Rodney Vg

Rodney Vg


How to Set up an SMS Notification With Python

Hi everyone :) Today I am beginning a new series of posts specifically aimed at Python beginners. The concept is rather simple: I’ll do a fun project, in as few lines of code as possible, and will try out as many new tools as possible.

For example, today we will learn to use the Twilio API, the Twitch API, and we’ll see how to deploy the project on Heroku. I’ll show you how you can have your own “Twitch Live” SMS notifier, in 30 lines of codes, and for 12 cents a month.

Prerequisite: You only need to know how to run Python on your machine and some basic commands in git (commit & push). If you need help with these, I can recommend these 2 articles to you:

Python 3 Installation & Setup Guide

The Ultimate Git Command Tutorial for Beginners from Adrian Hajdin.

What you’ll learn:

  • Twitch API
  • Twilio API
  • Deploying on Heroku
  • Setting up a scheduler on Heroku

What you will build:

The specifications are simple: we want to receive an SMS as soon as a specific Twitcher is live streaming. We want to know when this person is going live and when they leave streaming. We want this whole thing to run by itself, all day long.

We will split the project into 3 parts. First, we will see how to programmatically know if a particular Twitcher is online. Then we will see how to receive an SMS when this happens. We will finish by seeing how to make this piece of code run every X minutes, so we never miss another moment of our favorite streamer’s life.

Is this Twitcher live?

To know if a Twitcher is live, we can do two things: we can go to the Twitcher URL and try to see if the badge “Live” is there.

Screenshot of a Twitcher live streaming.

This process involves scraping and is not easily doable in Python in less than 20 or so lines of code. Twitch runs a lot of JS code and a simple request.get() won’t be enough.

For scraping to work, in this case, we would need to scrape this page inside Chrome to get the same content like what you see in the screenshot. This is doable, but it will take much more than 30 lines of code. If you’d like to learn more, don’t hesitate to check my recent web scraping guide.

So instead of trying to scrape Twitch, we will use their API. For those unfamiliar with the term, an API is a programmatic interface that allows websites to expose their features and data to anyone, mainly developers. In Twitch’s case, their API is exposed through HTTP, witch means that we can have lots of information and do lots of things by just making a simple HTTP request.

Get your API key

To do this, you have to first create a Twitch API key. Many services enforce authentication for their APIs to ensure that no one abuses them or to restrict access to certain features by certain people.

Please follow these steps to get your API key:

  • Create a Twitch account
  • Now create a Twitch dev account -> “Signing up with Twitch” top right
  • Go to your “dashboard” once logged in
  • “Register your application”
  • Name -> Whatever, Oauth redirection URL -> http://localhost, Category -> Whatever

You should now see, at the bottom of your screen, your client-id. Keep this for later.

Is that Twitcher streaming now?

With your API key in hand, we can now query the Twitch API to have the information we want, so let’s begin to code. The following snippet just consumes the Twitch API with the correct parameters and prints the response.

# requests is the go to package in python to make http request
import requests

# This is one of the route where Twich expose data, 
# They have many more:
endpoint = ""

# In order to authenticate we need to pass our api key through header
headers = {"Client-ID": "<YOUR-CLIENT-ID>"}

# The previously set endpoint needs some parameter, here, the Twitcher we want to follow
# Disclaimer, I don't even know who this is, but he was the first one on Twich to have a live stream so I could have nice examples
params = {"user_login": "Solary"}

# It is now time to make the actual request
response = request.get(endpoint, params=params, headers=headers)

The output should look like this:

         'title':"Wakz duoQ w/ Tioo - GM 400LP - On récupère le chall après les -250LP d'inactivité !",

This data format is called JSON and is easily readable. The data object is an array that contains all the currently active streams. The key type ensures that the stream is currently live. This key will be empty otherwise (in case of an error, for example).

So if we want to create a boolean variable in Python that stores whether the current user is streaming, all we have to append to our code is:

json_response = response.json()

# We get only streams
streams = json_response.get('data', [])

# We create a small function, (a lambda), that tests if a stream is live or not
is_active = lambda stream: stream.get('type') == 'live'
# We filter our array of streams with this function so we only keep streams that are active
streams_active = filter(is_active, streams)

# any returns True if streams_active has at least one element, else False
at_least_one_stream_active = any(streams_active)


At this point, at_least_one_stream_active is True when your favourite Twitcher is live.

Let’s now see how to get notified by SMS.

Send me a text, NOW!

So to send a text to ourselves, we will use the Twilio API. Just go over there and create an account. When asked to confirm your phone number, please use the phone number you want to use in this project. This way you’ll be able to use the $15 of free credit Twilio offers to new users. At around 1 cent a text, it should be enough for your bot to run for one year.

If you go on the console, you’ll see your Account SID and your Auth Token , save them for later. Also click on the big red button “Get My Trial Number”, follow the step, and save this one for later too.

Sending a text with the Twilio Python API is very easy, as they provide a package that does the annoying stuff for you. Install the package with pip install Twilio and just do:

from import Client
client = Client(<Your Account SID>, <Your Auth Token>)
	body='Test MSG',from_=<Your Trial Number>,to=<Your Real Number>)

And that is all you need to send yourself a text, amazing right?

Putting everything together

We will now put everything together, and shorten the code a bit so we manage to say under 30 lines of Python code.

import requests
from import Client
endpoint = ""
headers = {"Client-ID": "<YOUR-CLIENT-ID>"}
params = {"user_login": "Solary"}
response = request.get(endpoint, params=params, headers=headers)
json_response = response.json()
streams = json_response.get('data', [])
is_active = lambda stream:stream.get('type') == 'live'
streams_active = filter(is_active, streams)
at_least_one_stream_active = any(streams_active)
if at_least_one_stream_active:
    client = Client(<Your Account SID>, <Your Auth Token>)
	client.messages.create(body='LIVE !!!',from_=<Your Trial Number>,to=<Your Real Number>)

Avoiding double notifications

This snippet works great, but should that snippet run every minute on a server, as soon as our favorite Twitcher goes live we will receive an SMS every minute.

We need a way to store the fact that we were already notified that our Twitcher is live and that we don’t need to be notified anymore.

The good thing with the Twilio API is that it offers a way to retrieve our message history, so we just have to retrieve the last SMS we sent to see if we already sent a text notifying us that the twitcher is live.

Here what we are going do to in pseudocode:

if favorite_twitcher_live and last_sent_sms is not live_notification:
if not favorite_twitcher_live and last_sent_sms is live_notification:

This way we will receive a text as soon as the stream starts, as well as when it is over. This way we won’t get spammed - perfect right? Let’s code it:

# reusing our Twilio client
last_messages_sent = client.messages.list(limit=1)
last_message_id = last_messages_sent[0].sid
last_message_data = client.messages(last_message_id).fetch()
last_message_content = last_message_data.body

Let’s now put everything together again:

import requests
from import Client
client = Client(<Your Account SID>, <Your Auth Token>)

endpoint = ""
headers = {"Client-ID": "<YOUR-CLIENT-ID>"}
params = {"user_login": "Solary"}
response = request.get(endpoint, params=params, headers=headers)
json_response = response.json()
streams = json_response.get('data', [])
is_active = lambda stream:stream.get('type') == 'live'
streams_active = filter(is_active, streams)
at_least_one_stream_active = any(streams_active)

last_messages_sent = client.messages.list(limit=1)
if last_messages_sent:
	last_message_id = last_messages_sent[0].sid
	last_message_data = client.messages(last_message_id).fetch()
	last_message_content = last_message_data.body
    online_notified = "LIVE" in last_message_content
    offline_notified = not online_notified
	online_notified, offline_notified = False, False

if at_least_one_stream_active and not online_notified:
	client.messages.create(body='LIVE !!!',from_=<Your Trial Number>,to=<Your Real Number>)
if not at_least_one_stream_active and not offline_notified:
	client.messages.create(body='OFFLINE !!!',from_=<Your Trial Number>,to=<Your Real Number>)

And voilà!

You now have a snippet of code, in less than 30 lines of Python, that will send you a text a soon as your favourite Twitcher goes Online / Offline and without spamming you.

We just now need a way to host and run this snippet every X minutes.

The quest for a host

To host and run this snippet we will use Heroku. Heroku is honestly one of the easiest ways to host an app on the web. The downside is that it is really expensive compared to other solutions out there. Fortunately for us, they have a generous free plan that will allow us to do what we want for almost nothing.

If you don’t already, you need to create a Heroku account. You also need to download and install the Heroku client.

You now have to move your Python script to its own folder, don’t forget to add a requirements.txt file in it. The content of the latter begins:


This is to ensure that Heroku downloads the correct dependencies.

cd into this folder and just do a heroku create --app <app name>.

If you go on your app dashboard you’ll see your new app.

We now need to initialize a git repo and push the code on Heroku:

git init
heroku git:remote -a <app name>
git add .
git commit -am 'Deploy breakthrough script'
git push heroku master

Your app is now on Heroku, but it is not doing anything. Since this little script can’t accept HTTP requests, going to <app name> won’t do anything. But that should not be a problem.

To have this script running 24/7 we need to use a simple Heroku add-on call “Heroku Scheduler”. To install this add-on, click on the “Configure Add-ons” button on your app dashboard.

Then, on the search bar, look for Heroku Scheduler:

Click on the result, and click on “Provision”

If you go back to your App dashboard, you’ll see the add-on:

Click on the “Heroku Scheduler” link to configure a job. Then click on “Create Job”. Here select “10 minutes”, and for run command select python <name_of_your_script>.py. Click on “Save job”.

While everything we used so far on Heroku is free, the Heroku Scheduler will run the job on the $25/month instance, but prorated to the second. Since this script approximately takes 3 seconds to run, for this script to run every 10 minutes you should just have to spend 12 cents a month.

Ideas for improvements

I hope you liked this project and that you had fun putting it into place. In less than 30 lines of code, we did a lot, but this whole thing is far from perfect. Here are a few ideas to improve it:

  • Send yourself more information about the current streaming (game played, number of viewers …)
  • Send yourself the duration of the last stream once the twitcher goes offline
  • Don’t send you a text, but rather an email
  • Monitor multiple twitchers at the same time

Do not hesitate to tell me in the comments if you have more ideas.


I hope that you liked this post and that you learned things reading it. I truly believe that this kind of project is one of the best ways to learn new tools and concepts, I recently launched a web scraping API where I learned a lot while making it.

Please tell me in the comments if you liked this format and if you want to do more.

I have many other ideas, and I hope you will like them. Do not hesitate to share what other things you build with this snippet, possibilities are endless.

Happy Coding.


Don’t want to miss my next post:

You can subscribe here to my newsletter.


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How to Set up an SMS Notification With Python
Hermann  Frami

Hermann Frami


A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.


npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator


This plugin relies on your serverless yml file and on the serverless-offline plugin.

  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002


Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |


    location: '.webpack/service' # use webpack build directory
      endpoint: 'http://my-custom-dynamo:8000'


By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.


      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

      Ref: MyBucket # resolves to `my-bucket-name`

      Type: AWS::DynamoDB::Table
        TableName: myTable
      Type: AWS::S3::Bucket
        BucketName: my-bucket-name

# in your appsync config
    name: dynamosource
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

  • refMap takes a mapping of resource name to value pairs
  • getAttMap takes a mapping of resource name to attribute/values pairs
  • importValueMap takes a mapping of import name to values pairs


      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
      # define ElasticSearchInstance DomainName
        DomainEndpoint: 'localhost:9200'
      other-service-api-url: ''

# in your appsync config
    name: elasticsource
      # endpoint resolves as 'http://localhost:9200'
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

      Fn::ImportValue: other-service-api-${self:provider.stage}-url

      - key: other-service-api-${self:provider.stage}-url
        value: ''


This plugin only tries to resolve the following parts of the yml tree:

  • provider.environment
  • functions[*].environment
  • custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

  • DynamoDb tables
  • S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

  • NONE

Implemented by this plugin

  • HTTP

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
        #set( $discard = $vals.add("0") )
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
        #set ( $cur = "0" )
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
      #set($update = "$update,$toSnake$equals'$cur'" )
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$", "SELECT * FROM <name-of-table> WHERE id=$"]

Sample resolver for delete mutation

  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$", "SELECT * FROM <name-of-table> WHERE id=$"]

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  variableMap: {
    ":ID": $,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!


Author: Serverless-appsync
Source Code: 
License: MIT License

#serverless #sync #graphql 

Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Art  Lind

Art Lind


Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

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Art  Lind

Art Lind


How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.


In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

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