Python File Handling (with open, write)Handle text files and use pickle. Read in the lines of a text file.
Files. Python programs often open, write to, and append to files. Many useful defs are available in this language—batteries are included.
File defs. We use the open() method to access files. Methods like readlines() handle their data. With Python, often a loop is not even needed to read a whole file.
Read text lines. We begin with text files. Even if we just want to display all the lines from a file, newlines must be handled. We read all lines from a file with readlines().
Tip We first must create a new file object. And then we loop over the list returned by readlines().
Raw string This program uses the path syntax for a Windows system. We start the string with "r" to avoid errors with backslashes.
Path Please change the path to an existing text file (or create a "perls.txt" file at the required location).
End The parameter to print() modifies the behavior of print. When we use end="" the trailing newline is not printed to the console.
Console, print
Python program that reads all lines
# Open a file on the disk. f = open(r"C:\perls.txt", "r") # Print all its lines. for line in f.readlines(): # Modify the end argument. print(line, end="")
Line 1 Line 2
File object, loop. We do not need readlines() to access all the lines in a file—we do not even need read() or readline. We can loop over the file object directly.
Tip This example handles empty lines, which contain a newline character by itself.
Python program that reads lines, loops over file object
# Call open() to access the file. f = open(r"C:\programs\info.txt", "r") for line in f: # Empty lines contain a newline character. if line == "\n": print("::EMPTY LINE::") continue # Strip the line. line = line.strip() print(line)
Pets: 1. Dog 2. Cat 3. Bird
Pets: ::EMPTY LINE:: 1. Dog 2. Cat 3. Bird
With. This statement cleans up resources. It makes simpler the task of freeing system resources. It is used with file handling: open() is a common call. It improves readability.
First We use "with" in this simple program. The program opens and reads from a file.
Tip This statement makes sure the system resources are cleaned up properly. The with statement is similar to a try-finally statement.
Python program that uses with statement
name = r"C:\perls.txt" # Open the file in a with statement. with open(name) as f: print(f.readline(), end="") # Repeat. with open(name) as f: print(f.readline(), end="")
First line First line
Pickle, list. Often we need to store objects. With pickle, we write collections such as lists to a data file. It supports many objects. The with statement improves resource cleanup.
However In this example, we create a list. We pass this list to pickle.dump().
Dump This writes the list contents in binary form to the file f.pickle. The extension (pickle) has no importance.
Then After we call pickle.dump(), we ignore the original list in memory. We load that same data back from the disk with pickle.load().
Python program that uses pickle, list
import pickle # Input list data. list = ["one", "two", "three"] print("before:", list) # Open the file and call pickle.dump. with open("f.pickle", "wb") as f: pickle.dump(list, f) # Open the file and call pickle.load. with open("f.pickle", "rb") as f: data = pickle.load(f) print("after:", data)
before: ['one', 'two', 'three'] after: ['one', 'two', 'three']
New, empty file. The second argument to open() is a string containing "mode" flag characters. The "w" specifies write-only mode—no appending or reading is done.
Erased If the file happens to exist, it is erased. So be careful when developing programs with this call.
Python program that creates new, empty file
# Create new empty file. # ... If the file exists, it will be cleared of content. f = open("C:\\programs\\test.file", "w")
Write lines. This program writes lines to a file. It first creates an empty file for writing. It specifies the "w" mode to create an empty file. Then it writes two lines.
Tip The line separators (newline chars) are needed. There is no "writeline" method available.
Python program that uses write
# Create an empty file for writing. with open("C:\\programs\\test.file", "w") as f: # Write two lines to the file. f.write("cat\n") f.write("bird\n")
cat bird
Count character frequencies. This program opens a file and counts each character using a frequency dictionary. It combines open(), readlines, and dictionary's get().
Strip The program strips each line because we do not want to bother with newline characters.
Get The code uses the two-argument form of get. If a value exists, it is returned—otherwise, 0 is returned.
Example text, file.txt, Python:
aaaa bbbbb aaaa bbbbb aaaa bbbbb CCcc xx y y y y y Z
# Open a file. f = open(r"C:\programs\file.txt", "r") # Stores character counts. chars = {} # Loop over file and increment a key for each char. for line in f.readlines(): for c in line.strip(): # Get existing value for this char or a default of zero. # ... Add one and store that. chars[c] = chars.get(c, 0) + 1 # Print character counts. for item in chars.items(): print(item)
('a', 12) (' ', 5) ('C', 2) ('b', 15) ('c', 2) ('y', 5) ('x', 2) ('Z', 1)
Benchmark readlines, read. There is significant overhead in accessing a file for a read. Here we benchmark file usage on a file with about 1000 lines.
Version 1 This version of the code uses the readlines() method and then loops over each line, calling len on each line.
Version 2 Here we call read() on the file, and then access the len of the entire file at once.
Result It was far faster to read the entire file in a single call with the read() method. Using readlines was slower.
File, line repeated 1000 times, test.file:
This is an interesting file. This is an interesting file. ...
import time print(time.time()) # Version 1: use readlines. i = 0 while i < 10000: with open("C:\\programs\\test.file", "r") as f: count = 0 for line in f.readlines(): count += len(line) i += 1 print(time.time()) # Version 2: use read. i = 0 while i < 10000: with open("C:\\programs\\test.file", "r") as f: count = 0 data = f.read() count = len(data) i += 1 print(time.time())
1406148416.003978 1406148423.383404 readlines = 7.38 s 1406148425.989555 read = 2.61 s
Read binary data. A Python program can read binary data from a file. We must add a "b" at the end of the mode argument. We call read() to read the entire file into a bytes object.
Here A file on the local disk is read. This is a gzip file, which has special bytes at its start.
Python program that reads binary data
# Read file in binary form. # ... Specify "b" for binary read and write. f = open(r"C:\stage-perls-cf\file-python", "rb") # Read the entire file. data = f.read() # Print length of result bytes object. # ... Print first three bytes (which are gzip). print(len(data)) print(data[0]) print(data[1]) print(data[2])
42078 31 139 8
Readline. We can use the readline method to access each line. This method returns an empty string when the file send is encountered. And it returns a newline on blank lines.
IOError. File handling is an error-prone task. Sometimes a file is moved without our knowledge. Sometimes even a hardware error can occur. We cannot prevent this.
So We must handle IOError in important programs. We can use exception handling, like try and except.
Formats. Markup files are often used in computer programs. We handle HTML and XML files. There are many ways to parse or scan these formats. I show HTMLParser and Expat.
CSV files Parsing CSV files is important. It is tedious. We introduce the csv module to help make it easier.
Textwrap The textwrap module can be to rewrap text files. This can improve the formatting of files.
Complexity. Files are a source of complexity in programs. We must process known file formats. And sometimes we also must handle invalid or corrupted files.
A review. File handling is an important yet error-prone aspect of program development. It is essential. It gives us data persistence.
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