1598529480
JavaScript Array reverse() is an inbuilt function that reverses the order of the items in an array. The reverse() method will change the original array that is why it is not a pure function. Javascript reverse() returns an array that represents the array after it has been reversed. The reverse function does not take any argument.
If you want to reverse the items of the array then Javascript array reverse() function does the job for you.
The first array item becomes the last, and the last array element becomes the first due to the array reverse() method in Javascript.
JS array reverse() method transposes the items of the calling array object in place, mutating the array, and returning a reference to the array.
The reverse() is an intentionally generic method that can be called or applied to objects resembling arrays.
#javascript #js #js array reverse
1677668905
Mocking library for TypeScript inspired by http://mockito.org/
mock
) (also abstract classes) #examplespy
) #examplewhen
) via:verify
)reset
, resetCalls
) #example, #examplecapture
) #example'Expected "convertNumberToString(strictEqual(3))" to be called 2 time(s). But has been called 1 time(s).'
)npm install ts-mockito --save-dev
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance from mock
let foo:Foo = instance(mockedFoo);
// Using instance in source code
foo.getBar(3);
foo.getBar(5);
// Explicit, readable verification
verify(mockedFoo.getBar(3)).called();
verify(mockedFoo.getBar(anything())).called();
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub method before execution
when(mockedFoo.getBar(3)).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.getBar(3));
// prints null, because "getBar(999)" was not stubbed
console.log(foo.getBar(999));
// Creating mock
let mockedFoo:Foo = mock(Foo);
// stub getter before execution
when(mockedFoo.sampleGetter).thenReturn('three');
// Getting instance
let foo:Foo = instance(mockedFoo);
// prints three
console.log(foo.sampleGetter);
Syntax is the same as with getter values.
Please note, that stubbing properties that don't have getters only works if Proxy object is available (ES6).
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(2);
foo.getBar(2);
foo.getBar(3);
// Call count verification
verify(mockedFoo.getBar(1)).once(); // was called with arg === 1 only once
verify(mockedFoo.getBar(2)).twice(); // was called with arg === 2 exactly two times
verify(mockedFoo.getBar(between(2, 3))).thrice(); // was called with arg between 2-3 exactly three times
verify(mockedFoo.getBar(anyNumber()).times(4); // was called with any number arg exactly four times
verify(mockedFoo.getBar(2)).atLeast(2); // was called with arg === 2 min two times
verify(mockedFoo.getBar(anything())).atMost(4); // was called with any argument max four times
verify(mockedFoo.getBar(4)).never(); // was never called with arg === 4
// Creating mock
let mockedFoo:Foo = mock(Foo);
let mockedBar:Bar = mock(Bar);
// Getting instance
let foo:Foo = instance(mockedFoo);
let bar:Bar = instance(mockedBar);
// Some calls
foo.getBar(1);
bar.getFoo(2);
// Call order verification
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(2)); // foo.getBar(1) has been called before bar.getFoo(2)
verify(mockedBar.getFoo(2)).calledAfter(mockedFoo.getBar(1)); // bar.getFoo(2) has been called before foo.getBar(1)
verify(mockedFoo.getBar(1)).calledBefore(mockedBar.getFoo(999999)); // throws error (mockedBar.getFoo(999999) has never been called)
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(10)).thenThrow(new Error('fatal error'));
let foo:Foo = instance(mockedFoo);
try {
foo.getBar(10);
} catch (error:Error) {
console.log(error.message); // 'fatal error'
}
You can also stub method with your own implementation
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
when(mockedFoo.sumTwoNumbers(anyNumber(), anyNumber())).thenCall((arg1:number, arg2:number) => {
return arg1 * arg2;
});
// prints '50' because we've changed sum method implementation to multiply!
console.log(foo.sumTwoNumbers(5, 10));
You can also stub method to resolve / reject promise
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.fetchData("a")).thenResolve({id: "a", value: "Hello world"});
when(mockedFoo.fetchData("b")).thenReject(new Error("b does not exist"));
You can reset just mock call counter
// Creating mock
let mockedFoo:Foo = mock(Foo);
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
foo.getBar(1);
foo.getBar(1);
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
resetCalls(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
You can also reset calls of multiple mocks at once resetCalls(firstMock, secondMock, thirdMock)
Or reset mock call counter with all stubs
// Creating mock
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn("one").
// Getting instance
let foo:Foo = instance(mockedFoo);
// Some calls
console.log(foo.getBar(1)); // "one" - as defined in stub
console.log(foo.getBar(1)); // "one" - as defined in stub
verify(mockedFoo.getBar(1)).twice(); // getBar with arg "1" has been called twice
// Reset mock
reset(mockedFoo);
// Call count verification
verify(mockedFoo.getBar(1)).never(); // has never been called after reset
console.log(foo.getBar(1)); // null - previously added stub has been removed
You can also reset multiple mocks at once reset(firstMock, secondMock, thirdMock)
let mockedFoo:Foo = mock(Foo);
let foo:Foo = instance(mockedFoo);
// Call method
foo.sumTwoNumbers(1, 2);
// Check first arg captor values
const [firstArg, secondArg] = capture(mockedFoo.sumTwoNumbers).last();
console.log(firstArg); // prints 1
console.log(secondArg); // prints 2
You can also get other calls using first()
, second()
, byCallIndex(3)
and more...
You can set multiple returning values for same matching values
const mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(anyNumber())).thenReturn('one').thenReturn('two').thenReturn('three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinitely
Another example with specific values
let mockedFoo:Foo = mock(Foo);
when(mockedFoo.getBar(1)).thenReturn('one').thenReturn('another one');
when(mockedFoo.getBar(2)).thenReturn('two');
let foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(2)); // two
console.log(foo.getBar(1)); // another one
console.log(foo.getBar(1)); // another one - this is last defined behavior for arg '1' so it will be repeated
console.log(foo.getBar(2)); // two
console.log(foo.getBar(2)); // two - this is last defined behavior for arg '2' so it will be repeated
Short notation:
const mockedFoo:Foo = mock(Foo);
// You can specify return values as multiple thenReturn args
when(mockedFoo.getBar(anyNumber())).thenReturn('one', 'two', 'three');
const foo:Foo = instance(mockedFoo);
console.log(foo.getBar(1)); // one
console.log(foo.getBar(1)); // two
console.log(foo.getBar(1)); // three
console.log(foo.getBar(1)); // three - last defined behavior will be repeated infinity
Possible errors:
const mockedFoo:Foo = mock(Foo);
// When multiple matchers, matches same result:
when(mockedFoo.getBar(anyNumber())).thenReturn('one');
when(mockedFoo.getBar(3)).thenReturn('one');
const foo:Foo = instance(mockedFoo);
foo.getBar(3); // MultipleMatchersMatchSameStubError will be thrown, two matchers match same method call
You can mock interfaces too, just instead of passing type to mock
function, set mock
function generic type Mocking interfaces requires Proxy
implementation
let mockedFoo:Foo = mock<FooInterface>(); // instead of mock(FooInterface)
const foo: SampleGeneric<FooInterface> = instance(mockedFoo);
You can mock abstract classes
const mockedFoo: SampleAbstractClass = mock(SampleAbstractClass);
const foo: SampleAbstractClass = instance(mockedFoo);
You can also mock generic classes, but note that generic type is just needed by mock type definition
const mockedFoo: SampleGeneric<SampleInterface> = mock(SampleGeneric);
const foo: SampleGeneric<SampleInterface> = instance(mockedFoo);
You can partially mock an existing instance:
const foo: Foo = new Foo();
const spiedFoo = spy(foo);
when(spiedFoo.getBar(3)).thenReturn('one');
console.log(foo.getBar(3)); // 'one'
console.log(foo.getBaz()); // call to a real method
You can spy on plain objects too:
const foo = { bar: () => 42 };
const spiedFoo = spy(foo);
foo.bar();
console.log(capture(spiedFoo.bar).last()); // [42]
Author: NagRock
Source Code: https://github.com/NagRock/ts-mockito
License: MIT license
1670560264
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.
Let's get started!
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.
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.
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.
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
:
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()
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()
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()
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.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.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:
import array as arr
.numbers
array.arr.array()
because of import array as arr
.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.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.
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
.
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
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
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
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])
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.
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])
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])
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])
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
1666082925
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.
Let's get started!
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.
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.
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.
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
:
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()
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()
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()
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.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.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:
import array as arr
.numbers
array.arr.array()
because of import array as arr
.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.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.
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
.
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
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
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
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])
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.
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])
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])
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])
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
1632537859
Not babashka. Node.js babashka!?
Ad-hoc CLJS scripting on Node.js.
Experimental. Please report issues here.
Nbb's main goal is to make it easy to get started with ad hoc CLJS scripting on Node.js.
Additional goals and features are:
Nbb requires Node.js v12 or newer.
CLJS code is evaluated through SCI, the same interpreter that powers babashka. Because SCI works with advanced compilation, the bundle size, especially when combined with other dependencies, is smaller than what you get with self-hosted CLJS. That makes startup faster. The trade-off is that execution is less performant and that only a subset of CLJS is available (e.g. no deftype, yet).
Install nbb
from NPM:
$ npm install nbb -g
Omit -g
for a local install.
Try out an expression:
$ nbb -e '(+ 1 2 3)'
6
And then install some other NPM libraries to use in the script. E.g.:
$ npm install csv-parse shelljs zx
Create a script which uses the NPM libraries:
(ns script
(:require ["csv-parse/lib/sync$default" :as csv-parse]
["fs" :as fs]
["path" :as path]
["shelljs$default" :as sh]
["term-size$default" :as term-size]
["zx$default" :as zx]
["zx$fs" :as zxfs]
[nbb.core :refer [*file*]]))
(prn (path/resolve "."))
(prn (term-size))
(println (count (str (fs/readFileSync *file*))))
(prn (sh/ls "."))
(prn (csv-parse "foo,bar"))
(prn (zxfs/existsSync *file*))
(zx/$ #js ["ls"])
Call the script:
$ nbb script.cljs
"/private/tmp/test-script"
#js {:columns 216, :rows 47}
510
#js ["node_modules" "package-lock.json" "package.json" "script.cljs"]
#js [#js ["foo" "bar"]]
true
$ ls
node_modules
package-lock.json
package.json
script.cljs
Nbb has first class support for macros: you can define them right inside your .cljs
file, like you are used to from JVM Clojure. Consider the plet
macro to make working with promises more palatable:
(defmacro plet
[bindings & body]
(let [binding-pairs (reverse (partition 2 bindings))
body (cons 'do body)]
(reduce (fn [body [sym expr]]
(let [expr (list '.resolve 'js/Promise expr)]
(list '.then expr (list 'clojure.core/fn (vector sym)
body))))
body
binding-pairs)))
Using this macro we can look async code more like sync code. Consider this puppeteer example:
(-> (.launch puppeteer)
(.then (fn [browser]
(-> (.newPage browser)
(.then (fn [page]
(-> (.goto page "https://clojure.org")
(.then #(.screenshot page #js{:path "screenshot.png"}))
(.catch #(js/console.log %))
(.then #(.close browser)))))))))
Using plet
this becomes:
(plet [browser (.launch puppeteer)
page (.newPage browser)
_ (.goto page "https://clojure.org")
_ (-> (.screenshot page #js{:path "screenshot.png"})
(.catch #(js/console.log %)))]
(.close browser))
See the puppeteer example for the full code.
Since v0.0.36, nbb includes promesa which is a library to deal with promises. The above plet
macro is similar to promesa.core/let
.
$ time nbb -e '(+ 1 2 3)'
6
nbb -e '(+ 1 2 3)' 0.17s user 0.02s system 109% cpu 0.168 total
The baseline startup time for a script is about 170ms seconds on my laptop. When invoked via npx
this adds another 300ms or so, so for faster startup, either use a globally installed nbb
or use $(npm bin)/nbb script.cljs
to bypass npx
.
Nbb does not depend on any NPM dependencies. All NPM libraries loaded by a script are resolved relative to that script. When using the Reagent module, React is resolved in the same way as any other NPM library.
To load .cljs
files from local paths or dependencies, you can use the --classpath
argument. The current dir is added to the classpath automatically. So if there is a file foo/bar.cljs
relative to your current dir, then you can load it via (:require [foo.bar :as fb])
. Note that nbb
uses the same naming conventions for namespaces and directories as other Clojure tools: foo-bar
in the namespace name becomes foo_bar
in the directory name.
To load dependencies from the Clojure ecosystem, you can use the Clojure CLI or babashka to download them and produce a classpath:
$ classpath="$(clojure -A:nbb -Spath -Sdeps '{:aliases {:nbb {:replace-deps {com.github.seancorfield/honeysql {:git/tag "v2.0.0-rc5" :git/sha "01c3a55"}}}}}')"
and then feed it to the --classpath
argument:
$ nbb --classpath "$classpath" -e "(require '[honey.sql :as sql]) (sql/format {:select :foo :from :bar :where [:= :baz 2]})"
["SELECT foo FROM bar WHERE baz = ?" 2]
Currently nbb
only reads from directories, not jar files, so you are encouraged to use git libs. Support for .jar
files will be added later.
The name of the file that is currently being executed is available via nbb.core/*file*
or on the metadata of vars:
(ns foo
(:require [nbb.core :refer [*file*]]))
(prn *file*) ;; "/private/tmp/foo.cljs"
(defn f [])
(prn (:file (meta #'f))) ;; "/private/tmp/foo.cljs"
Nbb includes reagent.core
which will be lazily loaded when required. You can use this together with ink to create a TUI application:
$ npm install ink
ink-demo.cljs
:
(ns ink-demo
(:require ["ink" :refer [render Text]]
[reagent.core :as r]))
(defonce state (r/atom 0))
(doseq [n (range 1 11)]
(js/setTimeout #(swap! state inc) (* n 500)))
(defn hello []
[:> Text {:color "green"} "Hello, world! " @state])
(render (r/as-element [hello]))
Working with callbacks and promises can become tedious. Since nbb v0.0.36 the promesa.core
namespace is included with the let
and do!
macros. An example:
(ns prom
(:require [promesa.core :as p]))
(defn sleep [ms]
(js/Promise.
(fn [resolve _]
(js/setTimeout resolve ms))))
(defn do-stuff
[]
(p/do!
(println "Doing stuff which takes a while")
(sleep 1000)
1))
(p/let [a (do-stuff)
b (inc a)
c (do-stuff)
d (+ b c)]
(prn d))
$ nbb prom.cljs
Doing stuff which takes a while
Doing stuff which takes a while
3
Also see API docs.
Since nbb v0.0.75 applied-science/js-interop is available:
(ns example
(:require [applied-science.js-interop :as j]))
(def o (j/lit {:a 1 :b 2 :c {:d 1}}))
(prn (j/select-keys o [:a :b])) ;; #js {:a 1, :b 2}
(prn (j/get-in o [:c :d])) ;; 1
Most of this library is supported in nbb, except the following:
:syms
.-x
notation. In nbb, you must use keywords.See the example of what is currently supported.
See the examples directory for small examples.
Also check out these projects built with nbb:
See API documentation.
See this gist on how to convert an nbb script or project to shadow-cljs.
Prequisites:
To build:
bb release
Run bb tasks
for more project-related tasks.
Download Details:
Author: borkdude
Download Link: Download The Source Code
Official Website: https://github.com/borkdude/nbb
License: EPL-1.0
#node #javascript
1598445240
JavaScript Array reverse() is an inbuilt function that reverses the order of the items in an array. The reverse() method will change the original array that is why it is not a pure function. Javascript reverse() returns an array that represents the array after it has been reversed. The reverse function does not take any argument.
If you want to reverse the items of the array then Javascript array reverse() function does the job for you.
The first array item becomes the last, and the last array element becomes the first due to the array reverse() method in Javascript.
JS array reverse() method transposes the items of the calling array object in place, mutating the array, and returning a reference to the array.
#javascript #js #js array reverse()