Tools for generating regular expressions

RegexGenerator

In looking for libraries that work similarly to the other tools discussed in this article, my research turned up limited results. For Python, I found RegexGenerator [16] and its associated regex-generator-lib [17].

Listing 1 shows a short script for RegexGenerator, which determines a regular expression for the string 415-5553-7676. You can then save and run the regular expression as rg.py (Listing 2). The generated regex shown in Listing 2 does the trick: a pattern consisting of three digits, followed by a minus sign, four digits, another minus sign, and another four digits.

Listing 1

RegexGenerator Script

from RegexGenerator import RegexGenerator
myRegexGenerator = RegexGenerator("415-5553-7676")
print(myRegexGenerator.get_regex())

Listing 2

rg.py

$ python3 rg.py
\d{3}[-]\d{4}[-]\d{4}

However, this generated regex lacks precision. Not only does it match the above string, but it also matches other strings, such as 123-4567-8901 or foo-123-5553-7676-bar. According to this regular expression, the digits can be arbitrary and the pattern can include other characters because the regex does not use delimiters such as \b for word boundary, ^ for beginning of line, and $ for end of line.

Instead, A regex of ^415\-5553\-7676$ would be more precise and easier to read, resulting in the three digits 415 followed by a minus sign, three times the number 5 followed by a 3, another minus sign, and then two times the sequence of digits 76 including characters for the beginning of the line (^) and the end of the line ($).

rex

If you use the rex tool from Python's Test-Driven Data Analysis (tdda) package [18], there is a very neat, practical use case. The example shown in Listing 3 determines the regular expression for naming image files. All of the file names start with the three letters DSC, followed by five numbers, a period, and the three letters .JPG.

Listing 3

rex from tdda

$ ls images/*.JPG
DSC06743.JPG
DSC06745.JPG
DSC06751.JPG
DSC06754.JPG
$ ls images/*.JPG | python3 tdda/rexpy/rexpy.py
^DSC\d{5}\.JPG$

The regular expression is correct, as far as it goes; it also includes two additional delimiters, ^ for beginning of line and $ for end of line. The regex excludes false positives as long as the pattern consists of the three uppercase letters DSC followed by any five sections and the strings .JPG. However, a more precise regular expression would be DSC067((4[35])|(5[14]))\.JPG.

Again, the results returned by rex from the tdda library end up in the middle of the pack in terms of precision. While rex successfully matches the DSC and JPG portions of the pattern, it can produce a false positive for the digits in the sequence.

RegExTractor

To demonstrate the capabilities of RegExTractor [19], another Python regex extractor, I used random German license plates. Listing 4 first outputs the license plates followed by the regular expression that matches all license plates.

Listing 4

Running RegExTractor

$ python main.py
Kennzeichen:
A-BC 1234
CB-LN 5246E
FR-CG 1554
TUT-R 712
AA-LN 5E
The regex for this:
[A-Z][A-Z]{0,2}\-[A-Z][A-Z]?\ [0-9][0-9A-Z]{1,4}

However, the regular expression that RegExTractor outputs is not correct. In particular, the last partial pattern of [0-9][0-9A-Z]{1,4} allows any digit followed by a combination of one to four capital letters and digits.

A more accurate solution would be the subexpression [0-9]{1,4}E+ for one to four digits, followed only by the capital letter E for electric cars. In testing, this problem occurred repeatedly. Consequently, I cannot recommend RegExTractor.

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