A program means very little if it does not take input of some kind from the program user. Likewise, if there is no form of output from a program then one may ask why we have a program at all. Input and output operations can define the user experience and usability of any program. This chapter is all about how to put information or data into a program, and then how to display it or save it to a file. This chapter does not discuss working with databases, but rather, working at a more rudimentary level with files. Throughout this chapter you will learn such techniques as how to input data for a program via a terminal or command line, likewise, you will learn how to read input from a file and write to a file. After reading this chapter, you should know how to persist Python objects to disk using the pickle module and also how to retrieve objects from disk and use them.
As stated in the preface to this chapter, almost every program takes input from a user in one form or another. Most basic applications allow for keyboard entry via a terminal or command line environment. Python makes keyboard input easy, and as with many other techniques in Python there are more than one way to enable keyboard input. In this section, we’ll cover each of those different ways to perform this task, along with a couple of use-cases. In the end you should be able to identify the most suitable method of performing input and output for your needs.
sys.stdin and raw_input
Making use of std.stdin is by far the most widely used method to read input from the command line or terminal. This procedure consists of importing the sys package, then writing a message prompting the user for some input, and lastly reading the input by making a call to sys.stdin.readln() and assigning the returned value to a variable. The process looks like the code that is displayed below.
# Obtain a value from the command line and store it into a variable >>> import sys >>> fav_team = sys.stdin.readline() Cubs >>> sys.stdout.write("My favorite team is: %s" % fav_team) My favorite team is: Cubs You can see that the usage of sys modules is quite easy. However, another approach to performing this same task is to make use of the raw_input function. This function uses a more simplistic syntax in order to perform the same procedure. It basically generates some text on the command line or terminal, accepts user input, and assigns it to a variable. Let’s take a look at the same example from above using the raw_input syntax. Note that there is another function that performs a similar task named the input function. However, the input function needs to be used with great care as it could be a potential security risk. The raw_input function always returns content passed in as a string whereas the input function returns content and evaluates it as an expression. It is safest to stay away from using input whenever possible.
# Obtain a value using raw_input and store it into a variable >>> fav_team = raw_input("Enter your favorite team: ") Enter your favorite team: Cubs
Obtaining Variables from Jython Environment
It is possible to retrieve values directly from the Jython environment for use within your applications. For instance, we can obtain system environment variables or use the variables that are assigned to sys.argv at runtime. sys.argv is a list containing the strings that have been passed into the command line or terminal. For instance, let’s take a look at a simple function that prints the contents of sys.argv.
Script: sysargv_test.py import sys for x in sys.argv: print x Output: jython sysagv_test.py test test2 example9_1.py test test2
To use environment variable values within your Jython application, simply import the os module and use it’s environ dictionary to access them. Since this is a dictionary object, you can obtain a listing of all environment variables by simply typing os.environ .
>>> import os >>> os.environ["HOME"]
# Change home directory for the Python session >>> os.environ["HOME"] = "/newhome" >>> os.environ["HOME"] /newhome'
When you are executing a Jython module from the command prompt or terminal, you can make use of the sys.argv list that takes values from the command prompt or terminal after invoking the Jython module. For instance, if we are interested in having our program user enter some arguments to be used by the module, they can simply invoke the module and then type all of the text entries followed by spaces, using quotes if you wish to pass an argument that contains a space. The number of arguments can be any size (I’ve never hit an upper bound anyways), so the possibilities are endless.
# sysargv_print.py – Prints all of the arguments provided at the command line import sys for sysargs in sys.argv: print sysargs # Usage >>> jython sysargv_print.py test test2 "test three" sysargv_print.py test test2 test three
As you can see, the first entry in sys.argv is the script name, and then each additional argument provided after the module name is then added to the sys.argv list. This is quite useful for creating scripts to use for automating tasks, etc.
You learned a bit about the File data type in chapter 2 of this book. In that chapter, we briefly discussed a few of the operations that can be performed using this type. In this section, we will go into detail on what we can do with a File object. We’ll start with the basics, and move into more detail. To begin, you should take a look at the table below that lists all of the methods available to a *File *object and what they do.
|fileno()||Returns integer file descriptor|
|flush()||Used to flush or clear the output buffers and write content to the file|
|isatty()||If the file is an interactive terminal, returns 1|
|next()||Returns the next line in the file; iterates over the file. If no line is found, raises StopIteration|
|read(x)||Reads x bytes|
|readline(x)||Reads single line up to x characters, or entire line if x is omitted|
|readlines(size)||Reads all lines in file into a list. If size > 0, reads that number of characters|
|seek()||Moves cursor to a new position in the file|
|tell()||Returns the current position of the cursor|
|truncate(size)||Truncates file’s size. Size defaults to current position unless specified|
|write(string)||Writes a string to the file object|
|writelines(seq)||Writes all strings contained in a sequence with no separator|
Table 9-1: File Object Methods
We’ll start by creating a file for use. As discussed in chapter 2, the open(filename[, mode])*built-in function creates and opens a specified file in a particular manner. The *mode specifies what mode we will open the file into, be it read, read-write, etc.
>>> myFile = open('mynewfile.txt','w') >>> firstString = “This is the first line of text.” >>> myFile.write(firstString) >>> myFile.close()
In the example above, the file “mynewfile.txt” did not exist until the open function was called. If it did exist already, the previous version is overwritten by the new version and it is now empty. The file was created in write mode and then we do just that, write a string to the file. Now, it is important to make mention that the firstString is not actually written to the file until it is closed or flush() *is performed. It is also worth mentioning that if we were to close the file, reopen it, and perform a subsequent *write() operation on the file then the previous contents of the file would be overwritten by content of the new write.
Now we’ll step through each of the file functions in an example. The main focus of this example is to provide you with a place to look for actual working file I/O code.
# Write lines to file, flush, and close >>> myFile = open(‘mynewfile.txt’,’w’) >>> myFile.write('This is the first line of text.n') >>> myFile.write('This is the second line of text.n') >>> myFile.write('This is the last line of text.n') >>> myFile.flush() # Optional, really unneccesary if closing the file but useful to clear buffer >>> myFile.close()
# Open file in read mode >>> myFile = open('mynewfile.txt','r') >>> myFile.read()
# If we read again, we get a ‘’ because cursor is at the end of text >>> myFile.read() ''
# Seek back to the beginning of file and perform read again >>> myFile.seek(0) >>> myFile.read() This is the first line of text.This is the second line of text.This is the last line of text.'
# Seek back to beginning of file and perform readline() >>> myFile.seek(0) >>> myFile.readline() 'This is the first line of text.n' >>> myFile.readline() 'This is he second line of text.n' >>> myFile.readline() 'This is the last line of text.n' >>> myFile.readline() ''
# Use tell() to display current cursor position >>> myFile.tell() 93L >>> myFile.seek(0) >>> myFile.tell() 0L
# Loop through lines of file >>> for line in myFile: ... print line ... This is the first line of text.
This is the second line of text.
This is the last line of text.
There are a handful of read-only attributes that we can use to find out more information about file objects. For instance, if we are working with a file and want to see if it is still open or if it has been closed, we could view the closed attribute on the file to return a boolean stating whether the file is closed. The following table lists each of these attributes and what they tell us about a file object.
|closed||Returns a boolean to indicate if the file is closed|
|encoding||Returns a string indicating encoding on file|
|mode||Returns the I/O mode for a file(i.e.: 'r', 'w', 'r+,'rb', etc.)|
|name||Returns the name of the file|
|newlines||Returns the newline representation in the file. This keeps track of the types of newlines encountered while reading the file. Allows for universal newline support.|
>>> myFile.closed False >>> myFile.mode 'r' >>> myFile.name 'mynewFile.txt'
One of the most popular modules in the Python language is the pickle module. The goal of this module is basically to allow for the serialization and persistence of Python objects to disk in file format. A pickled object can be written to disk using this module, and it can also be read back in and utilized in object format. Just about any Python object can be persisted using pickle.
To write an object to disk, we call the pickle() function. The object will be written to file in a format that my be unusable by anything else, but we can then read that file back into our program and use the object as it was prior to writing it out. In the following example, we’ll create a Player object and then persist it to file using pickle. Later, we will read it back into a program and make use of it. We will make use of the File object when working with the pickle module.
>>> import pickle >>> class Player(object): ... def __init__(self, first, last, position): ... self.first = first ... self.last = last ... self.position = position ... >>> player = Player('Josh','Juneau','Forward') >>> pickleFile = open('myPlayer','wb') >>> pickle.dump(player, pickleFile) >>> pickleFile.close()
In the example above, we’ve persisted a Player object to disk using the dump(object, file) method in the pickle module. Now let’s read the object back into our program and print it out.
>>> pickleFile = open('myPlayer','rb') >>> player1 = pickle.load(pickleFile) >>> pickleFile.close() >>> player1.first 'Josh' >>> player1.last, player1.position ('Juneau', 'Forward')
Similarly, we read the pickled file back into our program using the method. Once read and stored into a variable, we can close the file and work with the object. If we had to perform a sequence of or tasks, we could do so one after the other without issue. You should also be aware that there are different protocols that can be used in order to make work in different Python environments. The default protocol is 0, but protocols 1 and 2 are also available for use. It is best to stick with the default as it works well in most situations, but if you run into any trouble using with binary formats then please give the others a try.
If we had to store objects to disk and reference them at a later time, it may make sense to use the module which acts like a dictionary for pickeled objects. With the technique, you basically an object and store it using a string-based key value. You can later retrieve the object by passing the key to the opened file object. This technique is very similar to a filing cabinet for our objects in that we can always reference our objects by key value. Let’s take a look at this technique and see how it works.
# Store different player objects >>> import shelve >>> player1 = Player('Josh','Juneau','forward') >>> player2 = Player('Jim','Baker','defense') >>> player3 = Player('Frank','Wierzbicki','forward') >>> player4 = Player('Leo','Soto','defense') >>> player5 = Player('Vic','Ng','center') >>> data = shelve.open("players") >>> data['player1'] = player1 >>> data['player2'] = player2 >>> data['player3'] = player3 >>> data['player4'] = player4 >>> data['player5'] = player5 >>> playerTemp = data['player3'] >>> playerTemp.first, playerTemp.last, playerTemp.position ('Frank', 'Wierzbicki', 'forward') >>> data.close()
In the scenario above, we used the same Player object that was defined in the previous examples. We then opened a new shelve and named it “players”, this shelve actually consists of a set of three files that are written to disk. These three files can be found on disk named “players.bak”, “players.dat”, and “players.dir” once the objects were persisted into the shelve and when close() was called on the object. As you can see, all of the Player objects we’ve instantiated have all been stored into this shelve unit, but they exist under different keys. We could have named the keys however we wished, as long as they were each unique. In the example, we persist five objects and then at the end one of the objects is retrieved and displayed. This is quite a nice technique to make a small data store.
We basically covered the print statement in chapter 2 very briefly when discussing string formatting. The print statement is by far the most utilized form of output in most Python programs. Although we covered some basics such as conversion types and how to format a line of output in chapter 2, here we will go into a bit more depth on some different variations of the print *statement as well as other techniques for generating output. There are basically two formats that can be used with the *print statement. We covered the first in chapter two, and it makes use of a string and some conversion types embedded within the string and preceded by a percent (%) symbol. After the string, we use another percent(%) symbol followed by a parenthesized list of arguments that will be substituted in place of the embedded conversion types in our string in order. Check out the examples of each depicted in the example below.
# Using the % symbol >>> x = 5 >>> y = 10 >>> print 'The sum of %d and %d is %d' % (x, y, (x + y)) The sum of 5 and 10 is 15 >>> adjective = "awesome" >>> print 'Jython programming is %s' % (adjective) Jython programming is awesome
You can also format floating-point output using the conversion types that are embedded in your string. You may specify a number of decimal places you’d like to print by using a “.# of places” syntax in the embedded conversion type.
>>> pi = 3.14 >>> print 'Here is some formatted floating point arithmetic: %.2f' % (pi + y) Here is some formatted floating point arithmetic: 13.14 >>> print 'Here is some formatted floating point arithmetic: %.3f' % (pi + y) Here is some formatted floating point arithmetic: 13.140
It goes without saying that Python has its share of input and output strategies. This chapter covered most of those techniques starting with basic terminal or command line I/O and then onto file manipulation. We learned how to make use of the open function for creating, reading, or writing a file. The command line sys.argv arguments are another way that we can grab input, and environment variables can also be used from within our programs. Following those topics, we took a brief look at the pickle module and how it can be used to persist Python objects to disk. shelve is another twist on using pickle that allows for multiple objects to be indexed and stored within the same file. Finally, we discussed a couple of techniques for performing output in our programs.
Although there are some details that were left out as I/O could consume an entire book, this chapter was a solid starting point into the broad topic of I/O in Python. As with much of the Python language specifics discussed in this book, there are many resources available on the web and in book format that will help you delve deeper into the topics if you wish. A good resource is 'Beginning Python: From Novice to Professional' by: Magnus Lie Hetland. You may also wish to look at the Python documentation which can be found at: http://www.python.org/doc/.