15 Must Know JavaScript Array Methods

In this post, we're going to see 15 array methods that can help you manipulate your data properly.

1. some()

2. reduce()

3. every()

4. map()

5. flat()

6. filter()

7. forEach()

8. findIndex()

9. find()

10. sort()

11. concat()

12. fill()

13. includes()

14. reverse()

15. flatMap()

#javascript

Understanding Arrays in Python

Learn how to use Python arrays. Create arrays in Python using the array module. You'll see how to define them and the different methods commonly used for performing operations on them.

The artcile covers arrays that you create by importing the array module. We won't cover NumPy arrays here.

Introduction to Arrays
1. The differences between Lists and Arrays
2. When to use arrays
How to use arrays
1. Define arrays
2. Find the length of arrays
3. Array indexing
4. Search through arrays
5. Loop through arrays
6. Slice an array
Array methods for performing operations
1. Change an existing value
2. Add a new value
3. Remove a value
Conclusion

Let's get started!

What are Python Arrays?

Arrays are a fundamental data structure, and an important part of most programming languages. In Python, they are containers which are able to store more than one item at the same time.

Specifically, they are an ordered collection of elements with every value being of the same data type. That is the most important thing to remember about Python arrays - the fact that they can only hold a sequence of multiple items that are of the same type.

What's the Difference between Python Lists and Python Arrays?

Lists are one of the most common data structures in Python, and a core part of the language.

Lists and arrays behave similarly.

Just like arrays, lists are an ordered sequence of elements.

They are also mutable and not fixed in size, which means they can grow and shrink throughout the life of the program. Items can be added and removed, making them very flexible to work with.

However, lists and arrays are not the same thing.

Lists store items that are of various data types. This means that a list can contain integers, floating point numbers, strings, or any other Python data type, at the same time. That is not the case with arrays.

As mentioned in the section above, arrays store only items that are of the same single data type. There are arrays that contain only integers, or only floating point numbers, or only any other Python data type you want to use.

When to Use Python Arrays

Lists are built into the Python programming language, whereas arrays aren't. Arrays are not a built-in data structure, and therefore need to be imported via the array module in order to be used.

Arrays of the array module are a thin wrapper over C arrays, and are useful when you want to work with homogeneous data.

They are also more compact and take up less memory and space which makes them more size efficient compared to lists.

If you want to perform mathematical calculations, then you should use NumPy arrays by importing the NumPy package. Besides that, you should just use Python arrays when you really need to, as lists work in a similar way and are more flexible to work with.

How to Use Arrays in Python

In order to create Python arrays, you'll first have to import the array module which contains all the necassary functions.

There are three ways you can import the array module:

By using import array at the top of the file. This includes the module array. You would then go on to create an array using array.array().

import array

#how you would create an array
array.array()

Instead of having to type array.array() all the time, you could use import array as arr at the top of the file, instead of import array alone. You would then create an array by typing arr.array(). The arr acts as an alias name, with the array constructor then immediately following it.

import array as arr

#how you would create an array
arr.array()

Lastly, you could also use from array import *, with * importing all the functionalities available. You would then create an array by writing the array() constructor alone.

from array import *

#how you would create an array
array()

How to Define Arrays in Python

Once you've imported the array module, you can then go on to define a Python array.

The general syntax for creating an array looks like this:

variable_name = array(typecode,[elements])

Let's break it down:

variable_name would be the name of the array.
The typecode specifies what kind of elements would be stored in the array. Whether it would be an array of integers, an array of floats or an array of any other Python data type. Remember that all elements should be of the same data type.
Inside square brackets you mention the elements that would be stored in the array, with each element being separated by a comma. You can also create an empty array by just writing variable_name = array(typecode) alone, without any elements.

Below is a typecode table, with the different typecodes that can be used with the different data types when defining Python arrays:

TYPECODE	C TYPE	PYTHON TYPE	SIZE
'b'	signed char	int	1
'B'	unsigned char	int	1
'u'	wchar_t	Unicode character	2
'h'	signed short	int	2
'H'	unsigned short	int	2
'i'	signed int	int	2
'I'	unsigned int	int	2
'l'	signed long	int	4
'L'	unsigned long	int	4
'q'	signed long long	int	8
'Q'	unsigned long long	int	8
'f'	float	float	4
'd'	double	float	8

Tying everything together, here is an example of how you would define an array in Python:

import array as arr 

numbers = arr.array('i',[10,20,30])


print(numbers)

#output

#array('i', [10, 20, 30])

Let's break it down:

First we included the array module, in this case with import array as arr .
Then, we created a numbers array.
We used arr.array() because of import array as arr .
Inside the array() constructor, we first included i, for signed integer. Signed integer means that the array can include positive and negative values. Unsigned integer, with H for example, would mean that no negative values are allowed.
Lastly, we included the values to be stored in the array in square brackets.

Keep in mind that if you tried to include values that were not of i typecode, meaning they were not integer values, you would get an error:

import array as arr 

numbers = arr.array('i',[10.0,20,30])


print(numbers)

#output

#Traceback (most recent call last):
# File "/Users/dionysialemonaki/python_articles/demo.py", line 14, in <module>
#   numbers = arr.array('i',[10.0,20,30])
#TypeError: 'float' object cannot be interpreted as an integer

In the example above, I tried to include a floating point number in the array. I got an error because this is meant to be an integer array only.

Another way to create an array is the following:

from array import *

#an array of floating point values
numbers = array('d',[10.0,20.0,30.0])

print(numbers)

#output

#array('d', [10.0, 20.0, 30.0])

The example above imported the array module via from array import * and created an array numbers of float data type. This means that it holds only floating point numbers, which is specified with the 'd' typecode.

How to Find the Length of an Array in Python

To find out the exact number of elements contained in an array, use the built-in len() method.

It will return the integer number that is equal to the total number of elements in the array you specify.

import array as arr 

numbers = arr.array('i',[10,20,30])


print(len(numbers))

#output
# 3

In the example above, the array contained three elements – 10, 20, 30 – so the length of numbers is 3.

Array Indexing and How to Access Individual Items in an Array in Python

Each item in an array has a specific address. Individual items are accessed by referencing their index number.

Indexing in Python, and in all programming languages and computing in general, starts at 0. It is important to remember that counting starts at 0 and not at 1.

To access an element, you first write the name of the array followed by square brackets. Inside the square brackets you include the item's index number.

The general syntax would look something like this:

array_name[index_value_of_item]

Here is how you would access each individual element in an array:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # gets the 3rd element

#output

#10
#20
#30

Remember that the index value of the last element of an array is always one less than the length of the array. Where n is the length of the array, n - 1 will be the index value of the last item.

Note that you can also access each individual element using negative indexing.

With negative indexing, the last element would have an index of -1, the second to last element would have an index of -2, and so on.

Here is how you would get each item in an array using that method:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[-1]) #gets last item
print(numbers[-2]) #gets second to last item
print(numbers[-3]) #gets first item
 
#output

#30
#20
#10

How to Search Through an Array in Python

You can find out an element's index number by using the index() method.

You pass the value of the element being searched as the argument to the method, and the element's index number is returned.

import array as arr 

numbers = arr.array('i',[10,20,30])

#search for the index of the value 10
print(numbers.index(10))

#output

#0

If there is more than one element with the same value, the index of the first instance of the value will be returned:

import array as arr 


numbers = arr.array('i',[10,20,30,10,20,30])

#search for the index of the value 10
#will return the index number of the first instance of the value 10
print(numbers.index(10))

#output

#0

How to Loop through an Array in Python

You've seen how to access each individual element in an array and print it out on its own.

You've also seen how to print the array, using the print() method. That method gives the following result:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers)

#output

#array('i', [10, 20, 30])

What if you want to print each value one by one?

This is where a loop comes in handy. You can loop through the array and print out each value, one-by-one, with each loop iteration.

For this you can use a simple for loop:

import array as arr 

numbers = arr.array('i',[10,20,30])

for number in numbers:
    print(number)
    
#output
#10
#20
#30

You could also use the range() function, and pass the len() method as its parameter. This would give the same result as above:

import array as arr  

values = arr.array('i',[10,20,30])

#prints each individual value in the array
for value in range(len(values)):
    print(values[value])

#output

#10
#20
#30

How to Slice an Array in Python

To access a specific range of values inside the array, use the slicing operator, which is a colon :.

When using the slicing operator and you only include one value, the counting starts from 0 by default. It gets the first item, and goes up to but not including the index number you specify.


import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#get the values 10 and 20 only
print(numbers[:2])  #first to second position

#output

#array('i', [10, 20])

When you pass two numbers as arguments, you specify a range of numbers. In this case, the counting starts at the position of the first number in the range, and up to but not including the second one:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])


#get the values 20 and 30 only
print(numbers[1:3]) #second to third position

#output

#rray('i', [20, 30])

Methods For Performing Operations on Arrays in Python

Arrays are mutable, which means they are changeable. You can change the value of the different items, add new ones, or remove any you don't want in your program anymore.

Let's see some of the most commonly used methods which are used for performing operations on arrays.

How to Change the Value of an Item in an Array

You can change the value of a specific element by speficying its position and assigning it a new value:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#change the first element
#change it from having a value of 10 to having a value of 40
numbers[0] = 40

print(numbers)

#output

#array('i', [40, 20, 30])

How to Add a New Value to an Array

To add one single value at the end of an array, use the append() method:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40)

print(numbers)

#output

#array('i', [10, 20, 30, 40])

Be aware that the new item you add needs to be the same data type as the rest of the items in the array.

Look what happens when I try to add a float to an array of integers:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40.0)

print(numbers)

#output

#Traceback (most recent call last):
#  File "/Users/dionysialemonaki/python_articles/demo.py", line 19, in <module>
#   numbers.append(40.0)
#TypeError: 'float' object cannot be interpreted as an integer

But what if you want to add more than one value to the end an array?

Use the extend() method, which takes an iterable (such as a list of items) as an argument. Again, make sure that the new items are all the same data type.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integers 40,50,60 to the end of numbers
#The numbers need to be enclosed in square brackets

numbers.extend([40,50,60])

print(numbers)

#output

#array('i', [10, 20, 30, 40, 50, 60])

And what if you don't want to add an item to the end of an array? Use the insert() method, to add an item at a specific position.

The insert() function takes two arguments: the index number of the position the new element will be inserted, and the value of the new element.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 in the first position
#remember indexing starts at 0

numbers.insert(0,40)

print(numbers)

#output

#array('i', [40, 10, 20, 30])

How to Remove a Value from an Array

To remove an element from an array, use the remove() method and include the value as an argument to the method.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30])

With remove(), only the first instance of the value you pass as an argument will be removed.

See what happens when there are more than one identical values:


import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Only the first occurence of 10 is removed.

You can also use the pop() method, and specify the position of the element to be removed:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

#remove the first instance of 10
numbers.pop(0)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Conclusion

And there you have it - you now know the basics of how to create arrays in Python using the array module. Hopefully you found this guide helpful.

You'll start from the basics and learn in an interacitve and beginner-friendly way. You'll also build five projects at the end to put into practice and help reinforce what you learned.

Thanks for reading and happy coding!

Original article source at https://www.freecodecamp.org

#python

Alex O'Sullivan

1666082925

How to Create Arrays in Python

In this tutorial, you'll know the basics of how to create arrays in Python using the array module. Learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.

This tutorialvideo on 'Arrays in Python' will help you establish a strong hold on all the fundamentals in python programming language. Below are the topics covered in this video:
1:15 What is an array?
2:53 Is python list same as an array?
3:48 How to create arrays in python?
7:19 Accessing array elements
9:59 Basic array operations
- 10:33 Finding the length of an array
- 11:44 Adding Elements
- 15:06 Removing elements
- 18:32 Array concatenation
- 20:59 Slicing
- 23:26 Looping

Python Array Tutorial – Define, Index, Methods

In this article, you'll learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.

The artcile covers arrays that you create by importing the array module. We won't cover NumPy arrays here.

Introduction to Arrays
1. The differences between Lists and Arrays
2. When to use arrays
How to use arrays
1. Define arrays
2. Find the length of arrays
3. Array indexing
4. Search through arrays
5. Loop through arrays
6. Slice an array
Array methods for performing operations
1. Change an existing value
2. Add a new value
3. Remove a value
Conclusion

Let's get started!

What are Python Arrays?

Arrays are a fundamental data structure, and an important part of most programming languages. In Python, they are containers which are able to store more than one item at the same time.

What's the Difference between Python Lists and Python Arrays?

Lists are one of the most common data structures in Python, and a core part of the language.

Lists and arrays behave similarly.

Just like arrays, lists are an ordered sequence of elements.

They are also mutable and not fixed in size, which means they can grow and shrink throughout the life of the program. Items can be added and removed, making them very flexible to work with.

However, lists and arrays are not the same thing.

When to Use Python Arrays

Lists are built into the Python programming language, whereas arrays aren't. Arrays are not a built-in data structure, and therefore need to be imported via the array module in order to be used.

Arrays of the array module are a thin wrapper over C arrays, and are useful when you want to work with homogeneous data.

They are also more compact and take up less memory and space which makes them more size efficient compared to lists.

How to Use Arrays in Python

In order to create Python arrays, you'll first have to import the array module which contains all the necassary functions.

There are three ways you can import the array module:

By using import array at the top of the file. This includes the module array. You would then go on to create an array using array.array().

import array

#how you would create an array
array.array()

Instead of having to type array.array() all the time, you could use import array as arr at the top of the file, instead of import array alone. You would then create an array by typing arr.array(). The arr acts as an alias name, with the array constructor then immediately following it.

import array as arr

#how you would create an array
arr.array()

Lastly, you could also use from array import *, with * importing all the functionalities available. You would then create an array by writing the array() constructor alone.

from array import *

#how you would create an array
array()

How to Define Arrays in Python

Once you've imported the array module, you can then go on to define a Python array.

The general syntax for creating an array looks like this:

variable_name = array(typecode,[elements])

Let's break it down:

variable_name would be the name of the array.
The typecode specifies what kind of elements would be stored in the array. Whether it would be an array of integers, an array of floats or an array of any other Python data type. Remember that all elements should be of the same data type.
Inside square brackets you mention the elements that would be stored in the array, with each element being separated by a comma. You can also create an empty array by just writing variable_name = array(typecode) alone, without any elements.

Below is a typecode table, with the different typecodes that can be used with the different data types when defining Python arrays:

TYPECODE	C TYPE	PYTHON TYPE	SIZE
'b'	signed char	int	1
'B'	unsigned char	int	1
'u'	wchar_t	Unicode character	2
'h'	signed short	int	2
'H'	unsigned short	int	2
'i'	signed int	int	2
'I'	unsigned int	int	2
'l'	signed long	int	4
'L'	unsigned long	int	4
'q'	signed long long	int	8
'Q'	unsigned long long	int	8
'f'	float	float	4
'd'	double	float	8

Tying everything together, here is an example of how you would define an array in Python:

import array as arr 

numbers = arr.array('i',[10,20,30])


print(numbers)

#output

#array('i', [10, 20, 30])

Let's break it down:

First we included the array module, in this case with import array as arr .
Then, we created a numbers array.
We used arr.array() because of import array as arr .
Inside the array() constructor, we first included i, for signed integer. Signed integer means that the array can include positive and negative values. Unsigned integer, with H for example, would mean that no negative values are allowed.
Lastly, we included the values to be stored in the array in square brackets.

Keep in mind that if you tried to include values that were not of i typecode, meaning they were not integer values, you would get an error:

import array as arr 

numbers = arr.array('i',[10.0,20,30])


print(numbers)

#output

#Traceback (most recent call last):
# File "/Users/dionysialemonaki/python_articles/demo.py", line 14, in <module>
#   numbers = arr.array('i',[10.0,20,30])
#TypeError: 'float' object cannot be interpreted as an integer

In the example above, I tried to include a floating point number in the array. I got an error because this is meant to be an integer array only.

Another way to create an array is the following:

from array import *

#an array of floating point values
numbers = array('d',[10.0,20.0,30.0])

print(numbers)

#output

#array('d', [10.0, 20.0, 30.0])

How to Find the Length of an Array in Python

To find out the exact number of elements contained in an array, use the built-in len() method.

It will return the integer number that is equal to the total number of elements in the array you specify.

import array as arr 

numbers = arr.array('i',[10,20,30])


print(len(numbers))

#output
# 3

In the example above, the array contained three elements – 10, 20, 30 – so the length of numbers is 3.

Array Indexing and How to Access Individual Items in an Array in Python

Each item in an array has a specific address. Individual items are accessed by referencing their index number.

Indexing in Python, and in all programming languages and computing in general, starts at 0. It is important to remember that counting starts at 0 and not at 1.

To access an element, you first write the name of the array followed by square brackets. Inside the square brackets you include the item's index number.

The general syntax would look something like this:

array_name[index_value_of_item]

Here is how you would access each individual element in an array:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # gets the 3rd element

#output

#10
#20
#30

Remember that the index value of the last element of an array is always one less than the length of the array. Where n is the length of the array, n - 1 will be the index value of the last item.

Note that you can also access each individual element using negative indexing.

With negative indexing, the last element would have an index of -1, the second to last element would have an index of -2, and so on.

Here is how you would get each item in an array using that method:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[-1]) #gets last item
print(numbers[-2]) #gets second to last item
print(numbers[-3]) #gets first item
 
#output

#30
#20
#10

How to Search Through an Array in Python

You can find out an element's index number by using the index() method.

You pass the value of the element being searched as the argument to the method, and the element's index number is returned.

import array as arr 

numbers = arr.array('i',[10,20,30])

#search for the index of the value 10
print(numbers.index(10))

#output

#0

If there is more than one element with the same value, the index of the first instance of the value will be returned:

import array as arr 


numbers = arr.array('i',[10,20,30,10,20,30])

#search for the index of the value 10
#will return the index number of the first instance of the value 10
print(numbers.index(10))

#output

#0

How to Loop through an Array in Python

You've seen how to access each individual element in an array and print it out on its own.

You've also seen how to print the array, using the print() method. That method gives the following result:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers)

#output

#array('i', [10, 20, 30])

What if you want to print each value one by one?

This is where a loop comes in handy. You can loop through the array and print out each value, one-by-one, with each loop iteration.

For this you can use a simple for loop:

import array as arr 

numbers = arr.array('i',[10,20,30])

for number in numbers:
    print(number)
    
#output
#10
#20
#30

You could also use the range() function, and pass the len() method as its parameter. This would give the same result as above:

import array as arr  

values = arr.array('i',[10,20,30])

#prints each individual value in the array
for value in range(len(values)):
    print(values[value])

#output

#10
#20
#30

How to Slice an Array in Python

To access a specific range of values inside the array, use the slicing operator, which is a colon :.

When using the slicing operator and you only include one value, the counting starts from 0 by default. It gets the first item, and goes up to but not including the index number you specify.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#get the values 10 and 20 only
print(numbers[:2])  #first to second position

#output

#array('i', [10, 20])

When you pass two numbers as arguments, you specify a range of numbers. In this case, the counting starts at the position of the first number in the range, and up to but not including the second one:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])


#get the values 20 and 30 only
print(numbers[1:3]) #second to third position

#output

#rray('i', [20, 30])

Methods For Performing Operations on Arrays in Python

Arrays are mutable, which means they are changeable. You can change the value of the different items, add new ones, or remove any you don't want in your program anymore.

Let's see some of the most commonly used methods which are used for performing operations on arrays.

How to Change the Value of an Item in an Array

You can change the value of a specific element by speficying its position and assigning it a new value:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#change the first element
#change it from having a value of 10 to having a value of 40
numbers[0] = 40

print(numbers)

#output

#array('i', [40, 20, 30])

How to Add a New Value to an Array

To add one single value at the end of an array, use the append() method:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40)

print(numbers)

#output

#array('i', [10, 20, 30, 40])

Be aware that the new item you add needs to be the same data type as the rest of the items in the array.

Look what happens when I try to add a float to an array of integers:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40.0)

print(numbers)

#output

#Traceback (most recent call last):
#  File "/Users/dionysialemonaki/python_articles/demo.py", line 19, in <module>
#   numbers.append(40.0)
#TypeError: 'float' object cannot be interpreted as an integer

But what if you want to add more than one value to the end an array?

Use the extend() method, which takes an iterable (such as a list of items) as an argument. Again, make sure that the new items are all the same data type.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integers 40,50,60 to the end of numbers
#The numbers need to be enclosed in square brackets

numbers.extend([40,50,60])

print(numbers)

#output

#array('i', [10, 20, 30, 40, 50, 60])

And what if you don't want to add an item to the end of an array? Use the insert() method, to add an item at a specific position.

The insert() function takes two arguments: the index number of the position the new element will be inserted, and the value of the new element.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 in the first position
#remember indexing starts at 0

numbers.insert(0,40)

print(numbers)

#output

#array('i', [40, 10, 20, 30])

How to Remove a Value from an Array

To remove an element from an array, use the remove() method and include the value as an argument to the method.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30])

With remove(), only the first instance of the value you pass as an argument will be removed.

See what happens when there are more than one identical values:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Only the first occurence of 10 is removed.

You can also use the pop() method, and specify the position of the element to be removed:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

#remove the first instance of 10
numbers.pop(0)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Conclusion

And there you have it - you now know the basics of how to create arrays in Python using the array module. Hopefully you found this guide helpful.

Thanks for reading and happy coding!

#python #programming

Oleksandr Siryi

1671543249

Migrating From Jira Server: Guide, Pros, And Cons

February 15, 2022 marked a significant milestone in Atlassian’s Server EOL (End Of Life) roadmap. This was not the final step. We still have two major milestones ahead of us: end of new app sales in Feb 2023, and end of support in Feb 2024. In simpler words, businesses still have enough time to migrate their Jira Server to one of the two available products – Atlassian Cloud or Atlassian DC. But the clock is ticking.

Jira Cloud VS Data Center

If we were to go by Atlassian numbers, 95% of their new customers choose cloud.

“About 80% of Fortune 500 companies have an Atlassian Cloud license. More than 90% of new customers choose cloud first.” – Daniel Scott, Product Marketing Director, Tempo

So that’s settled, right? We are migrating from Server to Cloud? And what about the solution fewer people talk about yet many users rely on – Jira DC?

Both are viable options and your choice will depend greatly on the needs of your business, your available resources, and operational processes.

Let’s start by taking a look at the functionality offered by Atlassian Cloud and Atlassian DC.

Feature	Atlassian Cloud	Atlassian Data Center
Product Plans	Multiple plans	One plan
Billing	Monthly and annual	Annual only
Pricing model	Per user or tiered	Tiered only
Support	Varying support levels depending on your plan: Enterprise support coverage is equivalent to Atlassian’s Data Center Premier Support offering	Varying support levels depending on the package: Priority Support or Premier Support (purchased separately)
Total Cost of Ownership	TCO includes your subscription fee, plus product administration time	TCO includes your subscription fee and product administration time, plus: costs related to infrastructure provisioning or IaaS fees (for example, AWS costs) planned downtime time and resources needed for software upgrades
Data encryption services
Data residency services
Audit logging	Organization-level audit logging available via Atlassian Access (Jira Software, Confluence) Product-level audit logs (Jira Software, Confluence)	Advanced audit logging
Device security	Mobile device management support (Jira Software, Confluence, Jira Service Management) Mobile application management (currently on the roadmap)	Mobile device management support (Jira Software, Confluence, Jira Service Management)
Content security
Data Storage limits	2 GB (Free) 250 GB (Standard) Unlimited storage (Premium and Enterprise)	No limits
Performance	Continuous performance updates to improve load times, search responsiveness, and attachments Cloud infrastructure hosted in six geographic regions to reduce latency	Rate limitingCDN supports Smart mirrors and mirror farms (Bitbucket)
Backup and data disaster recovery	Jira leverages multiple geographically diverse data centers, has a comprehensive backup program, and gains assurance by regularly testing their disaster recovery and business continuity plans. Backups are generated daily and retained for 30 days to allow for point-in-time data restoration
Containerization and orchestration		Docker images Kubernetes support (on the roadmap for now)
Change management and upgrades	Atlassian automatically handles software and security upgrades for you Sandbox instance to test changes (Premium and Enterprise) Release track options for Premium and Enterprise (Jira Software, Jira Service Management, Confluence)
Direct access to the database	No direct access to change the database structure, file system, or other server infrastructure Extensive REST APIs for programmatic data access	Direct database access
Insights and reporting	Organization and admin insights to track adoption of Atlassian products, and evaluate the security of your organization.	Data Pipeline for advanced insightsConfluence analytics

Pros and cons of Jira Cloud

When talking about pros and cons, there’s always a chance that a competitive advantage for some is a dealbreaker for others. That’s why I decided to talk about pros and cons in matching pairs.

Pro: Scalability is one of the primary reasons businesses are choosing Jira Cloud. DC is technically also scalable, but you’ll need to scale on your own whereas the cloud version allows for the infrastructure to scale with your business.

Con: Despite the cloud’s ability to grow with your business, there is still a user limit of 35k users. In addition to that, the costs will grow alongside your needs. New users, licenses, storage, and computing power – all come at an additional cost. So, when your organization reaches a certain size, migrating to Jira DC becomes more cost-efficient.

Pro: Jira takes care of maintenance and support for you.

Con: Your business can suffer from unpredicted downtime. And there are certain security risks.

Pro: Extra bells and whistles:

Sandbox: Sandbox is a safe environment system admins can use to test applications and integrations before rolling them out to the production environment.
Release tracks: Admins can be more flexible with their product releases as they can access batch and control cloud releases. This means they’ll have much more time to test existing configurations and workflows against a new update.
Insight Discovery: More data means more ways you can impact your business or product in a positive, meaningful way.
Team Calendars: This is a handy feature for synchronization and synergy across teams.

Con: Most of these features are locked behind a paywall and are only available to either Premium and Enterprise or only Enterprise licenses (either fully or through addition of functionality. For example, Release tracks are only available to Enterprise customers.) In addition, the costs will grow as you scale the offering to fit your growing needs.

Pros and cons of Jira Data Center

I’ll be taking the same approach to talking about the pros and cons as I did when writing about Atlassian Cloud. Pros and cons are paired.

Pro: Hosting your own system means you can scale horizontally and vertically through additional hardware. Extension of your systems is seamless, and there is no downtime (if you do everything correctly). Lastly, you don’t have to worry about the user limit – there is none.

Con: While having more control over your systems is great, it implies a dedicated staff of engineers, additional expenses on software licensing, hardware, and physical space. Moreover, seamless extension and 0% downtime are entirely on you.

Pro: Atlassian has updated the DC offering with native bundled applications such as Advanced Roadmaps, team calendars and analytics for confluence, insight asset management, and insight discovery in Jira Service Management DC.

Con: Atlassian has updated their pricing to reflect these changes. And you are still getting fewer “bells and whistles” than Jira Cloud users (as we can see from the feature comparison).

Pro: You are technically safer as the system is supported on your hardware by your specialists. Any and all Jira server issues, poor updates, and downtime are simply not your concern.

Con: Atlassian offers excellent security options: data encryption in transit and rest, to mobile app management, to audit offerings and API token controls. In their absence, your team company has to dedicate additional resources to security.

Pro: Additional benefits from Atlassian, such as the Priority Support bundle (all DC subscriptions have this option), and the Data center loyalty discount (more on that in the pricing section.)

The Pricing

Talking about pricing of SaaS products is always a challenge as there are always multiple tiers and various pay-as-you go features. Barebones Jira Cloud, for instance, is completely free of charge, yet there are a series of serious limitations.

Standard Jira Cloud will cost you an average of $7.50 per user per month while premium cranks that price up to $14.50. The Enterprise plan is billed annually and the cost is determined on a case-by-case basis. You can see the full comparison of Jira Cloud plans here. And you can use this online calculator to learn the cost of ownership in your particular case.

50 Users	Standard (Monthly/Annually)	Premium (Monthly/Annually)
Jira Software	$387.50 / $3,900	$762.50 / $7,650
Jira Work Management	$250 / $2,500
Jira Service Management	$866.25 / $8,650	$2,138.25 / $21,500
Confluence	$287.50 / $2,900	$550 / $5,500

100 Users	Standard (Monthly/Annually)	Premium (Monthly/Annually)
Jira Software	$775 / $7,750	$1,525 / $15,250
Jira Work Management	$500 / $5,000
Jira Service Management	$1,653.75 / $16,550	$4,185.75 / $42,000
Confluence	$575 / $5,750	$1,100 / $11,000

500 Users	Standard (Monthly/Annually)	Premium (Monthly/Annually)
Jira Software	$3,140 / $31,500	$5,107.50 / $51,000
Jira Work Management	$1,850 / $18,500
Jira Service Management	$4,541.25 / $45,400	$11,693.25 / $117,000
Confluence	$2,060 / $20,500	$3,780 / $37,800

Please note that these prices were calculated without any apps included.

Jira Data Center starts at $42,000 per year and the plan includes up to 500 users. If you are a new client and are not eligible for any discounts*, here’s a chart that should give you an idea as to the cost of ownership of Jira DC. You can find more information regarding your specific case here.

Users	Commercial Annual Plan	Academic Annual Plan
1-500	USD 42,000	USD 21,000
501-1000	USD 72,000	USD 36,000
1001-2000	USD 120,000	USD 60,000
Confluence for Data Center
1-500	USD 27,000	USD 13,500
501-1000	USD 48,000	USD 24,000
1001-2000	USD 84,000	USD 42,000
Bitbucket for Data Center
1-25	USD 2,300	USD 1,150
26-50	USD 4,200	USD 2,100
51-100	USD 7,600	USD 3,800
Jira Service Management for Data Center
1-50	USD 17,200	USD 8,600
51-100	USD 28,600	USD 14,300
101-250	USD 51,500	USD 25,750

*Discounts:

Centralized per-user licensing allows users access all enterprise instances with a single Enterprise license.
There’s an option for dual licensing for users who purchase an annual cloud subscription with 1,001 or more users. In this case, Atlassian extends your existing server maintenance or Data Center subscription for up to one year at a 100% discount.
There are certain discounts for apps depending on your partnership level.
Depending on your situation, you may qualify for several Jira Data Center discount programs:
- Academic Data Center licensing offers a 50% discount.
- Community Data Center licensing for Non-profit organizations is free of charge.
- Lastly, there is a loyalty discount for Server customers who choose to migrate to the Data Center. Check this link to find out if you are eligible.

What should be your User Migration strategy?

Originally, there were several migration methods: Jira Cloud Migration Assistant, Jira Cloud Site Import, and there was an option to migrate via CSV export (though Jira actively discourages you from using this method). However, Jira’s team has focused their efforts on improving the Migration Assistant and have chosen to discontinue Cloud Site Import support.

Thanks to the broadened functionality of the assistant, it is now the only go-to method for migration with just one exception. If you are migrating over 1000 users and you absolutely need to migrate advanced roadmaps – you’ll need to rely on Site Import. At least for now, as Jira is actively working on implementing this feature in their assistant.

Here’s a quick comparison of the options and their limitations.

	Features	Limitations
Cloud Migration Assistant	App migration Existing data on a Cloud Site is not overwritten You choose the projects, users, and groups you want to migrate Jira Service Management customer account migration Better UI to guide you through the migration Potential migration errors are displayed in advance Migration can be done in phases reducing the downtime Pre- and post-migration reports	You must be on a supported self-managed version of Jira
Site Export	Can migrate Advanced Roadmaps	App data is not migrated Migration overrides existing data on the Cloud site Separate user importUsers from external directories are not migrated No choice of data you want or don’t want migrated There’s a need to split attachments into up to 5GB chunks Higher risks of downtime due to the “all or nothing” approach You must be on a supported self-managed version of Jira

Pro tip: If you have a large base of users (above 2000), migrate them before you migrate projects and spaces. This way, you will not disrupt the workflow as users are still working on Server and the latter migration of data will take less time.

How to migrate to Jira Cloud

Now that we have settled on one particular offering based on available pricing models as well as the pros and the cons that matter the most to your organization, let’s talk about the “how”.

How does one migrate from Jira Server to Jira Cloud?

Pre-migration checklist

Jira’s Cloud Migration Assistant is a handy tool. It will automatically review your data for common errors. But it is incapable of doing all of the work for you. That’s why we – and Atlassian for that matter – recommend creating a pre-migration checklist.

Smart Checklist will help you craft an actionable, context-rich checklist directly inside a Jira ticket. This way, none of the tasks will be missed, lost, or abandoned.

Below is an example of how your migration checklist will look like in Jira.

Feel free to copy the code and paste it into your Smart Checklist editor and you’ll have the checklist at the ready.

# Create a user migration plan #must
> Please keep in mind that Jira Cloud Migration Assistant migrates all users and groups as well as users and groups related to selected projects
- Sync your user base
- Verify synchronization
- External users sync verification
- Active external directory verification
## Check your Jira Server version #must
- Verify via user interface or Support Zip Product Version Verification
> Jira Migration Assistant will not work unless Jira is running on a supported version
## Fix any duplicate email addresses #must
- Verify using SQL
> Duplicate email addresses are not supported by Jira Cloud and therefore can't be migrated with the Jira Cloud Migration Assistant. To avoid errors, you should find and fix any duplicate email addresses before migration. If user information is managed in an LDAP Server, you will need to update emails there and sync with Jira before the migration. If user information is managed locally, you can fix them through the Jira Server or Data Center user interface.
## Make sure you have the necessary permissions #must
- System Admin global permissions on the Server instance
- Exists in the target Cloud site
- Site Administrator Permission in the cloud
## Check for conflicts with group names #must
- Make sure that the groups in your Cloud Site don't have the same names as groups in Server
> Unless you are actively trying to merge them
- Delete or update add-on users so not to cause migration issues
- Verify via SQL
## Update firewall allowance rules #must
- None of the domains should be blocked by firewall or proxy
## Find a way to migrate apps #must
- Contact app vendors
## Check public access settings #must
- Projects
- Filters
- Filters
- Boards
- Dashboards
## Review server setup #mst
- at least 4gb Heap Allocation
- Open Files limit review
- Verify via support zip
## Check Server timezone #must for merging Cloud sites
- Switch to UTC is using any other timezone
> Add a system flag to the Jira Server instance -Duser.timezone=UTC as outlined in this article about updating documentation to include timezone details.
## Fix any duplicate shared configuration
## Storage limits
## Prepare the server instance
- Check data status
- All fields have value and are not null
-Any archived projects you wish to migrate are activated
## Prepare your cloud site
- Same Jira products enabled
- Same language
- User migration strategy
## Data backup
- Backup Jira Server site
- Backup Cloud site
## Run a test migration
- Done
## Notify Jira support
- Get in touch with Jira migration support

Use backups

On the one hand, having all of your Jira products on a server may seem like a backup in and of itself. On the other hand, there are data migration best practices we should follow even if it’s just a precaution. No one has ever felt sorry for their data being too safe.

In addition, there are certain types of migration errors that can be resolved much faster with having a backup at hand.

Jira Server Database backup: this step creates a DB backup in an XML format.
1. Log in with Jira System Admin permissions
2. Go to system -> Import and Export -> Backup Manager -> Backup for server.
3. Click the create Backup for server button.
4. Type in the name for your backup.
5. Jira will create a zipped XML file and notify you once the backup is ready.

Jira Cloud Backup: This backup also saves your data in an XML format. The process is quite similar to creating a Jira Server backup with the only difference taking place on the Backups page.
1. Select the option to save your attachments, logos, and avatars.
2. Click on the Create backup button.

As you can see, the Cloud backup includes the option to save attachments, avatars, and logos. This step should be done manually when backing up Server data.
1. Create a Zip archive for this data
2. Make sure it follows the structure suggested by Atlassian

Migrating your Jira instance to the cloud via the Jira Migration Assistant

Jira Cloud Migration Assistant is a free add-on Atlassian recommends using when migrating to the cloud. It accesses and evaluates your apps and helps migrate multiple projects.

Overall, the migration assistant offers a more stable and reliable migration experience. It automatically checks for certain errors. It makes sure all users have unique and valid emails, and makes sure that none of the project names and keys conflict with one another.

This is a step-by-step guide for importing your Jira Server data backup file into Jira Cloud.

Log into Jira Cloud with admin permissions
Go to System -> Import and Export -> External System Import
Click on the Jira Server import option

Select the backup Zip you have created
Jira will check the file for errors and present you with two options: enable or disable outgoing mail. Don’t worry, you will be able to change this section after the migration process is complete.
Then you will be presented with an option to merge Jira Server and Jira Cloud users
1. Choosing overwrite will replace the users with users from the imported files
2. The merge option will merge groups with the same name
3. Lastly, you can select the third option if you are migrating users via Jira’s assistant
Run the import

How do you migrate Jira Server into Jira DC?

Before we can proceed with the migration process, please make sure you meet the following prerequisites:

Make sure you are installing Jira on one of the supported platforms. Atlassian has a list of supported platforms for Jira 9.1.
Make sure the applications you are using are compatible with Jira DC. You will be required to switch to datacenter-compatible versions of your applications (they must be available).
Make sure you meet the necessary software and hardware requirements:
1. You have a DC license
2. You are using a supported database, OS, and Java version
3. You are using OAuth authentication if your application links to other Atlassian products

Once you are certain you are ready to migrate your Jira Server to Jira Data Center, you can proceed with an installation that’s much simpler than one would expect.

Upgrade your apps to be compatible with Jira DC
Go to Administration -> Applications -> Versions and licenses
Enter your Jira DC License Key
Restart Jira

That’s it. You are all set. Well, unless your organization has specific needs such as continuous uptime, performance under heavy loads, and scalability, in which case you will need to set up a server cluster. You can find out more about setting up server clusters in this guide.

Rose Lancy

1596298980

9 Must Know JavaScript Array Methods

Arrays are one of the most common things that you’re going to use as a programmer. So, I’m going to explain nine JavaScript array methods that are going to make your life so much easier and more enjoyable.

To get started I just have an array of items, that we’re going to use for all these different array methods. Without wasting much time, let’s dive deep in to the pool of arrays (wink…)

const arrayItems = [
  {name: 'cheese cake', price: 25},
  {name: 'ham burger', price: 30},
  {name: 'cheesy tacos', price: 20},
  {name: 'beef burito', price: 18},
  {name: 'maxican chille rice', price: 15},
  {name: 'hot chocolate', price: 12},
  {name: 'apple frudge', price: 28},
  {name: 'chicken lassagna', price: 35},
]

filter() method

So let’s assume that we want to get all the items in this list that are less than or equal to 26 dollars of price. All we need to use is the filter method to filter out everything that’s under 26 dollars. So, let’s just say that, we have a variable which is going to be filteredItems. The filter method just takes a single function which is going to have one parameter.

const filteredItems = arrayItems.filter((item) => {
  return item.price <= 26;
})

#web-development #javascript #arrays #array-methods

Shahab Uddin

1588963515

JavaScript array() methods, every JavaScript developer must know

1. push() method allows us to add one or more item at the end of an array.
Example:

let numbers = [1,2,3,4,5];
numbers.push(6); // Adding 6 at the end of the array
console.log(numbers); 
//Output: [1,2,3,4,5,6]

2. pop() method allows us to remove the item from the end of an array.
Example:

let numbers = [1,2,3,4,5];
numbers.pop(); // Removing last item from the array
console.log(numbers); 
//Output: [1,2,3,4]

3. shift() method allow us to remove an item from the front of the array
Example:

let numbers = [1,2,3,4,5];
numbers.shift(); // Removing the first item of the array
console.log(numbers); 
//Output: [2,3,4,5]

4. unshift() method allow us to add new items at the front of the array
Example:

let numbers = [1,2,3,4,5];
numbers.unshift(0); // Adding ‘0’ at the beginning of the array
console.log(numbers);
//Output: [0,1,2,3,4,5]

5. forEach() method will help you to iterate over array’s items.
Example:

let numbers = [1, 2, 3, 4, 5];
numbers.forEach(item => {
	// Let's itrate the given array items and add 1 to each item.
    console.log(item + 1); 
});
//Output: 
2 
3 
4 
5 
6

6. includes() method return booleans to check either your array length includes the specific item passed in the method or not.
Example:

let numbers = [1, 2, 3, 4, 5];
numbers.includes(0); 
//Output: false
numbers.includes(4); 
//Output: true

7. filter() method creates a new array with a subset of elements of the original array.
Example:

Lets create an array object ‘names’ to apply filter()

let names = [
    {name: 'Shahab', age: 35},
    {name: 'Ibaad', age: 10},
    {name: 'Ayaan', age: 30},
    {name: 'Hamad', age: 20},
    {name: 'Pari', age: 22}
];
// Filtering names data by age > 10;
let filterd_items = names.filter(item => item.age > 10);
console.log(filterd_items);

// Output:
0: {name: "Shahab", age: 35}
1: {name: "Ayaan", age: 30}
2: {name: "Hamad", age: 20}
3: {name: "Pari", age: 22}

8. sort() method allows us to sort data and return the elements after changing the positions of the elements in the original array.
The sort() method sorts the array elements in ascending order by default.

let numbers = [1, 5, 2, 0, 40, 3, 10 ];
numbers.sort();
console.log(numbers);
//Output:  [0, 1, 10, 2, 3, 40, 5]

Look at the above output given by sort() method and the output is not as per expected,
To solve this issue, we need to pass a comparison function to the sort() method.

Example:

numbers.sort((a,b) => {
    if(a > b) return 1;
    if(a < b) return -1;
    return 0;
});
console.log(numbers);
//Output: [0, 1, 2, 3, 5, 10, 40]

9. splice() method allows us to delete items in an array, to get result we have to pass two arguments to the splice() method.

Syntax:
Array.splice(position,num);

Example:

let numbers = [1,2,3,4,5];
let deletedNumbs = numbers.splice(0,2);

//The original numbers array now contains only 3 items. i.e: 3,4,5
console.log(numbers); //  [3,4,5]

The new deletedNumbs array contains the deleted items from the original array
console.log(deletedNumbs); // [1, 2]

10. map() method take an array, manipulate its elements, and return a new array by calling the provided function in every element.

Example:

let numbers = [1,2,3,4,5];
Let's multiply each item and get the output doubled
let output = numbers.map(item => item * 2)
console.log(output);
//Output: [2, 4, 6, 8, 10]

#javascript #array #methods #arrowfunction

15 Must Know JavaScript Array Methods

What is GEEK

Buddha Community

Understanding Arrays in Python

Learn how to use Python arrays. Create arrays in Python using the array module. You'll see how to define them and the different methods commonly used for performing operations on them.

Table of Contents

What are Python Arrays?

What's the Difference between Python Lists and Python Arrays?

When to Use Python Arrays

How to Use Arrays in Python

How to Define Arrays in Python

How to Find the Length of an Array in Python

Array Indexing and How to Access Individual Items in an Array in Python

How to Search Through an Array in Python

How to Loop through an Array in Python

How to Slice an Array in Python

Methods For Performing Operations on Arrays in Python

How to Change the Value of an Item in an Array

How to Add a New Value to an Array

How to Remove a Value from an Array

Conclusion

How to Create Arrays in Python

In this tutorial, you'll know the basics of how to create arrays in Python using the array module. Learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.

Table of Contents

What are Python Arrays?

What's the Difference between Python Lists and Python Arrays?

When to Use Python Arrays

How to Use Arrays in Python

How to Define Arrays in Python

How to Find the Length of an Array in Python

Array Indexing and How to Access Individual Items in an Array in Python

How to Search Through an Array in Python

How to Loop through an Array in Python

How to Slice an Array in Python

Methods For Performing Operations on Arrays in Python

How to Change the Value of an Item in an Array

How to Add a New Value to an Array

How to Remove a Value from an Array

Conclusion

Migrating From Jira Server: Guide, Pros, And Cons

Jira Cloud VS Data Center

Pros and cons of Jira Cloud

Pros and cons of Jira Data Center

The Pricing

What should be your User Migration strategy?

How to migrate to Jira Cloud

Pre-migration checklist

Use backups

Migrating your Jira instance to the cloud via the Jira Migration Assistant

How do you migrate Jira Server into Jira DC?

9 Must Know JavaScript Array Methods

filter() method

JavaScript array() methods, every JavaScript developer must know