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Reusing regular expressions with re.compile

From: Python 3 Essential Training

Video: Reusing regular expressions with re.compile

Python's regular expression module has a way that you can pre-compile a regular expression when you're going to be using it over and over again. This is an efficiency and it also allows you access to some of its more advanced functionalities. So let's go ahead and make a working copy of regex.py, call it regex-working.py. I will open that working copy up and you'll see here that we have a tight little loop that's using the same pattern over and over again and it's using it to search for this pattern, in line after line of text.

Reusing regular expressions with re.compile

Python's regular expression module has a way that you can pre-compile a regular expression when you're going to be using it over and over again. This is an efficiency and it also allows you access to some of its more advanced functionalities. So let's go ahead and make a working copy of regex.py, call it regex-working.py. I will open that working copy up and you'll see here that we have a tight little loop that's using the same pattern over and over again and it's using it to search for this pattern, in line after line of text.

So we can get some more efficiency out of this loop by pre-compiling the regular expression. So up here we open the file. We can say pattern = re.compile and then we will come down here and we will cut and paste our pattern and then when we do the search down here, you can say pattern like that. And regular expression module will recognize that that's a pattern object.

That's a precompiled regular expression object. And we will use that, so when we save this and run it. You see we get the same result, but it's more efficient because we are simply compiling that regular expression once rather than otherwise the regular expression module needs to compile the regular expression each time it uses it and this is in a tight little loop and we want that loop to be fast. This also gives us the ability to use some of the regular expression module's other features like for example, you'll notice in the raven text, the very last use of the word nevermore, it's not capitalized at the beginning.

And so we don't have this line, "Shall be lifted - nevermore!" at the end of our results. So we can tell the regular expression model to ignore case, just by putting in re.IGNORECASE. And in fact you can use just an I, like that. I like to use the whole thing because it's more explicit and when I come back to look at it years from now, after maybe I have not used Python for some reason for a while or not used this particular feature, I will remember what it means.

So it's something you just need to type out once and so it's worth the extra effort. So if I save this and run it, now we get that last line as well, because we are telling the regular expression module to ignore case. So a number of efficiencies are available if we are using pre-complied regular expressions. For example, if I want to do a substitution down here, I can say pattern.sub comma line, like that and now I have the efficiency of having a pre-compiled pattern.

I can go ahead and use the regular expression module to do the substitution and I don't necessarily have to get the result out separately and then use the string module substitution. So this allows me to use the regular expression engine for more things without the inefficiencies of having to compile the pattern over and over and over again. So if I save this and run it, now we have that same result and it's easier to read and it flows in with our whole pattern if you're using the regular expression module and we even have that last line with the lowercase nevermore.

It's still working because the pattern was compiled with the IGNORECASE. So that's just some of the efficiencies that you can get from using pre-compiled regular expressions in Python. It's not hard to do. I recommend that you do it that way if you're going to be using your regular expressions in a loop or for any purpose that's more than just once or twice.

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This video is part of

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Python 3 Essential Training

87 video lessons · 43223 viewers

Bill Weinman
Author

 
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  1. 5m 14s
    1. Welcome
      1m 32s
    2. Understanding prerequisites for Python
      2m 4s
    3. Using the exercise files
      1m 38s
  2. 33m 29s
    1. Getting started with "Hello World"
      4m 43s
    2. Selecting code with conditionals
      4m 45s
    3. Repeating code with a loop
      4m 13s
    4. Reusing code with a function
      2m 43s
    5. Creating sequences with generator functions
      2m 46s
    6. Reusing code and data with a class
      4m 39s
    7. Greater reusability with inheritance and polymorphism
      7m 17s
    8. Handling errors with exceptions
      2m 23s
  3. 22m 32s
    1. Installing Python 3 and Eclipse for Windows
      11m 24s
    2. Installing Python 3 and Eclipse for Mac
      11m 8s
  4. 28m 0s
    1. Creating a main script
      3m 27s
    2. Understanding whitespace in Python
      4m 8s
    3. Commenting code
      3m 28s
    4. Assigning values
      3m 37s
    5. Selecting code and values with conditionals
      4m 46s
    6. Creating and using functions
      3m 54s
    7. Creating and using objects
      4m 40s
  5. 31m 23s
    1. Understanding variables and objects in Python
      2m 46s
    2. Distinguishing mutable and immutable objects
      2m 41s
    3. Using numbers
      3m 34s
    4. Using strings
      6m 38s
    5. Aggregating values with lists and tuples
      4m 55s
    6. Creating associative lists with dictionaries
      4m 24s
    7. Finding the type and identity of a variable
      4m 45s
    8. Specifying logical values with True and False
      1m 40s
  6. 9m 42s
    1. Selecting code with if and else conditional statements
      2m 22s
    2. Setting multiple choices with elif
      2m 14s
    3. Understanding other strategies for multiple choices
      2m 38s
    4. Using the conditional expression
      2m 28s
  7. 11m 26s
    1. Creating loops with while
      1m 27s
    2. Iterating with for
      3m 54s
    3. Enumerating iterators
      3m 22s
    4. Controlling loop flow with break, continue, and else
      2m 43s
  8. 23m 28s
    1. Performing simple arithmetic
      2m 14s
    2. Operating on bitwise values
      3m 30s
    3. Comparing values
      3m 32s
    4. Operating on Boolean values
      2m 59s
    5. Operating on parts of a container with the slice operator
      6m 52s
    6. Understanding operator precedence
      4m 21s
  9. 11m 34s
    1. Using the re module
      1m 4s
    2. Searching with regular expressions
      3m 12s
    3. Replacing with regular expressions
      3m 29s
    4. Reusing regular expressions with re.compile
      3m 49s
  10. 9m 10s
    1. Learning how exceptions work
      1m 18s
    2. Handling exceptions
      4m 15s
    3. Raising exceptions
      3m 37s
  11. 23m 1s
    1. Defining functions
      6m 23s
    2. Using lists of arguments
      2m 26s
    3. Using named function arguments
      4m 32s
    4. Returning values from functions
      1m 55s
    5. Creating a sequence with a generator function
      7m 45s
  12. 47m 29s
    1. Understanding classes and objects
      5m 12s
    2. Using methods
      6m 12s
    3. Using object data
      10m 4s
    4. Understanding inheritance
      5m 11s
    5. Applying polymorphism to classes
      7m 13s
    6. Using generators
      9m 48s
    7. Using decorators
      3m 49s
  13. 18m 54s
    1. Understanding strings as objects
      3m 25s
    2. Working with common string methods
      5m 24s
    3. Formatting strings with str.format
      5m 31s
    4. Splitting and joining strings
      2m 49s
    5. Finding and using standard string methods
      1m 45s
  14. 25m 27s
    1. Creating sequences with tuples and lists
      4m 6s
    2. Operating on sequences with built-in methods
      5m 50s
    3. Organizing data with dictionaries
      4m 56s
    4. Operating on character data with bytes and byte arrays
      10m 35s
  15. 11m 46s
    1. Opening files
      2m 4s
    2. Reading and writing text files
      4m 33s
    3. Reading and writing binary files
      5m 9s
  16. 21m 27s
    1. Creating a database with SQLite 3
      6m 56s
    2. Creating, retrieving, updating, and deleting records
      7m 31s
    3. Creating a database object
      7m 0s
  17. 18m 27s
    1. Using standard library modules
      8m 0s
    2. Finding third-party modules
      5m 47s
    3. Creating a module
      4m 40s
  18. 23m 11s
    1. Dealing with syntax errors
      8m 19s
    2. Dealing with runtime errors
      4m 0s
    3. Dealing with logical errors
      4m 22s
    4. Using unit tests
      6m 30s
  19. 19m 56s
    1. Normalizing a database interface
      6m 39s
    2. Deconstructing a database application
      8m 9s
    3. Displaying random entries from a database
      5m 8s
  20. 29s
    1. Goodbye
      29s

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