Python File I/O

Python file I/OIn the previous articles, we covered quite a bit of rudimentary Python programming, but we haven’t covered on of the most important elements of any programming language: the ability to perform file I/O. In this article, we will cover file operations, and put it into practice by using Python file I/O to generate a file of numbers to sort with the quicksort algorithm developed in the previous article.

Python File I/O: Simple Commands

To open a file, we use open(), which returns a file object, and is commonly used with two arguments: open(filename, mode).

>>> f = open(‘mylist.txt’,’w’)

The first argument is a string containing the filename. The second argument is another string describing how the file will be used. ‘r’ is specified when the file will only be read, ‘w’ for only writing (an existing file with the name name will be erased), and ‘a’ opens the file for appending. Any data written to the file is automatically added to the end. ‘r+’ opens the file for both reading and writing. The mode argument is optional: ‘r’ is the default value if it is omitted.

On Windows, ‘b’ appended to the mode opens the file in binary mode. Python on Windows makes a distinction between text and binary files; the end-of-line characters in text files are automatically altered slightly when data is read or written. This modification is OK for ASCII text files, but it will corrupt binary data like that in JPEG or EXE files. On Unix, it doesn’t hurt to append a ‘b’ to the mode, so you can use it platform-independently for all binary files.

To read a file’s content, call the read() function of the object returned by open() (in the above example, f). read() reads some quantity of data and returns it as a string. When size is omitted or negative, the entire contents of the file, so you probably want to specify a number of bytes if the file is large. If the end of the file has been reached, f.read() will return an empty string:

>>> f.read()
‘This is the contents of a text file.\n’

readline() reads a single line from the file; a newline character is left at the end of the string. It is only omitted on the last line of the file if the file does not end in a newine. Thus if f.readline() returns an empty string, the end of file has been reached, while a blank line is represented by ‘\n’.

For readling lines from a file, you can loop over the file object:

>>> for line in f:
print line

If you want to read all the files of a file, you can also use list(f) or f.readlines().

That covers read operations. write(string) writes the contents of string to the file, returning None.

To write something other than a string, it needs to be converted to a string first; e.g.:

>>> value = (‘The sum is ‘,101)
>>> s = str(value)
>>> f.write(s)

f.tell() returns an integer giving the file object’s current position in the file, measured in bytes from the beginning of the file. To change the file’s object position, we use f.seek(offset, param). The position is computed from adding offset to a reference point. The reference point is selected by the param argument. A param value of 0 measures from the beginning of the file; 1 uses the current file position, and 2 uses the end of the file as the reference point. The second parameter can be omitted; the default value is 0, using the beginning of the file as a reference point. You may have noticed that the behavior of this function is similar to that of the fseek() function in C/C++. When you’re done with a file, call f.close() and free up any system resources taken up by the open file. After calling f.close(), attempts to use the file will automatically fail.

Python File I/O: Serialization

Finally, you can write data to a file easily with serialization. The read() function only returns strings, and when you want to save complex data types like nested lists and dictionaries, it can become unwieldy. Python, however, allows you to use the popular data interchange format called JSON (JavaScript Object Notation). The standard module called json can take Python data hierarchies, and convert them to string representations. This process is called serializing, and reconstructing the data from the string representation is called deserializing. To write an object x to a file object f opened for writing, we use:

json.dump(x, f)

And to decode the object, we use the following:

x = json.load(f)

This simple serialization technique can handle lists and dictionaries without any additional effort, but serializing arbitrary class instances in JSON requires some extra work.

Here’s a chance to apply what we know about Python file I/O to generate a file containing randomly-generated numbers. We will then read the data into a list, and use quicksort to sort the list. We start with a function to generate the file:

def generateNumbers(filename,num):
'''Use Python file I/O to generate a file of name 
filename and fill it with num randomly-generated 
integers of range 1 to num'''
temp = []
f = open(filename,'w')
for i in range(0,num):
temp.append(int((random.random()*num)+1))
json.dump(temp,f)
f.close()

As you can see, I used JSON to save the data to the file, which should make the process of reading the numbers in easier. Now for the function to read in the data:

def readList(filename):
'''Use Python file I/O to read in a file of name 
filename using serialization'''
retval = []
f = open(filename,'r')
temp = []
try:
retval = json.load(f)
except EOFError:
print('EOF error')
f.close()
return retval

The following code uses Python file I/O to generate a list of 1000 integers, reads in the same list, sorts the list and prints out both the size of the list along with the sorted list:

generateNumbers('mylist.lst',1000)
myList = readList('mylist.lst')
quickSort(myList)
print('Size of myList = ',len(myList))
print(myList)

We could save the list of integers as ASCII text, but if we did, we would have to parse the list when we read it back in, which would be somewhat cumbersome. Serialization makes the process easy, and it is undoubtedly a technique we will use in the future.

External Links:

Reading and writing Files at docs.python.org