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Joey Bernard - Python Recipes Handbook: A Problem-Solution Approach

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Book:
Python Recipes Handbook: A Problem-Solution Approach
Author:
Joey Bernard
Publisher:
Apress
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Books / Computer
Year:
2016
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Learn the code to write algorithms, numerical computations, data analysis and much more using the Python language: look up and re-use the recipes for your own Python coding. This book is your handy code cookbook reference. Whether youre a maker, game developer, cloud computing programmer and more, this is a must-have reference for your library.

Python RecipesHandbook gives you the most common and contemporary code snippets, using pandas (Python Data Analysis Library), NumPy, and other numerical Python packages.

What Youll Learn

Code with the pandas (Python Data Analysis Library)
Work with the various Python algorithms useful for todays big data analytics and cloud applications
Use NumPy and other numerical Python packages and code for doing various kinds of analysis
Discover Pythons new popular modules, packages, extensions and templates library

Who This Book Is For

This handy reference is for those with some experience with Python.

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Joey Bernard 2016

Joey Bernard Python Recipes Handbook 10.1007/978-1-4842-0241-8_1

1. Strings and Texts

Joey Bernard 1

(1)

Fredericton, New Brunswick, Canada

Since the earliest days of computing, data used in computations was stored in basic text files. Anyone who has written shell scripts knows all too well that Unix systems and their utilities are built around the assumption that processing text will be much of the work of the program. Python is no different; it provides several programming elements to help with basic text processing tasks.

To begin, lets note how Python stores strings. Strings are immutable lists, so they cannot be changed. Any change to a strings contents requires making copies to new locations in memory. You must always keep this in mind when you try to optimize any text processing portions of your code.

1-1. Concatenating Strings

Problem

You want to build strings up from a number of smaller strings. This process is called concatenation .

Solution

The simplest way to build up a string is to use the + operator. In this case, the strings are put together and the complete new string is returned.

How It Works

Listing shows an example.

>>> new_str = "hello " + "world"

>>> print(new_str)

hello world

Listing 1-1.

Basic Concatenation

This code returns the strin g hello world. If you want a space between the two words, you need to explicitly add a space to one of the strings.

You can also create strings from multiple copies of a smaller string. This is done by using the * operator and essentially multiplying by the number of copies you want. See Listing for an example.

>>> new_str = "Hello" * 3

>>> print(new_str)

HelloHelloHello

Listing 1-2.

Multiplicative Concatenation

This returns the string HelloHelloHello.

These two operators work well when you are working with only strings. If you want to use other data types, you can use the above examples by first passing your data into the function str() . In this way, you can add numbers to your constructed string. An example is shown in Listing .

>>> New_str = "Count = " + str(42)

>>> print(New_str)

Count = 42

Listing 1-3.

Concatenating Non-Strings

1-2. Comparing Strings

Problem

You want to compare strings, checking to see whether two strings have the same value or checking to see whether two names point to the same string object.

Solution

There are two ways of doing comparisons, using is or using == . The first is a way of testing whether two variable names refer to the same object, and the second is a way of comparing the actual value of each variable.

How It Works

To test if the same text is stored in two separate strings, use code like that in Listing .

str1 = "Hello"

str2 = "World"

if str1 == str2:

print("The strings are equal")

else:

print("The strings are not equal")

Listing 1-4.

Comparing Strings

This code returns The strings are not equal. You can use any of the usual comparison operators, like != , < , or >.

Note

When doing a greater than or less than comparison, strings are compared letter by letter. Also, Python treats uppercase letters differently from lowercase letters. Uppercase letters come before lowercase letters, so Z comes before a.

1-3. Searching for a Substring

Problem

You want to search a string object for a substring.

Solution

You can detect whether a substring exists by using the in operator. You can locate the starting index for this substring by using the find() method of the string object.

How It Works

In Python, there is a polymorphic operator named in that you can use to see if one element of data exists within a larger set of data elements. This also works when you need to see if a substring exists within another string object. The usage is given in Listing .

>>> Str1 = 'This is a string'

>>> 'is' in Str1

True

>>> 'me' in Str1

False

Listing 1-5.

Looking for a Substring

As you can see, it returns a Boolean value telling you whether the substring was found or not. If you need to instead find the location of a substring use the find method of the string object. Using the above code, you can look for a substring with

>>> Str1.find('is')

>>> Str1.find('me')

-1

Listing 1-6.

Finding the Index of a Substring

This code returns the index for the first instance of the substring. If you want to find other instances, you can include a start and/or end index value over which to search. So, to find the second instance of is , use the code in Listing .

>>> Str1.find('is', 3)

Listing 1-7.

Finding a Substring Beyond the First One

1-4. Getting a Substring

Problem

You need to get a substring from a string object.

Solution

Once you find the index for a substring, you can get it by copying out a slice of the original string. This is done by using the slice notation to grab the elements from the string.

How It Works

Slices are defined by a start index and an end index. To grab the first word in a string, you can use either of the options shown in Listing .

>>> Str2 = 'One two three'

>>> Str2[0:2]

>>> Str2[:2]

>>> Str2[8:]

three

Listing 1-8.

Slice Notation

Note

Slices apply to all lists in Python. You can also use negative index values to count backwards, rather than forwards.

1-5. Replacing Text Matches

Problem

You need to replace a section of a string with new contents.

Solution

Since Python strings are immutable, replacing a substring involves chopping up the original string and then concatenating everything back together again into a new string.

How It Works

Lets use the above examples of slices and concatenation and put them together, as shown in Listing .

>>> str1 = "Here are a string"

>>> corrected_str1 = str1[:5] + "is" + str1[7:]

>>> print(corrected_str1)

Here is a string

Listing 1-9.

Manual String Replacement

The string object includes a method called replace() that can also be used to replace one or more instances of a substring. You hand in the old substring, the new substring that you want to replace it with, and a count of how many instances to replace. See Listing .

>>> corrected_str1 = str1.replace("are", "is", 1)

Listing 1-10.

Using the replace() Function

If the count is omitted, this method will replace every instance in the string.

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