「转」Learn X in Y Minutes - Python

# Single line comments start with a number symbol.
# 单行注释用井号打头

""" Multiline strings can be written
    using three "s, and are often used
    as comments
"""
""" 多行字符串用
	 三个 "打头，
	 也可用于注释
"""

####################################################
## 1. Primitive Datatypes and Operators
## 1. 基本数据类型和操作符
####################################################

# You have numbers
# 数字
3  # => 3

# Math is what you would expect
# 基本运算也正常
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.
# 除法稍微复杂点。计算结果自动取整。
5 / 2  # => 2

# To fix division we need to learn about floats.
# 为了修正除法的问题，我们需要先学习浮点数。
2.0     # This is a float这是个浮点数
11.0 / 4.0  # => 2.75 ahhh...much better好多了

# Result of integer division truncated down both for positive and negative.
# 无论正负，整数除法的结果都会取整。
5 // 3     # => 1
5.0 // 3.0 # => 1.0 # works on floats too浮点数也一样
-5 // 3  # => -2
-5.0 // 3.0 # => -2.0

# Note that we can also import division module(Section 6 Modules)
# to carry out normal division with just one '/'.
# 我们也可以导入division module（第六章的模块），要进行正常的除法，只需要一个 '/'
from __future__ import division
11/4    # => 2.75  ...normal division
11//4   # => 2 ...floored division  

# Modulo operation
# 取余数
7 % 3 # => 1

# Exponentiation (x to the yth power)
# 幂运算（x 的 y 次幂）
2**4 # => 16

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

# Boolean Operators
# Note "and" and "or" are case-sensitive
# 布尔运算符 注意 "and" "or"区分大小写
True and False #=> False
False or True #=> True

# Note using Bool operators with ints
# 注意在整数上使用布尔运算符
0 and 2 #=> 0
-5 or 0 #=> -5
0 == False #=> True
2 == True #=> False
1 == True #=> True

# negate with not
# 用"not"取反
not True  # => False
not False  # => True

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

# Inequality is !=
# != 是不等于
1 != 1  # => False
2 != 1  # => True

# More comparisons
# 更多的比较符
1 < 10  # => True
1 > 10  # => False
2 <= 2  # => True
2 >= 2  # => True

# Comparisons can be chained!
# 比较符可以连在一起
1 < 2 < 3  # => True
2 < 3 < 2  # => False

# Strings are created with " or '
# 用单引号和双引号新建字符串
"This is a string."
'This is also a string.'

# Strings can be added too!
# 字符串可以相加
"Hello " + "world!"  # => "Hello world!"
# Strings can be added without using '+'
# 字符串不用加号也可以相加
"Hello " "world!"  # => "Hello world!"

# ... or multiplied
# 也可以相乘
"Hello" * 3  # => "HelloHelloHello"

# A string can be treated like a list of characters
# 字符串可以当做是字符的表
"This is a string"[0]  # => 'T'

# % can be used to format strings, like this:
# 百分号可以用来格式化字符串
"%s can be %s" % ("strings", "interpolated")

# A newer way to format strings is the format method.
# This method is the preferred way
# 用 format 来格式化字符串，这也是首选的方法
"{0} can be {1}".format("strings", "formatted")
# You can use keywords if you don't want to count.
# 如果你不想数数的话，也可以使用关键字
"{name} wants to eat {food}".format(name="Bob", food="lasagna")

# None is an object
# None 也是一个对象
None  # => None

# Don't use the equality "==" symbol to compare objects to None
# Use "is" instead
# 别用 "==" 来比较 None，用 "is"
"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.
# "is"操作符用于对象。但不怎么适用于基本数据类型，最好还是用于处理对象。
# None, 0, and empty strings/lists all evaluate to False.
# All other values are True
# None，0，和空字符串，空表都被视为 False，其他的都是 True。
bool(0)  # => False
bool("")  # => False


####################################################
## 2. Variables and Collections
## 2. 变量与集合
####################################################

# Python has a print statement
# 输出
print "I'm Python. Nice to meet you!" # => I'm Python. Nice to meet you!

# Simple way to get input data from console
# 从控制台获得输入
input_string_var = raw_input("Enter some data: ") # Returns the data as a string
input_var = input("Enter some data: ") # Evaluates the data as python code
# Warning: Caution is recommended for input() method usage
# Note: In python 3, input() is deprecated and raw_input() is renamed to input()
# 使用 input() 的时候最好有警告
# 在 Python 3中，input() 已经不使用了，raw_input()也重命名为input()

# No need to declare variables before assigning to them.
# 在变量赋值之前不用声明
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.
# 访问一个未赋值的变量会产生一个异常。
# 进一步了解异常处理，可参见下一节《控制流》。
some_other_var  # Raises a name error 抛出一个名称错误

# if can be used as an expression
# if 可以作为表达式来使用
# Equivalent of C's '?:' ternary operator
# 和 C 的 "?:" 三元等号一样
"yahoo!" if 3 > 2 else 2  # => "yahoo!"

# Lists store sequences
# 列表储存了顺序
li = []
# You can start with a prefilled list
# 预先填充好的列表
other_li = [4, 5, 6]


# Add stuff to the end of a list with append
# 使用 append 方法把元素添加到列表的尾部
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
# 使用 pop 来移除最后一个元素
li.pop()        # => 3 and li is now [1, 2, 4]
# Let's put it back
# 使用 append 来添加
li.append(3)    # li is now [1, 2, 4, 3] again.

# Access a list like you would any array
# 像访问数组一样访问列表
li[0]  # => 1
# Assign new values to indexes that have already been initialized with =
# 使用 = 来分配新的值
li[0] = 42
li[0]  # => 42
li[0] = 1  # Note: setting it back to the original value
# Look at the last element
# 访问最后一个值
li[-1]  # => 3

# Looking out of bounds is an IndexError
# 超出边界会报错
li[4]  # Raises an IndexError

# You can look at ranges with slice syntax.
# (It's a closed/open range for you mathy types.)
# 你可以使用切片语法来查询列表的一个范围。
# （这个范围相当于数学中的左闭右开区间。）
li[1:3]  # => [2, 4]
# Omit the beginning
# 从某值开始
li[2:]  # => [4, 3]
# Omit the end
# 到某值结束
li[:3]  # => [1, 2, 4]
# Select every second entry
# 每两个遍历
li[::2]   # =>[1, 4]
# Reverse a copy of the list
# 倒序遍历
li[::-1]   # => [3, 4, 2, 1]
# Use any combination of these to make advanced slices
# 使用以下方法高级遍历
# li[start:end:step]
# 列表名[开始:结束:步]

# Remove arbitrary elements from a list with "del"
# 使用 del 来删除列表中的值
del li[2]   # li is now [1, 2, 3]

# You can add lists
# 列表也可以相加
li + other_li   # => [1, 2, 3, 4, 5, 6]
# Note: values for li and for other_li are not modified.
# 注意： 上述两个列表中的值都没有改变

# Concatenate lists with "extend()"
# 使用 extend() 来合并列表
li.extend(other_li)   # Now li is [1, 2, 3, 4, 5, 6]现在 li 长这样

# Remove first occurrence of a value
# 删除第一个出现的值
li.remove(2)  # li is now [1, 3, 4, 5, 6]第一个 2 被删除了
li.remove(2)  # Raises a ValueError as 2 is not in the list报错了，没有 2 了

# Insert an element at a specific index
# 把值插入准确位置
li.insert(1, 2)  # li is now [1, 2, 3, 4, 5, 6] again

# Get the index of the first item found
# 查询第一个值出现的位置
li.index(2)  # => 3
li.index(7)  # Raises a ValueError as 7 is not in the list

# Check for existence in a list with "in"
# 使用 in 来查询列表中是否存在某值
1 in li   # => True

# Examine the length with "len()"
# 使用 len()来查询列表长度
len(li)   # => 6


# Tuples are like lists but are immutable.
# 元组像是不能改变的列表
tup = (1, 2, 3)
tup[0]   # => 1
tup[0] = 3  # Raises a TypeError

# You can do all those list thingies on tuples too
# 列表的操作也可以使用在元组上
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
# 可以把元组或者列表中的值复制给多个变量
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
# 如果没有括号的话会建立元组
d, e, f = 4, 5, 6
# Now look how easy it is to swap two values
# 交换两个值
e, d = d, e     # d is now 5 and e is now 4


# Dictionaries store mappings
# 字典储存映射关系
empty_dict = {}
# Here is a prefilled dictionary
# 创建一个字典
filled_dict = {"one": 1, "two": 2, "three": 3}

# Look up values with []
# 用[]来查询对应值
filled_dict["one"]   # => 1

# Get all keys as a list with "keys()"
# 把所有键名导出为列表
filled_dict.keys()   # => ["three", "two", "one"]
# Note - Dictionary key ordering is not guaranteed.
# 注意：字典没有顺序
# Your results might not match this exactly.
# 得到的结果可能和上面不一样

# Get all values as a list with "values()"
# 把所有键值导出为列表
filled_dict.values()   # => [3, 2, 1]
# Note - Same as above regarding key ordering.
# 注意：没有顺序

# Check for existence of keys in a dictionary with "in"
# 使用 in 来查询是否有某个键名
"one" in filled_dict   # => True
1 in filled_dict   # => False

# Looking up a non-existing key is a KeyError
# 查询不存在的键名会报错
filled_dict["four"]   # KeyError

# Use "get()" method to avoid the KeyError
# 用 get() 来避免查询报错
filled_dict.get("one")   # => 1
filled_dict.get("four")   # => None
# The get method supports a default argument when the value is missing
# get() 方法可以设置一个默认值，在没有这个键名的时候有返回值
filled_dict.get("one", 4)   # => 1
filled_dict.get("four", 4)   # => 4
# note that filled_dict.get("four") is still => None
# 注意这个默认值不会改变，现在还是 None
# (get doesn't set the value in the dictionary)
# get() 不会向字典中插入值

# set the value of a key with a syntax similar to lists
# 向字典中插入键对
filled_dict["four"] = 4  # now, filled_dict["four"] => 4

# "setdefault()" inserts into a dictionary only if the given key isn't present
# Setdefault() 只能在值不存在时添加到字典里
filled_dict.setdefault("five", 5)  # filled_dict["five"] is set to 5 没有值的时候添加
filled_dict.setdefault("five", 6)  # filled_dict["five"] is still 5 有值的时候不变


# Sets store ... well sets (which are like lists but can contain no duplicates)
# 用 set() 来储存集合，像是列表一样，但是不能复制值
empty_set = set()
# Initialize a "set()" with a bunch of values
# 用值来初始化 set()
some_set = set([1, 2, 2, 3, 4])   # some_set is now set([1, 2, 3, 4])

# order is not guaranteed, even though it may sometimes look sorted
# 初始化之后进行的储存都存不进去
another_set = set([4, 3, 2, 2, 1])  # another_set is now set([1, 2, 3, 4])

# Since Python 2.7, {} can be used to declare a set
# 从 Python 2.7 开始，{} 可以用来声明一个集合
filled_set = {1, 2, 2, 3, 4}   # => {1, 2, 3, 4}

# Add more items to a set
# 把更多的元素添加进一个集合
filled_set.add(5)   # filled_set is now {1, 2, 3, 4, 5}

# Do set intersection with &
# 使用 & 来获取交集
other_set = {3, 4, 5, 6}
filled_set & other_set   # => {3, 4, 5}

# Do set union with |
# 使用 | 来获取并集
filled_set | other_set   # => {1, 2, 3, 4, 5, 6}

# Do set difference with -
# 使用 - 来获取补集
{1, 2, 3, 4} - {2, 3, 5}   # => {1, 4}

# Do set symmetric difference with ^
# 用 ^ 来取交集的补集
{1, 2, 3, 4} ^ {2, 3, 5}  # => {1, 4, 5}

# Check if set on the left is a superset of set on the right
# 右边是否是左边的子集
{1, 2} >= {1, 2, 3} # => False

# Check if set on the left is a subset of set on the right
# 左边是否是右边的子集
{1, 2} <= {1, 2, 3} # => True

# Check for existence in a set with in
# 使用 in 来检查是否存在于某个集合中
2 in filled_set   # => True
10 in filled_set   # => False


####################################################
## 3. Control Flow
## 3. 控制流
####################################################

# Let's just make a variable
# 创建一个变量
some_var = 5

# Here is an if statement. Indentation is significant in python!
# 这里有个条件语句，缩进在 Python 当中很重要。
# prints "some_var is smaller than 10"
# 打印"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. elif 子句可选。
    print "some_var is smaller than 10."
else:           # This is optional too.这句也是可选的。
    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 {0} to interpolate formatted strings. (See above.)
    # 使用 {0} 来格式化字符串
    print "{0} is a mammal".format(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

"""
"range(lower, upper)" returns a list of numbers
from the lower number to the upper number
prints:
    4
    5
    6
    7
"""
for i in range(4, 8):
    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
# 使用 try/except 代码块来处理异常
# Works on Python 2.6 and up:
# 适用于 Python 2.6 及以上版本：
try:
    # Use "raise" to raise an error
    # 使用 raise 来抛出错误
    raise IndexError("This is an index error")
except IndexError as e:
    pass    # Pass is just a no-op. Usually you would do recovery here. pass 只是一个空操作。通常你应该在这里做一些恢复工作。
except (TypeError, NameError):
    pass    # Multiple exceptions can be handled together, if required. 如果需要的话，好几个异常可以一起处理。
else:   # Optional clause to the try/except block. Must follow all except blocks 可选的分句，用于处理异常，必须写在所有异常语句之后
    print "All good!"   # Runs only if the code in try raises no exceptions 这里的语句只在没异常的时候运行
finally: #  Execute under all circumstances 处理所有情况
    print "We can clean up resources here"

# Instead of try/finally to cleanup resources you can use a with statement 使用 with 来避免出错
with open("myfile.txt") as f:
    for line in f:
        print line

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

# Use "def" to create new functions
# 使用 def 来新建函数
def add(x, y):
    print "x is {0} and y is {1}".format(x, y)
    return x + y    # Return values with a return statement 返回值

# Calling functions with parameters
# 调用函数，传入参数
add(5, 6)   # => prints out "x is 5 and y is 6" and returns 11

# Another way to call functions is with keyword arguments
# 调用函数的另一种方式是传入关键字参数
add(y=6, x=5)   # Keyword arguments can arrive in any order. 关键字参数可以以任意顺序传入


# You can define functions that take a variable number of
# positional args, which will be interpreted as a tuple if you do not use the *
# 你可以定义一个函数，并让它接受可变数量的定位参数，如果你不用 * 的话会被解释为一个元组。
def varargs(*args):
    return args

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


# You can define functions that take a variable number of
# keyword args, as well, which will be interpreted as a dict if you do not use **
# 你也可以定义一个函数，并让它接受可变数量的关键字参数，如果不用 ** 的话会被解释为一个字典
def keyword_args(**kwargs):
    return kwargs

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


# You can do both at once, if you like
# 你还可以同时使用这两类参数，只要你愿意：
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 positional args and use ** to expand keyword args.
# 在调用函数时，定位参数和关键字参数还可以反过来用。
# 使用 * 来展开元组，使用 ** 来展开关键字参数。
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)

# you can pass args and kwargs along to other functions that take args/kwargs
# by expanding them with * and ** respectively
# 各自使用* 和 ** 可以把元组和关键字参数展开传递到其他的函数中。
def pass_all_the_args(*args, **kwargs):
    all_the_args(*args, **kwargs)
    print varargs(*args)
    print keyword_args(**kwargs)

# Function Scope
# 函数范围
x = 5

def set_x(num):
    # Local var x not the same as global variable x
    # 这里的 x 是私有变量
    x = num # => 43
    print x # => 43

def set_global_x(num):
    global x
    print x # => 5
    x = num # global var x is now set to 6
    print x # => 6

set_x(43)
set_global_x(6)

# Python has first class functions
# 函数在 Python 中优先级很高
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
# 匿名函数
(lambda x: x > 2)(3)   # => True
(lambda x, y: x ** 2 + y ** 2)(2, 1) # => 5

# There are built-in higher order functions
# 内建的高阶函数
map(add_10, [1, 2, 3])   # => [11, 12, 13]
map(max, [1, 2, 3], [4, 2, 1])   # => [4, 2, 3]

filter(lambda x: x > 5, [3, 4, 5, 6, 7])   # => [6, 7]

# We can use list comprehensions for nice maps and filters
# 我们可以使用列表推导式来模拟 map 和 filter
[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
## 5. 类
####################################################

# We subclass from object to get a class.
# 我们可以从对象中继承，来得到一个类。
class Human(object):

    # A class attribute. It is shared by all instances of this class
    # 下面是一个类属性。它将被这个类的所有实例共享。

    species = "H. sapiens"

    # Basic initializer, this is called when this class is instantiated.
    # 在初始化类的时候构造函数。
    # 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.
    # 注意： __XXX__ 表示一个类，也可能表示 Python 内置的某个变量，不要轻易修改它。
    
    def __init__(self, name):
        # Assign the argument to the instance's name attribute
        # 把参数赋值为实例的 name 属性
        self.name = name

        # Initialize property
        # 初始化参数
        self.age = 0


    # An instance method. All methods take "self" as the first argument
    # 下面是一个实例方法。所有方法都以 self 作为第一个参数。
    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
    # 类方法会被所有实例共享。
    # 类方法在调用时，会将类本身作为第一个函数传入。

    @classmethod
    def get_species(cls):
        return cls.species

    # A static method is called without a class or instance reference
    # 静态方法在调用时，不会传入类或实例的引用。
    @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.
    # 参数就像是一个函数，返回一个只读的同名方法
    @property
    def age(self):
        return self._age

    # This allows the property to be set
    # 设置参数
    @age.setter
    def age(self, age):
        self._age = age

    # This allows the property to be deleted
    # 删除参数
    @age.deleter
    def age(self):
        del self._age


# Instantiate a class
# 实例化一个类
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
# 调用类的方法
i.get_species()   # => "H. sapiens"

# Change the shared attribute
# 修改共享的参数
Human.species = "H. neanderthalensis"
i.get_species()   # => "H. neanderthalensis"
j.get_species()   # => "H. neanderthalensis"

# Call the static method
# 调用静态方法
Human.grunt()   # => "*grunt*"

# Update the property
# 修改参数
i.age = 42

# Get the property
# 获得参数值
i.age # => 42

# Delete the property
# 删除参数
del i.age
i.age  # => raises an AttributeError


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

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

# You can get specific functions from a module
# 从模块中导入指定函数
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
# 可以从模块中导入所有函数，但不建议这么做。
from math import *

# You can shorten module names
# 缩短模块的名字
import math as m
math.sqrt(16) == m.sqrt(16)   # => True
# you can also test that the functions are equivalent
from math import sqrt
# 测试函数是否和调用的函数一样
math.sqrt == m.sqrt == sqrt  # => 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.
# Python 模块就是普通的 Python 文件。
# 你可以编写你自己的模块，然后导入它们。
# 模块的名称与文件名相同。

# You can find out which functions and attributes
# defines a module.
# 查看模块中的所有函数和参数
import math
dir(math)


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

# Generators help you make lazy code
# 生成器让写代码更简单
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.
# 生成器在运行的同时产生值，而不是一次性生成所有然后一个一个返回。大于15个两位数的值难以被执行。
# Note xrange is a generator that does the same thing range does.
# Creating a list 1-900000000 would take lot of time and space to be made.
# xrange creates an xrange generator object instead of creating the entire list
# like range does.
# xrange 就是这样一种生成器，他的效果和 range 一样，但是生成 1-900000000 会花费很多时间，xrange 会实时生成而非 range 那样全部生成。
# We use a trailing underscore in variable names when we want to use a name that
# would normally collide with a python keyword
# 如果想简单表明这个变量只是后面的关键字集合的话，我们只是在这个关键字后面加一个下划线来命名这个变量。
xrange_ = xrange(1, 900000000)

# will double all numbers until a result >=30 found
# 把所有数加倍，直到结果大于30
for i in double_numbers(xrange_):
    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(target_function):
    @wraps(target_function)
    def wrapper(*args, **kwargs):
        msg, say_please = target_function(*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 :(