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Mastering flat_map in Python with List Comprehension

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Introduction In Python, when working with nested lists or iterables, one common challenge is flattening them into a single list while applying transformations. Many programming languages provide a built-in flatMap function, but Python does not have an explicit flat_map method. However, Python’s powerful list comprehensions offer an elegant way to achieve the same functionality. This article examines implementation behavior using Python’s list comprehensions and other methods. What is flat_map ? Functional programming  flatMap is a combination of map and flatten . It transforms the collection's element and flattens the resulting nested structure into a single sequence. For example, given a list of lists, flat_map applies a function to each sublist and returns a single flattened list. Example in a Functional Programming Language: List(List(1, 2), List(3, 4)).flatMap(x => x.map(_ * 2)) // Output: List(2, 4, 6, 8) Implementing flat_map in Python Using List Comprehension Python’...
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Python Program: JSON to CSV Conversion

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JavaScript object notion is also called JSON file, it's data you can write to a CSV file. Here's a sample python logic for your ready reference. 




You can write a simple python program by importing the JSON, and CSV packages. This is your first step. It is helpful to use all the JSON methods in your python logic. That means the required package is JSON.

So far, so good. In the next step, I'll show you how to write a Python program. You'll also find each term explained.


What is JSON File

JSON is key value pair file. The popular use of JSON file is to transmit data between heterogeneous applications. Python supports JSON file.


What is CSV File

The CSV is comma separated file. It is popularly used to send and receive data.


How to Write JSON file data to a CSV file

Here the JSON data that has written to CSV file. It's simple method and you can use for CSV file conversion use.

import csv, json

json_string = '[{"value1": 1, "value2": 2,"value3": 1.234}]'
data = json.loads(json_string)
headers = data[0].keys()

with open('sample.csv', 'w') as f:
writer = csv.DictWriter(f, fieldnames=headers)
writer.writeheader()
writer.writerows(data)


with open('sample.csv', 'r') as f:
    print(f)
    for row in f:
        print(row)

Output:

<_io.TextIOWrapper name='file.csv' mode='r' encoding='UTF-8'>
value1,value2,value3

1,2,1.234


** Process exited - Return Code: 0 **
Press Enter to exit terminal

Conclusion

The output CSV file has both headers and rows, and the data is comma seprated.


References

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