1659601560
Store up to 64 multiple flags (bit array) in a single integer column with ActiveRecord. From a UI standpoint, it can be used as a multi-select checkbox storage.
Perfect solution to store multiple boolean values such as preferences, notification settings, achievement status, profile options, etc. in a single column.
WHERE languages & 3 > 0
is faster than WHERE (english = true) OR (spanish = true) OR ...
If you want a simple enum column, take a look at EnumAccessor.
If you need to work with huge bit arrays, take a look at Bitwise.
class Profile < ActiveRecord::Base
flag :languages, [:english, :spanish, :chinese, :french, :japanese]
end
# {:english=>1, :spanish=>2, :chinese=>4, :french=>8, :japanese=>16 }
# Instance methods
profile.languages #=> #<ActiveFlag::Value: {:english, :japanese}>
profile.languages.english? #=> true
profile.languages.set?(:english) #=> true
profile.languages.unset?(:english) #=> false
profile.languages.set(:spanish)
profile.languages.unset(:japanese)
profile.languages.raw #=> 3
profile.languages.to_a #=> [:english, :spanish]
profile.languages = [:spanish, :japanese] # Direct assignment that works with forms
# Class methods
Profile.languages.maps #=> {:english=>1, :spanish=>2, :chinese=>4, :french=>8, :japanese=>16 }
Profile.languages.humans #=> {:english=>"English", :spanish=>"Spanish", :chinese=>"Chinese", :french=>"French", :japanese=>"Japanese"}
Profile.languages.pairs #=> {"English"=>:english, "Spanish"=>:spanish, "Chinese"=>:chinese, "French"=>:french, "Japanese"=>:japanese}
Profile.languages.to_array(3) #=> [:english, :spanish]
# Scope methods
Profile.where_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 > 0
Profile.where_all_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 = 10
Profile.where_not_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 = 0
Profile.where_not_all_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 < 10
Profile.languages.set_all!(:chinese) #=> UPDATE "profiles" SET languages = COALESCE(languages, 0) | 4
Profile.languages.unset_all!(:chinese) #=> UPDATE "profiles" SET languages = COALESCE(languages, 0) & ~4
gem 'active_flag'
It is recommended to set 0
by default.
t.integer :languages, null: false, default: 0, limit: 8
# OR
add_column :users, :languages, :integer, null: false, default: 0, limit: 8
limit: 8
is only required if you need more than 32 flags.
For a querying purpose, use where_[column]
, where_all_[column]
, where_not_[column]
and where_not_all_[column]
scopes.
Profile.where_languages(:french) #=> SELECT * FROM profiles WHERE languages & 8 > 0
Also takes multiple values.
Profile.where_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 > 0
By default, it returns profiles that have either French or Spanish.
To get profiles that have both French and Spanish, use:
Profile.where_all_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 = 10
To get profiles that do not have either French or Spanish, use:
Profile.where_not_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 = 0
To get profiles that do not have both French and Spanish, use:
Profile.where_not_all_languages(:french, :spanish) #=> SELECT * FROM profiles WHERE languages & 10 < 10
ActiveFlag
supports i18n just as ActiveModel does.
For instance, create a Japanese translation in config/locales/ja.yml
ja:
active_flag:
profile:
languages:
english: 英語
spanish: スペイン語
chinese: 中国語
french: フランス語
japanese: 日本語
and now to_human
method returns a translated string.
I18n.locale = :ja
profile.languages.to_human #=> ['英語', 'スペイン語']
I18n.locale = :en
profile.languages.to_human #=> ['English', 'Spanish']
Thanks to the translation support, forms just work as you would expect with the pairs
convenience method.
# With FormBuilder
= form_for(@profile) do |f|
= f.collection_check_boxes :languages, Profile.languages.pairs
# With SimpleForm
= simple_form_for(@profile) do |f|
= f.input :languages, as: :check_boxes, collection: Profile.languages.pairs
There are plenty of gems that share the same goal. However they have messy syntax than necessary in my opinion, and I wanted a better API to achieve that goal.
Also, ActiveFlag
has one of the simplest code base that you can easily reason about or hack on.
Author: kenn
Source code: https://github.com/kenn/active_flag
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
1596962520
Given an array A[ ] consisting of non-negative integers and matrix Q[ ][ ] consisting of queries of the following two types:
The task for each query of second type is to print the index of lower_bound of value K.
Examples:
_Input: __A[ ] = {1, 2, 3, 5, 8}, Q[ ][ ] = {{1, 0, 2}, {2, 5}, {1, 3, 5}} _
_Output: __1 _
Explanation:
Query 1: Update A[0] to A[0] + 2. Now A[ ] = {3, 2, 3, 5, 8}
_Query 2: lower_bound of K = 5 in the prefix sum array {3, 5, 8, 13, 21} is 5 and index = 1. _
Query 3: Update A[3] to A[3] + 5. Now A[ ] = {3, 2, 3, 10, 8}
_Input: __A[ ] = {4, 1, 12, 8, 20}, Q[ ] = {{2, 50}, {1, 3, 12}, {2, 50}} _
_Output: __-1 _
Recommended: Please try your approach on {IDE} first, before moving on to the solution.
Naive approach:
The simplest approach is to firstly build a prefix sum array of given array A[ ], and for queries of Type 1, update values and recalculate the prefix sum. For query of Type 2, perform a Binary Search on the prefix sum array to find lower bound.
Time Complexity:_ O(Q*(N*logn))_
_Auxiliary Space: _O(N)
Efficient Approach:
The above approach can be optimized using Fenwick Tree. Using this Data Structure, the update queries in prefix sum array can be performed in logarithmic time.
Follow the steps below to solve the problem:
Below is the implementation of the above approach:
// Java program to implement
// the above appraoch
**import**
java.util.*;
**import**
java.io.*;
**class**
GFG {
// Function to calculate and return
// the sum of arr[0..index]
**static**
**int**
getSum(``**int**
BITree[],
**int**
index)
{
**int**
ans =
0``;
index +=
1``;
// Traverse ancestors
// of BITree[index]
**while**
(index >
0``) {
// Update the sum of current
// element of BIT to ans
ans += BITree[index];
// Update index to that
// of the parent node in
// getSum() view by
// subtracting LSB(Least
// Significant Bit)
index -= index & (-index);
}
**return**
ans;
}
// Function to update the Binary Index
// Tree by replacing all ancestores of
// index by their respective sum with val
**static**
**void**
updateBIT(``**int**
BITree[],
**int**
n,
**int**
index,
**int**
val)
{
index = index +
1``;
// Traverse all ancestors
// and sum with 'val'.
**while**
(index <= n) {
// Add 'val' to current
// node of BIT
BITree[index] += val;
// Update index to that
// of the parent node in
// updateBit() view by
// adding LSB(Least
// Significant Bit)
index += index & (-index);
}
}
// Function to construct the Binary
// Indexed Tree for the given array
**static**
**int**``[] constructBITree(
**int**
arr[],
**int**
n)
{
// Initialize the
// Binary Indexed Tree
**int**``[] BITree =
**new**
**int**``[n +
1``];
**for**
(``**int**
i =
0``; i <= n; i++)
BITree[i] =
0``;
// Store the actual values in
// BITree[] using update()
**for**
(``**int**
i =
0``; i < n; i++)
updateBIT(BITree, n, i, arr[i]);
**return**
BITree;
}
// Function to obtian and return
// the index of lower_bound of k
**static**
**int**
getLowerBound(``**int**
BITree[],
**int**``[] arr,
**int**
n,
**int**
k)
{
**int**
lb = -``1``;
**int**
l =
0``, r = n -
1``;
**while**
(l <= r) {
**int**
mid = l + (r - l) /
2``;
**if**
(getSum(BITree, mid) >= k) {
r = mid -
1``;
lb = mid;
}
**else**
l = mid +
1``;
}
**return**
lb;
}
**static**
**void**
performQueries(``**int**
A[],
**int**
n,
**int**
q[][])
{
// Store the Binary Indexed Tree
**int**``[] BITree = constructBITree(A, n);
// Solve each query in Q
**for**
(``**int**
i =
0``; i < q.length; i++) {
**int**
id = q[i][``0``];
**if**
(id ==
1``) {
**int**
idx = q[i][``1``];
**int**
val = q[i][``2``];
A[idx] += val;
// Update the values of all
// ancestors of idx
updateBIT(BITree, n, idx, val);
}
**else**
{
**int**
k = q[i][``1``];
**int**
lb = getLowerBound(
BITree, A, n, k);
System.out.println(lb);
}
}
}
// Driver Code
**public**
**static**
**void**
main(String[] args)
{
**int**
A[] = {
1``,
2``,
3``,
5``,
8
};
**int**
n = A.length;
**int**``[][] q = { {
1``,
0``,
2
},
{
2``,
5
},
{
1``,
3``,
5
} };
performQueries(A, n, q);
}
}
Output:
1
Time Complexity:_ O(Q*(logN)2)_
Auxiliary Space:_ O(N)_
Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready.
#advanced data structure #arrays #bit magic #mathematical #searching #array-range-queries #bit #prefix-sum
1623911281
Printing an array is a quick way to give us visibility on the values of the contents inside. Sometimes the array values are the desired output of the program.
In this article, we’ll take a look at how to print an array in Java using four different ways.
While the “best way” depends on what your program needs to do, we begin with the simplest method for printing and then show more verbose ways to do it.
#java #array #how to print an array in java #array in java #print an array in java #print
1659199883
With this gem, you can easily generate strings supplying a very simple pattern. Even generate random words in English or Spanish. Also, you can validate if a text fulfills a specific pattern or even generate a string following a pattern and returning the wrong length, value... for testing your applications. Perfect to be used in test data factories.
Also you can use regular expressions (Regexp) to generate strings: /[a-z0-9]{2,5}\w+/.gen
To do even more take a look at nice_hash gem
Add this line to your application's Gemfile:
gem 'string_pattern'
And then execute:
$ bundle
Or install it yourself as:
$ gem install string_pattern
A pattern is a string where we supply these elements "a-b:c" where a is min_length, b is max_length (optional) and c is a set of symbol_type
min_length: minimum length of the string
max_length (optional): maximum length of the string. If not provided, the result will be with the min_length provided
symbol_type: The type of the string we want.
x: from a to z (lowercase)
X: A to Z (capital letters)
L: A to Z and a to z
T: National characters defined on StringPattern.national_chars
n or N: for numbers. 0 to 9
$: special characters, $%&#... (includes blank space)
_: blank space
*: all characters
0: empty string will be accepted. It needs to be at the beginning of the symbol_type string
@: It will generate a valid email following the official algorithm. It cannot be used with other symbol_type
W: for English words, capital and lower. It cannot be used with other symbol_type
w: for English words only lower and words separated by underscore. It cannot be used with other symbol_type
P: for Spanish words, capital and lower. It cannot be used with other symbol_type
p: for Spanish words only lower and words separated by underscore. It cannot be used with other symbol_type
To generate a string following a pattern you can do it using directly the StringPattern class or the generate method in the class, be aware you can always use also the alias method: gen
require 'string_pattern'
#StringPattern class
p StringPattern.generate "10:N"
#>3448910834
p StringPattern.gen "5:X"
#>JDDDK
#String class
p "4:Nx".gen
#>xaa3
#Symbol class
p :"10:T".generate
#>AccBdjklñD
#Array class
p [:"3:N", "fixed", :"3:N"].gen
#>334fixed920
p "(,3:N,) ,3:N,-,2:N,-,2:N".split(',').generate
#>(937) 980-65-05
#Kernel
p gen "3:N"
#>443
If you want to generate for example 1000 strings and be sure all those strings are different you can use:
StringPattern.dont_repeat = true #default: false
1000.times {
puts :"6-20:L/N/".gen
}
StringPattern.cache_values = Hash.new() #to clean the generated values from memory
Using dont_repeat all the generated string during the current run will be unique.
In case you just want one particular string to be unique but not the rest then add to the pattern just in the end the symbol: &
The pattern needs to be a symbol object.
1000.times {
puts :"6-20:L/N/&".gen #will be unique
puts :"10:N".gen
}
To generate a string of the length you want that will include only real words, use the symbol types:
require 'string_pattern'
puts '10-30:W'.gen
#> FirstLieutenant
puts '10-30:w'.gen
#> paris_university
puts '10-30:P'.gen
#> SillaMetalizada
puts '10-30:p'.gen
#> despacho_grande
If you want to use a different word separator than "_" when using 'w' or 'p':
# blank space for example
require 'string_pattern'
StringPattern.word_separator = ' '
puts '10-30:w'.gen
#> paris university
puts '10-30:p'.gen
#> despacho grande
The word list is loaded on the first request to generate words, after that the speed to generate words increases amazingly. 85000 English words and 250000 Spanish words. The vocabularies are a sample of public open sources.
Take in consideration this feature is not supporting all possibilities for Regular expressions but it is fully functional. If you find any bug or limitation please add it to issues: https://github.com/MarioRuiz/string_pattern/issues
In case you want to change the default maximum for repetitions when using * or +: StringPattern.default_infinite = 30
. By default is 10.
If you want to translate a regular expression into an StringPattern use the method we added to Regexp class: to_sp
Examples:
/[a-z0-9]{2-5}\w+/.to_sp
#> ["2-5:nx", "1-10:Ln_"]
#regular expression for UUID v4
/[0-9A-F]{8}-[0-9A-F]{4}-4[0-9A-F]{3}-[89AB][0-9A-F]{3}-[0-9A-F]{12}/.to_sp
#> ["8:n[ABCDEF]", "-", "4:n[ABCDEF]", "-4", "3:n[ABCDEF]", "-", "1:[89AB]", "3:n[ABCDEF]", "-", "12:n[ABCDEF]"]
If you want to generate a random string following the regular expression, you can do it like a normal string pattern:
regexp = /[0-9A-F]{8}-[0-9A-F]{4}-4[0-9A-F]{3}-[89AB][0-9A-F]{3}-[0-9A-F]{12}/
# using StringPattern class
puts StringPattern.generate(regexp)
# using Kernel
puts generate(regexp)
# using generate method added to Regexp class
puts regexp.generate
#using the alias 'gen'
puts regexp.gen
# output:
#>7009574B-6F2F-436E-BB7A-EA5FDA6B4E47
#>5FB1718F-108A-4F62-8170-33C43FD86B1D
#>05745B6F-93BA-475F-8118-DD56E5EAC4D1
#>2D6FC189-8D50-45A8-B182-780193838502
In case you need to specify that the string is generated selecting one or another fixed string or pattern, you can do it by using Array of patterns and in the position you want you can add an array with the possible values
p ["uno:", :"5:N", ['.red','.green', :'3:L'] ].gen
# first position a fixed string: "uno:"
# second position 5 random numbers
# third position one of these values: '.red', '.green' or 3 letters
# example output:
# 'uno:34322.red'
# 'uno:44432.green'
# 'uno:34322.red'
# 'uno:28795xAB'
Take in consideration that this is only available to generate successful strings but not for validation
Also, it's possible to provide the characters we want. To do that we'll use the symbol_type [characters]
If we want to add the character ] we have to write ]]
Examples
# four chars from the ones provided: asDF9
p "4:[asDF9]".gen #> aaaa, asFF, 9sFD
# from 2 to 20 chars, capital and lower chars (Xx) and also valid the characters $#6
p "2-20:[$#6]Xx".gen #> aaaa, asFF, 66, B$DkKL#9aDD
# four chars from these: asDF]9
p "4:[asDF]]9]".gen #> aa]a, asFF, 9s]D
We'll use the symbol / to specify which characters or symbols we want to be included on the resulting string as required values /symbols or characters/
If we need to add the character / we'll use //
Examples:
# four characters. optional: capitals and numbers, required: lower
"4:XN/x/".gen # aaaa, FF9b, j4em, asdf, ADFt
# from 6 to 15 chars. optional: numbers, capitals and the chars $ and Æ. required the chars: 23abCD
"6-15:[/23abCD/$Æ]NX".gen # bCa$D32, 32DJIOKLaCb, b23aD568C
# from 4 to 9 chars. optional: numbers and capitals. required: lowers and the characters $ and 5
"4-9:[/$5/]XN/x/".generate # aa5$, F5$F9b, j$4em5, a5sdf$, $ADFt5
If we want to exclude a few characters in the result, we'll use the symbol %characters%
If you need to exclude the character %, you should use %%
Examples:
# from 2 to 20 characters. optional: Numbers and characters A, B and C. excluded: the characters 8 and 3
"2-20:[%83%ABC]N".gen # B49, 22900, 9CAB, 22, 11CB6270C26C4572A50C
# 10 chars. optional: Letters (capital and lower). required: numbers. excluded: the characters 0 and WXYzZ
"10:L/n/[%0WXYzZ%]".gen # GoO2ukCt4l, Q1Je2remFL, qPg1T92T2H, 4445556781
If we want our resulting string doesn't fulfill the pattern we supply, then we'll use the symbol ! at the beginning
Examples:
"!4:XN/x/".gen # a$aaa, FF9B, j4DDDem, as, 2345
"!10:N".gen # 123, 34899Add34, 3434234234234008, AAFj#kd2x
Usually, for testing purposes you need to generate strings that don't fulfill a specific pattern, then you can supply as a parameter expected_errors (alias: errors)
The possible values you can specify is one or more of these ones: :length, :min_length, :max_length, :value, :required_data, :excluded_data, :string_set_not_allowed
:length: wrong length, minimum or maximum
:min_length: wrong minimum length
:max_length: wrong maximum length
:value: wrong resultant value
:required_data: the output string won't include all necessary required data. It works only if required data supplied on the pattern.
:excluded_data: the resultant string will include one or more characters that should be excluded. It works only if excluded data supplied on the pattern.
:string_set_not_allowed: it will include one or more characters that are not supposed to be on the string.
Examples:
"10-20:N".gen errors: [:min_length]
#> 627, 098262, 3408
"20:N".gen errors: [:length, :value]
#> |13, tS1b)r-1)<RT65202eTo6bV0g~, 021400323<2ahL0NP86a698063*56076
"10:L/n/".gen errors: [:value]
#> 1hwIw;v{KQ, mpk*l]!7:!, wocipgZt8@
If you need to validate if a specific text is fulfilling the pattern you can use the validate method.
If a string pattern supplied and no other parameters supplied the output will be an array with the errors detected.
Possible output values, empty array (validation without errors detected) or one or more of: :min_length, :max_length, :length, :value, :string_set_not_allowed, :required_data, :excluded_data
In case an array of patterns supplied it will return only true or false
Examples:
#StringPattern class
StringPattern.validate((text: "This text will be validated", pattern: :"10-20:Xn")
#> [:max_length, :length, :value, :string_set_not_allowed]
#String class
"10:N".validate "333444"
#> [:min_length, :length]
#Symbol class
:"10:N".validate("333444")
#> [:min_length, :length]
#Array class
["5:L","3:xn","4-10:n"].validate "DjkljFFc343444390"
#> false
If we want to validate a string with a pattern and we are expecting to get specific errors, you can supply the parameter expected_errors (alias: errors) or not_expected_errors (aliases: non_expected_errors, not_errors).
In this case, the validate method will return true or false.
Examples:
"10:N".val "3445", errors: [:min_length]
#> true
"10:N/[09]/".validate "4434039440", errors: [:value]
#> false
"10-12:XN/x/".validate "FDDDDDAA343434", errors: [:max_length, :required_data]
#> true
This gem adds the methods generate (alias: gen) and validate (alias: val) to the Ruby classes: String, Array, and Symbol.
Also adds the method generate (alias: gen) to Kernel. By default (true) it is always added.
In case you don't want to be added, just before requiring the library set:
SP_ADD_TO_RUBY = false
require 'string_pattern'
In case it is set to true (default) then you will be able to use:
require 'string_pattern'
#String object
"20-30:@".gen
#>dkj34MljjJD-df@jfdluul.dfu
"10:L/N/[/-./%d%]".validate("12ds6f--.s")
#>[:value, :string_set_not_allowed]
"20-40:@".validate(my_email)
#Kernel
gen "10:N"
#>3433409877
#Array object
"(,3:N,) ,3:N,-,2:N,-,2:N".split(",").generate
#>(937) 980-65-05
%w{( 3:N ) 1:_ 3:N - 2:N - 2:N}.gen
#>(045) 448-63-09
["1:L", "5-10:LN", "-", "3:N"].gen
#>zqWihV-746
To specify which national characters will be used when using the symbol type: T, you use StringPattern.national_chars, by default is the English alphabet
StringPattern.national_chars = (('a'..'z').to_a + ('A'..'Z').to_a).join + "áéíóúÁÉÍÓÚüÜñÑ"
"10-20:Tn".gen #>AAñ34Ef99éNOP
If true it will check on the strings of the array positions supplied if they have the pattern format and assume in that case that is a pattern. If not it will assume the patterns on the array will be supplied as symbols. By default is set to true.
StringPattern.optimistic = false
["5:X","fixedtext", "3:N"].generate
#>5:Xfixedtext3:N
[:"5:X","fixedtext", :"3:N"].generate
#>AUJKJfixedtext454
StringPattern.optimistic = true
["5:X","fixedtext", "3:N"].generate
#>KKDMEfixedtext344
[:"5:X","fixedtext", :"3:N"].generate
#>SAAERfixedtext988
Bug reports and pull requests are welcome on GitHub at https://github.com/marioruiz/string_pattern.
The gem is available as open source under the terms of the MIT License.
Author: MarioRuiz
Source code: https://github.com/MarioRuiz/string_pattern
License: MIT license