Regular Expressions 101

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An explanation of your regex will be automatically generated as you type.
Detailed match information will be displayed here automatically.
  • All Tokens
  • Common Tokens
  • General Tokens
  • Anchors
  • Meta Sequences
  • Quantifiers
  • Group Constructs
  • Character Classes
  • Flags/Modifiers
  • Substitution
  • A single character of: a, b or c
    [abc]
  • A character except: a, b or c
    [^abc]
  • A character in the range: a-z
    [a-z]
  • A character not in the range: a-z
    [^a-z]
  • A character in the range: a-z or A-Z
    [a-zA-Z]
  • Any single character
    .
  • Alternate - match either a or b
    a|b
  • Any whitespace character
    \s
  • Any non-whitespace character
    \S
  • Any digit
    \d
  • Any non-digit
    \D
  • Any word character
    \w
  • Any non-word character
    \W
  • Non-capturing group
    (?:...)
  • Capturing group
    (...)
  • Zero or one of a
    a?
  • Zero or more of a
    a*
  • One or more of a
    a+
  • Exactly 3 of a
    a{3}
  • 3 or more of a
    a{3,}
  • Between 3 and 6 of a
    a{3,6}
  • Start of string
    ^
  • End of string
    $
  • A word boundary
    \b
  • Non-word boundary
    \B

Regular Expression
No Match

r"
"
g

Test String

Code Generator

Generated Code

# coding=utf8 # the above tag defines encoding for this document and is for Python 2.x compatibility import re regex = r"(?<=[;\(])([\w\s]+(et al.)?,\s+\d{4})(?=[;\)])" test_str = "What appears to us an effortless task, the opening of our eyes, engages an extensive and anatomical complex network of brain areas. The first stages of visual processing differentiate bright luminance increments from dark decrements by separate ON– and OFF–channels in the retina and dorsal lateral geniculate nucleus (dLGN) (Schiller, 1992). Most ON– and OFF–cell receptive fields (RFs) are selective for stimulus size and local contrast via antagonistic interactions between center and surround (Figure 1A) (Kuffler, 1953; Barlow et al., 1957; Allman et al., 1985). These interactions also impact the transient rebound responses when a non-preferred stimulus is removed from the RF (Singer, 1970; Jung, 1973); and they are reflected in our perceptual experience, revealing close similarities between the tuning properties of neural and perceptual RFs (Oehler, 1985; Spillmann and Werner, 1990)." matches = re.finditer(regex, test_str) for matchNum, match in enumerate(matches, start=1): print ("Match {matchNum} was found at {start}-{end}: {match}".format(matchNum = matchNum, start = match.start(), end = match.end(), match = match.group())) for groupNum in range(0, len(match.groups())): groupNum = groupNum + 1 print ("Group {groupNum} found at {start}-{end}: {group}".format(groupNum = groupNum, start = match.start(groupNum), end = match.end(groupNum), group = match.group(groupNum))) # Note: for Python 2.7 compatibility, use ur"" to prefix the regex and u"" to prefix the test string and substitution.

Please keep in mind that these code samples are automatically generated and are not guaranteed to work. If you find any syntax errors, feel free to submit a bug report. For a full regex reference for Python, please visit: https://docs.python.org/3/library/re.html