Navigating ESA Letter Laws in 10 US States

Emotional Support Animals (ESAs) are something past pets. They give companionship, comfort, and love to individuals who experience the evil impacts of mental prosperity issues. Under the Fair Housing Act (FHA) and the Air Transporter Access Act (ACAA), ESAs are allowed to live with their owners in housing and travel on airplanes. Notwithstanding, to participate in these honors, individuals ought to procure an esa letter. In this article, we will look at what an esa letter is, the method for getting one, and how it works in 10 US states.

To get an ESA letter, individuals ought to follow the accompanying advances:

Survey Whether You Fit the bill for an ESA

To possess all the necessary qualities for an ESA, individuals ought to have an analyzed emotional health issue that significantly impacts their regular presence. Typical mental health gives that fit the bill for an ESA consolidate anxiety, horror, post-terrible tension issue (PTSD), and thought inadequacy hyperactivity mix (ADHD).

Find an Approved Emotional prosperity Capable

Individuals ought to find an approved emotional wellbeing master to give their ESA letter. This can be an approved subject matter expert, clinician, or specialist. A couple of electronic organizations, such as RealEsaLetter, outfit telehealth meetings to communicate individuals with approved mental health specialists.

Plan an Arrangement

Ensuing to find an approved mental prosperity capable, individuals ought to plan an arrangement for an evaluation. During the arrangement, the emotional prosperity capable will review the individual's emotional prosperity and choose if an ESA is fundamental.

Get the ESA Letter

Expecting the mental prosperity capable of confirming that an ESA is important, they will give the individual an ESA letter. The letter ought to consolidate the basic information represented in the past fragment. To get an esa letter from doctor, you ought to get medication from an approved mental wellbeing capable.

Here is the altered fragment looking at ESAs in 10 unmistakable US states:

Oregon

In Oregon, individuals with ESAs are protected by state guidelines. Landlords are not permitted to charge additional pet costs for ESAs. Besides, individuals with ESAs are allowed to live in housing that doesn't allow pets.

Michigan

The fact that it safeguards individuals with ESAs makes michigan another express. Landlords are not allowed to charge additional pet costs for ESAs, and individuals with ESAs are permitted to live in housing that doesn't allow pets.

North Carolina

In North Carolina, landlords are allowed to charge additional pet costs for ESAs. In any case, individuals with ESAs are permitted to live in housing that doesn't allow pets. It is important to observe that ESAs are not allowed there.

Utah

In Utah, landlords are allowed to charge additional pet costs for ESAs. In any case, individuals with ESAs are permitted to live in housing that doesn't allow pets. Moreover, individuals with ESAs are allowed to go with their animals in the hotel of an airplane without additional charges.

Pennsylvania

Pennsylvania has guidelines like those in Utah. Landlords are allowed to charge additional pet costs for ESAs, yet individuals with ESAs are permitted to live in housing that doesn't allow pets. Likewise, individuals with ESAs are allowed to go with their animals in the hotel of an airplane without additional costs.

Illinois

In Illinois, landlords are not permitted to charge additional pet costs for ESAs. In any case, landlords can demand an ESA letter from an approved mental prosperity capable of actually looking at the necessity for an ESA. Individuals with ESAs are allowed to live in housing that doesn't allow pets.

Virginia

Virginia is a freeway that licenses landlords to charge additional pet costs for ESAs. Regardless, individuals with ESAs are allowed to live in housing that doesn't allow pets. It is important to observe that ESAs are not allowed there in Virginia.

Colorado

In Colorado, landlords are not permitted to charge additional pet costs for ESAs. Notwithstanding, landlords can demand an ESA letter from an approved mental prosperity capable of affirming the necessity for an ESA. Individuals with ESAs are allowed to live in housing that doesn't allow pets.

Alabama

In Alabama, landlords are allowed to charge additional pet costs for ESAs. Anyway, individuals with ESAs are permitted to live in housing that doesn't allow pets. Also, individuals with ESAs are allowed to go with their animals in the hotel of an airplane without additional charges.

Washington

Washington is another express that has protective guidelines for individuals with ESAs. Landlords are not permitted to charge additional pet costs for ESAs, and individuals with ESAs are allowed to live in housing that doesn't allow pets. Additionally, individuals with ESAs are allowed to go with their animals in the cabin of an airplane without additional costs.

Considering everything, regular reassurance animals can give truly fundamental comfort and support for individuals fighting with mental health issues. In any case, investigating the standards and rules enveloping ESAs can be problematic, especially with respect to securing an ESA letter. In case you are excited about getting an esa letter for dog, there are a couple of things you should know about.

Individuals truly should chat with an approved mental prosperity capable of concluding whether an ESA would be useful for their emotional prosperity and to get the fundamental documentation to guarantee they have the authentic right to live with their ESA and travel with them in the cabin of an airplane. By understanding the guidelines concerning ESAs in their state, individuals can guarantee that they and their shaggy companions are obtained and maintained.

In case you are excited about getting an esa letter for a substitute sort of animal, it is important to investigate the guidelines in your state to guarantee that the animal is allowed without trying to hide places and in speculation properties.

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Corey Brooks

1657254050

Top 9+ Common CSS Mistakes To Avoid

In this tutorial, we'll summarise what the top 9+ CSS mistakes are and how to avoid them.

Top 9+ Common CSS Mistakes To Avoid

It’s easy to get tripped up with CSS. Here are some common CSS mistakes we all make.

1. Not Using a Proper CSS Reset

Web browsers are our fickle friends. Their inconsistencies can make any developer want to tear their hair out. But at the end of the day, they’re what will present your website, so you better do what you have to do to please them.

One of the sillier things browsers do is provide default styling for HTML elements. I suppose you can’t really blame them: what if a “webmaster” chose not to style their page? There has to be a fallback mechanism for people who choose not to use CSS.

In any case, there’s rarely a case of two browsers providing identical default styling, so the only real way to make sure your styles are effective is to use a CSS reset. What a CSS reset entails is resetting (or, rather, setting) all the styles of all the HTML elements to a predictable baseline value. The beauty of this is that once you include a CSS reset effectively, you can style all the elements on your page as if they were all the same to start with.

It’s a blank slate, really. There are many CSS reset codebases on the web that you can incorporate into your work. I personally use a modified version of the popular Eric Meyer reset and Six Revisions uses a modified version of YUI Reset CSS.

You can also build your own reset if you think it would work better. What many of us do is utilizing a simple universal selector margin/padding reset.

* { margin:0; padding:0; }

Though this works, it’s not a full reset.

You also need to reset, for example, borders, underlines, and colors of elements like list items, links, and tables so that you don’t run into unexpected inconsistencies between web browsers. Learn more about resetting your styles via this guide: Resetting Your Styles with CSS Reset.

2. Over-Qualifying Selectors

Being overly specific when selecting elements to style is not good practice. The following selector is a perfect example of what I’m talking about:

ul#navigation li a { ... }

Typically the structure of a primary navigation list is a <ul> (usually with an ID like #nav or #navigation) then a few list items (<li>) inside of it, each with its own <a> tag inside it that links to other pages.

This HTML structure is perfectly correct, but the CSS selector is really what I’m worried about. First things first: There’s no reason for the ul before #navigation as an ID is already the most specific selector. Also, you don’t have to put li in the selector syntax because all the a elements inside the navigation are inside list items, so there’s no reason for that bit of specificity.

Thus, you can condense that selector as:

#navigation a { ... }

This is an overly simplistic example because you might have nested list items that you want to style differently (i.e. #navigation li a is different from #navigation li ul li a); but if you don’t, then there’s no need for the excessive specificity.

I also want to talk about the need for an ID in this situation. Let’s assume for a minute that this navigation list is inside a header div (#header). Let us also assume that you will have no other unordered list in the header besides the navigation list.

If that is the case, we can even remove the ID from the unordered list in our HTML markup, and then we can select it in CSS as such:

#header ul a { ... }

Here’s what I want you to take away from this example: Always write your CSS selectors with the very minimum level of specificity necessary for it to work. Including all that extra fluff may make it look more safe and precise, but when it comes to CSS selectors, there are only two levels of specificity: specific, and not specific enough.

3. Not Using Shorthand Properties

Take a look at the following property list:

#selector { margin-top: 50px; margin-right: 0; margin-bottom: 50px; margin-left 0; }

What is wrong with this picture? I hope that alarm bells are ringing in your head as you notice how much we’re repeating ourselves. Fortunately, there is a solution, and it’s using CSS shorthand properties.

The following has the same effect as the above style declaration, but we’ve reduced our code by three lines.

#selector { margin: 50px 0; }

Check out this list of properties that deals with font styles:

font-family: Helvetica; font-size: 14px; font-weight: bold; line-height: 1.5;

We can condense all that into one line:

font: bold 14px/1.5 Helvetica;

We can also do this for background properties. The following:

background-image: url(background.png); background-repeat: repeat-y; background-position: center top;

Can be written in shorthand CSS as such:

background: url(background.png) repeat-y center top;

4. Using 0px instead of 0

Say you want to add a 20px margin to the bottom of an element. You might use something like this:

#selector { margin: 20px 0px 20px 0px; }

Don’t. This is excessive.

There’s no need to include the px after 0. While this may seem like I’m nitpicking and that it may not seem like much, when you’re working with a huge file, removing all those superfluous px can reduce the size of your file (which is never a bad thing).

5. Using Color Names Instead of Hexadecimal

Declaring red for color values is the lazy man’s #FF0000. By saying:

color: red;

You’re essentially saying that the browser should display what it thinks red is. If you’ve learned anything from making stuff function correctly in all browsers — and the hours of frustration you’ve accumulated because of a stupid list-bullet misalignment that can only be seen in IE7 — it’s that you should never let the browser decide how to display your web pages.

Instead, you should go to the effort to find the actual hex value for the color you’re trying to use. That way, you can make sure it’s the same color displayed across all browsers. You can use a color cheatsheet that provides a preview and the hex value of a color.

This may seem trivial, but when it comes to CSS, it’s the tiny things that often lead to the big gotchas.

6. Redundant Selectors

My process for writing styles is to start with all the typography, and then work on the structure, and finally on styling all the colors and backgrounds. That’s what works for me. Since I don’t focus on just one element at a time, I commonly find myself accidentally typing out a redundant style declaration.

I always do a final check after I’m done so that I can make sure that I haven’t repeated any selectors; and if I have, I’ll merge them. This sort of mistake is fine to make while you’re developing, but just try to make sure they don’t make it into production.

7. Redundant Properties

Similar to the one above, I often find myself having to apply the same properties to multiple selectors. This could be styling an <h5> in the header to look exactly like the <h6> in the footer, making the <pre>‘s and <blockquote>‘s the same size, or any number of things in between. In the final review of my CSS, I will look to make sure that I haven’t repeated too many properties.

For example, if I see two selectors doing the same thing, such as this:

#selector-1 { font-style: italic; color: #e7e7e7; margin: 5px; padding: 20px } .selector-2 { font-style: italic; color: #e7e7e7; margin: 5px; padding: 20px }

I will combine them, with the selectors separated by a comma (,):

#selector-1, .selector-2 { font-style: italic; color: #e7e7e7; margin: 5px; padding: 20px }

I hope you’re seeing the trend here: Try to be as terse and as efficient as possible. It pays dividends in maintenance time and page-load speed.

8. Not Providing Fallback Fonts

In a perfect world, every computer would always have every font you would ever want to use installed. Unfortunately, we don’t live in a perfect world. @font-face aside, web designers are pretty much limited to the few so called web-safe fonts (e.g.

Arial, Georgia, serif, etc.). There is a plus side, though. You can still use fonts like Helvetica that aren’t necessarily installed on every computer.

The secret lies in font stacks. Font stacks are a way for developers to provide fallback fonts for the browser to display if the user doesn’t have the preferred font installed. For example:

#selector { font-family: Helvetica; }

Can be expanded with fallback fonts as such:

#selector { font-family: Helvetica, Arial, sans-serif; }

Now, if the user doesn’t have Helvetica, they can see your site in Arial, and if that doesn’t work, it’ll just default to any sans-serif font installed.

By defining fallback fonts, you gain more control as to how your web pages are rendered.

9. Unnecessary Whitespace

When it comes to trying to reduce your CSS file sizes for performance, every space counts. When you’re developing, it’s OK to format your code in the way that you’re comfortable with. However, there is absolutely no reason not to take out excess characters (a process known as minification) when you actually push your project onto the web where the size of your files really counts.

Too many developers simply don’t minify their files before launching their websites, and I think that’s a huge mistake. Although it may not feel like it makes much of a difference, when you have huge CSS files

10. Not Organizing Your CSS in a Logical Way

When you’re writing CSS, do yourself a favor and organize your code. Through comments, you can insure that the next time you come to make a change to a file you’ll still be able to navigate it.

I personally like to organize my styles by how the HTML that I’m styling is structured. This means that I have comments that distinguish the header, body, sidebar, and footer. A common CSS-authoring mistake I see is people just writing up their styles as soon as they think of them.

The next time you try to change something and can’t find the style declaration, you’ll be silently cursing yourself for not organizing your CSS well enough.

11. Using Only One Stylesheet for Everything

This one’s subjective, so bear with me while I give you my perspective. I am of the belief, as are others, that it is better to split stylesheets into a few different ones for big sites for easier maintenance and for better modularity. Maybe I’ll have one for a CSS reset, one for IE-specific fixes, and so on.

By organizing CSS into disparate stylesheets, I’ll know immediately where to find a style I want to change. You can do this by importing all the stylesheets into a stylesheet like so:

@import url("reset.css"); @import url("ie.css"); @import url("typography.css"); @import url("layout.css");

Let me stress, however, that this is what works for me and many other developers. You may prefer to squeeze them all in one file, and that’s okay; there’s nothing wrong with that.

But if you’re having a hard time maintaining a single file, try splitting your CSS up.

12. Not Providing a Print Stylesheet

In order to style your site on pages that will be printed, all you have to do is utilize and include a print stylesheet. It’s as easy as:

<link rel="stylesheet" href="print.css" media="print" />

Using a stylesheet for print allows you to hide elements you don’t want printed (such as your navigation menu), reset the background color to white, provide alternative typography for paragraphs so that it’s better suited on a piece of paper, and so forth. The important thing is that you think about how your page will look when printed.

Too many people just don’t think about it, so their sites will simply print the same way you see them on the screen.

I Made These 2 BEGINNER CSS Mistakes

No matter how long you've been writing code, it's always a good time to revisit the basics. While working on a project the other day, I made 2 beginner mistakes with the CSS I was writing. I misunderstood both CSS specificity and how transform:scale affects the DOM!

Stack Overflow about transform:scale - https://stackoverflow.com/questions/32835144/css-transform-scale-does-not-change-dom-size
CSS Specificity - https://www.w3schools.com/css/css_specificity.asp

#css

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.

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.

Thanks for reading and happy coding!

#python #programming

Connor Mills

1670560264

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

Melinda Drury

1676521086