In this day, My plan is to understand how to build the normal Data Structure by Python.
Start Form List:
we can use list as stack or queue very conveniently.
Is that all? Nope, there are some other build-in functions which are very usefull when used with lists: that is filter( ), map( ), reduce( ).
“filter(function, sequence)” returns a sequence consisting of those items from the sequence for which function(item) is true. If sequence is a string or tuple, the result will be of the same type; otherwise, it is always a list.
Example:
>>> def f(x): return x % 2 != 0 and x % 3 != 0
...
>>> filter(f, range(2, 25))
[5, 7, 11, 13, 17, 19, 23]
“map(function, sequence)” calls function(item) for each of the sequence’s items and returns a list of the return values. For example, to compute some cubes:
>>> def cube(x): return x*x*x
...
>>> map(cube, range(1, 11))
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]
More than one sequence may be passed; the function must then have as many arguments as there are sequences and is called with the corresponding item from each sequence (or None if some sequence is shorter than another). For example:
>>> seq = range(8)
>>> def add(x, y): return x+y
...
>>> map(add, seq, seq)
[0, 2, 4, 6, 8, 10, 12, 14]
“reduce(function, sequence)” returns a single value constructed by calling the binary function function on the first two items of the sequence, then on the result and the next item, and so on. For example, to compute the sum of the numbers 1 through 10:
>>> def add(x,y): return x+y
...
>>> reduce(add, range(1, 11))
55
If there’s only one item in the sequence, its value is returned; if the sequence is empty, an exception is raised.
LIST Comprehensions provides a more derect way to generate a list.
>>> [str(round(355/113.0, i)) for i in range(1,6)]
['3.1', '3.14', '3.142', '3.1416', '3.14159']
Use del L to delete a list or del L[index] to delete some elements of a list.
About Tuble
See some illustrations from Dive Into Python
A tuple is an immutable list. A tuple can not be changed in any way once it is created.
Example 3.15. Defining a tuple
>>> t = ("a", "b", "mpilgrim", "z", "example") 
>>> t
('a', 'b', 'mpilgrim', 'z', 'example')
>>> t[0] 
'a'
>>> t[-1] 
'example'
>>> t[1:3] 
('b', 'mpilgrim')
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A tuple is defined in the same way as a list, except that the whole set of elements is enclosed in parentheses instead of square brackets. |
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The elements of a tuple have a defined order, just like a list. Tuples indices are zero-based, just like a list, so the first element of a non-empty tuple is always t[0]. |
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Negative indices count from the end of the tuple, just as with a list. |
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Slicing works too, just like a list. Note that when you slice a list, you get a new list; when you slice a tuple, you get a new tuple. |
Example 3.16. Tuples Have No Methods
>>> t
('a', 'b', 'mpilgrim', 'z', 'example')
>>> t.append("new")
Traceback (innermost last):
File "<interactive input>", line 1, in ?
AttributeError: 'tuple' object has no attribute 'append'
>>> t.remove("z")
Traceback (innermost last):
File "<interactive input>", line 1, in ?
AttributeError: 'tuple' object has no attribute 'remove'
>>> t.index("example")
Traceback (innermost last):
File "<interactive input>", line 1, in ?
AttributeError: 'tuple' object has no attribute 'index'
>>> "z" in t
True
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You can’t add elements to a tuple. Tuples have no append or extend method. |
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You can’t remove elements from a tuple. Tuples have no remove or pop method. |
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You can’t find elements in a tuple. Tuples have no index method. |
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You can, however, use in to see if an element exists in the tuple. |
So what are tuples good for?
- Tuples are faster than lists. If you’re defining a constant set of values and all you’re ever going to do with it is iterate through it, use a tuple instead of a list.
- It makes your code safer if you “write-protect” data that does not need to be changed. Using a tuple instead of a list is like having an implied assert statement that shows this data is constant, and that special thought (and a specific function) is required to override that.
- Remember that I said that dictionary keys can be integers, strings, and “a few other types“? Tuples are one of those types. Tuples can be used as keys in a dictionary, but lists can’t be used this way.Actually, it’s more complicated than that. Dictionary keys must be immutable. Tuples themselves are immutable, but if you have a tuple of lists, that counts as mutable and isn’t safe to use as a dictionary key. Only tuples of strings, numbers, or other dictionary-safe tuples can be used as dictionary keys.
- Tuples are used in string formatting, as you’ll see shortly.
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| Tuples can be converted into lists, and vice-versa. The built-in tuple function takes a list and returns a tuple with the same elements, and the list function takes a tuple and returns a list. In effect, tuple freezes a list, and list thaws a tuple. |
Set:
Python also includes a data type for sets. A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference.
A set gonna be faster to execute member test. and what’s more two sets can + – | & ^ (letters in a or b but not both)
Dictionary:
The dictionary in Python is actruly the same as a hash table, like ” associative memories” or “associative arrays”.
The keys() method of a dictionary object returns a list of all the keys used in the dictionary, in arbitrary order (if you want it sorted, just apply the sort() method to the list of keys). To check whether a single key is in the dictionary, either use the dictionary’s has_key() method or the in keyword.
The dict() constructor builds dictionaries directly from lists of key-value pairs stored as tuples. When the pairs form a pattern, list comprehensions can compactly specify the key-value list.
Loop:
When looping through dictionaries, the key and corresponding value can be retrieved at the same time using the iteritems() method.
>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
>>> for k, v in knights.iteritems():
... print k, v
...
gallahad the pure
robin the brave
When looping through a sequence, the position index and corresponding value can be retrieved at the same time using the enumerate() function.
>>> for i, v in enumerate(['tic', 'tac', 'toe']):
... print i, v
...
0 tic
1 tac
2 toe
To loop over two or more sequences at the same time, the entries can be paired with the zip() function.
>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
... print 'What is your %s? It is %s.' % (q, a)
...
What is your name? It is lancelot.
What is your quest? It is the holy grail.
What is your favorite color? It is blue.
To loop over a sequence in reverse, first specify the sequence in a forward direction and then call the reversed() function.
>>> for i in reversed(xrange(1,10,2)):
... print i
...
9
7
5
3
1
To loop over a sequence in sorted order, use the sorted() function which returns a new sorted list while leaving the source unaltered.
>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> for f in sorted(set(basket)):
... print f
...
apple
banana
orange
pear
Tips about comparations
The Boolean operators and and or are so-called short-circuit operators: their arguments are evaluated from left to right, and evaluation stops as soon as the outcome is determined. For example, if A and C are true but B is false, A and B and C does not evaluate the expression C. When used as a general value and not as a Boolean, the return value of a short-circuit operator is the last evaluated argument.
Note that in Python, unlike C, assignment cannot occur inside expressions. C programmers may grumble about this, but it avoids a common class of problems encountered in C programs: typing = in an expression when == was intended.
too sequence can be compared with each other. like any dictionary.
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