summaryrefslogtreecommitdiffhomepage
path: root/python.html.markdown
blob: 210c96198d07b01a0e5577d10fe84cc749eaf199 (plain)
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
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
---
language: python
contributors:
    - ["Louie Dinh", "http://ldinh.ca"]
    - ["Amin Bandali", "http://aminbandali.com"]
filename: learnpython.py
---

Python was created by Guido Van Rossum in the early 90's. It is now one of the most popular
languages in existence. I fell in love with Python for its syntactic clarity. It's basically
executable pseudocode.

Feedback would be highly appreciated! You can reach me at [@louiedinh](http://twitter.com/louiedinh) or louiedinh [at] [google's email service]

Note: This article applies to Python 2.7 specifically, but should be applicable
to Python 2.x. Look for another tour of Python 3 soon!

```python

# Single line comments start with a number symbol.

""" Multiline strings can be written
    using three "'s, and are often used
    as comments
"""

####################################################
## 1. Primitive Datatypes and Operators
####################################################

# You have numbers
3  # => 3

# Math is what you would expect
1 + 1  # => 2
8 - 1  # => 7
10 * 2  # => 20
35 / 5  # => 7

# Division is a bit tricky. It is integer division and floors the results
# automatically.
5 / 2  # => 2

# To fix division we need to learn about floats.
2.0     # This is a float
11.0 / 4.0  # => 2.75 ahhh...much better

# Enforce precedence with parentheses
(1 + 3) * 2  # => 8

# Boolean values are primitives
True
False

# negate with not
not True  # => False
not False  # => True

# Equality is ==
1 == 1  # => True
2 == 1  # => False

# Inequality is !=
1 != 1  # => False
2 != 1  # => True

# More comparisons
1 < 10  # => True
1 > 10  # => False
2 <= 2  # => True
2 >= 2  # => True

# Comparisons can be chained!
1 < 2 < 3  # => True
2 < 3 < 2  # => False

# Strings are created with " or '
"This is a string."
'This is also a string.'

# Strings can be added too!
"Hello " + "world!"  # => "Hello world!"

# A string can be treated like a list of characters
"This is a string"[0]  # => 'T'

# % can be used to format strings, like this:
"%s can be %s" % ("strings", "interpolated")

# A newer way to format strings is the format method.
# This method is the preferred way
"{0} can be {1}".format("strings", "formatted")
# You can use keywords if you don't want to count.
"{name} wants to eat {food}".format(name="Bob", food="lasagna")

# None is an object
None  # => None

# Don't use the equality "==" symbol to compare objects to None
# Use "is" instead
"etc" is None  # => False
None is None  # => True

# The 'is' operator tests for object identity. This isn't
# very useful when dealing with primitive values, but is
# very useful when dealing with objects.

# None, 0, and empty strings/lists all evaluate to False.
# All other values are True
bool(0)  # => False
bool("")  # => False


####################################################
## 2. Variables and Collections
####################################################

# Python has a print function, available in versions 2.7 and 3...
print("I'm Python. Nice to meet you!")
# and an older print statement, in all 2.x versions but removed from 3.
print "I'm also Python!"


# No need to declare variables before assigning to them.
some_var = 5    # Convention is to use lower_case_with_underscores
some_var  # => 5

# Accessing a previously unassigned variable is an exception.
# See Control Flow to learn more about exception handling.
some_other_var  # Raises a name error

# if can be used as an expression
"yahoo!" if 3 > 2 else 2  # => "yahoo!"

# Lists store sequences
li = []
# You can start with a prefilled list
other_li = [4, 5, 6]

# Add stuff to the end of a list with append
li.append(1)    # li is now [1]
li.append(2)    # li is now [1, 2]
li.append(4)    # li is now [1, 2, 4]
li.append(3)    # li is now [1, 2, 4, 3]
# Remove from the end with pop
li.pop()        # => 3 and li is now [1, 2, 4]
# Let's put it back
li.append(3)    # li is now [1, 2, 4, 3] again.

# Access a list like you would any array
li[0]  # => 1
# Look at the last element
li[-1]  # => 3

# Looking out of bounds is an IndexError
li[4]  # Raises an IndexError

# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
li[1:3]  # => [2, 4]
# Omit the beginning
li[2:]  # => [4, 3]
# Omit the end
li[:3]  # => [1, 2, 4]
# Select every second entry
li[::2]   # =>[1, 4]
# Revert the list
li[::-1]   # => [3, 4, 2, 1]
# Use any combination of these to make advanced slices
# li[start:end:step]

# Remove arbitrary elements from a list with "del"
del li[2]   # li is now [1, 2, 3]

# You can add lists
li + other_li   # => [1, 2, 3, 4, 5, 6] - Note: values for li and for other_li are not modified.

# Concatenate lists with "extend()"
li.extend(other_li)   # Now li is [1, 2, 3, 4, 5, 6]

# Check for existence in a list with "in"
1 in li   # => True

# Examine the length with "len()"
len(li)   # => 6


# Tuples are like lists but are immutable.
tup = (1, 2, 3)
tup[0]   # => 1
tup[0] = 3  # Raises a TypeError

# You can do all those list thingies on tuples too
len(tup)   # => 3
tup + (4, 5, 6)   # => (1, 2, 3, 4, 5, 6)
tup[:2]   # => (1, 2)
2 in tup   # => True

# You can unpack tuples (or lists) into variables
a, b, c = (1, 2, 3)     # a is now 1, b is now 2 and c is now 3
# Tuples are created by default if you leave out the parentheses
d, e, f = 4, 5, 6
# Now look how easy it is to swap two values
e, d = d, e     # d is now 5 and e is now 4


# Dictionaries store mappings
empty_dict = {}
# Here is a prefilled dictionary
filled_dict = {"one": 1, "two": 2, "three": 3}

# Look up values with []
filled_dict["one"]   # => 1

# Get all keys as a list with "keys()"
filled_dict.keys()   # => ["three", "two", "one"]
# Note - Dictionary key ordering is not guaranteed.
# Your results might not match this exactly.

# Get all values as a list with "values()"
filled_dict.values()   # => [3, 2, 1]
# Note - Same as above regarding key ordering.

# Check for existence of keys in a dictionary with "in"
"one" in filled_dict   # => True
1 in filled_dict   # => False

# Looking up a non-existing key is a KeyError
filled_dict["four"]   # KeyError

# Use "get()" method to avoid the KeyError
filled_dict.get("one")   # => 1
filled_dict.get("four")   # => None
# The get method supports a default argument when the value is missing
filled_dict.get("one", 4)   # => 1
filled_dict.get("four", 4)   # => 4

# "setdefault()" inserts into a dictionary only if the given key isn't present
filled_dict.setdefault("five", 5)  # filled_dict["five"] is set to 5
filled_dict.setdefault("five", 6)  # filled_dict["five"] is still 5


# Sets store ... well sets
empty_set = set()
# Initialize a "set()" with a bunch of values
some_set = set([1, 2, 2, 3, 4])   # some_set is now set([1, 2, 3, 4])

# Since Python 2.7, {} can be used to declare a set
filled_set = {1, 2, 2, 3, 4}   # => {1, 2, 3, 4}

# Add more items to a set
filled_set.add(5)   # filled_set is now {1, 2, 3, 4, 5}

# Do set intersection with &
other_set = {3, 4, 5, 6}
filled_set & other_set   # => {3, 4, 5}

# Do set union with |
filled_set | other_set   # => {1, 2, 3, 4, 5, 6}

# Do set difference with -
{1, 2, 3, 4} - {2, 3, 5}   # => {1, 4}

# Check for existence in a set with in
2 in filled_set   # => True
10 in filled_set   # => False


####################################################
## 3. Control Flow
####################################################

# Let's just make a variable
some_var = 5

# Here is an if statement. Indentation is significant in python!
# prints "some_var is smaller than 10"
if some_var > 10:
    print("some_var is totally bigger than 10.")
elif some_var < 10:    # This elif clause is optional.
    print("some_var is smaller than 10.")
else:           # This is optional too.
    print("some_var is indeed 10.")


"""
For loops iterate over lists
prints:
    dog is a mammal
    cat is a mammal
    mouse is a mammal
"""
for animal in ["dog", "cat", "mouse"]:
    # You can use % to interpolate formatted strings
    print("%s is a mammal" % animal)

"""
"range(number)" returns a list of numbers
from zero to the given number
prints:
    0
    1
    2
    3
"""
for i in range(4):
    print(i)

"""
While loops go until a condition is no longer met.
prints:
    0
    1
    2
    3
"""
x = 0
while x < 4:
    print(x)
    x += 1  # Shorthand for x = x + 1

# Handle exceptions with a try/except block

# Works on Python 2.6 and up:
try:
    # Use "raise" to raise an error
    raise IndexError("This is an index error")
except IndexError as e:
    pass    # Pass is just a no-op. Usually you would do recovery here.


####################################################
## 4. Functions
####################################################

# Use "def" to create new functions
def add(x, y):
    print("x is %s and y is %s" % (x, y))
    return x + y    # Return values with a return statement

# Calling functions with parameters
add(5, 6)   # => prints out "x is 5 and y is 6" and returns 11

# Another way to call functions is with keyword arguments
add(y=6, x=5)   # Keyword arguments can arrive in any order.


# You can define functions that take a variable number of
# positional arguments
def varargs(*args):
    return args

varargs(1, 2, 3)   # => (1, 2, 3)


# You can define functions that take a variable number of
# keyword arguments, as well
def keyword_args(**kwargs):
    return kwargs

# Let's call it to see what happens
keyword_args(big="foot", loch="ness")   # => {"big": "foot", "loch": "ness"}


# You can do both at once, if you like
def all_the_args(*args, **kwargs):
    print(args)
    print(kwargs)
"""
all_the_args(1, 2, a=3, b=4) prints:
    (1, 2)
    {"a": 3, "b": 4}
"""

# When calling functions, you can do the opposite of args/kwargs!
# Use * to expand tuples and use ** to expand kwargs.
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args)   # equivalent to foo(1, 2, 3, 4)
all_the_args(**kwargs)   # equivalent to foo(a=3, b=4)
all_the_args(*args, **kwargs)   # equivalent to foo(1, 2, 3, 4, a=3, b=4)


# Python has first class functions
def create_adder(x):
    def adder(y):
        return x + y
    return adder

add_10 = create_adder(10)
add_10(3)   # => 13

# There are also anonymous functions
(lambda x: x > 2)(3)   # => True

# There are built-in higher order functions
map(add_10, [1, 2, 3])   # => [11, 12, 13]
filter(lambda x: x > 5, [3, 4, 5, 6, 7])   # => [6, 7]

# We can use list comprehensions for nice maps and filters
[add_10(i) for i in [1, 2, 3]]  # => [11, 12, 13]
[x for x in [3, 4, 5, 6, 7] if x > 5]   # => [6, 7]

####################################################
## 5. Classes
####################################################


# We subclass from object to get a class.
class Human(object):

    # A class attribute. It is shared by all instances of this class
    species = "H. sapiens"

    # Basic initializer
    def __init__(self, name):
        # Assign the argument to the instance's name attribute
        self.name = name

    # An instance method. All methods take "self" as the first argument
    def say(self, msg):
        return "%s: %s" % (self.name, msg)

    # A class method is shared among all instances
    # They are called with the calling class as the first argument
    @classmethod
    def get_species(cls):
        return cls.species

    # A static method is called without a class or instance reference
    @staticmethod
    def grunt():
        return "*grunt*"


# Instantiate a class
i = Human(name="Ian")
print(i.say("hi"))     # prints out "Ian: hi"

j = Human("Joel")
print(j.say("hello"))  # prints out "Joel: hello"

# Call our class method
i.get_species()   # => "H. sapiens"

# Change the shared attribute
Human.species = "H. neanderthalensis"
i.get_species()   # => "H. neanderthalensis"
j.get_species()   # => "H. neanderthalensis"

# Call the static method
Human.grunt()   # => "*grunt*"


####################################################
## 6. Modules
####################################################

# You can import modules
import math
print(math.sqrt(16))  # => 4

# You can get specific functions from a module
from math import ceil, floor
print(ceil(3.7))  # => 4.0
print(floor(3.7))   # => 3.0

# You can import all functions from a module.
# Warning: this is not recommended
from math import *

# You can shorten module names
import math as m
math.sqrt(16) == m.sqrt(16)   # => True

# Python modules are just ordinary python files. You
# can write your own, and import them. The name of the
# module is the same as the name of the file.

# You can find out which functions and attributes
# defines a module.
import math
dir(math)


####################################################
## 7. Advanced
####################################################

# Generators help you make lazy code
def double_numbers(iterable):
    for i in iterable:
        yield i + i

# A generator creates values on the fly.
# Instead of generating and returning all values at once it creates one in each
# iteration.  This means values bigger than 15 wont be processed in
# double_numbers.
# Note range is a generator too. Creating a list 1-900000000 would take lot of
# time to be made
_range = range(1, 900000000)
# will double all numbers until a result >=30 found
for i in double_numbers(_range):
    print(i)
    if i >= 30:
        break


# Decorators
# in this example beg wraps say
# Beg will call say. If say_please is True then it will change the returned
# message
from functools import wraps


def beg(_say):
    @wraps(_say)
    def wrapper(*args, **kwargs):
        msg, say_please = _say(*args, **kwargs)
        if say_please:
            return "{} {}".format(msg, "Please! I am poor :(")
        return msg

    return wrapper


@beg
def say(say_please=False):
    msg = "Can you buy me a beer?"
    return msg, say_please


print(say())  # Can you buy me a beer?
print(say(say_please=True))  # Can you buy me a beer? Please! I am poor :(
```

## Ready For More?

### Free Online

* [Learn Python The Hard Way](http://learnpythonthehardway.org/book/)
* [Dive Into Python](http://www.diveintopython.net/)
* [The Official Docs](http://docs.python.org/2.6/)
* [Hitchhiker's Guide to Python](http://docs.python-guide.org/en/latest/)
* [Python Module of the Week](http://pymotw.com/2/)
* [A Crash Course in Python for Scientists](http://nbviewer.ipython.org/5920182)

### Dead Tree

* [Programming Python](http://www.amazon.com/gp/product/0596158106/ref=as_li_qf_sp_asin_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0596158106&linkCode=as2&tag=homebits04-20)
* [Dive Into Python](http://www.amazon.com/gp/product/1441413022/ref=as_li_tf_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=1441413022&linkCode=as2&tag=homebits04-20)
* [Python Essential Reference](http://www.amazon.com/gp/product/0672329786/ref=as_li_tf_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=0672329786&linkCode=as2&tag=homebits04-20)