Table of Contents

Strings
1. String Formatting
2. String Methods
2.1. find
2.2. join
2.3. lower
2.4. replace
2.5. split
2.6. strip
3. Introduction to the standard library
4. I/O: Reading and Writing Files
4.1. Opening Files
4.2. Reading and Writing files
5. Dictionaries
5.1. dict()
5.2. Dictionary Methods

Strings


Strings were briefly introduced previously in the introduction document. In this section strings will be presented in greater detail. All the standard operations that can be performed on sequences such as indexing, slicing, multiplication, length minimum and maximum can be performed on string variables as well. One thing to be noted is that strings are immutable, which means that string variables are unchangeable. Hence, all item and slice assignments on strings are illegal. Let us look at a few example.

>>> name = 'PythonFreak'
>>> print name[3]
h
>>> print name[-1]
k
>>> print name[6:]
Freak
>>> name[6:0] = 'Maniac'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'str' object does not support item assignment

This is quite expected, since string objects are immutable as already mentioned. The error message is clear in mentioning that 'str' object does not support item assignment.

1.String Formatting

String formatting can be performed using the string formatting operator represented as the percent (%) sign. The string placed before the % sign is formatted with the value placed to the right of it. Let us look at a simple example.

>>> format = 'Hello %s, from PythonFreak'
>>> str1 = 'world!'
>>> print format % str1
Hello world!, from PythonFreak

The %s parts of the format string are called the coversion specifiers. The coversion specifiers mark the places where the formatting has to be performed in a string. In the example the %s is replaced by the value of str1. More than one value can also be formatted at a time by specifying the values to be formatted using tuples and dictionaries (explained in later sections). Let us look at an example.

>>> format = 'Hello %s, from %s'
>>> values = ('world!', 'PythonFreak')
>>> print format % values
Hello world!, from PythonFreak

In this example it can be observed that the format string contains two conversion specifiers and they are formatted using the tuple of values as shown.

The s in %s specifies that the value to be replaced is of type string. Values of other types can be specified as well such as integers and floats. Integers are specified as %d and floats as %f. The precision with which the integer or the float values are to be represented can also be specified using a . (dot) followed by the precision value.

2.String Methods

Similar to list methods, strings also have a rich set of methods to perform various operations on strings. Some of the most important and popular ones are presented in this section.

2.1.find

The find method is used to search for a substring within a given string. It returns the left most index of the first occurence of the substring. If the substring is not found in the string then it returns -1. Let us look at a few examples.

>>> longstring = 'Hello world!, from PythonFreak'
>>> longstring.find('Python')
19
>>> longstring.find('Perl')
-1

2.2.join

The join method is used to join the elements of a sequence. The sequence elements that are to be join ed should all be strings. Let us look at a few examples.

>>> seq = ['With', 'great', 'power', 'comes', 'great', 'responsibility']
>>> sep = ' '
>>> sep.join(seq)
'With great power comes great responsibility'
>>> sep = ',!'
>>> sep.join(seq)
'With,!great,!power,!comes,!great,!responsibility'

Try this yourself

>>> seq = [12,34,56,78]
>>> sep.join(seq)

2.3.lower

The lower method, as the name indicates, converts the entire text of a string to lower case. It is specially useful in cases where the programmers deal with case insensitive data. Let us look at a few examples.

>>> sometext = 'Hello world!, from PythonFreak'
>>> sometext.lower()
'hello world!, from pythonfreak'

2.4.replace

The replace method replaces a substring with another substring within a given string and returns the new string. Let us look at an example.

>>> sometext = 'Concise, precise and criticise is some of the words that end with ise'
>>> sometext.replace('is', 'are')
'Concaree, precaree and criticaree are some of the words that end with aree'

Observe here that all the occurences of the substring is have been replaced, even the is in concise, precise and criticise have been replaced.

2.5.split

The split is one of the very important string methods. split is the opposite of the join method. It is used to split a string based on the argument passed as the delimiter. It returns a list of strings. By default when no argument is passed it splits with space (' ') as the delimiter. Let us look at an example.

>>> grocerylist = 'butter, cucumber, beer(a grocery item??), wheatbread'
>>> grocerylist.split(',')
['butter', ' cucumber', ' beer(a grocery item??)', ' wheatbread']
>>> grocerylist.split()
['butter,', 'cucumber,', 'beer(a', 'grocery', 'item??),', 'wheatbread']

Observe here that in the second case when the delimiter argument was not set split was done with space as the delimiter.

2.6.strip

The strip method is used to remove or strip off any whitespaces that exist to the left and right of a string, but not the whitespaces within a string. Let us look at an example.

>>> spacedtext = "               Where's the text??                 "
>>> spacedtext.strip()
"Where's the text??"

Observe that the whitespaces between the words have not been removed.

Note: Very important thing to note is that all the methods shown above do not
      transform the source string. The source string still remains the same.
      Remember that **strings are immutable**.

3.Introduction to the standard library

Python is often referred to as a "Batteries included!" language, mainly because of the Python Standard Library. The Python Standard Library provides an extensive set of features some of which are available directly for use while some require to import a few modules. The Standard Library provides various built-in functions like:

  • abs()

  • dict()

  • enumerate()

The built-in constants like True and False are provided by the Standard Library. More information about the Python Standard Library is available


http://docs.python.org/library/

4.I/O: Reading and Writing Files

Files are very important aspects when it comes to computing and programming. Up until now the focus has been on small programs that interacted with users through input() and raw_input(). Generally, for computational purposes it becomes necessary to handle files, which are usually large in size as well. This section focuses on basics of file handling.

4.1.Opening Files

Files can be opened using the open() method. open() accepts 3 arguments out of which 2 are optional. Let us look at the syntax of open():

f = open( filename, mode, buffering)

The filename is a compulsory argument while the mode and buffering are optional. The filename should be a string and it should be the complete path to the file to be opened (The path can be absolute or relative). Let us look at an example.

>>> f = open ('basic_python/interim_assessment.rst')

The mode argument specifies the mode in which the file has to be opened. The following are the valid mode arguments:

r - Read mode w - Write mode a - Append mode b - Binary mode + - Read/Write mode

The read mode opens the file as a read-only document. The write mode opens the file in the Write only mode. In the write mode, if the file existed prior to the opening, the previous contents of the file are erased. The append mode opens the file in the write mode but the previous contents of the file are not erased and the current data is appended onto the file. The binary and the read/write modes are special in the sense that they are added onto other modes. The read/write mode opens the file in the reading and writing mode combined. The binary mode can be used to open a files that do not contain text. Binary files such as images should be opened in the binary mode. Let us look at a few examples.

>>> f = open ('basic_python/interim_assessment.rst', 'r')
>>> f = open ('armstrong.py', 'r+')

The third argument to the open() method is the buffering argument. This takes a boolean value, True or 1 indicates that buffering has to be enabled on the file, that is the file is loaded on to the main memory and the changes made to the file are not immediately written to the disk. If the buffering argument is 0 or False the changes are directly written on to the disk immediately.

4.2.Reading and Writing files

4.2.1.write()

write(), evidently, is used to write data onto a file. It takes the data to be written as the argument. The data can be a string, an integer, a float or any other datatype. In order to be able to write data onto a file, the file has to be opened in one of w, a or + modes.

4.2.2.read()

read() is used to read data from a file. It takes the number of bytes of data to be read as the argument. If nothing is specified by default it reads the entire contents from the current position to the end of file.

Let us look at a few examples:

>>> f = open ('randomtextfile', 'w')
>>> f.write('Hello all, this is PythonFreak. This is a random text file.')
>>> f = open ('../randomtextfile', 'r')
>>> f = open ('../randomtextfile', 'r')
>>> f.read(5)
'Hello'
>>> f.read()
' all, this is PythonFreak. This is a random text file.'
>>> f.close()

4.2.3.readline()

readline() is used to read a file line by line. readline() reads a line of a file at a time. When an argument is passed to readline() it reads that many bytes from the current line.

One other method to read a file line by line is using the read() and the for construct. Let us look at this block of code as an example.

>>> f = open('../randomtextfile', 'r')
>>> for line in f:
...     print line
...
Hello all!

This is PythonFreak on the second line.

This is a random text file on line 3

4.2.4.close()

One must always close all the files that have been opened. Although, files opened will be closed automatically when the program ends. When files opened in read mode are not closed it might lead to uselessly locked sometimes. In case of files opened in the write mode it is more important to close the files. This is because, Python maybe using the file in the buffering mode and when the file is not closed the buffer maybe lost completely and the changes made to the file are lost forever.

5.Dictionaries

A dictionary in general, are designed to be able to look up meanings of words. Similarly, the Python dictionaries are also designed to look up for a specific key and retrieve the corresponding value. Dictionaries are data structures that provide key-value mappings. Dictionaries are similar to lists except that instead of the values having integer indexes, dictionaries have keys or strings as indexes. Let us look at an example of how to define dictionaries.

>>> dct = { 'Sachin': 'Tendulkar', 'Rahul': 'Dravid', 'Anil': 'Kumble'}

The dictionary consists of pairs of strings, which are called keys and their corresponding values separated by : and each of these key-value pairs are comma(',') separated and the entire structure wrapped in a pair curly braces {}.

Note: The data inside a dictionary is not ordered. The order in which you enter
the key-value pairs is not the order in which they are stored in the dictionary.
Python has an internal storage mechanism for that which is out of the purview
of this document.

5.1.dict()

The dict() function is used to create dictionaries from other mappings or other dictionaries. Let us look at an example.

>>> diction = dict(mat = 133, avg = 52.53)

String Formatting with Dictionaries:

String formatting was discussed in the previous section and it was mentioned that dictionaries can also be used for formatting more than one value. This section focuses on the formatting of strings using dictionaries. String formatting using dictionaries is more appealing than doing the same with tuples. Here the keyword can be used as a place holder and the value corresponding to it is replaced in the formatted string. Let us look at an example.

>>> player = { 'Name':'Rahul Dravid', 'Matches':133, 'Avg':52.53, '100s':26 }
>>> strng = '%(Name)s has played %(Matches)d with an average of %(Avg).2f and has %(100s)d hundreds to his name.'
>>> print strng % player
Rahul Dravid has played 133 with an average of 52.53 and has 26 hundreds to his name.

5.2.Dictionary Methods

5.2.1.clear()

The clear() method removes all the existing key-value pairs from a dictionary. It returns None or rather does not return anything. It is a method that changes the object. It has to be noted here that dictionaries are not immutable. Let us look at an example.

>>> dct
{'Anil': 'Kumble', 'Sachin': 'Tendulkar', 'Rahul': 'Dravid'}
>>> dct.clear()
>>> dct
{}

5.2.2.copy()

The copy() returns a copy of a given dictionary. Let us look at an example.

>>> dct = {'Anil': 'Kumble', 'Sachin': 'Tendulkar', 'Rahul': 'Dravid'}
>>> dctcopy = dct.copy()
>>> dctcopy
{'Anil': 'Kumble', 'Sachin': 'Tendulkar', 'Rahul': 'Dravid'}

5.2.3.get()

get() returns the value for the key passed as the argument and if the key does not exist in the dictionary, it returns None. Let us look at an example.

>>> print dctcopy.get('Saurav')
None
>>> print dctcopy.get('Anil')
Kumble

5.2.4.has_key()

This method returns True if the given key is in the dictionary, else it returns False.

>>> dctcopy.has_key('Saurav')
False
>>> dctcopy.has_key('Sachin')
True

5.2.5.pop()

This method is used to retrieve the value of a given key and subsequently remove the key-value pair from the dictionary. Let us look at an example.

>>> print dctcopy.pop('Sachin')
Tendulkar
>>> dctcopy
{'Anil': 'Kumble', 'Rahul': 'Dravid'}

5.2.6.popitem()

This method randomly pops a key-value pair from a dictionary and returns it. The key-value pair returned is removed from the dictionary. Let us look at an example.

>>> print dctcopy.popitem()
('Anil', 'Kumble')
>>> dctcopy
{'Rahul': 'Dravid'}

Note that the item chosen is completely random since dictionaries are unordered
as mentioned earlier.

5.2.7.update()

The update() method updates the contents of one dictionary with the contents of another dictionary. For items with existing keys their values are updated, and the rest of the items are added. Let us look at an example.

>>> dctcopy.update(dct)
>>> dct
{'Anil': 'Kumble', 'Sachin': 'Tendulkar', 'Rahul': 'Dravid'}
>>> dctcopy
{'Anil': 'Kumble', 'Sachin': 'Tendulkar', 'Rahul': 'Dravid'}