10 Common Pythonic Coding Practices and Tips

Python is praised for its concise syntax, and writing code that reads like pseudocode improves readability and performance; as Harold Abelson said, "Programs must be written for people to read, and only incidentally for machines to execute."

1. Variable swapping can be done without a temporary variable:

>> a = 1
>>> b = 2
>>> a, b = b, a

2. Looping over a range is more Pythonic using range (or xrange in Python 2):

for i in range(6):
    print i2

3. Iterating with index is cleaner with enumerate:

for i, color in enumerate(colors):
    print i, '-->', color

4. String concatenation should prefer str.join to avoid repeated temporary strings: print ', '.join(names) 5. File handling is safest with a with statement, which automatically closes the file:

with open('data.txt') as f:
    data = f.read()

6. List comprehensions provide a concise one‑liner for building lists: [i*2 for i in xrange(10)] 7. Decorators can abstract caching logic from business code:

def cache(func):
    saved = {}
    def wrapper(url):
        if url in saved:
            return saved[url]
        page = func(url)
        saved[url] = page
        return page
    return wrapper

@cache
def web_lookup(url):
    return urllib.urlopen(url).read()

8. Choosing the right list structure improves performance; for frequent insertions/removals at both ends, collections.deque is preferable:

from collections import deque
names = deque(['raymond', 'rachel', ...])
names.popleft()
names.appendleft('mark')

9. Sequence unpacking assigns multiple variables in a single statement: name, gender, age, email = p 10. Dictionary iteration is most efficient using items() (or iteritems() in Python 2) to avoid extra lookups:

for k, v in d.items():
    print k, '-->', v

These Pythonic patterns make code cleaner, faster, and easier to maintain; many more exist, and exploring open‑source projects can provide further inspiration.