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

const regex = new RegExp('(?<=\\W)\\$[a-zA-Z_\\\\\\{\\}= +\\']+\\$', 'gm') const 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: \\begin{itemize} \\item \$\\mu_{A_T}\$ and \$\\sigma_{A_T}\$, the mean and standard deviation of the tiles area \$A_T\$, respectively; \\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; \\item \\todo{does it worth?}; \\item \\todo{does it worth?}; \\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\$. 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: \\begin{itemize} \\item average tile precision \$P\$ \\item average tile recall \$R\$ \\item tile count error \$C\$ \\end{itemize} Let \$T\$ be a tile on the ground truth \$\\mathcal{T}\$ with area \$A_T\$. 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'\$. Let \$n\$ and \$n'\$ the number of tiles respectively in the ground truth and in the segmented image. Metrics are defined as: \\begin{align} P &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_{T'}} \\\\ R &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_T} \\\\ C &amp;= \\frac{|n-n'|}{n} \\end{align} 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: \\begin{itemize} \\item \$\\mu_{A_T}\$ and \$\\sigma_{A_T}\$, the mean and standard deviation of the tiles area \$A_T\$, respectively; \\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; \\item \\todo{does it worth?}; \\item \\todo{does it worth?}; \\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\$. 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: \\begin{itemize} \\item average tile precision \$P\$ \\item average tile recall \$R\$ \\item tile count error \$C\$ \\end{itemize} Let \$T\$ be a tile on the ground truth \$\\mathcal{T}\$ with area \$A_T\$. 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'\$. Let \$n\$ and \$n'\$ the number of tiles respectively in the ground truth and in the segmented image. Metrics are defined as: \\begin{align} P &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_{T'}} \\\\ R &amp;= \\frac{1}{n} \\sum_{T \\in \\mathcal{T}} \\frac{A_{T \\cap T'}}{A_T} \\\\ C &amp;= \\frac{|n-n'|}{n} \\end{align}`; // Reset `lastIndex` if this regex is defined globally // regex.lastIndex = 0; let m; while ((m = regex.exec(str)) !== null) { // This is necessary to avoid infinite loops with zero-width matches if (m.index === regex.lastIndex) { regex.lastIndex++; } // The result can be accessed through the `m`-variable. m.forEach((match, groupIndex) => { console.log(`Found match, group ${groupIndex}: ${match}`); }); }

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 JavaScript, please visit: https://developer.mozilla.org/en/docs/Web/JavaScript/Guide/Regular_Expressions