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
Processing...

Test String

Code Generator

Language

Generated Code

import re regex = re.compile(r"([a-zA-Z,.:;\s]+)") test_str = (" Cross, Kumaraswamy Layout Bangalore-560078, India \n" "Date of Birth: 17 January, 1990 Phone: 9916970905 Email: neelmani.nm@gmail.com \n" " \n" "Seeking Data Scientist position \n" "SYNOPSIS: * \n" " Proficient in programming, statistical analysis, data visualization in R \n" " On-time delivery with utmost quality \n" " Data driven solution for business problems \n" " Remarkable ability to identify, extract, analyze and disseminate statistical analysis \n" " Highly motivated to learn and grow in Data Science \n" " \n" "PROFESSIONAL EXPERIENCE \n" " \n" "ORGANIZATION: Flutura Data \n" "Science and Analytics \n" " \n" "Category: Service provider \n" "Domain: Energy, Online Search \n" "Designation: Data Scientist (Apr 2015 – July 2015) \n" " \n" "Role and Responsibilities \n" " Understanding project requirements \n" " Getting and Cleaning the data from different data sources using R and Python \n" " Exploratory data analysis, Data Mining, Data Modelling \n" " Insight generation and recommendations \n" " \n" "ORGANIZATION: Trianz Holding \n" "Pvt. Ltd. \n" " \n" "Category: Service provider \n" "Domain: e-Governance, Security and \n" "Protection, Maritime Logistics \n" "Designation: Software Engineer (July 2012 – Sep 2014) \n" " \n" "Role and Responsibilities \n" " Understanding and gathering project requirements \n" " Gathering information regarding different data sources \n" " Identification and conversion of data for analytical modeling \n" " Report development on the insights of the data \n" " Migration of data between different data storage location \n" " Insight generation and recommendations \n" " \n" " \n" "EDUCATION \n" " \n" "Dayananda Sagar College of Engineering, \n" "Bangalore \n" "Bachelor of Engineering (B.E), June 2012 \n" "Major: Telecom., 64.5% \n" "CBSE – 2006 (XIIth ) – Guru Govind Singh Public School, Bokaro - 73% \n" "CBSE – 2004 (Xth ) – Jeevan Deep Public School, Nawada - 84% \n" " \n" " \n" " \n" " \n" " \n" " \n" " SKILLS \n" " \n" "Proficient in R, SQL, MS EXCEL, Pentaho and analytical techniques like linear regression, logistic regression, Hypothesis \n" "testing, chi square test, ANOVA etc \n" "Exposer of Python, Qlikview, Tableau \n" " \n" " \n" " CERTIFICATIONS \n" " \n" " Foundation of Data Science, University of Texas (MOOC Programme) \n" " The Data Scientist’s Toolbox, Jhons Hopkins University (Coursera verified certificate) \n" " R Programming, Jhons Hopkins University (Coursera verified certificate) \n" " Getting and Cleaning Data, Jhons Hopkins University (Coursera verified certificate) \n" " Exploratory Data Analysis, Jhons Hopkins University (Coursera verified certificate) \n" " Reproducibility of Research, Jhons Hopkins University (Coursera verified certificate) \n" " Statistical Inference, Jhons Hopkins University (Coursera verified certificate) \n" " Certification in ITIL Foundation \n" " \n" "PROJECTS \n" " \n" "Online Search:- \n" "Reports and dashboard for analyzing the user preference for using online search engine. Reports have to be generated for regular \n" "time interval using R to analyze the trend. \n" "Energy:- \n" "Analyzed churn problem by using data from different data sources and logistic regression. A statistical model for predicting the \n" "future churn. Analyzed the problem and the retail energy domain in US which helped to come up with a statistical model. \n" "Marine Industry:- \n" "Gather data from different data sources involving different information regarding the vessel. On top of which analytical insights \n" "for the vessel performance. \n" " \n" "Security and Protection:- \n" "Fortune 500 company in the securities and protection. Using different data sources centralized reporting system has been \n" "developed \n" " \n" "e-Governance:- \n" "e-Govenance is a data migration project which is meant to migrate the different department data of the government to a common \n" "data model. \n") matches = regex.finditer(test_str) for match_num, match in enumerate(matches, start=1): print(f"Match {match_num} was found at {match.start()}-{match.end()}: {match.group()}") for group_num, group in enumerate(match.groups(), start=1): print(f"Group {group_num} found at {match.start(group_num)}-{match.end(group_num)}: {group}")

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