How to Handle Files in Python

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Dealing with recordsdata is a vital side in any programming language. And Python additionally helps working with recordsdata in several modes, equivalent to studying and writing to recordsdata, and extra.

On the finish of this tutorial it is possible for you to to:

  • open and skim recordsdata in Python,
  • learn strains from a textual content file,
  • write and append to recordsdata, and
  • use context managers to work with recordsdata in Python.

How one can learn a file in Python

To open a file in Python you should use the final syntax: open('file_name','mode').

  • Right here, file_name is the title of the file.

Comment: If the file you wish to open is within the present working listing, you’ll be able to solely listing the title of the file. Whether it is positioned in one other folder in your work setting, you will need to embrace the trail to the file.

  • The parameters mode specifies the mode through which you wish to open the file.

The default mode for opening a file is learn-indicated by the letter 'r'. Nonetheless, it is strongly recommended apply to specify the mode explicitly.

Earlier than we start, let’s overview the file lib.txtwhich we are going to use on this instance.

📁 Obtain the textual content file and code used on this tutorial from this GitHub repo.

The code snippet beneath reveals how one can open a textual content file 'lib.txt' use in Python open() operate and skim its contents.

file = open('lib.txt','r')
contents = file.learn()
print(contents)
file.shut()


# Output
Hi there, there!
Listed below are just a few useful Python libraries:
1) NumPy
2) pandas
3) matplotlib
4) seaborn
5) scikit-learn
6) BeautifulSoup
7) Scrapy
8) nltk
9) Bokeh
10) statsmodels

Within the instance above

  • The open() operate returns a file object and we select to name it file.
  • Then we name the learn() technique on file.
  • The variable contents now comprises the contents of the file. And we print it out.
  • Lastly, we shut the file.

Nonetheless, for those who neglect to shut the file, there could also be a waste of assets. Working with numerous such recordsdata may end up in important reminiscence utilization. It’s because you opened a number of recordsdata, however closed none.

Now let’s be taught a greater approach to open recordsdata with context managers. The code snippet beneath reveals you how one can use them.

with open('lib.txt','r') as f:
  contents = f.learn()
  print(contents)

Whenever you use contact managers to work with recordsdata, you do not want the shut() technique. The recordsdata are robotically closed after the I/O operation is accomplished.

How one can learn strains from a file in Python

In our pattern textual content file, we solely had just a few strains. So studying all of the contents of the file directly was no drawback.

python read file

Nonetheless, when you might want to learn in giant recordsdata, use the learn() technique, as proven above, will not be very environment friendly.

If the textual content file could be very giant, the reminiscence can replenish shortly. Due to this fact, you might wish to learn read-only strains from a textual content file. On this part you’ll discover ways to do that.

Use Python’s readline() technique to learn strains from a file

The readline() technique reads line by line from the file.

Run the next code snippet. 

with open('lib.txt','r') as f:
  line = f.readline()
  print(line)
  line = f.readline()
  print(line)


# Output
Hi there, there!

Listed below are just a few useful Python libraries:

You’ll be able to see that after the primary readline() technique name, the primary line within the file is printed. And the second name to the readline() technique returns the second line within the file.

It’s because, after the primary technique name, the file pointer is originally of the second line.

In Python you should use the inform() technique to get the present file pointer location. And to maneuver the file pointer to a selected location, you should use the search() technique.

Within the code snippet beneath, we use f.search(0) after the primary technique name. This strikes the file pointer to the start of the textual content file. Due to this fact, each instances, the primary line within the file is printed.

with open('lib.txt','r') as f:
  line = f.readline()
  print(line)
  f.search(0)
  line = f.readline()
  print(line)


# Output
Hi there, there!

Hi there, there!

Use Python’s readlines() technique to learn strains from a file

There’s one other carefully associated technique known as readlines().

Whenever you run the next code snippet, you will notice that the readlines() technique returns an inventory of all strains within the file. 

with open('lib.txt','r') as f:
  strains = f.readlines()
  print(strains)


# Output
['Hello, there!n', 'Here are a few helpful Python libraries:n', 
'1) NumPyn', '2) pandasn', '3) matplotlibn', 
'4) seabornn', '5) scikit-learnn', '6) BeautifulSoupn', 
'7) Scrapyn', '8) nltkn', '9) Bokehn', '10) statsmodelsn', 'n']

Utilizing Python’s for Loop to learn strains from a file

To learn the strains from a textual content file, you can too use the for loop.

After getting a file object, you should use it for loop to browse the contents of the file line by line and print them as proven beneath. Discover how we solely open one line at a time and do not learn all the contents of the file.

with open('lib.txt','r') as f:
  for line in f:
    print(line, finish='')

Comment: When utilizing Python print() operate, the default delimiter is a newline—'n' character. However within the unique file we do not have these newlines. So set the delimiter argument to an empty string: finish = '' to print the contents of the file as is.

How one can learn bits of content material from a file in Python

In Python you can too select to learn the contents of the file in small chunks.

Learn the code beneath:

  • Right here we set the chunk_size Disagreeable 50. Because of this the primary 50 characters of the file are learn in, and we additionally print them out.
  • Now name the inform() technique on the file object f. You’ll be able to see that the file pointer is now at place 51, as anticipated.
chunk_size = 50
with open('lib.txt','r') as f:
  chunk = f.learn(chunk_size)
  print(chunk)
  present = f.inform()
  print(f"Present place of file pointer: {present}")

# Output
Hi there, there!
Listed below are just a few useful Python librar
Present place of file pointer: 51

You can even use this method to learn all the file in small chunks.

The next code snippet reveals you ways to do that. 

chunk_size = 50
with open('lib.txt','r') as f:
  chunk = f.learn(chunk_size)
  print(chunk,finish='')

  whereas(len(chunk)>0):
    chunk = f.learn(chunk_size)
    print(chunk,finish='')

# Output
Hi there, there!
Listed below are just a few useful Python libraries:
1) NumPy
2) pandas
3) matplotlib
4) seaborn
5) scikit-learn
6) BeautifulSoup
7) Scrapy
8) nltk
9) Bokeh
10) statsmodels

Right here we use one whereas loop to learn the contents of the file. We learn the contents of the file in chunks of fifty till we attain the tip of the file. ✅

How one can write to file in Python

To put in writing to a textual content file in Python, you will need to open it in write mode—particularly 'w'.

python-write-to-file

The code snippet beneath reveals you ways to do that.

with open('new_file.txt','w') as f:
  f.write('Hi there, Python!')

You will notice 'new_file.txt' has been created in your working listing.

Now run the above code cell once more.

In your terminal, run the next command:

cat new_file.txt

# Output: Hi there, Python!

Ideally, we wrote to the file twice. So Hi there, Python! ought to have printed twice, sure?

However you will notice that it was solely printed as soon as. Effectively, it’s because if you open a file in to put in writing (w) mode, really Overwrite the contents of the brand new content material file.

If you would like add to the tip of the file with out overwriting any current content material, you will need to open the file within the add mode. And you will see how to do that within the subsequent part.

How one can append to file in Python

So as to add content material to a file with out overwriting it, open it within the add mode.

To do that, use `'a'—a for add-and specify the mode explicitly.

Then run the next code cell twice. 

with open('new_file.txt','a') as f:
  f.write('Hi there, Python!')

Discover how the textual content is now printed twice as we added to the file.

cat new_file.txt

# Output: Hi there, Python!Hi there, Python!

Conclusion

Let’s shortly recap what we have mentioned on this tutorial.

  • You may have realized the frequent file I/O operations, equivalent to studying, writing, and including to a file.
  • You additionally realized how one can use the to look() technique to maneuver the file pointer to a selected place, and
  • how one can use the narrate() technique to get the present place of the file pointer.

I hope you discovered this tutorial useful. Now that you have realized how one can work with textual content recordsdata in Python, discover ways to work with JSON recordsdata in Python.

Associated:

Test the size of an inventory in Python in 3 steps.

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