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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

The Crucial Difference Between List and NumPy Array

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Here are the differences between List and NumPy Array. Both store data, but technically these are not the same. You'll find here where they differ from each other. Python Lists Here is all about Python lists: Lists can have data of different data types. For instance, data = [3, 3.2, 4.6, 6, 6.8, 9, “hello”, ‘a’] Operations such as subtraction, multiplying, and division allow doing through loops Storage space required is more, as each element is considered an object in Python Execution time is high for large datasets Lists are inbuilt data types How to create array types in Python NumPy Arrays Here is all about NumPy Arrays: Numpy arrays are containers for storing only homogeneous data types. For example: data= [3.2, 4.6, 6.8]; data=[3, 6, 9]; data=[‘hello’, ‘a’] Numpy is designed to do all mathematical operations in parallel and is also simpler than Python Numpy storage space is very much less compared to the list due to the practice of homogeneous data type Execution time is

How to Understand AWS Load Balancers Quickly

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The load balancer's purpose is to balance the incoming traffic. It allocates the incoming traffic to the available healthy servers. Here are the top AWS load balancers. AWS Load balancers These are Application Load Balancer, Gateway Load Balancer, and Network Load Balancer. Application Load Balancers Gateway Load Balancers Network Load Balancers   1. Application Load Balancers (ALB) A Load balancer contains two parts - Listeners and Target groups. The listener then connects to a target group. The listener first checks the availability of connection according to the IP address and Port you did configure. Adopted from Amazon AWS   2. Gateway Load Balancers (GWLB) A Gateway Load Balancer receives traffic from the source and sends the traffic to targets. It sends requests to multiple virtual appliances. It's the prime difference between ALB and GWLB. 3. Network Load Balancers (NLB) A Network Load Balancer functions at the fourth layer of the Open Systems Interconnection (OSI) model

How to Create an Array and Its Types in Python

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Python supports various array types. Here is a list of arrays and how to create examples for your reference.  What is an array? A  Python array  is a class that mimics the array type of other languages and offers efficiency in storage, exchanging that for flexibility. How to create an array Here is the syntax to create an array: data = array('f', [12.8, 5.4, 8.0, 8.0, 9.21, 3.14]) It creates an array of 6 floating point numbers; the type is indicated by the 'f' as the first parameter to the constructor. This concept is unlike the Python norm of types being dynamic and malleable. An array is an array of one kind of thing, and an array can only hold a restricted set of types. Types of arrays Here is a list of arrays: 'b' A C++ char type 'B' A C++ unsigned char type 'i': A C++ int type 'l': A C++ long type 'f': A C++ float type 'd': A C++ double type What is an array type? Arrays are class objects and are provided in the buil

How to Find Folder Space in Linux Easily

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Here's an example that shows how to use find command to get directory utilized space in Linux. Many of a time during production support, or when crontab jobs failed, the reasons behind is space shortage of a directory. The find is handy you can use to get utilized space of a directory. That helps you to delete unnecessary files (that actually make some space). Linux find command Here's the find command that I  have used in our project . You will find here the detailed explanation of this command and how to use it. find  /home/srini -xdev -ls | sort +6rn | head -20 Part#1: Directory path In the first part,  after the find you need to give the directory's path for which  folder you are going to find  space. Part#2: Option -xdev The second part is  -xdev , which gives the space usage of all the subdirectories. Part#3: Option -ls The next part is the -ls option that provides a sorted list of all the subdirectories.  Part#4: Sort command Then, the sort command sorts based on the

How to Use Tail Command in Linux

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Here's a way that shows how to use tail command in Linux. The uses are VIZ: display last lines from single file, display last lines from multiple files, display the last entries of log files. The tail is handy command and popular to check last lines of a file in Linux/Unix operating systems. Tail Command in Linux While working with files and production support the usage of tail command is helpful. Here are the selected examples that how you can use effectively. 1. Display last lines in a file Here's the tail command that shows last three lines of a file. cat sample.txt | tail -3 It displays last 3 lines of a file. The same command you can use as tail -3 sample.txt 2. Display last lines of multiple files There are three files. sample2.txt, sample3.txt, sample4.txt. The command displays the last 3 lines from all the three files. tail -3 sample[2-4].txt 3. Tail -f option  The –f option is to check status of long-running process that is redirecting output to a file. For example, if

4 Important Arguments in Python

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Here are four types of exclusive arguments in python. The arguments are passers to functions. These are Required arguments, Keyword arguments, Default arguments and Variable-length arguments. Here're 4 Important Arguments in Python The arguments supply input to functions . Because these are various types, herein you will know the details and usage of those types. Argument#1: Required arguments Positional arguments are known as  required arguments  and are passed to a function in the correct order. The arguments in the function call should match the number in the function definition. Sample program: def cal(a,b):     """program to calculate sum of 2 numbers"""     sum=a+b     return sum a=int(input("enter 1st number")) b=int(input("enter 2nd number")) print(cal(a,b)) Output enter 1st number 10 enter 2nd number 22 32 ** Process exited - Return Code: 0 ** Press Enter to exit terminal Argument#2: Keyword arguments A default argument is