LESSER-KNOWN YET POWERFUL FEATURES AND FUNCTIONS
Unlocking Python’s Hidden Gems: 60 Code Snippets to Elevate Your Coding Skills
Dive into the Depths of Python’s Lesser-Known Features and Functions for Next-Level Programming Mastery
In this comprehensive exploration, we delve into 60 of these lesser-known Python gems, each capable of adding a new dimension to your coding toolkit. From optimizing data structures to streamlining algorithms, and enhancing readability to boosting performance, these snippets are more than just code — they’re keys to unlocking Python’s full potential.
1. else clause on loops: You can use an else block with a for or while loop. It runs if the loop completes normally (without hitting a break statement).
for i in range(3):
print(i)
else:
print("Loop finished normally")2. enumerate function: This function adds a counter to an iterable and returns it.
for index, value in enumerate(['a', 'b', 'c']):
print(f"{index}: {value}")3. List comprehensions with if clause: You can filter items in a list comprehension.
even_numbers = [x for x in range(10) if x % 2 == 0]4. getattr function: Dynamically get a property of an object.
class MyClass:
name = "Chat"
obj = MyClass()
print(getattr(obj, 'name')) # Outputs: Chat5. setattr function: Dynamically set a property of an object.
setattr(obj, 'name', 'Chat')
print(obj.name) # Outputs: Chat6. Function argument unpacking: You can unpack lists or tuples into function arguments using *.
def func(a, b, c):
print(a, b, c)
args = [1, 2, 3]
func(*args)7. Dictionary unpacking in function arguments: Use ** to unpack dictionaries into keyword arguments.
def func(a=0, b=0):
print(a, b)
kwargs = {'a': 1, 'b': 2}
func(**kwargs)8. zip function: Combine multiple iterables into one.
names = ['Alice', 'Bob', 'Charlie']
ages = [25, 30, 35]
for name, age in zip(names, ages):
print(f"{name} is {age} years old")9. eval function: Evaluate a string as a Python expression.
result = eval("5 * 5")
print(result) # Outputs: 2510. exec function: Execute dynamically created Python code.
exec("print('Hello World')")11. slice objects: Create slice objects for slicing operations.
my_list = [0, 1, 2, 3, 4, 5]
s = slice(1, 5, 2)
print(my_list[s]) # Outputs: [1, 3]12. globals and locals functions: Access global and local symbol tables.
x = 10
def func():
y = 5
print(globals()['x']) # Access global variable
print(locals()['y']) # Access local variable
func()13. reversed function: Reverse any sequence.
for i in reversed(range(5)):
print(i)14. any and all functions: Check if any or all elements in an iterable are true.
print(any([False, True, False])) # Outputs: True
print(all([True, True, True])) # Outputs: True15. defaultdict from collections: Provides a default value for a missing key.
from collections import defaultdict
d = defaultdict(int)
d[‘key’] += 1
print(d[‘key’]) # Outputs: 116. Counter from collections: Count items in an iterable.
from collections import Counter
c = Counter('hello')
print(c) # Outputs: Counter({'l': 2, 'h': 1, 'e': 1, 'o': 1})17. itertools module: Provides a collection of tools for handling iterators.
import itertools
for p in itertools.permutations('AB'):
print(p)18. @staticmethod and @classmethod decorators: Define methods that are not bound to an instance or class.
class MyClass:
@staticmethod
def static_method():
return "static method called"
@classmethod
def class_method(cls):
return cls.__name__
print(MyClass.static_method())
print(MyClass.class_method())19. __slots__ in classes: Optimize memory usage by explicitly declaring instance attributes.
class MyClass:
__slots__ = ['name', 'value']
def __init__(self, name, value):
self.name = name
self.value = value20. frozenset: Immutable version of a set.
my_set = frozenset([1, 2, 3])
print(my_set)21. divmod function: Returns the quotient and remainder when dividing two numbers.
quotient, remainder = divmod(10, 3)
print(f"Quotient: {quotient}, Remainder: {remainder}")22. namedtuple from collections: Creates tuple-like objects with named fields.
from collections import namedtuple
Point = namedtuple('Point', ['x', 'y'])
p = Point(1, 2)
print(p.x, p.y)23. iter function with sentinel value: Create an iterator that stops at a sentinel value.
with open('file.txt', 'r') as f:
for line in iter(lambda: f.readline().strip(), 'END'):
print(line)24. List slicing tricks: Advanced ways to slice lists.
my_list = [0, 1, 2, 3, 4, 5]
print(my_list[::2]) # Outputs every second element25. itertools.cycle: Cycle through an iterable indefinitely.
import itertools
count = 0
for item in itertools.cycle(['A', 'B', 'C']):
if count > 5:
break
print(item)
count += 126. itertools.chain: Chain multiple iterables.
import itertools
for i in itertools.chain([1, 2, 3], ['a', 'b']):
print(i)27. itertools.combinations and itertools.permutations: Generate combinations and permutations.
import itertools
print(list(itertools.combinations('ABC', 2)))
print(list(itertools.permutations('ABC', 2)))28. functools.partial: Create partial functions with pre-filled arguments.
from functools import partial
def multiply(x, y):
return x * y
double = partial(multiply, 2)
print(double(5))29. functools.lru_cache: Cache function call results.
from functools import lru_cache
@lru_cache(maxsize=32)
def fibonacci(n):
if n < 2:
return n
return fibonacci(n-1) + fibonacci(n-2)30. contextlib.suppress: Suppress specified exceptions.
from contextlib import suppress
with suppress(FileNotFoundError):
open('non_existent_file.txt')31. next with default: Get the next item from an iterator, with a default if exhausted.
it = iter([1, 2, 3])
print(next(it, 'done')) # Outputs 1
print(next(it, 'done')) # Outputs 2
print(next(it, 'done')) # Outputs 3
print(next(it, 'done')) # Outputs 'done'32. operator.itemgetter: Efficiently fetch items from a collection.
from operator import itemgetter
data = [('Alice', 25), ('Bob', 30), ('Charlie', 35)]
print(sorted(data, key=itemgetter(1))) # Sort by age33. operator.attrgetter: Fetch attributes from objects.
from operator import attrgetter
class Person:
def __init__(self, name, age):
self.name = name
self.age = age
people = [Person('Alice', 30), Person('Bob', 25)]
print(sorted(people, key=attrgetter('age')))34. string.ascii_letters and related constants: Predefined string constants.
import string
print(string.ascii_letters)
print(string.digits)35. os.walk: Traverse directory trees.
import os
for root, dirs, files in os.walk('.'):
print(root, dirs, files)36. glob.glob: Pattern matching for file names.
import glob
for filename in glob.glob('*.txt'):
print(filename)37. heapq module: Provides functions for implementing heaps.
import heapq
heap = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0]
heapq.heapify(heap)
heapq.heappush(heap, -5)
print([heapq.heappop(heap) for _ in range(3)])38. bisect module for binary search: Insert into a list in sorted order.
import bisect
a = [1, 2, 4, 5]
bisect.insort(a, 3)
print(a)39. collections.deque: Double-ended queue.
from collections import deque
d = deque('ghi')
d.append('j')
d.appendleft('f')
print(d)40. csv module for CSV file handling: Read and write CSV files.
import csv
with open('example.csv', 'w', newline='') as f:
writer = csv.writer(f)
writer.writerow(['Name', 'Age'])
writer.writerow(['Alice', 30])
writer.writerow(['Bob', 25])41. filter function: Filters elements of an iterable based on a function.
numbers = [1, 2, 3, 4, 5]
even_numbers = filter(lambda x: x % 2 == 0, numbers)
print(list(even_numbers)) # Outputs: [2, 4]42. map function: Applies a function to every item of an iterable.
squares = map(lambda x: x**2, numbers)
print(list(squares)) # Outputs: [1, 4, 9, 16, 25]43. complex for complex numbers: Creates a complex number.
c = complex(2, 3)
print(c) # Outputs: (2+3j)44. __dict__ in classes: Access the properties of an object.
class MyClass:
def __init__(self):
self.a = 1
self.b = 2
obj = MyClass()
print(obj.__dict__) # Outputs: {'a': 1, 'b': 2}45. itertools.tee: Creates n independent iterators from a single iterable.
import itertools
iter1, iter2 = itertools.tee(numbers, 2)
print(list(iter1), list(iter2))46. itertools.islice: Slicing for iterators.
slice_iter = itertools.islice(range(10), 2, 6)
print(list(slice_iter)) # Outputs: [2, 3, 4, 5]47. itertools.starmap: Similar to map but arguments are obtained from the iterable.
data = [(2, 5), (3, 2), (10, 3)]
result = itertools.starmap(pow, data)
print(list(result)) # Outputs: [32, 9, 1000]48. collections.ChainMap: Groups multiple dictionaries into a single view.
from collections import ChainMap
dict1 = {'a': 1, 'b': 2}
dict2 = {'c': 3, 'd': 4}
combined = ChainMap(dict1, dict2)
print(combined['a']) # Outputs: 149. functools.reduce: Applies a function cumulatively to the items of an iterable.
from functools import reduce
sum_of_numbers = reduce(lambda x, y: x + y, numbers)
print(sum_of_numbers) # Outputs: 1550. itertools.accumulate: Returns accumulated sums or other binary functions.
import itertools
acc = itertools.accumulate(numbers, lambda x, y: x + y)
print(list(acc)) # Outputs: [1, 3, 6, 10, 15]51. functools.total_ordering: Decorator to automatically generate ordering methods.
from functools import total_ordering
@total_ordering
class MyClass:
def __init__(self, value):
self.value = value
def __eq__(self, other):
return self.value == other.value
def __lt__(self, other):
return self.value < other.value52. hashlib for hashing: Generate hash values from strings.
import hashlib
hash_value = hashlib.sha256(b'Hello World').hexdigest()
print(hash_value)53. sys.getsizeof: Get the size of an object in bytes.
import sys
num = 5
print(sys.getsizeof(num)) # Outputs: Size in bytes54. shlex.split: Split the string using shell-like syntax.
import shlex
cmd = 'ls -l /var/www'
print(shlex.split(cmd))55. os.environ: Access environment variables.
import os
print(os.environ['PATH'])56. calendar module: Useful functions related to calendars.
import calendar
print(calendar.isleap(2024)) # Checks if a year is leap57. uuid module for unique IDs: Generate universally unique IDs.
import uuid
unique_id = uuid.uuid4()
print(unique_id)58. asyncio for asynchronous programming: Write concurrent code using async/await syntax.
import asyncio
async def main():
await asyncio.sleep(1)
print('Hello')
asyncio.run(main())59. __name__ == "__main__": Checks if the script is run directly.
if __name__ == "__main__":
print("Script run directly")60. pprint for pretty printing: Print Python data structures in a formatted way.
import pprint
data = {'a': [1, 2, 3], 'b': [4, 5, 6]}
pprint.pprint(data)Conclusion
The 60 Python hidden features and functions explored above unveil the depth and versatility of Python. From enhancing code efficiency with lesser-known data structures and itertools, ensuring robust and cleaner code with context managers and decorators, to harnessing the full potential of object-oriented features and memory management, these elements underscore Python’s capacity to cater to a wide array of programming needs.
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