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1.6 File Management
This section discusses the basics of working with files.
Reading
File Input and Output
Open a file.
f = open('foo.txt', 'rt') # Open for reading (text)
g = open('bar.txt', 'wt') # Open for writing (text)
Reading data.
data = f.read()
# Read only up to 'maxbytes' bytes
data = f.read([maxbytes])
Writing text to a file.
g.write('some text')
Close when you are done.
f.close()
g.close()
Files should be properly closed. This is why the preferred approach is to use the with statement.
with open(filename, 'rt') as f:
# Use the file `f`
...
# No need to close explicitly
...statements
This automatically closes the file when control leaves the indented code block.
Common Idioms for Reading File Data
Reading an entire file all at once as a string.
with open('foo.txt', 'rt') as f:
data = f.read()
# `data` is a string with all the text in `foo.txt`
Reading a file line-by-line
with open(filename, 'rt') as f:
for line in f:
# Process the line `f`
Writing string data.
with open('outfile', 'wt') as f:
f.write('Hello World\n')
...
Redirecting the print function.
with open('outfile', 'wt') as f:
print('Hello World', file=f)
...
Exercises 1.6
This exercise depends on a file Data/portfolio.csv. The file contains a list of lines with information on a portfolio of stocks.
Locate the file and look at its contents:
(a) File Preliminaries
*Note: Make sure you are running Python in a location where you can access the portfolio.csv file.
You can find out where Python thinks it's running by doing this:
>>> import os
>>> os.getcwd()
'/Users/beazley/Desktop/practical-python' # Output vary
>>>
First, try reading the entire file all at once as a big string:
>>> with open('Data/portfolio.csv', 'rt') as f:
data = f.read()
>>> data
'name,shares,price\n"AA",100,32.20\n"IBM",50,91.10\n"CAT",150,83.44\n"MSFT",200,51.23\n"GE",95,40.37\n"MSFT",50,65.10\n"IBM",100,70.44\n'
>>> print(data)
name,shares,price
"AA",100,32.20
"IBM",50,91.10
"CAT",150,83.44
"MSFT",200,51.23
"GE",95,40.37
"MSFT",50,65.10
"IBM",100,70.44
>>>
In the above example, it should be noted that Python has two modes of output.
In the first mode where you type data at the prompt, Python shows you the raw string representation including quotes and escape codes.
When you type print(data), you get the actual formatted output of the string.
Although reading a file all at once is simple, it is often not the most appropriate way to do it—especially if the file happens to be huge or if contains lines of text that you want to handle one at a time.
To read a file line-by-line, use a for-loop like this:
>>> with open('Data/portfolio.csv', 'rt') as f:
for line in f:
print(line, end='')
name,shares,price
"AA",100,32.20
"IBM",50,91.10
...
>>>
When you use this code as shown, lines are read until the end of the file is reached at which point the loop stops.
On certain occasions, you might want to manually read or skip a single line of text (e.g., perhaps you want to skip the first line of column headers).
>>> f = open('Data/portfolio.csv', 'rt')
>>> headers = next(f)
>>> headers
'name,shares,price\n'
>>> for line in f:
print(line, end='')
"AA",100,32.20
"IBM",50,91.10
...
>>> f.close()
>>>
next() returns the next line of text in the file. If you were to call it repeatedly, you would get successive lines.
However, just so you know, the for loop already uses next() to obtain its data.
Thus, you normally wouldn’t call it directly unless you’re trying to explicitly skip or read a single line as shown.
Once you’re reading lines of a file, you can start to perform more processing such as splitting. For example, try this:
>>> f = open('Data/portfolio.csv', 'rt')
>>> headers = next(f).split(',')
>>> headers
['name', 'shares', 'price\n']
>>> for line in f:
row = line.split(',')
print(row)
['"AA"', '100', '32.20\n']
['"IBM"', '50', '91.10\n']
...
>>> f.close()
Note: In these examples, f.close() is being called explicitly because the with statement isn’t being used.
(b) Reading a data file
Now that you know how to read a file, let’s write a program to perform a simple calculation.
The columns in portfolio.csv correspond to the stock name, number of
shares, and purchase price of a single share. Write a program called
pcost.py that opens this file, reads all lines, and calculates how
much it cost to purchase all of the shares in the portfolio.
Hint: to convert a string to an integer, use int(s). To convert a string to a floating point, use float(s).
Your program should print output such as the following:
Total cost 44671.15
(c) Other kinds of 'files'
What if you wanted to read a non-text file such as a gzip-compressed datafile?
The builtin open() function won’t help you here, but Python has a library module gzip that can read gzip compressed files.
Try it:
>>> import gzip
>>> with gzip.open('Data/portfolio.csv.gz') as f:
for line in f:
print(line, end='')
... look at the output ...
>>>