Python

NumPy Save Dict

This article will teach you how to save a dictionary in Python using the most important methods. Numpy.save() from the NumPy module in Python is the commonly used method for this purpose. We will figure out what it is for and how to use it. Let’s begin the discussion.

What Is a Dictionary?

A dictionary is defined as an unordered data value in Python. It can be used to store data values similar to those of a map. Unlike some other Data Types, which can only retain a single value as either an element, dictionary can include a key:value pair. To make it more effective, the dictionary comprises a key-value pair.

A dictionary is built in Python by enclosing a sequence of entries in curly braces and separating them with a comma.

Numpy.save() in Python

We can use Python’s numpy.save() function from transforming an array into a binary file when saving it. This method also can be used to store the dictionary in Python. When you merely want to save data to reuse in Python, npy files are an excellent alternative.

They are included in the NumPy module since they are native to it. Importing and exporting npy files is more effective and convenient. As a result, saving to .npy files will save you a significant amount of time and effort during the import and export of the data.

Below are several examples that will help you understand the key steps for saving a dictionary in Python.

Example 1

In this example, the NumPy library’s save() method is used to save a dictionary to a file. The save() function accepts the file name and the dictionary we want to save as inputs and saves the dictionary to a file as the .npy file.

Look at the following code. We have imported the NumPy module and constructed a dictionary with the following values: ‘Red’: 3, ‘Yellow’: 3, ‘Pink’: 8, and ‘Orange’: 1. Following that, we used the numpy.save() function to save it to the ‘my_file.npy’ file.

import numpy
dict_val = { 'Red': 3, 'Yellow': 3, 'Pink': 8, 'Orange': 1}
numpy.save('my_file.npy', dict_val)

The following code example demonstrates how to read a .npy file containing a Python dictionary. To load the saved dictionary from the .npy file, the load() method of the NumPy library is used, and it requires the file name and the “allow_pickle” option to be set to True.

import numpy
dict_val = numpy.load('my_file.npy', allow_pickle='TRUE')
print(dict_val.item())

The file contents are fetched from the file and shown on the screen, as seen here:

Example 2

Here’s another example of how to utilize Python’s numpy.save() method. After clearing the background, look at the following code to understand how to save an array with the numpy.save() method. We started by importing the NumPy module and creating an array in which we specified the range. The NumPy array named ‘my_arr’ was constructed in the first four lines of the code. As you can see, the following code saves the array in a file named ‘my_file’.

import numpy
my_arr = numpy.arange(10)
print("Data is as follows :")
print(my_arr)
numpy.save('my_file', my_arr)
print("Your array is saved to my_file.npy")

You may construct and save the array to a .npy file by running the previous lines of code. See the results in the following table. The output shows the produced array and the message indicating it was successfully saved in the specified file, which in our case is “my_file”.

Example 3

This example shows how to use the dump() method of the pickle module to save a dictionary to a file in Python. Python objects can be serialized and deserialized with the help of this module.

Pickle is a built-in module available in Python that deals with object serialization. It is not only cross-platform but also cross-language, meaning it can store and load objects among Python applications on different operating systems and Python programs on other platforms.

Try to read and comprehend the sample code in the following section. The code example provided below explains how to save a dictionary using the pickle module’s dump() method and then read a dictionary out from the saved file using the load() function. The dictionary and the file object are passed to the pickle module’s dump() function, which saves the dictionary as the a.pkl file.

The following code demonstrates that we have imported the pickle module, which is required for the program’s execution. Following that, a dictionary named “dict sample” is generated. The dictionary contains the following data: {‘Red’: 3, ‘Yellow’: 3, ‘Pink’: 8, ‘Orange’: 1}. It’s followed by the open() function, which opens the file and uses the dump() function to save the dictionary’s data.

import pickle as pk
dict_sample = {'Red': 3, 'Yellow': 3, 'Pink': 8, 'Orange': 1}
with open("my_dict.pkl", "wb") as tt:
    pk.dump(dict_sample,tt)

The following code example shows how to read a dictionary stored in a file to use the load() function. The load() function takes a file object as an input to load the dictionary from the .pkl file.

import pickle as pk
with open("my_dict.pkl", "wb") as tt:
    dict_sample = pk.load(tt)
print(dict_sample)

The data from the dictionary we constructed and saved in a file may be seen in the following output image:

Conclusion

This post went over how to store a dictionary using the numpty module in depth, complete with example programs. The save() method included in the NumPy library of Python can be used to save a dictionary to a file. To achieve this save() method of Python, take the file’s name along with the dictionary that we intend to store as inputs. We discussed the.load() method under the NumPy module in addition to the.save() method. We taught about .npy files and how to import and export data using them.

About the author

Kalsoom Bibi

Hello, I am a freelance writer and usually write for Linux and other technology related content