Paul Gerrard [Paul Gerrard] - Lean Python: Learn Just Enough Python to Build Useful Tools
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- Book:Lean Python: Learn Just Enough Python to Build Useful Tools
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Learn only the essential aspects of Python without cluttering up your mind with features you may never use. This compact book is not a best way to write code type of book; rather, the author goes over his most-used functions, which are all you need to know as a beginner and some way beyond.
Lean Python takes 58 Python methods and functions and whittles them down to 15: as author Paul Gerrard says, I havent found a need for the rest.
What Youll Learn
- Discover lean Python and how to learn just enough to build useful tools
- Use Python objects, program structure, I/O, modules and more
- Handle errors and exceptions
- Test your code
- Access the Web; do searching; and persist data
Who This Book Is For
This book is aimed at three categories of reader: The experienced programmer if you already know a programming language, this book gives you a shortcut to understanding the Python language and some of its design philosophy.
You work in IT and need a programming primer you might be a tester who needs to have more informed technical discussions with programmers. Working through the examples will help you to appreciate the challenge of good programming.
First-timer you want a first book on programming that you can assimilate quickly to help you decide whether programming is for you.
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Paul Gerrard 2016
Paul Gerrard , Lean Python , 10.1007/978-1-4842-2385-7_10
Paul Gerrard 1
(1) Maidenhead, Berkshire, UK
Searching for text in strings is a common activity and the built-in string function find() is all you need for simple searches. It returns the position (offset) of the find or if not found.
>>> txt="The quick brown fox jumps over the lazy dog">>> txt.find('jump')20>>> txt.find('z')37>>> txt.find('green')-1There are often circumstances when the search is not so simple. Rather than a simple string, we need to look for a pattern and extract the information we really want from the matched text. Suppose for example, we wanted to extract all the URLs in links on a web page. Here are some example lines of HTML text from a real web page.
123PyPI TutorialLine 1 refers to an RSS feed.Line 2 has an href attribute, but it refers to a Cascading Style Sheets (CSS) file, not a link.Line 3 is a true link but the URL is relative; it doesnt contain the web site part of the URL.Line 4 is a link to an external site.
4There is quite a lot going on in the text here.
How can we hope to use some software to find the links that we care about? Well, this is where regular expressions come in.
Introducing Regular ExpressionsRegular expressions are a way of using pattern matching to find the text we are interested in. Not only are patterns matched, but the re module can extract the data we really want out of the matched text.
Many more examples could be written, and in fact there are whole books written about regular expressions (e.g., [16], [17]). There are many web sites, but the most useful is probably http://www.regular-expressions.info .
A regex is a string containing both text and special characters that define a pattern that the re functions can use for matching.
The simplest regex is a text string that you want to find in another string, as shown in Table .
Regex | String Matched |
|---|---|
jumps | jumps |
The Queen | The Queen |
Pqr123 | Pqr123 |
There are special characters, listed in Table , that influence how the match is to be performed.
Symbols | Description | Example |
|---|---|---|
literal | Match a literal string | Jumps |
re1|re2 | Match string re1 OR re2 | Yes|No |
. | Match any single character (except \n) | J.mps |
^ | Match start of string | ^The |
$ | Match end of string | well$ |
* | Match 0 or more occurrences of preceding regex | [A-Z]* |
+ | Match 1 or more occurrences of preceding regex | [A-Z]+ |
? | Match 0 or 1 occurrences of preceding regex | [a-z0-9]? |
{m,n} | Match between m and n occurrences of the preceding regex (n optional) | [0-9]{2,4} |
[...] | Match any character from character class | [aeiou] |
[x-y] | Match any character from range | [0-9],[A-Za-z] |
[^...] | Do not match any character from character class | [^aeiou] |
There are a number of special characters, listed in Table , that can be matched, too.
Special Character | Description | Example |
|---|---|---|
\d | Match any decimal digit | BBC\d |
\w | Match any alphanumeric character | Radio\w+ |
\s | Match any whitespace character | The\sBBC |
Table gives some examples of regular expressions and the strings that they would match.
Regex | String(s) Matched |
|---|---|
smith|jones | smith, jones |
UNE..O | Any two characters between UN and O; e.g., UNESCO, UNEzyO, UNE99O |
^The | Any string that starts with The |
end$ | Any string that ends with end |
c[aiou]t | cat, cit, cot, cut |
[dg][io][gp] | dig, dip, dog, dop, gig, gip, gog, gop |
[a-d][e-i] | 2 chars a/b/c/d followed by e/f/g/h/i |
NoteRegexes can use any combination of text and special characters, so they can look extremely complicated sometimes. Start simple.
Finding substrings in text is fine, but often we want to find patterns in text, rather than literal strings. Suppose we wanted to extract numeric values, phone numbers, or web site URLs from text. How do we do that? This is where the real power of regular expressions lies.
Here is an example regex:
\s[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,4}[\s]Can you guess what it might find? It is a regex for finding e-mail addresses in text. At first glance, this looks pretty daunting, so lets break it down into its constituent parts. First, the regex refers only to uppercase letters (to reduce the length of the regex), so this assumes that the string to be searched has already been uppercased.
There are six elements to this regex:
1 \s 2 [A-Z0-9._%+-]+ 3 @ 4 [A-Z0-9.-]+ 5 \. 6 [A-Z]{2,4} 7 [\s\.] | Leading whitespace One or more characters @ character A-Z , 0-9 . Dot character 2 to 4 text characters Whitespace or full stop |
Obviously, you need to know the rules for the pattern you search for and there are specific rules for the construction of e-mail addresses.
Here is the file remail.py .
1 import re # The RegEx library2 #3 # our regular expression (to find e-mails)4 # and text to search5 #6 regex = '\s[A-Z0-9._%+-]+@[A-Z0-9.-]+\.[A-Z]{2,4}[\s]'7 text="""This is some text with x@y.z embedded e-mails8 that we'll use as@example.com9 some lines have no email addresses10 others@have.two valid email@addresses.comFont size:
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