How to delete a key from a Python dictionary

Estimated reading time: 2 minutes

This is an addition to the list of questions you may get when in an interview and you are asked to give an overview of Python.

As with how to create an empty dictionary in Python, how to add values to a python dictionary, and how to sort a python dictionary we will take you through the steps here of how to delete a key from a python dictionary.

How to delete a key from a Python dictionary.

How to use the pop() method to delete a key from a dictionary

In the below example we tell Python to find the key “Key1”, then when it does it prints the python dictionary without that key or its value.

empty_dict1 = {}

empty_dict1['Key2'] = '2'
empty_dict1['Key1'] = '1'
empty_dict1['Key3'] = '3'
print(empty_dict1)

#1. Use the pop function
empty_dict1.pop('Key1')
print(empty_dict1)

Result:
{'Key2': '2', 'Key3': '3'}

How to use the Del keyword to delete a key from a dictionary

In this example, we are taking the output of the above example, and just telling the logic to remove the key “Key2” then what it does is it prints the python dictionary without that key or its value.

del empty_dict1["Key2"]
print(empty_dict1)

Result:
{'Key3': '3'}

How to use dict.clear() to delete a key from a dictionary

In this final example, we use dict.clear(). Note this will empty everything out of the dictionary, so be careful in its use.

As can be seen, it takes the output of the previous example and empties it completely.

empty_dict1.clear() # Removes everything from the dictionary.
print(empty_dict1)

Result:
{}

How to sort a Python Dictionary

Estimated reading time: 3 minutes

In our Python Overview Interview Questions we started off the process of trying to prepare you how to answer any questions that may come up in an interview scenario.

We then moved on to show how to discuss Python Dictionary Interview Questions and what may come up.

One of the questions that you may be asked is how to deal with sorting a python dictionary using a key.

Some of the ways that you may want to sort are as follows, read on for code examples:

Python Dictionary Interview Questions

How to use the sorted and Items Method in Python

In the below code, we have created an empty dictionary and then appened in three key-value pairs.

The first print statement just prints out the dictionary in its unordered fashion.

The second print statement does two things:

  1. It, first of all, sorts the empty_dict1 items in order
  2. Then it goes and creates them in a dictionary.

The reason we have to do step two is that the sorted() function returns a sorted list, as a result, it is not in a dictionary format.

empty_dict1 = {}

empty_dict1['Key2'] = '2'
empty_dict1['Key1'] = '1'
empty_dict1['Key3'] = '3'
print("Your unsorted by key dictionary is:",empty_dict1)
print("Your sorted by key dictionary is:",dict(sorted(empty_dict1.items())))

Result:
Your unsorted by key dictionary is: {'Key2': '2', 'Key1': '1', 'Key3': '3'}
Your sorted by key dictionary is: {'Key1': '1', 'Key2': '2', 'Key3': '3'}

How to use List comprehension to sort a dictionary

As a follow on to the above, we could also just iterate over the dictionary using list comprehensions.

The below creates a variable called d. This is set equal to the output of the list comprehension.

Note that inside the {} brackets you have a:b, this purely creates two sets of values that will be used as the output to generate the dictionary.

You will also see that this creates index values, starting at 0, not the actual values we want.

As a result, we just drop these index values and replace them with the values we want using the pop() method.

The final two print statements show the before and after of sorting the dictionary!

d = {a:b for a, b in enumerate(empty_dict1.values())}
print(d)
d["Key2"] = d.pop(0) #replaces 0 with Key2
d["Key1"] = d.pop(1) #replaces 1 with Key1
d["Key3"] = d.pop(2) #replaces 2 with Key3
print(d)
print(dict(sorted(d.items())))

Result:
{0: '2', 1: '1', 2: '3'}
{'Key2': '2', 'Key1': '1', 'Key3': '3'}
{'Key1': '1', 'Key2': '2', 'Key3': '3'}

How To Add Values to a Python Dictionary

Estimated reading time: 1 minute

As part of our ongoing series about Python Interview questions, we discussed how you would create an empty dictionary.

In this posting, we are going to go through the different ways you could add values to your dictionary.

In the below code, we have created an empty dictionary for you.

So as we go down through lines 5 and 6, you can see that we have created two key names and assigned them values. This has the result of populating those key-value pairs to empty_dict1.

Now as you build out your Python logic, you may just want to update the dictionary by using empty_dict1.update(Add key-value pair here).

Finally, there is the option to just use an if statement that checks if the values you want to add exist already, and if not it adds them in.

#How do add values to a python dictionary
empty_dict1 = {}
empty_dict2 = dict()

empty_dict1['Key1'] = '1'
empty_dict1['Key2'] = '2'
print(empty_dict1)

#Example1 - #Appending values to a python dictionary
empty_dict1.update({'key3': '3'})
print(empty_dict1)

#Example2 - Use an if statement
if "key4" not in empty_dict1:
    empty_dict1["key4"] = '4'
else:
    print("Key exists, so not added")
print(empty_dict1)

Output:
{'Key1': '1', 'Key2': '2'}
{'Key1': '1', 'Key2': '2', 'key3': '3'}
{'Key1': '1', 'Key2': '2', 'key3': '3', 'key4': '4'}

Python Dictionary Interview Questions

Estimated reading time: 6 minutes

In our first video on python interview questions we discussed some of the high-level questions you may be asked in an interview.

In this post, we will discuss interview questions about python dictionaries.

So what are Python dictionaries and their properties?

First of all, they are mutable, meaning they can be changed, please read on to see examples.

As a result, you can add or take away key-value pairs as you see fit.

Also, key names can be changed.

One of the other properties that should be noted is that they are case-sensitive, meaning the same key name can exist if it is in different caps.

So how do you create an empty dictionary in Python?

As can be seen below, the process is straightforward, you just declare a variable equal to two curly brackets, and hey presto you are up and running.

An alternative is to declare a variable equal to dict(), and in an instance, you have an empty dictionary.

The below block of code should be a good example of how to do this:

# How do you create an empty dictionary?
empty_dict1 = {}
empty_dict2 = dict()
print(empty_dict1)
print(empty_dict2)
print(type(empty_dict1))
print(type(empty_dict2))

Output:
{}
{}
<class 'dict'>
<class 'dict'>

How do you add values to a Python dictionary?

If you want to add values to your Python dictionary, there are several ways possible, the below code, can help you get a better idea:

#How do add values to a python dictionary
empty_dict1 = {}
empty_dict2 = dict()

empty_dict1['Key1'] = '1'
empty_dict1['Key2'] = '2'
print(empty_dict1)

#Example1 - #Appending values to a python dictionary
empty_dict1.update({'key3': '3'})
print(empty_dict1)

#Example2 - Use an if statement
if "key4" not in empty_dict1:
    empty_dict1["key4"] = '4'
else:
    print("Key exists, so not added")
print(empty_dict1)

Output:
{'Key1': '1', 'Key2': '2'}
{'Key1': '1', 'Key2': '2', 'key3': '3'}
{'Key1': '1', 'Key2': '2', 'key3': '3', 'key4': '4'}

How do you sort a Python dictionary?

One of the properties of dictionaries is that they are unordered, as a result, if it is large finding what you need may take a bit.

Luckily Python has provided the ability to sort as follows:

#How to sort a python dictionary?
empty_dict1 = {}

empty_dict1['Key2'] = '2'
empty_dict1['Key1'] = '1'
empty_dict1['Key3'] = '3'
print("Your unsorted by key dictionary is:",empty_dict1)
print("Your sorted by key dictionary is:",dict(sorted(empty_dict1.items())))

#OR - use list comprehension
d = {a:b for a, b in enumerate(empty_dict1.values())}
print(d)
d["Key2"] = d.pop(0) #replaces 0 with Key2
d["Key1"] = d.pop(1) #replaces 1 with Key1
d["Key3"] = d.pop(2) #replaces 2 with Key3
print(d)
print(dict(sorted(d.items())))

Output:
Your unsorted by key dictionary is: {'Key2': '2', 'Key1': '1', 'Key3': '3'}
Your sorted by key dictionary is: {'Key1': '1', 'Key2': '2', 'Key3': '3'}
{0: '2', 1: '1', 2: '3'}
{'Key2': '2', 'Key1': '1', 'Key3': '3'}
{'Key1': '1', 'Key2': '2', 'Key3': '3'}

How do you delete a key from a Python dictionary?

From time to time certain keys may not be required anymore. In this scenario, you will need to delete them. In doing this you also delete the value associated with the key.

#How do you delete a key from a dictionary?
empty_dict1 = {}

empty_dict1['Key2'] = '2'
empty_dict1['Key1'] = '1'
empty_dict1['Key3'] = '3'
print(empty_dict1)

#1. Use the pop function
empty_dict1.pop('Key1')
print(empty_dict1)

#2. Use Del

del empty_dict1["Key2"]
print(empty_dict1)

#3. Use dict.clear()
empty_dict1.clear() # Removes everything from the dictionary.
print(empty_dict1)

Output:
{'Key2': '2', 'Key1': '1', 'Key3': '3'}
{'Key2': '2', 'Key3': '3'}
{'Key3': '3'}
{}

How do you delete more than one key from a Python dictionary?

Sometimes you may need to remove multiple keys and their values. Using the above code repeatedly may not be the most efficient way to achieve this.

To help with this Python has provided a number of ways to achieve this as follows:

#How do you delete more than one key from a dictionary
#1. Create a list to lookup against
empty_dict1 = {}

empty_dict1['Key2'] = '2'
empty_dict1['Key1'] = '1'
empty_dict1['Key3'] = '3'
empty_dict1['Key4'] = '4'
empty_dict1['Key5'] = '5'
empty_dict1['Key6'] = '6'

print(empty_dict1)

dictionary_remove = ["Key5","Key6"] # Lookup list

#1. Use the pop method

for key in dictionary_remove:
  empty_dict1.pop(key)
print(empty_dict1)

#2 Use the del method
dictionary_remove = ["Key3","Key4"]
for key in dictionary_remove:
  del empty_dict1[key]
print(empty_dict1)

How do you change the name of a key in a Python dictionary?

There are going to be scenarios where the key names are not the right names you need, as a result, they will need to be changed.

It should be noted that when changing the key names, the new name should not already exist.

Below are some examples that will show you the different ways this can be acheived.

# How do you change the name of a key in a dictionary
#1. Create a new key , remove the old key, but keep the old key value

# create a dictionary
European_countries = {
    "Ireland": "Dublin",
    "France": "Paris",
    "UK": "London"
}
print(European_countries)
#1. rename key in dictionary
European_countries["United Kingdom"] = European_countries.pop("UK")
# display the dictionary
print(European_countries)

#2. Use zip to change the values

European_countries = {
    "Ireland": "Dublin",
    "France": "Paris",
    "United Kingdom": "London"
}

update_elements=['IRE','FR','UK']

new_dict=dict(zip(update_elements,list(European_countries.values())))

print(new_dict)

Output:
{'Ireland': 'Dublin', 'France': 'Paris', 'UK': 'London'}
{'Ireland': 'Dublin', 'France': 'Paris', 'United Kingdom': 'London'}
{'IRE': 'Dublin', 'FR': 'Paris', 'UK': 'London'}

How do you get the min and max key and values in a Python dictionary?

Finally, you may have a large dictionary and need to see the boundaries and or limits of the values contained within it.

In the below code, some examples of what you can talk through should help explain your knowledge.

#How do you get the min and max keys and values in a dictionary?
dict_values = {"First": 1,"Second": 2,"Third": 3}

#1. Get the minimum value and its associated key
minimum = min(dict_values.values())
print("The minimum value is:",minimum)
minimum_key = min(dict_values.items())
print(minimum_key)

#2. Get the maximum value and its associated key
maximum = max(dict_values.values())
print("The maximum value is:",maximum)
maximum_key = max(dict_values.items())
print(maximum_key)

#3. Get the min and the max key
minimum = min(dict_values.keys())
print("The minimum key is:",minimum)

#2. Get the maximum value and its associated key
maximum = max(dict_values.keys())
print("The maximum key is:",maximum)

Output:
The minimum value is: 1
('First', 1)
The maximum value is: 3
('Third', 3)
The minimum key is: First
The maximum key is: Third

Python Overview Interview Questions

Estimated reading time: 4 minutes

So you have landed an interview and worked hard at upskilling your Python knowledge. There are going to be some questions about Python and the different aspects of it that you will need to be able to talk about that are not all coding!

Here we discuss some of the key elements that you should be comfortable explaining.

What are the key Features of Python?

In the below screenshot that will feature in our video, if you are asked this question they will help you be able to discuss.

Below I have outlined some of the key benefits you should be comfortable discussing.

It is great as it is open source and well-supported, you will always find an answer to your question somewhere.

Also as it is easy to code and understand, the ability to quickly upskill and deliver some good programs is a massive benefit.

As there are a lot of different platforms out there, it has been adapted to easily work on any with little effort. This is a massive boost to have it used across a number of development environments without too much tweaking.

Finally, some languages need you to compile the application first, Python does not it just runs.

What are the limitations of Python?

While there is a lot of chat about Python, it also comes with some caveats which you should be able to talk to.

One of the first things to discuss is that its speed can inhibit how well an application performs. If you require real-time data and using Python you need to consider how well performance will be inhibited by it.

There are scenarios where an application is written in an older version of code, and you want to introduce new functionality, with a newer version. This could lead to problems of the code not working that currently exists, that needs to be rewritten. As a result, additional programming time may need to be factored in to fix the compatibility issues found.

Finally, As Python uses a lot of memory you need to have it on a computer and or server that can handle the memory requests. This is especially important where the application is been used in real-time and needs to deliver output pretty quickly to the user interface.

What is Python good for?

As detailed below, there are many uses of Python, this is not an exhaustive list I may add.

A common theme for some of the points below is that Python can process data and provide information that you are not aware of which can aid decision-making.

Alternatively, it can also be used as a tool for automating and or predicting the behaviour of the subjects it pertains to, sometimes these may not be obvious, but helps speed up the delivery of certain repetitive tasks.

What are the data types Python support?

Finally below is a list of the data types you should be familiar with, and be able to discuss. Some of these are frequently used.

These come from the Python data types web page itself, so a good reference point if you need to further understand or improve your knowledge.

ValueError: Columns must be same length as key

Estimated reading time: 3 minutes

Are you looking to learn python , and in the process coming across this error and trying to understand why it occurs?

In essence, this usually occurs when you have more than one data frames and in the process of writing your program you are trying to use the data frames and their data, but there is a mismatch in the no of items in each that the program cannot process until it is fixed.

A common scenario where this may happen is when you are joining data frames or splitting out data, these will be demonstrated below.

Scenario 1 – Joining data frames

Where we have df1[[‘a’]] = df2 we are assigning the values on the left side of the equals sign to what is on the right.

When we look at the right-hand side it has three columns, the left-hand side has one.

As a result the error “ValueError: Columns must be same length as key” will appear, as per the below.

import pandas as pd

list1 = [1,2,3]
list2 = [[4,5,6],[7,8,9]]

df1 = pd.DataFrame(list1,columns=['column1'])
df2 = pd.DataFrame(list2,columns=['column2','column3','column4'])

df1[['a']] = df2

The above code throws the below error:

The objective here is to have all the columns from the right-hand side, beside the columns from the left-hand side as follows:

What we have done is make both sides equal regards the no of columns to be shown from df2
Essentially we are taking the column from DF1, and then bringing in the three columns from DF2.
The columna, columnb, columnc below correspond to the three columns in DF2, and will store the data from them.

The fix for this issue is : df1[[‘columna’,’columnb’,’columnc’]] = df2

print (df1)

Scenario 2 – Splitting out data

There may be an occasion where you have a python list, and you need to split out the values of that list into separate columns.

new_list1 = ['1 2 3']
df1_newlist = pd.DataFrame(new_list1,columns=['column1'])

In the above, we have created a list, with three values that are part of one string. Here what we are looking to do is create a new column with the below code:

df1_newlist[["column1"]] = df1_newlist["column1"].str.split(" ", expand=True) #Splitting based on the space between the values.

print(df1_newlist)

When we run the above it throws the following valueerror:

The reason it throws the error is that the logic has three values to be split out into three columns, but we have only defined one column in df1_newlist[[“column1”]]

To fix this, we run the below code:

df1_newlist[["column1","column2","column3"]] = df1_newlist["column1"].str.split(" ", expand=True) #Splitting based on the space between the values.

print(df1_newlist)

This returns the following output, with the problem fixed!

How to Create Multiple XML Files From Excel With Python

So you have an Excel file that has hundreds or maybe thousands of records, but you want to convert it to an XML file, and have each row as a separate file?

This can be achieved very easily using Python, in three easy steps.

First of all, what is XML?

XML stands for “extensible markup language”, and is used extensively with websites, Webservices and where companies want to transfer data between each other in a predefined format that follows a recognised standard.

To understand more about what is xml, follow the link. One thing to note is that it may reference the financial services industry, but XML is used widely across multiple industries too, as we are now digitising a lot of our processes, the transfer of data needs to follow a standard that everyone can work with seamlessly.

Step 1 – Let’s look at our raw data

Below is an excel file with three columns and eight rows. The objective is to create eight separate XML files for each row.

raw data to populate multiple excel files

Step 2 – Import the data and create a master XML file

Below is the logic I used in How to Create an XML File from Excel using Python, I have attached comments where necessary to explain what each line is doing.

The purpose at this point is to create one file with all the data from excel called output.xml. We will then use this to create the separate files we need and then delete it.

The next steps will take you through that.

import pandas as pd
from lxml import etree as et
import os


# STEP 1 - This step creates a master XML file

raw_data = pd.read_excel(r'\Users\haugh\OneDrive\dataanalyticsireland\YOUTUBE\how_to_read_each_excel_row_into_a_separate_XML_file\excel_raw_data_city.xlsx')

root = et.Element('root')

for row in raw_data.iterrows(): #==> This is a loop that takes runs through each record and populates for each tag.
    root_tags = et.SubElement(root, 'ExportData') #=== > Root name
# These are the tag names for each row (SECTION 1)
    Column_heading_1 = et.SubElement(root_tags, 'City')
    Column_heading_2 = et.SubElement(root_tags, 'Area')
    Column_heading_3 = et.SubElement(root_tags, 'Population')


###These are the values that will be populated for each row above
# The values inside the [] are the raw file column headings.(SECTION 2)
    Column_heading_1.text = str(row[1]['City'])
    Column_heading_2.text = str(row[1]['Area'])
    Column_heading_3.text = str(row[1]['Population'])

# This Section outputs the data to an xml file
# Unless you tell it otherwise it saves it to the same folder as the script.
tree = et.ElementTree(root) #==> The variable tree is to hold all the values of "root"
et.indent(tree, space="\t", level=0) #===> This just formats in a way that the XML is readable
tree.write('output.xml', encoding="utf-8") #==> The data is saved to an XML file

Step 3 – Loop through each row and create the separate files

In the below code, it opens the output.xml file and using the loop looks for all the data between the tags “ExportData”.

Then it copies them and then creates a new file.

Once one is done, it moves to the next set of tags and repeats the process, till it reaches the end of the output.xml file.

master_file = et.iterparse('output.xml', events=('end', ))
index = 0
for i, j in master_file:
    if j.tag == 'ExportData':
        index += 1
        filename = format(str(index) + ".xml")
        with open(filename, 'wb') as f:
            f.write(et.tostring(j))

Step 4 – Delete the output.xml file – purely optional

The objective here was to create separate XML files, based on the input of the original Excel file.

We have also created an additional file called output.xml to get us to the end goal.

If we have no need for this file then it can be removed with the below code, be sure that it is at the very end of your logic.

The import statement for os.unlink is in step two.

os.unlink(r'\Users\haugh\OneDrive\dataanalyticsireland\YOUTUBE\how_to_read_each_excel_row_into_a_separate_XML_file\output.xml')

How To Run Python Validation From Javascript

Estimated reading time: 6 minutes

More and more, website developers are looking to blend different programming technologies to allow them to use functionality, that maybe is not available to them in the current programming language they utilise.

In previous posts how to pass python variables to Javascript and how to run python directly from javascript, we touched on how to use Python and Javascript interchangeably to pass data.

Here in this blog post, we are going to look at data validation using Python, with data captured by Javascript. The purpose here is to allow another way to validate data other than relying on javascript.

Python Validation run from Javascript

There are a number of reasons for this:

  1. You may want to use Python to process the data and provide output.
  2. The data could be passed from Python into a database, you need to run some checks before you proceed.
  3. Python is your core language, you only use Javascript to capture the data and pass it from a website.

There are four validation checks

  1. Validation if a username exists.
  2. Validation if a number has been entered on a username field.
  3. Validation of a password entered.
  4. A validation check to make sure that an email address entered is in the correct format.

We have two files with the requisite code in them as follows:

  1. app.py ===> As this application is built in Python Flask, this file holds the logic to open the website files, and it holds the Python validation checks.
  2. index.html ====> This file holds the HTML that creates the pages, labels, and input boxes that appear in the web browser. It also includes the Javascript that will capture the data to be passed to Python for validation.

Code Overview – App.PY

Below, I will look to explain what is going on as follows:

The variable Regex is used in the email validation to check if the email entered is correct.

def inputcheck ===> This is just checking the username passed over and performing some validations on it.

def inputvalidation ====> This also is checking the username but looking at if numbers only are entered, or if it is empty.

def passvalidation ====> In this piece of logic, it checks if the password is empty, less than five characters, is numbers only.

def emailvalidation ====> All this is doing is checking if the data received from the Javascript is in the correct email format. It references the regex variable above, which is used to confirm if the format is correct or otherwise.

Within each of the functions, there are if statements which are the core validation checks used by Python.

Also, all the popup menus use ctypes, which allows you to access the windows libraries that hold message boxes, customise them and call within your program.

import json
import ctypes
import re
from flask import request,redirect,url_for

from flask import Flask, render_template

app = Flask(__name__)

regex = '^[a-z0-9]+[\._]?[a-z0-9]+[@]\w+[.]\w{2,3}$'

@app.route('/')
def index():
    return render_template('index.html')


@app.route('/inputcheck', methods=['GET','POST'])
def inputcheck():
    output = request.get_json()
    result = json.loads(output) #this converts the json output to a python dictionary
    username_list = ['joe','john']
    if result['username'] in username_list:
        MessageBox = ctypes.windll.user32.MessageBoxW(0, 'Username ' + result['username'] + ' ' + 'exists', "Username check", 0x00001000)
        return render_template('various.html')
    elif result['username'] == '':
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'You cannot enter an empty value', 'Username check', 0x00001000)
    else:
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Username ' + result['username'] + ' ' + 'does not exist', 'Username check', 0x00001000)

@app.route('/inputvalidation', methods=['GET','POST'])
def inputvalidation():
    output = request.get_json()
    result = json.loads(output) #this converts the json output to a python dictionary
    if result['username'].isdecimal():
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your username cannot be numbers',"Number check", 0x00001000)
    elif result['username'] == '':
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'The username cannot be empty', "Number check",0x00001000)
    else:
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your username looks ok', "Number check", 0x00001000)
    return render_template('index.html')

@app.route('/passvalidation', methods=['GET','POST'])
def passvalidation():
    output = request.get_json()
    result = json.loads(output) #this converts the json output to a python dictionary
    if result['password'].isdecimal():
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your password cannot be numbers',"Password check", 0x00001000)
    elif result['password'] == '':
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'The password cannot be empty', "Password empty check",0x00001000)
    elif len(result['password']) < 5:
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your username should be greater than five characters', "Password length check", 0x00001000)
    else:
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your password looks ok', "Number check", 0x00001000)
    return render_template('index.html')

@app.route('/emailvalidation', methods=['GET','POST'])
def emailvalidation():
    output = request.get_json()
    result = json.loads(output) #this converts the json output to a python dictionary
    if re.search(regex, result['email']):
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your email is in the correct format', "Email check", 0x00001000)
    else:
        MessageBox = ctypes.windll.user32.MessageBoxW(None, 'Your email is invalid, please correct', "Email check", 0x00001000)
    return render_template('index.html')



if __name__ == "__main__":
    app.run(debug=True)


Code Overview – Index.html

The below code is the page code, that allows the capturing of data through a web browser HTML page.

Between the <style></style> tags these are the CSS properties that format the labels and buttons on the page.

Within the <div></div> tags are where we create the labels and buttons to show on the screen. Also within these, are the references to the on click event function that should run once the buttons are clicked.

Within the <script></script> tags, this is where the javascript is written which captures the data entered into the input boxes within the <div> tags.

Also, you will see within this javascript, there are sections called $.ajax, which is where the data captured by the javascript is stored, and then passed onto the Python script file (app.py)

Note that in each ajax , url:”/APAGENAME” is referenced. These are the sections within the app.py that the data is passed to, and then the Python logic kicks in and validates the data.

<html lang="en">

<head>

    <title>Data Analytics Ireland</title></head>
<style>
.button1 {
    position: absolute;
    top: 50%;
    left: 55%;
    width: 900px;
    height: 300px;
    margin-left: -300px;
    margin-top: -80px;
}



.labels {
    position: absolute;
    top: 50%;
    left: 55%;
    width: 900px;
    height: 300px;
    margin-left: -300px;
    margin-top: -150px;
}

</style>

<body>



<div class="labels" id="mem1" >
<label  for="username">username:</label> <input type="text" id="username" name="username">
<label for="password">password:</label><input type="text" id="password" name="password">
    <label for="email">email:</label><input type="text" id="email" name="password">
</div>


<div class="button1" id="mem2" >
<button type="submit" onclick='myfunction();'>Click here to validate your username</button>
<button type="submit" onclick='myfunctionval();'>Click here to check if a number</button>
    <button type="submit" onclick='myfunctionpass();'>Click here to check password</button>
      <button type="submit" onclick='myfunctionemail();'>Click here to check your email</button>
</div>


<script type="text/javascript" src="http://ajax.googleapis.com/ajax/libs/jquery/1.5/jquery.min.js"></script>

<script>
    function myfunction() {

        const username = document.getElementById("username").value;
        const password = document.getElementById("password").value;


        const dict_values = {username, password} //Pass the javascript variables to a dictionary.
        const s = JSON.stringify(dict_values); // Stringify converts a JavaScript object or value to JSON.
        console.log(s); // Prints the variables to console window, which are in the JSON format
        //window.alert(s)
        $.ajax({
            url:"/inputcheck",
            type:"POST",
            contentType: "application/json",
            data: JSON.stringify(s)});
}
</script>
<script>
    function myfunctionval() {

        const username = document.getElementById("username").value;
        const password = document.getElementById("password").value;


        const dict_values = {username, password} //Pass the javascript variables to a dictionary.
        const s = JSON.stringify(dict_values); // Stringify converts a JavaScript object or value to JSON.
        console.log(s); // Prints the variables to console window, which are in the JSON format
        //window.alert(s)
        $.ajax({
            url:"/inputvalidation",
            type:"POST",
            contentType: "application/json",
            data: JSON.stringify(s)});
}
</script>

<script>
    function myfunctionpass() {

        const username = document.getElementById("username").value;
        const password = document.getElementById("password").value;


        const dict_values = {username, password} //Pass the javascript variables to a dictionary.
        const s = JSON.stringify(dict_values); // Stringify converts a JavaScript object or value to JSON.
        console.log(s); // Prints the variables to console window, which are in the JSON format
        //window.alert(s)
        $.ajax({
            url:"/passvalidation",
            type:"POST",
            contentType: "application/json",
            data: JSON.stringify(s)});
}
</script>

<script>
    function myfunctionemail() {

        const email = document.getElementById("email").value;


        const dict_values = {email} //Pass the javascript variables to a dictionary.
        const s = JSON.stringify(dict_values); // Stringify converts a JavaScript object or value to JSON.
        console.log(s); // Prints the variables to console window, which are in the JSON format
        //window.alert(s)
        $.ajax({
            url:"/emailvalidation",
            type:"POST",
            contentType: "application/json",
            data: JSON.stringify(s)});
}
</script>




</body>
</html>

How to Pass Python Variables to Javascript

Estimated reading time: 4 minutes

In our recent blog posting How to Pass a Javascript Variable to Python using JSON, we demonstrated how to easily use AJAX to pass whatever data you wanted and then manipulate it with Python.

In this blog posting, we are going to show how to do this the other way around. The scenario is that you have an application and or website that wants to use data generated through Python, but let Javascript then use it within the application.

As Python can be connected to numerous databases and files ( txt, excel) etc, this piece of logic is very useful for the programmer looking to integrate both programming languages.

Let’s start looking at the code, and see how this can be achieved.

Step 1 – What Files are generated?

This program uses Python Flask to create a web page, that has a drop-down menu. The two files used to generate this are as follows:

(A) app.py – This is the python file that creates a website and loads a template HTML file as outlined below.

(B) Index.html – This is the template file that loads into the browser and runs all the javascript. The javascript loaded here also loads the python data passed over from app.py

Step 2 – APP.PY code overview

The Python library that enables webpage creation is called Flask, and as can be seen below it has to be imported.

In addition, we need to also import render_template which tells the program to go to the templates folder and load “Index.HTML”

The variable that is been passed to JavaScript is called name, and these are the values that you will see in the web browser when it is loaded.

from flask import Flask, render_template

app = Flask(__name__)

@app.route('/')
def index():
    name = ['Joe','John','Jim','Paul','Niall','Tom']
    return render_template('index.html', name=name)

if __name__ == "__main__":
    app.run(debug=True)

Step 3 – Index.HTML overview

Here is the template HTML file that runs in the browser. You can add CSS etc to this to make it look nicer and more user friendly.

As you can see it has the usual HTML tags appear as part of a website.

Well look at some of the code further:

In this bit <select id =’select’> </select>, this is the dropdown menu that will appear when Index.html is opened. It will store all the values passed from python. Note that its id is “select”, this will be used later on.

The main parts to focus on next is between <script></script>. This is what reads in the python data and populates it to the dropdown menu.

In step 2 we mentioned that there was a variable called “name”, with values to be passed over.

This is acheived on this line:

var select = document.getElementById(“select”), test = {{ name | tojson }};

Notice that name appears here, and this is referencing back to the exact same value that was discussed in step 2.

For the rest of the lines, I have explained with comments what each does.

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Pass Python variable to Javascript</title>
</head>
<body>

<select id ='selectvalue'>
</select>
<script>
    //name = ['Joe','John','Jim','Paul','Niall','Tom']

    var selectvalue = document.getElementById("selectvalue"), test = {{ name | tojson }};
    //The increment operator (++) increments (adds one to) its operand and returns a value.
    for(var i = 0; i < test.length; i++) // This line checks for the length of the data you feeding in i.e the no of items
         {
var selection = document.createElement("OPTION"), // This line creates a variable to store the different values fed in from the JSON object "TEST"
txt = document.createTextNode(test[i]); // This just reads each value from the test JSON variable above
selection.appendChild(txt); // This line appends each value as it is read.
selection.setAttribute("value",test[i]); // This line sets each value read in as a value for the drop down
selectvalue.insertBefore(selection,selectvalue.lastChild); //This reads eah value into the dropdown based on the order in the "TEST" above.
 }
</script>
</body>
</html>

Step 4 – What the output looks like!

From step 2, these are values we asked to be used in Javascript to populate a dropdown:

name = [‘Joe’,’John’,’Jim’,’Paul’,’Niall’,’Tom’]

Python variable passed to Javascript

How to run Python directly from Javascript

Estimated reading time: 3 minutes

Are you developing a website and looking to execute some Python script directly from the website?

Here we take you through how to achieve this using Python Flask, the scenarios we demonstrate are as follows:

  1. Javascript on load event – execute Python script
  2. Javascript on click event – execute a Python script

In both scenarios above you will be presented with pop-up boxes like below, but the python code can be changed to whatever you like.

Page load message box
On button press, calls the python script to load a message box

The code you will need to run this is split into two. (A) The Index.HTML logic and (B) the app.py logic

The code for the INDEX.HTML page

This is the page that the user is presented with. As you can see the logic has two pieces of javascript that when run, go over to the python code and run some logic that it wishes the webpage to run.

In this instance, the app.py python script holds the commands that need to be executed.

Note the page load event goes to the route in app.py, namely ” @app.route(‘/’)”

Whereas the button click event is pointed directly at “@app.route(‘/test’ )” – essentially this will not run until the javascript asks it to, on the button click event.

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Sample Home Page</title>
</head>
<body>
<! -- Calls a function on the page load. -- >
<element onload="myfunction_onload">
<button type="submit" onclick='myfunction_clickevent()'>Run my Python!</button>
<script type="text/javascript" src="https://ajax.googleapis.com/ajax/libs/jquery/1.5/jquery.min.js"></script>
<! -- This script runs the python script on the page load -->
<script>
    function myfunction_onload(){
        $.ajax({
            url: "app.py",
             context: document.body
            })
        }
    </script>
<! -- This script runs the python script when the button is clicked -->
<script>
    function myfunction_clickevent(){
        $.ajax({
            url:"/test",
            context: document.body});}
</script>


</body>
</html>
How to run Python directly from Javascript

The code for the APP.PY Python script

Here we are linking to the index.html page and taking commands from it and executing those requests.

In this scenario, the message boxes are rendered by using the win32api package.

The app is using the flask package to run the website.

The powerful thing here is you can start customising this logic to do what you like, examples include:

(A) Return graphs to the webpage.

(B) Process data received and return statistics on the data.

(C) Validate data received in Python and return a response. An example here could be a user logging into a database.

import win32api
from flask import Flask, render_template

app = Flask(__name__)


#Using the below, the popup message appears on the page load of index.html
#0x00001000 - This makes the popup appear over the browser window
@app.route('/')
def index():
    win32api.MessageBox(0, 'You have just run a python script on the page load!', 'Running a Python Script via Javascript', 0x00001000)
    return render_template('index.html')

#Using the below, the popup message appears when the button is clicked on the webpage.
#0x00001000 - This makes the popup appear over the browser window
@app.route('/test')
def test():
    win32api.MessageBox(0, 'You have just run a python script on the button press!', 'Running a Python Script via Javascript', 0x00001000)
    return render_template('index.html')

if __name__ == "__main__":
    app.run(debug=True)