├── LICENSE
├── README.md
└── _config.yml


/LICENSE:
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 1 | MIT License
 2 | 
 3 | Copyright (c) 2019 Nicholas Young
 4 | 
 5 | Permission is hereby granted, free of charge, to any person obtaining a copy
 6 | of this software and associated documentation files (the "Software"), to deal
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/README.md:
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  1 | ## Table of Contents
  2 | - [Built-in Types](#built-in-types)
  3 |   - [Boolean Types](#boolean-types)
  4 |   - [Numeric Types](#numeric-types)
  5 |   - [Sequence Types](#sequence-types)
  6 |     - [Mutable Sequences](#mutable-sequences)
  7 |     - [Immutable Sequences](#immutable-sequences)
  8 |   - [Set Types](#set-types)
  9 |   - [Mapping Types](#mapping-types)
 10 | - [Dictionaries](#dictionaries)
 11 |   - [Iteration](#dictionary-iteration)
 12 |   - [Sorting](#dictionary-sorting)
 13 | - [Lists](#lists)
 14 |   - [Comprehensions](#list-comprehensions)
 15 |   - [Initialization](#list-initialization)
 16 |   - [Reversal](#list-reversal)
 17 |   - [Sorting](#list-sorting)
 18 | - [Strings](#strings)
 19 |   - [From List](#from-list)
 20 |   - [Python String Constants](#string-constants)
 21 |   - [`isalnum()`](#isalnum)
 22 |   - [`split()`](#split)
 23 |   - [`strip()`](#strip)
 24 |   - [`str()` vs `repr()`](#str-vs-repr)
 25 | - [Iterators](#iterators)
 26 |   - [Iterator vs Iterable](#iterator-vs-iterable)
 27 |   - [How for loop actually works](#how-for-loop-actually-works)
 28 |   - [Creating an Iterator](#creating-an-iterator)
 29 | - [Functional Iteration](#functional-iteration)
 30 |   - [`map()`](#map)
 31 |   - [`filter()`](#filter)
 32 |   - [`reduce()`](#reduce)
 33 | - [Decorators](#decorators)
 34 |   - [`@classmethod`](#classmethod)
 35 |   - [`@staticmethod`](#staticmethod)
 36 |   - [`@property`](#property)
 37 | - [Generators](#generators)
 38 |   - [Using `yield`](#using-yield)
 39 |   - [Generator Expressions](#generator-expressions)
 40 | - [Other Useful Built-in Functions](#other-useful-built-in-functions)
 41 |   - [`abs()`](#abs)
 42 |   - [`any()`](#any)
 43 |   - [`all()`](#all)
 44 |   - [`chr()`](#chr)
 45 |   - [`enumerate()`](#enumerate)
 46 |   - [`input()`](#input)
 47 |   - [`isinstance()`](#isinstance)
 48 |   - [`len()`](#len)
 49 |   - [`max()`](#max)
 50 |   - [`min()`](#min)
 51 |   - [`ord()`](#ord)
 52 |   - [`pow()`](#pow)
 53 |   - [`type()`](#type) 
 54 | - [Common Gotchas](#common-gotchas)
 55 |   - [Nested List Initialization](#nested-list-initialization)
 56 |   - [Mutable Default Arguments](#mutable-default-arguments)
 57 | 
 58 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
 59 | ## Built-in Types
 60 | In this section I have included information on the more basic built-in types. For information on more specialized built-in types, check out the [Python documentation](https://docs.python.org/3/library/stdtypes.html)
 61 | 
 62 | ### Boolean Types
 63 | ```python3
 64 | class 'bool'
 65 | ```
 66 | 
 67 | By default, an object is considered `True` unless its class defines either a `__bool__()` method that returns `False` or a `__len__()` method that returns zero. Here are most of the built-in objects considered `False`:
 68 | - constants defined to be false: `None` and `False`
 69 | - zero of any numeric type: `0`, `0.0`, `0j`, `Decimal(0)`, `Fraction(0, 1)`
 70 | - empty sequences and collections: `''`, `()`, `[]`, `{}`, `set()`, `range(0)`
 71 | 
 72 | ### Numeric Types
 73 | ```python3
 74 | class 'int'
 75 | class 'float'
 76 | class 'complex'
 77 | ```
 78 | 
 79 | Integers have unlimited precision. Floating point numbers are usually implemented using `double` in C, and are therefore system-dependent. Complex numbers have a real and imaginary part, which can be accessed using `z.real` and `z.imag`, respectively. Complex numbers must include `j` appended to a numeric literal (`0j` is acceptable for when you want a `complex` value with no imaginary part).
 80 | 
 81 | The standard libarary includes additional numeric types, [Fraction](https://docs.python.org/3/library/fractions.html#module-fractions)s which hold rationals, and [Decimal](https://docs.python.org/3/library/decimal.html#module-decimal)s which hold floating-point numbers with user-definable precision.
 82 | 
 83 | ### Sequence Types
 84 | Immutable sequences have support for the `hash()` built-in, while mutable sequences do not. This means that immutable sequences can be used as `dict` keys or stored in `set` and `frozenset` instances, while mutable sequences cannot.
 85 | 
 86 | #### Mutable Sequences
 87 | ```python3
 88 | class 'list'
 89 | class 'bytearray
 90 | ```
 91 | 
 92 | `bytearray` objects are a mutable counterpart to `bytes` objects.
 93 | 
 94 | #### Immutable Sequences
 95 | ```python3
 96 | class 'tuple'
 97 | class 'range'
 98 | class 'str'
 99 | class 'bytes'
100 | ```
101 | 
102 | `bytes` objects are sequences of single bytes. The syntax for `bytes` literals is largely the same as that for string literals, except that a `b` prefix is added:  
103 | - Single quotes: `b'still allows embedded "double" quotes'`
104 | - Double quotes: `b"still allows embedded 'single' quotes"`
105 | - Triple quotes: `b'''3 single quotes'''`, `b"""3 double quotes"""`
106 | 
107 | Only ASCII chars are permitted in `bytes` literals.  
108 | `bytes` objects actually behave like immutable sequences of integers, with each value restricted to `0 <= x < 256`.
109 | 
110 | `bytes` objects can be created in several ways:
111 | - A zero-filled bytes object of a specific length: `bytes(10)`
112 | - From an iterable of integers: `bytes(range(20))`
113 | - Copying existing binary data via the buffer protocol: `bytes(obj)`
114 | 
115 | ### Set Types
116 | ```python3
117 | class 'set'
118 | class 'frozenset'
119 | ```
120 | 
121 | `set` is mutable, while `frozenset` is immutable.  
122 | Note that since `frozenset` is immutable, it must be entirely populated at the moment of construction. It cannot use the literal curly brace syntax that ordinary `set` uses, as that syntax is reserved for `set`.
123 | 
124 | Instead, use `frozenset([iterable])`.
125 | 
126 | ### Mapping Types
127 | ```python3
128 | class 'dict'
129 | ```
130 | 
131 | See the [Dictionaries](#dictionaries) section for more info.
132 | 
133 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
134 | ## Dictionaries
135 | ### Dictionary Iteration
136 | Get w/ default value if key not in dict:
137 | ```python
138 | my_dict[k] = my_dict.get(k, 0) + 1; # get retrieves value for k, or 0 if k not in dict
139 | ```
140 | 
141 | Iterating a dict iterates only the keys:
142 | ```python
143 | for k in my_dict:  # k will be each key, not each key-value pair
144 |     ...
145 | ```
146 | 
147 | Testing membership: `if k in dict: ...`
148 | 
149 | To get actual key-value pairs at the same time:
150 | ```python
151 | for k,v in my_dict.items():
152 |     ...
153 | ```
154 | applies to comprehensions as well: `new_d = {k: v+1 for k,v in d.items()}`
155 | 
156 | ### Dictionary Sorting
157 | It is not possible to sort a dictionary, only to get a representation of a dictionary that is sorted. Dictionaries are inherently orderless, but other types, such as lists and tuples, are not. So you need an ordered data type to represent sorted values, which will be a list—probably a list of tuples.  
158 | - `sorted(d.items())`
159 |   - sorted list of key-value pairs by key
160 |   - by value: `sorted(d.items(), key=lambda x: x[1]`
161 | - `sorted(d)`
162 |   - sorted list of keys only
163 |   - sorted list of keys by value: `sorted(d, key=lambda x: d[x])`
164 | 
165 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
166 | ## Lists
167 | ### List Comprehensions
168 | General Syntax:
169 | ```python
170 | [<expression> for item in list if conditional]
171 | ```
172 | is equivalent to:
173 | ```python
174 | for item in list:
175 |     if conditional:
176 |         <expression>
177 | ```
178 | 
179 | Note how the order of the `for` and `if` statements remains the same.
180 | For example, 
181 | ```python
182 | for row in grid:
183 |     for x in row:
184 |         <expression>
185 | ```
186 | is the same as
187 | ```python
188 | [<expression> for row in grid for x in row]
189 | ```
190 | 
191 | ### List Initialization
192 | Can use comprehensions:
193 | ```python
194 | my_list = [i for i in range(10)] # [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
195 | ```
196 | 2-D list (list of lists):
197 | ```python
198 | my_list = [[] for i in range(3)] # [[], [], []]
199 | ```
200 | This is useful for a "visited" grid of some kind (common in Dynamic Programming problems):
201 | ```python
202 | visited = [[0 for i in range(len(grid[0]))] for j in range(len(grid))]
203 | ```
204 | *BE CAREFUL* when initializing a matrix.
205 | Do this:
206 | ```python
207 | my_list = [[None] * n for i in range(n)]
208 | ```
209 | **NOT** this:
210 | ```python
211 | my_list = [[None] * n] * n
212 | ```
213 | The latter method makes copies of the **reference** to the original list, thus any modification to one row will change the other rows in the same way. The first method does not do this.
214 | 
215 | A list can be created from a string using `list(my_str)`
216 | We can apply a filter as well:
217 | ```python
218 | my_list = list(c for c in my_str if c not in ('a', 'c', 'e'))
219 | ```
220 | 
221 | ### List Reversal
222 |  - `my_list[::-1]`
223 |    - returns copy of list in reverse
224 |  - `reversed(my_list)`
225 |    - returns an iterator on the list in reverse
226 |    - can turn into a list via `list(reversed(my_list))`
227 |  - `my_list.reverse()`
228 |    - actually modifies the list
229 |  
230 | ### List Sorting
231 |  - `sorted(my_list)`
232 |    - returns copy of sorted list
233 |  - `my_list.sort()`
234 |    - actually modifies the list
235 |    
236 |  By default, these methods will sort the list in ascending order.
237 |  For descending order, we can supply the arg `reverse=True` to either of the aforementioned methods.
238 |  
239 |  We can also override the key for sorting by supplying the `key` arg.
240 |  For example, if we have a list of tuples and we want to use the second item as the key:
241 |  ```python
242 |  list1 = [(1, 2), (3, 3), (4, 1)] 
243 |  list1.sort(key=lambda x: x[1]) # list1 is now [(4, 1), (1, 2), (3, 3)]
244 |  ```
245 |  Additionally, if we want to sort in descending order:
246 |  ```python
247 |  list1.sort(key=lambda x: x[1], reverse=True) # list1 is now [(3, 3), (1, 2), (4, 1)]
248 |  ```
249 |  
250 |  When using `sorted()` it works the same, except we supply the list as the first arg:
251 |  ```python
252 |  list2 = sorted(list1, key=lambda x: x[1], reverse=True)
253 |  ```
254 | 
255 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
256 | ## Strings
257 | ### From List
258 | ```python
259 | my_list = ['te', 's', 't', '1', '2', '3', '_']
260 | s = ''.join(my_list) # "test123_"
261 | s2 = ''.join(c for c in my_list if c.isalnum()) # "test123"
262 | ```
263 | 
264 | ### String Constants
265 | Python has a lot of useful string constants. A few of them are shown below.
266 | For a complete list, see the [documentation](https://docs.python.org/3.7/library/string.html)
267 |  - `string.ascii_letters`
268 |  - `string.digits`
269 |  - `string.whitespace`
270 |  
271 |  e.g. `if d in string.digits: ...`
272 |  
273 | ### `isalnum()`
274 | Returns `True` if a string consists only of alphanumeric characters.
275 | ```python
276 | s = "test123"
277 | s.isalnum() # True
278 | ```
279 | 
280 | ### `split()`
281 | Return a list of the words in the string, using `sep` as the delimiter string. If `maxsplit` is given, at most `maxsplit` splits are done (thus, the list will have at most `maxsplit + 1` elements). If `maxsplit` is not specified or `-1`, then there is no limit on the number of splits (all possible splits are made).  
282 | Usage:
283 | ```python3
284 | str.split(sep=None, maxsplit=-1)
285 | ```
286 | 
287 | ```python3
288 | '1,2,3'.split(',')             # ['1', '2', '3']
289 | '1,2,3'.split(',', maxsplit=1) # ['1', '2,3']
290 | '1,2,,3,'.split(',')           # ['1', '2', '', '3', '']
291 | ```
292 | 
293 | ### `strip()`
294 | Returns copy of string without surrounding whitespace, if any.
295 | ```python
296 | s = "   test "
297 | s.strip() # "test"
298 | ```
299 | 
300 | ### `str()` vs `repr()`
301 | See [this GeeksForGeeks article](https://www.geeksforgeeks.org/str-vs-repr-in-python/) for more info.
302 | 
303 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
304 | ## Iterators
305 | In Python, an iterator is an object with a countable number of values that can be iterated upon.
306 | An iterator is an object which implements the iterator protocol, consisting of `__iter__()` and `__next__()`.  
307 | The `__iter__()` method returns an iterator on the object, and the `__next__()` method gets the next item using the iterator, or raises a `StopIteration` exception if the end of the iterable is reached.
308 | 
309 | ### Iterator vs Iterable
310 | Lists, tuples, dictionaries, and sets are all iterable objects. They are iterable *containers* which you can get an iterator from.
311 | All these objects have a `__iter__()` method which is used to get an iterator:
312 | ```python3
313 | mytuple = ("apple", "banana", "cherry")
314 | myit = iter(mytuple)
315 | 
316 | print(next(myit)) # apple
317 | print(next(myit)) # banana
318 | print(next(myit)) # cherry
319 | print(next(myit)) # raises StopIteration exception
320 | ```
321 | Note -- `next(obj)` is the same as `obj.__next__()`.
322 | 
323 | 
324 | ### How for loop actually works
325 | The `for` loop can iterate any iterable.  
326 | The `for` loop in Python is actually implemented like so:
327 | ```python3
328 | iter_obj = iter(iterable) # create iterator object from iterable
329 | 
330 | # infinite loop
331 | while True:
332 |     try:
333 |         element = next(iter_obj) # get the next item
334 |         # do something with element
335 |     except StopIteration:
336 |         break
337 | ```
338 | So, internally, the `for` loop creates an iterator object by calling `iter()` on the iterable, and then repeatedly calling `next()` until a `StopIteration` exception is raised.
339 | 
340 | ### Creating an Iterator
341 | Here is an example of an iterator that will give us the next power of two in each iteration.
342 | ```python3
343 | class PowTwo:
344 |     """Class to implement an iterator of powers of two"""
345 | 
346 |     def __init__(self, max = 0):
347 |         self.max = max
348 | 
349 |     def __iter__(self):
350 |         self.n = 0
351 |         return self
352 | 
353 |     def __next__(self):
354 |         if self.n <= self.max:
355 |             result = 2 ** self.n
356 |             self.n += 1
357 |             return result
358 |         else:
359 |             raise StopIteration
360 | ```
361 | 
362 | Now we can use it as follows:
363 | ```python3
364 | >>> a = PowTwo(4)
365 | >>> i = iter(a)
366 | >>> next(i)
367 | 1
368 | >>> next(i)
369 | 2
370 | >>> next(i)
371 | 4
372 | >>> next(i)
373 | 8
374 | >>> next(i)
375 | 16
376 | >>> next(i)
377 | Traceback (most recent call last):
378 | ...
379 | StopIteration
380 | ```
381 | Or, alternatively, using a `for` loop:
382 | ```python3
383 | >>> for i in PowTwo(5):
384 | ...     print(i)
385 | ...     
386 | 1
387 | 2
388 | 4
389 | 8
390 | 16
391 | 32
392 | ```
393 | 
394 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
395 | ## Functional Iteration
396 | For some good explanations and examples for the following functions, see [here](http://book.pythontips.com/en/latest/map_filter.html).
397 | 
398 | Note that `map()` and `filter()` both return iterators, so if you want a list, you need to use `list()` on the output. However, this is typically better accomplished with list comprehensions or `for` loops for the sake of readability.
399 |   
400 | ### `map()`
401 | `map()` applies a function to all the items in a list.
402 | ```python
403 | map(function_to_apply, list_of_inputs)
404 | ```
405 |   
406 | For example, the following code:
407 | ```python
408 | items = [1, 2, 3, 4, 5]
409 | squared = []
410 | for i in items:
411 |     squared.append(i**2)
412 | ```
413 | can be accomplished more easily with `map()`:
414 | ```python3
415 | items = [1, 2, 3, 4, 5]
416 | squared = list(map(lambda x: x**2, items))
417 | ```
418 | 
419 | ### `filter()`
420 | `filter()` creates a list of elements for which a function returns `True`.
421 |   
422 | Here's an example:
423 | ```python3
424 | number_list = range(-5, 5)
425 | less_than_zero = list(filter(lambda x: x < 0, number_list))
426 | print(less_than_zero) # [-5, -4, -3, -2, -1]
427 | ```
428 | 
429 | ### `reduce()`
430 | `reduce()` is used to perform a rolling computation on a list.
431 | 
432 | Here's an example:
433 | ```python3
434 | from functools import reduce
435 | number_list = [1, 2, 3, 4]
436 | product = reduce((lambda x, y: x * y), number_list) # output: 24
437 | ```
438 | 
439 | Often times, an explicit `for` loop is more readable than using `reduce()`.
440 | But if you're trying to flex in an interview, and the problem calls for it, it could be a nice way to subtly show your understanding of functional programming.
441 | 
442 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
443 | ## Decorators
444 | A [decorator](https://www.scaler.com/topics/python/python-decorators/) is a function returning another function, usually applied as a function transformation using the `@wrapper` syntax. This syntax is merely syntactic sugar.
445 | 
446 | The following two function definitions are semantically equivalent:
447 | ```python3
448 | def f(...):
449 |     ...
450 | f = staticmethod(f)
451 | 
452 | @staticmethod
453 | def f(...):
454 |     ...
455 | ```
456 | 
457 | ### @classmethod
458 | Transform a method into a class method. A class method receives the class as implicit first argument, just like how an instance method receives the instance. To declare a class method:
459 | ```python3
460 | class C:
461 |     @classmethod
462 |     def f(cls, arg1, arg2, ...):
463 |         ...
464 | ```
465 | 
466 | A class method can be called either on the class (like `C.f()`) or on an instance (like `C().f()`). The instance is ignored except for its class. If a class method is called for a derived class, the derived class object is passed as the implied first argument.
467 | 
468 | Note that class methods are not the same as C++ or Java static methods. If you want those, see [`@staticmethod`](#staticmethod).
469 | 
470 | ### @staticmethod
471 | Transform a method into a static method. A static method does not receive an implicit first argument. To declare a static method:
472 | ```python3
473 | class C:
474 |     @staticmethod
475 |     def f(arg1, arg2, ...):
476 |         ...
477 | ```
478 | 
479 | A static method can be called either on the class (like `C.f()`) or on an instance (like `C().f()`). Static methods in Python are similar to those found in Java or C++.
480 | 
481 | ### @property
482 | Return a property attribute.
483 | Usage:
484 | ```python3
485 | property(fget=None, fset=None, fdel=None, doc=None)
486 | ```
487 | `fget` is a function for getting an attribute value. `fset` is a function for setting an attribute value. `fdel` is a function for deleting an attribute value. `doc` creates a docstring for the attribute.
488 | 
489 | The following is a typical use case for defining a managed attribute `x`:
490 | ```python3
491 | class C:
492 |     def __init__(self):
493 |         self._x = None
494 | 
495 |     def getx(self):
496 |         return self._x
497 | 
498 |     def setx(self, value):
499 |         self._x = value
500 | 
501 |     def delx(self):
502 |         del self._x
503 | 
504 |     x = property(getx, setx, delx, "I'm the 'x' property.")
505 | ```
506 | Or, equivalently:
507 | ```python3
508 | class C:
509 |     def __init__(self):
510 |         self._x = None
511 | 
512 |     @property
513 |     def x(self):
514 |         """I'm the 'x' property."""
515 |         return self._x
516 | 
517 |     @x.setter
518 |     def x(self, value):
519 |         self._x = value
520 | 
521 |     @x.deleter
522 |     def x(self):
523 |         del self._x
524 | ```    
525 | 
526 | If `c` is an instance of `C`, then `c.x` will invoke the getter; `c.x = value` will invoke the setter; and `del c.x` the deleter.
527 | 
528 | If `doc` is not provided, the property will copy `fget`'s docstring, if it exists. Thus, it is straightforward to create read-only properties with the `@property` decorator:
529 | ```python3
530 | class Parrot:
531 |     def __init__(self):
532 |         self._voltage = 100000
533 | 
534 |     @property
535 |     def voltage(self):
536 |         """Get the current voltage."""
537 |         return self._voltage
538 | ```
539 | The `@property` decorator turns the `voltage()` method into a “getter” for a read-only attribute with the same name, and it sets the docstring for `voltage` to “Get the current voltage.”
540 | 
541 | For more information, check out [the documentation](https://docs.python.org/3/library/functions.html#property) and [this Programiz article](https://www.programiz.com/python-programming/property).
542 | 
543 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
544 | ## Generators
545 | Generators are simpler ways of creating [iterators](#iterators). The overhead of creating `__iter__()`, `__next__()`, raising `StopIteration`, and keeping track of state can all be handled internally by a generator.
546 | 
547 | A generator is a function that returns an object (iterator) which we can iterate over, one value at a time. 
548 | 
549 | ### Using `yield`
550 | To create a generator, simply define a function using a `yield` statement.
551 | 
552 | A function containing at least one `yield` statement (it may contain other `yield` and `return` statements) becomes a generator.
553 | 
554 | Both `yield` and `return` return some value from a function. The difference is that, while a `return` statement terminates a function entirely, `yield` pauses the function, saving its state and continuing from where it left off in successive calls.
555 | 
556 | Once a function yields, it is paused and control is transferred back to the caller. Local variables and their states are remembered between successive calls. When the function terminates, `StopIteration` is raised automatically on further calls.
557 | 
558 | Below is a simple generator example, for the sake of demonstrating how generators work.
559 | ```python3
560 | def my_gen():
561 |     n = 1
562 |     print('This is printed first')
563 |     yield n
564 | 
565 |     n += 1
566 |     print('This is printed second')
567 |     yield n
568 |     
569 | # Without for loop:
570 | a = my_gen()
571 | next(a) # 'This is printed first'
572 | next(a) # 'This is printed second'
573 | next(a) # Traceback ... StopIteration
574 | 
575 | # With for loop:
576 | for item in my_gen():
577 |     print(item)
578 | ````
579 | 
580 | Below is a more typical example. Generators often use loops with a suitable terminating condition.
581 | ```python3
582 | def reverse(my_str):
583 |     for i in range(len(my_str) - 1, -1, -1):
584 |         yield my_str[i]
585 |         
586 | for char in reverse("hello"):
587 |     print(char) # prints each char reverse on a new line
588 | ```
589 | Note that the above example works not just with strings, but also other kinds of iterables.
590 | 
591 | ### Generator Expressions
592 | Generator expressions can be used to create an anonymous generator function. The syntax is similar to that of [list comprehensions](#list-comprehensions), but uses parentheses instead of square brackets. However, while a list comprehension produces the entire list, generator expressions produce one item at a time.
593 | 
594 | Generator expressions are kind of lazy, producing items only when asked for. For this reason, using a generator expression is much more memory efficient than an equivalent list comprehension.
595 | 
596 | ```python3
597 | items = [1, 3, 6]
598 | item_squared = (item**2 for item in items)
599 | print(next(item_squared)) # 1
600 | print(next(item_squared)) # 9
601 | print(next(item_squared)) # 36
602 | next(item_squared) # StopIteration
603 | ```
604 | 
605 | Generator expressions can be used inside function calls. When used in such a way, the round parentheses can be dropped.
606 | ```python3
607 | sum(x**2 for x in items) # 46
608 | max(x**2 for x in items) # 36
609 | ```
610 | 
611 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
612 | ## Other Useful Built-in Functions
613 | For a complete list of built-ins in Python 3, see [the documentation](https://docs.python.org/3/library/functions.html).
614 | ### `abs()`
615 | Returns the absolute value of a number, either an integer or floating point number.
616 | If the argument is a complex number, its magnitude is returned.
617 | 
618 | ### `any()`
619 | Usage:
620 | ```python
621 | any(iterable)
622 | ```
623 | `any()` takes any iterable as an argument and returns `True` if at least one element of the iterable is `True`.
624 | 
625 | ```python
626 | any([1, 3, 4, 0])   # True
627 | any([0, False])     # False
628 | any([0, False, 5])  # True
629 | any([])             # False
630 | 
631 | any("This is good") # True
632 | any("0")            # True
633 | any("")             # False
634 | ```
635 | 
636 | See [here](https://www.programiz.com/python-programming/methods/built-in/any) for more info.
637 | 
638 | Check if any tuples contain a negative value:
639 | ```python
640 | if any(x < 0 or y < 0 for (x, y) in list_ranges): ...
641 | ```
642 | 
643 | ### `all()`
644 | ```python
645 | all(iterable)
646 | ```
647 | `all()` takes any iterable as an argument and returns `True` if all the elements of the iterable are `True`.
648 | 
649 | ```python
650 | all([1, 3, 4, 5])  # True
651 | all([0, False])    # False
652 | all([1, 3, 4, 0])  # False
653 | all([0, False, 5]) # False
654 | all([])            # True
655 | 
656 | all("This is good") # True
657 | all("0")            # True
658 | all("")             # True
659 | ```
660 | 
661 | See [here](https://www.programiz.com/python-programming/methods/built-in/all) for more info.
662 | 
663 | Check if all elements of a list are `x`: 
664 | ```python
665 | if all(c == x for c in alst): ...
666 | ```
667 | 
668 | ### `chr()`
669 | Returns the string representing a character whose Unicode code point is the integer passed.
670 | 
671 | For example, `chr(97)` returns the string `a`, while `chr(8364)` returns the string `€`.
672 | 
673 | This is the inverse of [`ord()`](#ord).
674 | 
675 | ### `enumerate()`
676 | Usage:
677 | ```python3
678 | enumerate(iterable, start=0)
679 | ```
680 | Returns an enumerate object. `iterable` must be a sequence, iterator, or some object which suports iteration. The `__next__()` method of the iterator returned by `enumerate()` returns a tuple containing a count (from `start` which defaults to zero) and the values obtained from iterating over the iterable.  
681 | 
682 | Example:
683 | ```python3
684 | seasons = ['Spring', 'Summer', 'Fall', 'Winter']
685 | list(enumerate(seasons))              # [(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')]
686 | list(enumerate(seasons, start=1))     # [(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')]
687 | ```
688 | This is equivalent to:
689 | ```python3
690 | def enumerate(sequence, start=0):
691 |     n = start
692 |     for elem in sequence:
693 |         yield n, elem
694 |         n += 1
695 | ```
696 | 
697 | ### `input()`
698 | Gets input from the user.
699 | Usage:
700 | ```python3
701 | input([prompt])
702 | ```
703 | 
704 | Example: 
705 | ```python3
706 | >>> s = input('-> ')  
707 | -> Monty Python's Flying Circus
708 | >>> s  
709 | "Monty Python's Flying Circus"
710 | ```
711 | If the `prompt` arg is present, it is written to stdout without a trailing newline.
712 | 
713 | ### `isinstance()`
714 | Usage:
715 | ```python3
716 | isinstance(object, classinfo)
717 | ```
718 | 
719 | Returns true if the `object` argument is an instance of the `classinfo` argument, or of a (direct, indirect, or virtual) subclass thereof. Returns false otherwise.
720 | 
721 | If `classinfo` is a tuple of type objects, return true if `object` is an instance of any of *any* of these types.
722 | 
723 | ### `len()`
724 | Return the length of an object. The argument may be a sequence (e.g. string, bytes, tuple, list, or range) or a collection (e.g. dictionary, set, frozen set).
725 | 
726 | ### `max()`
727 | Returns the max item in an iterable, or the max of multiple arguments passed.
728 | 
729 | ### `min()`
730 | Returns the min item in an iterable, or the min of multiple arguments passed.
731 | 
732 | ### `ord()`
733 | Given a string representing one Unicode character, return an integer representing the Unicode code point of that character.
734 | 
735 | For example, `ord('a')` returns the integer 97. `ord('€')` (Euro sign) return 8364. 
736 | 
737 | This is the inverse of [`chr()`](#chr).
738 | 
739 | ### `pow()`
740 | Usage:
741 | ```python3
742 | pow(x, y[, z])
743 | ```
744 | Return `x` to the power `y`; if `z` is present, return `x` to the power `y`, modulo `z` (computed more efficiently than `pow(x, y) % z`).  
745 | `pow(x, y)` is equivalent to `x**y`.
746 | 
747 | ### `type()`
748 | Usage:
749 | ```python3
750 | type(object)
751 | type(name, bases, dict)
752 | ```
753 | 
754 | With one argument, return the type of `object`. The return value is a type object and generally the same object as returned by `object.__class__`.
755 | 
756 | E.g.
757 | ```python3
758 | x = 5
759 | type(x)  # class 'int'
760 | ```
761 | 
762 | The [`isinstance()`](#isinstance) function is recommended for testing the type of an object, since it accounts for subclasses.
763 | 
764 | <sup><sub>[▲ TOP](#table-of-contents)</sub></sup>
765 | ## Common Gotchas
766 | ### Nested List Initialization
767 | When creating a list of lists, be sure to use the following structure:
768 | ```python
769 | my_list = [[None] * n for i in range(n)]
770 | ```
771 | Read the section on [list initialization](#list-initialization) to see why.
772 | 
773 | ### Mutable Default Arguments
774 | If we try to do something like `def f(x, arr=[])` this will most likely create undesirable behavior.
775 | Default arguments are resolved *only once*, when the function is first defined. The same arg will be used in successive function calls. In the case of a mutable type like a list, this means that changes made to the list in one call will be carried over in successive calls.
776 | Instead, consider doing:
777 | ```python
778 | def f(x, arr=None):
779 |     if not arr: arr = []
780 | ```
781 | 


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