second item in the list. 34 >>> st = “Hello World” >>> st[1] # Second character in string. ‘e’
- 6. Positive and negative indices >>> t = (23, ‘abc’, 4.56, (2,3), ‘def’) Positive index: count from the left, starting with 0 >>> t[1] ‘abc’ Negative index: count from right, starting with –1 >>> t[-3] 4.56
- 7. Slicing: return copy of a subset >>> t = (23, ‘abc’, 4.56, (2,3), ‘def’) Return a copy of the container with a subset of the original members. Start copying at the first index, and stop copying before second. >>> t[1:4] (‘abc’, 4.56, (2,3)) Negative indices count from end >>> t[1:-1] (‘abc’, 4.56, (2,3))
- 8. Slicing: return copy of a =subset >>> t = (23, ‘abc’, 4.56, (2,3), ‘def’) Omit first index to make copy starting from beginning of the container >>> t[:2] (23, ‘abc’) Omit second index to make copy starting at first index and going to end >>> t[2:] (4.56, (2,3), ‘def’)
- 9. Copying the Whole Sequence [ : ] makes a copy of an entire sequence >>> t[:] (23, ‘abc’, 4.56, (2,3), ‘def’) Note the difference between these two lines for mutable sequences >>> l2 = l1 # Both refer to 1 ref, # changing one affects both >>> l2 = l1[:] # Independent copies, two refs
- 10. The ‘in’ Operator Boolean test whether a value is inside a container: >>> t = [1, 2, 4, 5] >>> 3 in t False >>> 4 in t True >>> 4 not in t False For strings, tests for substrings >>> a = 'abcde' >>> 'c' in a True >>> 'cd' in a True >>> 'ac' in a False Be careful: the in keyword is also used in the syntax of for loops and list comprehensions
- 11. The + Operator The + operator produces a new tuple, list, or string whose value is the concatenation of its arguments. >>> (1, 2, 3) + (4, 5, 6) (1, 2, 3, 4, 5, 6) >>> [1, 2, 3] + [4, 5, 6] [1, 2, 3, 4, 5, 6] >>> “Hello” + “ ” + “World” ‘Hello World’
- 12. The * Operator The * operator produces a new tuple, list, or string that “repeats” the original content. >>> (1, 2, 3) * 3 (1, 2, 3, 1, 2, 3, 1, 2, 3) >>> [1, 2, 3] * 3 [1, 2, 3, 1, 2, 3, 1, 2, 3] >>> “Hello” * 3 ‘HelloHelloHello’