re - Regular Expressions

Q: Raw string required?

Not required but r"\n" vs "\\n" clarity strongly recommended.

Q: greedy vs lazy?

*?, +? lazy quantifiers - match minimal span.

Q: verbose regex?

re.compile(r"...", re.VERBOSE) allows comments and whitespace in pattern.

Q: Unicode?

Default unicode str patterns in Python 3; use (?a) for ASCII-only when needed.

Q: Replace count?

sub(pattern, repl, s, count=1) limit replacements.

Q: Lookahead?

(?=...) positive lookahead - assert without consuming.

Q: re vs regex PyPI?

regex module adds features; stdlib sufficient for most services.

The re module matches, searches, and substitutes text via regex. Compile patterns for reuse; use raw strings r"..." for readable escapes; prefer str methods when regex is overkill.

Recipe

import re
 
EMAIL = re.compile(r"^[\w.+-]+@[\w-]+\.[\w.-]+$")
 
def valid_email(value: str) -> bool:
    return bool(EMAIL.match(value))

When to reach for this:

Log parsing and extraction
Tokenizing structured but irregular text
Validation with known pattern limits
sed-like substitutions
Splitting on variable whitespace

Working Example

import re
 
LOG_LINE = re.compile(
    r"^(?P<level>INFO|ERROR)\s+(?P<msg>.+)$"
)
 
def parse_log_lines(text: str) -> list[dict[str, str]]:
    rows = []
    for line in text.strip().splitlines():
        m = LOG_LINE.match(line)
        if m:
            rows.append(m.groupdict())
    return rows
 
sample = "INFO started\nERROR disk full\n"
print(parse_log_lines(sample))
 
redacted = re.sub(r"\b\d{4}-\d{4}-\d{4}-\d{4}\b", "[CARD]", "4111-1111-1111-1111")
print(redacted)

What this demonstrates:

Named groups via (?P<name>...)
match anchors start; search scans anywhere
sub replaces sensitive data patterns
Compile once at module level for hot paths

Deep Dive

Common Methods

Method	Purpose
`re.search`	First match anywhere
`re.match`	Start of string
`re.findall`	All non-overlapping
`re.sub`	Replace

Flags

re.IGNORECASE, re.MULTILINE, re.DOTALL
re.compile(..., flags) combine

Gotchas

Catastrophic backtracking - evil nested quantifiers. Fix: possessive limits, atomic groups, or regex engine timeout.
Over-regex - email/url validation incomplete vs real RFC. Fix: pragmatic pattern + secondary verification.
Recompiling in loop - slow. Fix: module-level compiled patterns.
match vs search confusion - match misses mid-string. Fix: pick correct method.
Locale-dependent \w - unicode surprises. Fix: explicit character classes [A-Za-z0-9_].

Alternatives

Alternative	Use When	Don't Use When
str.split/partition	Fixed delimiter	Variable pattern
parsimonious/lark	Grammar languages	Simple extract
pandas str.extract	Columnar data	Single string

FAQs

Raw string required?

Not required but r"\n" vs "\\n" clarity strongly recommended.

findall groups?

Returns tuples if multiple capturing groups - use finditer for objects.

greedy vs lazy?

*?, +? lazy quantifiers - match minimal span.

verbose regex?

re.compile(r"...", re.VERBOSE) allows comments and whitespace in pattern.

Unicode?

Default unicode str patterns in Python 3; use (?a) for ASCII-only when needed.

Replace count?

sub(pattern, repl, s, count=1) limit replacements.

Lookahead?

(?=...) positive lookahead - assert without consuming.

Testing regex?

Table-driven cases in pytest; document pattern in docstring.

JSON in regex?

Do not parse JSON with regex - use json module.

re vs regex PyPI?

regex module adds features; stdlib sufficient for most services.

json & Serialization - structured parse instead
subprocess - parse command output
Standard Library Overview - map
Strings & f-strings - text basics

Python Standard Library Reference - Complete documentation for built-in modules and functions.
Python HOWTOs (Official) - Practical topic-focused guides.
Real Python - In-depth tutorials, courses, and practical guides.
Automate the Boring Stuff with Python (3rd Edition) - Practical automation (Al Sweigart).
Fluent Python (2nd Edition, O'Reilly) - Same book on O'Reilly.

Stack versions: This page was written for Python 3.14.0 (stable 3.14, maintenance 3.13), FastAPI 0.115+, Django 5.2, Flask 3.1, Pydantic 2, PyTorch 2.6+, pandas 2.2+, Polars 1.x, ruff 0.9+, and uv 0.6+.

Recipe

import re
 
EMAIL = re.compile(r"^[\w.+-]+@[\w-]+\.[\w.-]+$")
 
def valid_email(value: str) -> bool:
    return bool(EMAIL.match(value))

When to reach for this:

Log parsing and extraction
Tokenizing structured but irregular text
Validation with known pattern limits
sed-like substitutions
Splitting on variable whitespace

Working Example

import re
 
LOG_LINE = re.compile(
    r"^(?P<level>INFO|ERROR)\s+(?P<msg>.+)$"
)
 
def parse_log_lines(text: str) -> list[dict[str, str]]:
    rows = []
    for line in text.strip().splitlines():
        m = LOG_LINE.match(line)
        if m:
            rows.append(m.groupdict())
    return rows
 
sample = "INFO started\nERROR disk full\n"
print(parse_log_lines(sample))
 
redacted = re.sub(r"\b\d{4}-\d{4}-\d{4}-\d{4}\b", "[CARD]", "4111-1111-1111-1111")
print(redacted)

What this demonstrates:

Named groups via (?P<name>...)
match anchors start; search scans anywhere
sub replaces sensitive data patterns
Compile once at module level for hot paths

Deep Dive

Common Methods

Method	Purpose
`re.search`	First match anywhere
`re.match`	Start of string
`re.findall`	All non-overlapping
`re.sub`	Replace

Flags

re.IGNORECASE, re.MULTILINE, re.DOTALL
re.compile(..., flags) combine

Gotchas

Catastrophic backtracking - evil nested quantifiers. Fix: possessive limits, atomic groups, or regex engine timeout.
Over-regex - email/url validation incomplete vs real RFC. Fix: pragmatic pattern + secondary verification.
Recompiling in loop - slow. Fix: module-level compiled patterns.
match vs search confusion - match misses mid-string. Fix: pick correct method.
Locale-dependent \w - unicode surprises. Fix: explicit character classes [A-Za-z0-9_].

Alternatives

Alternative	Use When	Don't Use When
str.split/partition	Fixed delimiter	Variable pattern
parsimonious/lark	Grammar languages	Simple extract
pandas str.extract	Columnar data	Single string

FAQs

Raw string required?

Not required but r"\n" vs "\\n" clarity strongly recommended.

findall groups?

Returns tuples if multiple capturing groups - use finditer for objects.

greedy vs lazy?

*?, +? lazy quantifiers - match minimal span.

verbose regex?

re.compile(r"...", re.VERBOSE) allows comments and whitespace in pattern.

Unicode?

Default unicode str patterns in Python 3; use (?a) for ASCII-only when needed.

Replace count?

sub(pattern, repl, s, count=1) limit replacements.

Lookahead?

(?=...) positive lookahead - assert without consuming.

Testing regex?

Table-driven cases in pytest; document pattern in docstring.

JSON in regex?

Do not parse JSON with regex - use json module.

re vs regex PyPI?

regex module adds features; stdlib sufficient for most services.

json & Serialization - structured parse instead
subprocess - parse command output
Standard Library Overview - map
Strings & f-strings - text basics

Python Standard Library Reference - Complete documentation for built-in modules and functions.
Python HOWTOs (Official) - Practical topic-focused guides.
Real Python - In-depth tutorials, courses, and practical guides.
Automate the Boring Stuff with Python (3rd Edition) - Practical automation (Al Sweigart).
Fluent Python (2nd Edition, O'Reilly) - Same book on O'Reilly.

Stack versions: This page was written for Python 3.14.0 (stable 3.14, maintenance 3.13), FastAPI 0.115+, Django 5.2, Flask 3.1, Pydantic 2, PyTorch 2.6+, pandas 2.2+, Polars 1.x, ruff 0.9+, and uv 0.6+.

re - Regular Expressions

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re - Regular Expressions