Checking whether a string starts with XXXX

Python's swiss army knife: startswith()

The startswith function is built right in Python's standard library. It's known for its sieving capacity - separating strings that start with a certain substring.

city = "New York"
if city.startswith("New"):
    print("There's something new here!")  # See what I did there? ;)
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Checking multiple prefixes? No problem

startswith ain't a one-trick pony. It accepts a tuple of prefixes, allowing you to check against multiple strings at once. How neat is that?

protocols = ("http", "https")
url = "https://stackoverflow.com"

if url.startswith(protocols):
    # Web developers' version of Knock Knock jokes
    print("Knock Knock.\n- Who's there?\n- URL with a valid protocol!")
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Going beyond startswith with regular expressions

Sometimes, the task needs a little more firepower. Enter regular expressions -- complex patterns to the rescue. Python's got you covered with its re module.

import re

if re.match('^TheDoctor', "TheDoctor is in"):
    print("Doctor Who? Exactly!")  # Who doesn't love a Whovian joke?
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Compiled regex patterns: Power and Efficiency

For repeated checks, compiling regular expressions with re.compile and using them across your script boosts performance like a turbocharger.

# Compiling the "knock knock" pattern
knock_pattern = re.compile('^(Knock knock)')

if knock_pattern.match("Knock knock. Who's there?"):
    print("A perfectly matched joke!")
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You can use the | operator in regex to separate multiple patterns when compiling with re.compile. It's like playing matchmaker but for regex patterns!

Avoiding inefficient methods

For those who like going off the beaten path, string partitioning might be an option. However, startswith is far more efficient and readable.

# Slightly less efficient, but hey, it's variety
if "R2D2".rpartition('R2')[0] == '':
    print("R2D2 is here. May the Force be with you.")
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And let's not even talk about using rfind or rindex for checking the start of a string. Trust me, startswith is your Yoda here.

Mastering the time with timeit

Python isn't just about writing pretty code. It's also about running efficient code. The timeit module comes in handy to benchmark the performance of various methods:

import timeit

# Timer set, let the race begin
startswith_time = timeit.timeit(
    lambda: "hello world".startswith('hello'),
    number=10000
)

# On your mark, get set, go!
regex_time = timeit.timeit(
    lambda: bool(re.match('^hello', "hello world")),
    number=10000
)

print(f"startswith: {startswith_time}s")
print(f"Regex: {regex_time}s")  # May the fastest method win! :)
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Such tests should help you make your code not just beautiful, but also fast. Because nobody likes slow code.

Broader context: The right tool for the right job

Different problems need different tools. While startswith gets the job done most of the time, sometimes, regular expressions or more complex string operations might be your savior. Always consider the context!