Save file storage python

Writing List to a File in Python

In this article, you’ll learn how to write a list to a file in Python.

Often, we require storing a list, dictionary, or any in-memory data structure to persistent storage such as file or database so that we can reuse it whenever needed. For example, after analyzing data, you can store it in a file, and for the next time, that data can be read to use in an application.

There are multiple ways to write a Python list to a file. After reading this article, You’ll learn:

• Write a list to a text file and read it in a Python program when required using a write() and read() method.
• How to use Python’s pickle module to serialize and deserialize a list into a file. Serialize means saving a list object to a file. Deserialize means reading that list back into memory.
• Use of built-in json module to write a list to a json file.

Table of contents

Steps to Write List to a File in Python

Python offers the write() method to write text into a file and the read() method to read a file. The below steps show how to save Python list line by line into a text file.

1. Open file in write mode Pass file path and access mode w to the open() function. The access mode opens a file in write mode.
   For example, fp= open(r’File_Path’, ‘w’) .
2. Iterate list using a for loop Use for loop to iterate each item from a list. We iterate the list so that we can write each item of a list into a file.
3. Write current item into the file In each loop iteration, we get the current item from the list. Use the write(‘text’) method to write the current item to a file and move to the next iteration. we will repeat this step till the last item of a list.
4. Close file after completing the write operation When we complete writing a list to a file, we need to ensure that the file will be closed properly. Use file close() method to close a file.

Example to Write List to a File in Python

# list of names names = ['Jessa', 'Eric', 'Bob'] # open file in write mode with open(r'E:/demos/files_demos/account/sales.txt', 'w') as fp: for item in names: # write each item on a new line fp.write("%s\n" % item) print('Done')

Note: We used the \n in write() method to break the lines to write each item on a new line.

Below content got written in a file.

Example to Read List from a File in Python

Now, Let’s see how to read the same list from a file back into memory.

# empty list to read list from a file names = [] # open file and read the content in a list with open(r'E:\demos\files_demos\account\sales.txt', 'r') as fp: for line in fp: # remove linebreak from a current name # linebreak is the last character of each line x = line[:-1] # add current item to the list names.append(x) # display list print(names)

Write a list to file without using a loop

In this example, we are using a join method of a str class to add a newline after each item of a list and write it to a file.

The join() method will join all items in a list into a string, using a \n character as separator (which will add a new line after each list item).

# list of names names = ['Jessa', 'Eric', 'Bob'] with open(r'E:/demos/files_demos/account/sales.txt', 'w') as fp: fp.write('\n'.join(names))

If you want to convert all items of a list to a string when writing then use the generator expression.

# list of names names = ['Jessa', 'Eric', 'Bob'] with open(r'E:/demos/files_demos/account/sales.txt', 'w') as fp: fp.write("\n".join(str(item) for item in names))

Pickle module to write (serialize) list into a file

Python pickle module is used for serializing and de-serializing a Python object. For example, we can convert any Python objects such as list, dict into a character stream using pickling. This character stream contains all the information necessary to reconstruct the object in the future.

Any object in Python can be pickled and saved in persistent storage such as database and file for later use.

Example: Pickle and write Python list into a file

• First import the pickle module
• To write a list to a binary file, use the access mode ‘b’ to open a file. For writing, it will be wb , and for reading, it will be rb . The file open() function will check if the file already exists and, if not, will create one. If a file already exists, it gets truncated, and new content will be added at the start of a file.
• Next, The pickle’s dump(list, file_object) method converts an in-memory Python object into a bytes string and writes it to a binary file.

# Python program to store list to file using pickle module import pickle # write list to binary file def write_list(a_list): # store list in binary file so 'wb' mode with open('listfile', 'wb') as fp: pickle.dump(names, fp) print('Done writing list into a binary file') # Read list to memory def read_list(): # for reading also binary mode is important with open('sampleList', 'rb') as fp: n_list = pickle.load(fp) return n_list # list of names names = ['Jessa', 'Eric', 'Bob'] write_list(names) r_names = read_list() print('List is', r_names) 

Done writing list into a binary file List is ['Jessa', 'Eric', 'Bob']

Json module to write list into a JSON file

We can use it in the following cases.

• Most of the time, when you execute a GET request, you receive a response in JSON format, and you can store JSON response in a file for future use or for an underlying system to use.
• For example, you have data in a list, and you want to encode and store it in a file in the form of JSON.

In this example, we are going to use the Python json module to convert the list into JSON format and write it into a file using a json dump() method.

# Python program to store list to JSON file import json def write_list(a_list): print("Started writing list data into a json file") with open("names.json", "w") as fp: json.dump(a_list, fp) print("Done writing JSON data into .json file") # Read list to memory def read_list(): # for reading also binary mode is important with open('names.json', 'rb') as fp: n_list = json.load(fp) return n_list # assume you have the following list names = ['Jessa', 'Eric', 'Bob'] write_list(names) r_names = read_list() print('List is', r_names) 

Started writing list data into a json file Done writing JSON data into .json file List is ['Jessa', 'Eric', 'Bob']

writelines() method to write a list of lines to a file

We can write multiple lines at once using the writelines() method. For example, we can pass a list of strings to add to the file. Use this method when you want to write a list into a file.

# list of names names = ['Jessa', 'Eric', 'Bob'] with open(r'E:/demos/files_demos/account/sales.txt', 'w') as fp: fp.writelines(names)

Here is the output we are getting

cat sales.txt JessaEricBob

As you can see in the output, the file writelines() method doesn’t add any line separators after each list item.
To overcome this limitation, we can use list comprehension to add the new line character after each element in the list and then pass the list to the writelines method.

# list of names names = ['Jessa', 'Eric', 'Bob'] # add '\n' after each item of a list n_names = ["<>\n".format(i) for i in names] with open(r'E:/demos/files_demos/account/sales.txt', 'w') as fp: fp.writelines(n_names)

cat sales.txt Jessa Eric Bob

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About Vishal

I’m Vishal Hule, Founder of PYnative.com. I am a Python developer, and I love to write articles to help students, developers, and learners. Follow me on Twitter

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Best Ways to Save Data in Python

Hello readers! In this tutorial, we’ll be dealing with how we can effectively save data in Python.

How to Save Data in Python?

When we’re working on Python applications, we’ll be dealing with Python objects directly, since everything is an object in Python. Let’s look at some ways by which we can store them easily!

1. Using Pickle to store Python Objects

If we want to keep things simple, we can use the pickle module, which is a part of the standard library to save data in Python.

We can “pickle” Python objects to a pickle file, which we can use to save/load data.

So if you have a custom object which you might need to store / retrieve, you can use this format:

import pickle class MyClass(): def __init__(self, param): self.param = param def save_object(obj): try: with open("data.pickle", "wb") as f: pickle.dump(obj, f, protocol=pickle.HIGHEST_PROTOCOL) except Exception as ex: print("Error during pickling object (Possibly unsupported):", ex) obj = MyClass(10) save_object(obj)

If you run this script, you’ll notice a file called data.pickle , which contains the saved data.

To load the same object back again, we could use pickle.load() using similar logic.

import pickle class MyClass(): def __init__(self, param): self.param = param def load_object(filename): try: with open(filename, "rb") as f: return pickle.load(f) except Exception as ex: print("Error during unpickling object (Possibly unsupported):", ex) obj = load_object("data.pickle") print(obj.param) print(isinstance(obj, MyClass))

We’ve just retrieved our old data successfully!

2. Using Sqlite3 to save data in Python persistently

If you want to use a persistent database to save data in Python, you can use the sqlite3 library which provides you APIs for using Sqlite databases.

Again, this is a part of the standard library, so there’s no need to pip install anything!

However, since this is a Relational Database, you can’t directly dump Python objects like in pickle .

You’d have to serialize and de-serialize them to their appropriate Database types.

To look at some examples, you can refer to this article on using sqlite in Python.

3. Using SqliteDict as a persistent cache

If you find using sqlite3 too tedious, there’s a much better solution! You can use sqlitedict for storing persistent data, and this internally uses an sqlite3 database to handle the storage.

You have to install this package using pip:

The only thing you need to keep in mind is that you need to use key:value mappings to store / retrieve data, just like a dictionary!

Here’s a very simple example using the MyClass instance.

from sqlitedict import SqliteDict class MyClass(): def __init__(self, param): self.param = param def save(key, value, cache_file="cache.sqlite3"): try: with SqliteDict(cache_file) as mydict: mydictSave file storage python = value # Using dictSave file storage python to store mydict.commit() # Need to commit() to actually flush the data except Exception as ex: print("Error during storing data (Possibly unsupported):", ex) def load(key, cache_file="cache.sqlite3"): try: with SqliteDict(cache_file) as mydict: value = mydictSave file storage python # No need to use commit(), since we are only loading data! return value except Exception as ex: print("Error during loading data:", ex) obj1 = MyClass(10) save("MyClass_key", obj1) obj2 = load("MyClass_key") print(obj1.param, obj2.param) print(isinstance(obj1, MyClass), isinstance(obj2, MyClass))

Indeed, we’ve just loaded our Python object successfully! If you notice, sqlitedict will create a database cache.sqlite3 automatically, if it doesn’t exist, and then use it to store / load data.

Conclusion

In this article, we looked at how we can use Python to store data in different ways.

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