原来用过 python，学过几次 python，但是都没学会。。。（没有需求），现在工作上需要把 python 用起来。这里是一点笔记：
"str"
'str'
"a" + "b" (c++ style concat)
"a" "b" (c-style concat)
"str"[0]
len("str")
type(5)
and, or, not
1 < 2 < 3
5 // 3
5 / 3
if cond:
...
elif:
...
else:
...
for i in range(10):
...
for v in list:
...
for i, v in enumerate(list):
...
while cond:
...
# string interpolation
"{} is a {}".format("This", "placeholder")
"{0} can be {1}".format("strings", "formatted")
"{name} wants to eat {food}".format(name="Bob", food="lasagna")
"etc" is None
# Convention is to use lower_case_with_underscores
some_var = 5
# ternary operator
"yahoo!" if 3 > 2 else 2 # => "yahoo!"
li = [1, 2, 3]
li.append(4)
li.pop()
li[0]
li[start:stop:step]
del li[0]
li.remove(2) # remove first 2
2 in li
li.index(2) # find_first of 2 (raise error if not found)
# list concat
li_a + li_b # create new list
li_a.extend(li_b) # append to li_a
# Tuples are like lists but are immutable.
tp = (1, 3, 5)
tup[0] = 3 # Raises a TypeError
# 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
d, e, f = 4, 5, 6 # you can leave out the parentheses
# dict
filled_dict = {"one": 1, "two": 2, "three": 3}
filled_dict["one"]
filled_dict.get("one") # => 1
filled_dict.get("four") # => None
filled_dict.get("one", 4) # => 1
filled_dict.setdefault("five", 5) # set if key not here
# set
empty_set = set()
set(list_a)
filled_set = {1, 2, 2, 3, 4} # => {1, 2, 3, 4}
# set ops
filled_set & other_set # => {3, 4, 5} # intersection
filled_set | other_set # => {1, 2, 3, 4, 5, 6} # union
filled_set - other_set # => {1, 2, 3, 4, 5, 6} # diff
{1, 2, 3, 4} ^ {2, 3, 5} # => {1, 4, 5} # symmetric diff
{1, 2} >= {1, 2, 3} # => False # superset
{1, 2} >= {1, 2, 3} # => False # subset
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.
except (TypeError, NameError):
pass # Multiple exceptions can be handled together, if required.
else: # Optional clause to the try/except block. Must follow all except blocks
print "All good!" # Runs only if the code in try raises no exceptions
finally: # Execute under all circumstances
print "We can clean up resources here"
# Instead of try/finally to cleanup resources you can use a with statement
with open("myfile.txt") as f:
for line in f:
print line
def add(x, y):
return x + y
add(5, 6)
add(x=5, y=6)
add(y=6, x=5)
# *tuple args
# **dict kwargs
def all_the_args(*args, **kwargs):
print args
print kwargs
args = (1, 2, 3, 4)
kwargs = {"a": 3, "b": 4}
all_the_args(*args) # equivalent to all_the_args(1, 2, 3, 4)
all_the_args(**kwargs) # equivalent to all_the_args(a=3, b=4)
def set_global_x(num):
global x
print x # => 5
x = num # global var x is now set to 6
print x # => 6
# closure
def create_adder(x):
def adder(y):
return x + y
return adder
(lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5
# There are built-in higher order functions
map(add_10, [1, 2, 3]) # => [11, 12, 13]
map(max, [1, 2, 3], [4, 2, 1]) # => [4, 2, 3]
filter
# list comprehension
[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
{x for x in 'abcddeef' if x in 'abc'} # => {'a', 'b', 'c'}
{x: x ** 2 for x in range(5)} # => {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}
# 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, this is called when this class is instantiated.
# Note that the double leading and trailing underscores denote objects
# or attributes that are used by python but that live in user-controlled
# namespaces. You should not invent such names on your own.
def __init__(self, name):
# Assign the argument to the instance's name attribute
self.name = name
# Initialize property
self.age = 0
# An instance method. All methods take "self" as the first argument
def say(self, msg):
return "{0}: {1}".format(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*"
# A property is just like a getter.
# It turns the method age() into an read-only attribute
# of the same name.
@property
def age(self):
return self._age
# This allows the property to be set
@age.setter
def age(self, age):
self._age = age
# This allows the property to be deleted
@age.deleter
def age(self):
del self._age
# module
import math
print math.sqrt(16) # => 4
from math import ceil, floor
import math as m
# generator
def double_numbers_generator(iterable):
for i in iterable:
yield i + i
# Decorators
# A decorator is a higher order function, which accepts and returns a function.
# Simple usage example – add_apples decorator will add 'Apple' element into
# fruits list returned by get_fruits target function.
def add_apples(func):
def get_fruits():
fruits = func()
fruits.append('Apple')
return fruits
return get_fruits
@add_apples
def get_fruits():
return ['Banana', 'Mango', 'Orange']
# Prints out the list of fruits with 'Apple' element in it:
# Banana, Mango, Orange, Apple
print ', '.join(get_fruits())
import sys
print sys.argv
# numpy
import numpy as np
np.range(end)
np.range(start, end, step)
np.linspace(left, right, num)
np.zeros # init to zeros
np.ones # init to ones
np.empty # init to empty
np.may_share_memory(a, b)
x[start:end:step, start:end:step]
y = x[:, 2:]
z = x[:, 2:].copy()
# mask
x[x > 5]
c = np.ones((3,3))
c.dot(c) # matrix multiplication
c.T
x.sum(axis = 0) # sum col dimension (first)
x.sum(axis = 1) # sum row dimension (second)
x[0, :].sum()
x[0, :].max()
x[0, :].min()
x[0, :].argmax()
x[0, :].argmin()
np.median(x)
np.median(x, axis=-1)
np.sum
np.cumsum # cumulative sum
np.array_equal(a, b)
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