Python Flashcards
Filter a list
l = [“ab”, “a”, “c”]
Return items that have a length more than 1
list(filter(lambda x: len(x) > 1, l))
Use reduce on a List
from functions import reduce
reduce(lambda a, b: a + b, myList)
This will sum up all the numbers left to right.
reduce(lambda a, b: a if a > b else b, myList)
This will return the max value from list
Insert 5 into Index 0 in List
x = [1,2,3,4]
x.insert(0,5)
or
x[0:0] = 5
Get character length away from ‘a’
x = ‘f’
ord(x) - ord(‘a’)
Can use to build tuple of 26 letters and add count of letters for an anagram problem (can then compare tuples to see if they match and words are anagrams)
Separate word into list of characters
word = “hello”
chars = [*word]
Deque and Operations
from collections import deque
x = deque()
x.append()
x.appendleft()
x.pop()
x.popleft))
Create decoder with message and alphabet
import string
alpha = string.ascii_lowercase
decorder = dict(zip(msg, alpha))
Dictionary comprehension
d = {“a”: 1, “b”: 5, “c”: 10}
Return any key over 2
{k:v for k,v in d.items() if v > 2}
Check if number is int or float
(4/2).is_integer()
Sum up all dictionary values
sum(d.values())
Stack underflow
stack = []
stack[-1]
Create a list with x number of spots
l = [0] * x
Filter a list
Apply function to elements in list
a = [1,2,3,4]
list(map(lambda x: x + 1, a))
Apply function to elements in dict
d = {“x”: 1, “a”: 2, “c”: 3}
c = list(map(lambda x: x + 1, d.values()))
new_d = dict(zip(d.keys(), c))
What prints out:
nums = [1,2,3,4,5]
for i in range(0, len(nums)):
print(i)
0,1,2,3,4
What prints out:
nums = [1,2,3,4,5]
for i in range(0, len(nums) + 1):
print(i)
0,1,2,3,4,5
Set starting value of a number without using 0
x = float(“-inf”)
Create dict that won’t throw error when accessing key doesn’t exist
from collections import defaultdict
result = defaultdict(list)
Scope
Block of code where object remains relevant
local / global
*args vs **kwargs
*args = unnamed args passed a tuple
def func1(this, *args):
print(this)
print(args)
func1(1,2,3)
> 1, (2, 3)
**kwargs = keyword args passed as dict
def func2(**kwargs):
print(kwargs)
func2(this=1, that=2)
> {“this”: 1, “that”: 2)
Remove duplicates from a file and write to a second file
seen = set()
with open(file1, “r+”) as fromFile, open(file2, “w”) as toFile:
l = fromFile.readlines()
fromFile.seek(0)
fromFile.truncate()
for line in l:
if line in seen:
toFile.write(line)
else:
fromFile.write(line)
seen.add(line)
read() vs readline() vs readlines()
read(): returns entire file as str
readline(): returns a single line up to line break
readlines(): reads all lines into a list
Split a string into a list of lines
s = “This list\nThat list”
s.splitlines()
Sort list with Lambda
l = [“a”, “bb”. “ccc”]
l.sort(key=lambda x: len(x))
Delete key from dictionary
del d[‘key_name’]
Count number of chars in a string with standard library
from collections import Counter
x = Counter(“thisthat”)
> > Counter({‘t’: 3, ‘h’: 2, ‘i’: 1, ‘s’: 1, ‘a’: 1})
Can then conver to dict:
dict(x)
l.sort() vs sorted(l)
l.sort(): Sorts list in-place
sorted(l): Creates new list object that’s sorted
Magic methods
aka dunder methods
These methods provide a way to define how objects of a class behave in various contexts, such as arithmetic operations, string representations, comparisons, and more
__str__: defines behavior of ‘str(obj)’
__len__: defines behavior of ‘len(obj)’
__add__(self, other): ‘obj1 + obj2’
__eq__(self, other): ‘obj1 == obj2’
__getitem__(self, key): ‘obj[key]’
Python dictionary collisions
Python uses open addressing to handle dict collisions
Memory management
- Memory is managed by a private heap space. Interpreter take scare of heap
- Built-in garbage collector
Inheritance Types
- Single: When a class inherits only one superclass/parent
- Multiple: When a class inherits multiple superclasses
- Multilevel: When a class inherits a superclass, then another class inherits from it (parent, child, grandparent)
- Hierarchical: When one superclass is inherited by multiple derived/child classes
Decorators
Functions that help add functionality to an existing function without changing the structure of the function.
Three Types of Control Flow
- Break: Terminate loop or statement and pass control to next statement
- Continue: Force execution of the next iteration instead of terminating it
- Pass: Skip the execution
Count number of lines in a file
with open(file_path, ‘r’) as f:
line_count = sum(1 for line in f)
or
with open(file_path, ‘r’) as f:
for count, line in enumerate(fp):
pass
print(‘Total Lines’, count + 1)
Drop duplicates in a file using Pandas
import pandas as pd
df = pd.read_csv(fromFile)
df.drop_duplicates(inplace=True)
df.to_csv(toFile)
Use sets to get a list of all words in str1 not in str2 and vice versa
words1 = set(str1.split())
words2 = set(str2.split())
result = words1.symmetric_difference(words2)
RETURNS SET
Get key with max value from dictionary
d = {‘a’: 10, ‘b’: 5, ‘c’: 15, ‘d’: 7}
max(d, key=d.get)
Get key with nth largest value
d = {‘a’: 10, ‘b’: 5, ‘c’: 15, ‘d’: 7}
l = sorted(d, key=d.get, reverse=True)
l[n]
Join two sets together
a = set()
b = set()
a.union(b)
pass vs continue
continue will exit the iteration of the loop. pass will keep going
