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"
"
gm

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)\$[a-zA-Z_\\\{\}= +']+\$" test_str = ("We try to quantitatively capture these characteristics by defining a set of indexes, which can be computed using the mosaic image and the corresponding ground truth:\n" "\\begin{itemize}\n" " \\item $\\mu_{A_T}$ and $\\sigma_{A_T}$, the mean and standard deviation of the tiles area $A_T$, respectively;\n" " \\item $\\rho_\\text{filler}$, the ratio between the filler area and the overall mosaic are, computed as $\\rho_\\text{filler}=\\frac{\\sum_{T \\in \\mathcal{T} A_T}}{A}$, being $A$ the area of the mosaic;\n" " \\item \\todo{does it worth?};\n" " \\item \\todo{does it worth?};\n" " \\item $\\mu_{C_T}$, the mean of the tiles \\emph{color dispersion} $C_T$, being $C_T = \\sigma_R+\\sigma_G+\\sigma_B$, where $\\sigma_R$, $\\sigma_G$ and $\\sigma_B$ are the standard deviation of the red, green and blue channel values of the pixels within the tile $T$.\n" "After applying a method to an image, we compare the segmented image (i.e., the result) against the ground truth and assess the performance according to the following three metrics:\n" "\\begin{itemize}\n" " \\item average tile precision $P$\n" " \\item average tile recall $R$\n" " \\item tile count error $C$\n" "\\end{itemize}\n" "Let $T$ be a tile on the ground truth $\\mathcal{T}$ with area $A_T$.\n" "Let $T'$ be the tile in the segmented image which mostly overlaps $T$ and let $A_{T'}$ be the area of $T$; let $A_{T \\cap T'}$ be the overlapping area between $T$ and $T'$.\n" "Let $n$ and $n'$ the number of tiles respectively in the ground truth and in the segmented image.\n" "Metrics are defined as:\n" "\\begin{align}\n" " P &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_{T'}} \\\\\n" " R &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_T} \\\\\n" " C &amp;= \\frac{|n-n'|}{n}\n" "\\end{align}\n" "We try to quantitatively capture these characteristics by defining a set of indexes, which can be computed using the mosaic image and the corresponding ground truth:\n" "\\begin{itemize}\n" " \\item $\\mu_{A_T}$ and $\\sigma_{A_T}$, the mean and standard deviation of the tiles area $A_T$, respectively;\n" " \\item $\\rho_\\text{filler}$, the ratio between the filler area and the overall mosaic are, computed as $\\rho_\\text{filler}=\\frac{\\sum_{T \\in \\mathcal{T} A_T}}{A}$, being $A$ the area of the mosaic;\n" " \\item \\todo{does it worth?};\n" " \\item \\todo{does it worth?};\n" " \\item $\\mu_{C_T}$, the mean of the tiles \\emph{color dispersion} $C_T$, being $C_T = \\sigma_R+\\sigma_G+\\sigma_B$, where $\\sigma_R$, $\\sigma_G$ and $\\sigma_B$ are the standard deviation of the red, green and blue channel values of the pixels within the tile $T$.\n" "After applying a method to an image, we compare the segmented image (i.e., the result) against the ground truth and assess the performance according to the following three metrics:\n" "\\begin{itemize}\n" " \\item average tile precision $P$\n" " \\item average tile recall $R$\n" " \\item tile count error $C$\n" "\\end{itemize}\n" "Let $T$ be a tile on the ground truth $\\mathcal{T}$ with area $A_T$.\n" "Let $T'$ be the tile in the segmented image which mostly overlaps $T$ and let $A_{T'}$ be the area of $T$; let $A_{T \\cap T'}$ be the overlapping area between $T$ and $T'$.\n" "Let $n$ and $n'$ the number of tiles respectively in the ground truth and in the segmented image.\n" "Metrics are defined as:\n" "\\begin{align}\n" " P &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_{T'}} \\\\\n" " R &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_T} \\\\\n" " C &amp;= \\frac{|n-n'|}{n}\n" "\\end{align}") matches = re.finditer(regex, test_str, re.MULTILINE) 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