用这10个小技巧加速Python编程
>>> # Positive Indexing
... numbers = [1, 2, 3, 4, 5, 6, 7, 8]
... print("First Number:", numbers[0])
... print("First Four Numbers:", numbers[:4])
... print("Odd Numbers:", numbers[::2])
...
First Number: 1
First Four Numbers: [1, 2, 3, 4]
Odd Numbers: [1, 3, 5, 7]
>>> # Negative Indexing
... data_shape = (100, 50, 4)
... names = ["John", "Aaron", "Mike", "Danny"]
... hello = "Hello World!"
...
... print(data_shape[-1])
... print(names[-3:-1])
... print(hello[1:-1:2])
...
4
['Aaron', 'Mike']
el ol
if len(some_list) > 0:
# do something here when the list is not empty
else:
# do something else when the list is empty
>>> def check_container_empty(container):
... if container:
... print(f"{container} has elements.")
... else:
... print(f"{container} doesn't have elements.")
...
... check_container_empty([1, 2, 3])
... check_container_empty(set())
... check_container_empty({"zero": 0, "one": 1})
... check_container_empty(tuple())
...
[1, 2, 3] has elements.
set() doesn't have elements.
{'zero': 0, 'one': 1} has elements.
() doesn't have elements.
>>> # List of strings
... # The typical way
... columns = ['name', 'age', 'gender', 'address', 'account_type']
... print("* Literals:", columns)
...
... # Do this instead
... columns = 'name age gender address account_type'.split()
... print("* Split with spaces:", columns)
...
... # If the strings contain spaces, you can use commas instead
... columns = 'name, age, gender, address, account type'.split(', ')
... print("* Split with commas:", columns)
...
* Literals: ['name', 'age', 'gender', 'address', 'account_type']
* Split with spaces: ['name', 'age', 'gender', 'address', 'account_type']
* Split with commas: ['name', 'age', 'gender', 'address', 'account type']
# The typical way
if score > 90:
reward = "1000 dollars"
else:
reward = "500 dollars"
# Do this instead
reward = "1000 dollars" if score > 90 else "500 dollars"
# Another possible scenario
# You got a reward amount from somewhere else, but don't know if None/0 or not
reward = reward_known or "500 dollars"
# The above line of code is equivalent to below
reward = reward_known if reward_known else "500 dollars"
>>> # Create a text file that has the text: Hello World!
...
... # Open the file and append some new data
... text_file0 = open("hello_world.txt", "a")
... text_file0.write("Hello Python!")
...
... # Open the file again for something else
... text_file1 = open("hello_world.txt")
... print(text_file1.read())
...
Hello World!
>>> with open("hello_world.txt", "a") as file:
... file.write("Hello Python!")
...
... with open("hello_world.txt") as file:
... print(file.read())
...
... print("Is file close?", file.closed)
...
Hello World!Hello Python!Hello Python!
Is file close? True
# Multiple Comparisons
# The typical way
if a < 4 and a > 1:
# do something here# Do this instead
if 1 < a < 4:
# do somerthing here
# The typical way
if b == "Mon" or b == "Wed" or b == "Fri" or b == "Sun":
# do something here# Do this instead, you can also specify a tuple ("Mon", "Wed", "Fri", "Sun")
if b in "Mon Wed Fri Sun".split():
# do something here
# The typical ways
if a < 10 and b > 5 and c == 4:
# do somethingif a < 10 or b > 5 or c == 4:
# do something# Do these instead
if all([a < 10, b > 5, c == 4]):
# do somethingif any([a < 10, b > 5, c == 4]):
# do something
# The original form:
def generate_plot(data, image_name):
"""This function creates a scatter plot for the data"""
# create the plot based on the data
...
if image_name:
# save the image
...# In many cases, we don't need to save the image
generate_plot(data, None)# The one with a default value
def generate_plot(data, image_name=None):
pass# Now, we can omit the second parameter
generate_plot(data)
>>> words = ['an', 'boy', 'girl', 'an', 'boy', 'dog', 'cat', 'Dog', 'CAT', 'an','GIRL', 'AN', 'dog', 'cat', 'cat', 'bag', 'BAG', 'BOY', 'boy', 'an']
... unique_words = {x.lower() for x in set(words)}
... for word in unique_words:
... print(f"* Count of {word}: {words.count(word)}")
...
* Count of cat: 3
* Count of bag: 1
* Count of boy: 3
* Count of dog: 2
* Count of an: 5
* Count of girl: 1
>>> from collections import Counter
...
... word_counter = Counter(x.lower() for x in words)
... print("Word Counts:", word_counter)
...
Word Counts: Counter({'an': 5, 'boy': 4, 'cat': 4, 'dog': 3, 'girl': 2, 'bag': 2})
>>> # Find out the most common item
... print("Most Frequent:", word_counter.most_common(1))
Most Frequent: [('an', 5)]
>>> # Find out the most common 2 items
... print("Most Frequent:", word_counter.most_common(2))
Most Frequent: [('an', 5), ('boy', 4)]
>>> # A list of numbers and strings
... numbers = [1, 3, 7, 2, 5, 4]
... words = ['yay', 'bill', 'zen', 'del']
... # Sort them
... print(sorted(numbers))
... print(sorted(words))
...
[1, 2, 3, 4, 5, 7]
['bill', 'del', 'yay', 'zen']
>>> # Sort them in descending order
... print(sorted(numbers, reverse=True))
... print(sorted(words, reverse=True))
...
[7, 5, 4, 3, 2, 1]
['zen', 'yay', 'del', 'bill']
>>> # Create a list of tuples
... grades = [('John', 95), ('Aaron', 99), ('Zack', 97), ('Don', 92), ('Jennifer', 100), ('Abby', 94), ('Zoe', 99), ('Dee', 93)]
>>> # Sort by the grades, descending
... sorted(grades, key=lambda x: x[1], reverse=True)
[('Jennifer', 100), ('Aaron', 99), ('Zoe', 99), ('Zack', 97), ('John', 95), ('Abby', 94), ('Dee', 93), ('Don', 92)]
>>> # Sort by the name's initial letter, ascending
... sorted(grades, key=lambda x: x[0][0])
[('Aaron', 99), ('Abby', 94), ('Don', 92), ('Dee', 93), ('John', 95), ('Jennifer', 100), ('Zack', 97), ('Zoe', 99)]
>>> # Requirement: sort by name initial ascending, and by grades, descending
... # Both won't work
... sorted(grades, key=lambda x: (x[0][0], x[1]), reverse=True)
[('Zoe', 99), ('Zack', 97), ('Jennifer', 100), ('John', 95), ('Dee', 93), ('Don', 92), ('Aaron', 99), ('Abby', 94)]
>>> sorted(grades, key=lambda x: (x[0][0], x[1]), reverse=False)
[('Abby', 94), ('Aaron', 99), ('Don', 92), ('Dee', 93), ('John', 95), ('Jennifer', 100), ('Zack', 97), ('Zoe', 99)]
>>> # This will do the trick
... sorted(grades, key=lambda x: (x[0][0], -x[1]))
[('Aaron', 99), ('Abby', 94), ('Dee', 93), ('Don', 92), ('Jennifer', 100), ('John', 95), ('Zoe', 99), ('Zack', 97)]
>>> student = {'name': "John", 'age': 18}
... student['gender']
...
Traceback (most recent call last):
File "<input>", line 2, in <module>
KeyError: 'gender'
>>> letters = ["a", "a", "c", "d", "d", "c", "a", "b"]
... final_dict = {}
... for letter in letters:
... if letter not in final_dict:
... final_dict[letter] = []
... final_dict[letter].append(letter)
...
... print("Final Dict:", final_dict)
...
Final Dict: {'a': ['a', 'a', 'a'], 'c': ['c', 'c'], 'd': ['d', 'd'], 'b': ['b']}
>>> from collections import defaultdict
...
... final_defaultdict = defaultdict(list)
... for letter in letters:
... final_defaultdict[letter].append(letter)
...
... print("Final Default Dict:", final_defaultdict)
...
Final Default Dict: defaultdict(<class 'list'>, {'a': ['a', 'a', 'a'], 'c': ['c', 'c'], 'd': ['d', 'd'], 'b': ['b']})
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