regex¶

between¶

• Here's a regular expression to capture
• anything after "000," and anything before ",111"
• in the string "000, this is before and this i want to capture and this is after ,111"
• (?<=000,).*?(?=,111)

jargon detector¶

To match abbreviations that are often used as jargon, you could use a regular expression that looks for sequences of uppercase letters with optional periods in between:

[A-Z](?:\.[A-Z])+\.?

Explanation:

• [A-Z] matches any uppercase letter
• (?:.[A-Z])+ is a non-capturing group that matches a period followed by an uppercase letter, one or more times
• . matches a period
• .? matches zero or one period at the end, to account for cases where the abbreviation is at the end of a sentence and followed by a period.
• This regular expression should match common abbreviations such as "CEO", "U.S.", "DNA", etc. However, it may miss some less common or specialized abbreviations, and may also capture some non-jargon words that happen to be written in all uppercase letters.

timestamps¶

Here's a regular expression that matches timestamps in common formats such as "2022-02-04 14:15:16", "2022/02/04 14:15:16", "2022-02-04T14:15:16Z", etc.:

\d{4}([-/])\d{2}\1\d{2}[T ]\d{2}:\d{2}:\d{2}(Z|[-+]\d{2}:\d{2})?

Explanation:

• \d{4} matches four digits for the year
• ([-/])\d{2}\1\d{2} matches a separator (either "-" or "/") followed by two digits for the month, another separator that matches the first separator, and two digits for the day
• [T ] matches either a "T" or a space character, which separates the date from the time
• \d{2}:\d{2}:\d{2} matches two digits for the hour, minute, and second respectively, separated by colons
• (Z|[-+]\d{2}:\d{2})? optionally matches either the letter "Z" to indicate a UTC timezone, or a plus or minus sign followed by two digits for the offset from UTC, separated by a colon.

Note that this regular expression assumes that the timestamp is in the correct format, but does not validate whether the date and time are valid or make logical sense.

verbs¶

Here's a simple regular expression that captures verbs:

\w+ing\b|\b\w+ed\b

Explanation:

• \w+ing\b matches any word character one or more times, followed by "ing" at the end of a word boundary (e.g. "running", "singing", "dancing").
• \b\w+ed matches any word character one or more times, preceded by a word boundary and followed by "ed" (e.g. "walked", "jumped", "played").

This regular expression may not capture all verbs, particularly irregular verbs that do not follow the standard "-ed" or "-ing" patterns. However, it should capture many common verbs in their past tense or present participle forms.

csv¶

Assuming the CSV file has a header row with comma-separated field names, here's a regular expression that matches the header row:

^([^\n,]+)(,[^\n,]+)*$

Explanation:

• ^ matches the start of the string (i.e., the beginning of the header row)
• ([^\n,]+) matches one or more characters that are not commas or line breaks, capturing the field name in a group
• (,[^\n,]+)* matches zero or more comma-separated field names, where each field name consists of a comma followed by one or more non-comma and non-line break characters
• $ matches the end of the string (i.e., the end of the header row)

You can use this regular expression to extract the field names from the header row of a CSV file. Note that this regular expression assumes that the header row is a single line and that there are no commas or line breaks within the field names. If your CSV file has different formatting or field name rules, you may need to modify the regular expression accordingly.

py csv¶

You can use the built-in csv module in Python to parse a CSV file. Here's an example code snippet that reads a CSV file named example.csv and prints its contents:

import csv

with open('example.csv', newline='') as csvfile:
    reader = csv.reader(csvfile, delimiter=',', quotechar='"')
    for row in reader:
        print(', '.join(row))

This code opens the file example.csv using a with statement, which automatically closes the file after reading. It then creates a csv.reader object, which reads the CSV file and separates the fields using commas. The quotechar argument specifies that fields within double quotes should be treated as a single field, even if they contain commas. Finally, the code iterates over each row of the CSV file and prints its contents as a comma-separated string.

You can modify this code to perform other operations on the CSV data, such as storing it in a database or performing calculations on the fields. The csv module in Python provides a flexible and easy-to-use interface for working with CSV files.

js csv¶

To parse a CSV file in JavaScript, you can use the csv-parser package, which is available through npm. Here's an example code snippet that reads a CSV file named example.csv and logs its contents to the console:

const csv = require('csv-parser')
const fs = require('fs')

fs.createReadStream('example.csv')
  .pipe(csv())
  .on('data', (row) => {
    console.log(row)
  })
  .on('end', () => {
    console.log('CSV file successfully processed.')
  })

This code first imports the csv-parser package and the built-in fs module in Node.js. It then creates a readable stream from the example.csv file using fs.createReadStream. The pipe method is used to pass the stream through the csv() function, which parses the CSV data and returns an object for each row.

The on('data', ...) method is used to handle each row of the CSV file, logging it to the console in this case. Finally, the on('end', ...) method is used to indicate that the CSV file has been fully processed.

You can modify this code to perform other operations on the CSV data, such as storing it in a database or performing calculations on the fields. The csv-parser package in JavaScript provides a flexible and easy-to-use interface for working withgg CSV files.

grep logs¶

sql¶

log levels¶

\b(DEBUG|INFO|WARN|ERROR)\b

If you want to capture the log level along with the message that follows it, you can modify the regular expression I provided earlier by adding a capture group for the message:

\b(DEBUG|INFO|WARN|ERROR)\b\s*(.*)

Explanation:

• \b(DEBUG|INFO|WARN|ERROR)\b matches one of the four log level options inside a capture group, with word boundaries to ensure it's not part of a longer word
• \s* matches zero or more whitespace characters
• (.*) matches the message that follows the log level, which can contain any characters except for line breaks, and captures it in a separate group

You can use this regular expression to find log levels along with their corresponding messages in log files or other text that follows this format. Note that this regular expression assumes that the log levels are in uppercase letters. If log levels are in lowercase or mixed case, you can modify the regular expression accordingly.

json¶

you can write a regular expression that matches basic JSON syntax, but this will not be able to handle more complex cases like nested objects, arrays, or escaped characters:

\{\s*("[^"]*"\s*:\s*(?:"[^"]*"|\d+)\s*,?\s*)*\}

Explanation:

• { matches a left curly brace
• \s* matches zero or more whitespace characters
• ("[^{"]"\s:\s*(?:"[}"]"|\d+)\s,?\s) is a group that matches zero or more key-value pairs separated by commas. Each key-value pair consists of a string (in quotes) followed by a colon, followed by either another string in quotes or a number.
• "[^"]*" matches a string in quotes
• \s:\s matches a colon with optional whitespace before and after
• (?:"[^"]*"|\d+) matches either a string in quotes or a number
• \s,?\s matches optional whitespace followed by an optional comma, followed by optional whitespace
• } matches a right curly brace.

This regular expression should match simple JSON structures like {"key": "value", "number": 123}, but it will not be able to handle more complex JSON structures with nested objects or arrays, or escaped characters inside strings.

winston format¶

^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}(\.\d{3})?)\]\s*(\w+)\s*:\s*(.*)$

Explanation:

• ^ matches the start of the line
• [(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}(.\d{3})?)] matches a timestamp in square brackets. The timestamp can be in the format "YYYY-MM-DD HH:mm:ss" with an optional fraction of a second.
• \s* matches zero or more whitespace characters
• (\w+) matches one or more word characters, which represents the log level (e.g. "info", "warn", "error")
• \s:\s matches a colon surrounded by optional whitespace characters
• (.*) matches the JSON message itself, which can contain any characters except for line breaks
• $ matches the end of the line

This regular expression captures the timestamp, log level, and JSON message as separate capture groups, which can then be parsed further. Note that this regular expression assumes that the w logs are in a consistent format and do not contain additional information or non-JSON messages.

const logRegex = /^\[(\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}(\.\d{3})?)\]\s*(\w+)\s*:\s*(.*)$/;

function parseWinstonLog(logString) {
  const match = logString.match(logRegex);
  if (!match) {
    return null; // not a valid log
  }
  const timestamp = match[1];
  const logLevel = match[3];
  const message = match[4];
  let data;
  try {
    data = JSON.parse(message);
  } catch (e) {
    data = message;
  }
  return {
    timestamp,
    logLevel,
    data
  };
}

// Example usage
const logString = '[2023-02-04 10:00:00.123] info: {"message": "Hello, world!"}';
const parsedLog = parseWinstonLog(logString);
console.log(parsedLog);
// Output: { timestamp: '2023-02-04 10:00:00.123', logLevel: 'info', data: { message: 'Hello, world!' } }