Need a Python Django Developer in Boston? OT PROJECTS

Need a Python Django developer in Boston MA? Contact OT PROJECTS.

Django is an excellent choice for a rapid development, while having the ability to scale the application. Backed by the flexibility of Python and ease template engine, it provide the ability to develop code that can be reused in Web, Desktop and background processing.

Various Python Django web applications developed and deployed.

Most environment are:

  • Linux
  • Amazon EC2
  • Python 2.7
  • Different Django versions

Some Projects done:

  • Car washing on demand ordering system
  • Online reporting application
  • Medical Survey system
  • RSVP system

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Python Developer – Send an email using Python

This example shows how to send an email (SMTP)
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Make the needed changes where there’s *** in the code

import smtplib
import time
import sys

from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.header import Header
from email.utils import formataddr

print 'start'

# change the parameters according to your SMTP settings
_my_name="*** Your name *** "
_smtp_domain='*** enter here your smtp server name ***'
_port=587 # put the right port
_login_user ='*** enter here the SMTP user name (usually your email) ****'
_password='*** enter here your password ***'
_from='%s <%s>' % (_my_name,_login_user)
_to='*** enter here the recipient email ***'

This is an eample

' msg = MIMEText(html, 'html') msg['Subject'] = 'OT PROJECTS - a Python sample email procedure' msg['From'] = _from msg['To'] = _to msg['Reply-to']=_from tries=0 while tries<3: # for login try: email_server = smtplib.SMTP(_smtp_domain,_port) email_server.login(_login_user,_password) tries=4 # exit the try except: print 'email error, wait 10 sec.' time.sleep(4) tries+=1 # try again after 10 seconds if tries==3: sys.exit('Error login in to email server') try: rv=email_server.sendmail(_from, _to, msg.as_string()) except Exception as e: print 'Error sending email: ', e email_server.quit() print 'send email completed'

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Python Developer – Python socket example.

Socket server by default is TCP IP. Save the 2 codes in 2 files, run the server first.
* Note the client IP is pointed to, assuming the client and the server are on the same machine.

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This is the server file code:

import socket
import time

print "Socket server started"
socket_server = socket.socket()         
ip = '' 
port = 5050 #choose any, larger than 1024 (otherwise you need to have admin/root permission to execute)               
socket_server.bind((ip, port))        

while True:
   client, client_address = socket_server.accept()     
   print client_address, 'connected'
   client.send('Connection time: ' + str(time.asctime(time.localtime())))

This is the client file code:

import socket 
import time 
ip_of_the_socket_server = ''
port_of_the_socket_server = 5050     # must be the server port number       

#send 10 messages, 10 sec delay between each
for i in range(1,11):
	my_connection = socket.socket()  
	my_connection.connect((ip_of_the_socket_server, port_of_the_socket_server))	
	print i,')', my_connection.recv(4096)

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Python Scientific Libraries

Python is a popular programming language that is used for web development. It is also an important element for complex data visualization, analysis, and machine learning. Various scientific libraries and tools utilize Python and its innovative features, making it a significant and functional language for scientific computing.

Popular Python Scientific Libraries

There are five popular scientific libraries that utilize Python as its programming language namely Astropy, Biopython, Pandas, matplotlib, and NumPy. Knowing and understanding these features gives you a more profound and comprehensive understanding of their uses. Astropy highlights the effort in creating an astronomy core package with the use of Python to collaborate, use, and interoperate the programming language and astronomy packages.

Other scientific libraries that use Python and its powerful features for a programming language benefit from its improved usability and function. Learn more about the different industries that enjoy much better features with the help of the Python programming language.

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Python Fintech developement potential

Python fintech coverage is comprehensive given the importance and vulnerability of financial technology against cyber-attack and hacking. Fintech or financial technology is a trendy and popular niche especially for startups because of its high potentials for growth and profitability. The financial technology also promises unlimited possibilities for disruptive innovation.

Facts about Python Fintech Coverage

A promising future of fintech, stating that more than $150 billion investments are possible among the fintech key players in a span of three to five years. Thus, using a reliable and innovative programming language for financial technology is a must and this is where Python comes in. Fintech covers different industries and verticals including lending and financing, account management, payment processing, insurance, capital markets, and regulation.

The Python fintech coverage is a clear proof that the financial technology has nowhere to go but up. Fintech companies appeal to small and large-scale enterprises due to their capacity to effectively respond to the needs of their clients

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Python Fintech developer – application Capabilities

The Python fintech capabilities prove that the programming language is the right choice if you are looking for something that you could easily handle with scalable output for your website. The high-performing and mature programming language comes with components and ready-made libraries that help you avoid any skyrocketing costs in your tech stack.

List of Python Fintech Capabilities

The Python backend language is quite prevalent among fintechs whether they are in start-up or unicorn levels. The programming language works best for a python Fintech developer. Startups particularly in the financial industry where you need easy to use and innovative features. Banks utilize Python along with key players in the hedge funds and investment banking industries. It helps in solving quantitative problems concerning risk management, pricing, and trade management platforms.

The Python fintech capabilities are encompassing and comprehensive, making the backend language a fast-growing and popular option for IT companies. Financial giants see the advantages of using a reliable programming language with untainted track record.

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Amazon AWS Computing Capabilities – How to Optimize Computer Functions

Amazon AWS computing capabilities allow you to maximize the web to its full potentials. Computers calculate process data, and primarily compute, processing data analysis and graphics rendering in a much faster phase. Opting to use innovative options such as going on the cloud is a more popular choice today rather than buying more hardware.

How Amazon AWS Computing Capabilities Work

Owning the computer hardware is an asset but you must also consider the idle time that you waste when your computers are not making actual processing work as well as the high maintenance requirements. Going to the cloud allows you to only pay for the services that you use. Moreover, cloud computing scales numerous processing nodes in a matter of minutes.

Amazon AWS computing capabilities highlight its flagship, Elastic Compute Cloud or EC2, offering accessible computing on demand. EC2 rivals popular products such as the Virtual Machines and Virtual Machine Scale Sets from Azure and Google’s Compute Engine.

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Server backend development

Server backend development leads to the need to understand the significance of a back-end language, which is important in user authentication, application logic, and database operations. Several online bootcamps and programs use a specific back-end language.

Backend Language with Widespread Use in Server Backend Development


Numerous problems teach and use Ruby as their primary back-end language. Rails and Sinatra are widely used frameworks that develop Ruby.


The backend language is basically a JavaScript environment thus, there is no need to learn a new one in the process. Several online programs utilize Node.js with the popular framework Express allowing you to successfully develop web applications.


The backend language is developed in widely known frameworks Flask and Django.


It is not commonly taught these days especially for full-stack web development but is still an in-demand backend language for most companies.


Even if it is not a commonly taught language in today’s programs, PHP is considered a cornerstone in a contemporary web application.

It does not really matter what back-end language you utilize for server backend development as long as you have a sufficient understanding of the language and the related nuances you will encounter along the way.

Python Backend Developer – Behind the Backend Development Phenomenon

Python backend developer plays a crucial role in a web application especially in enabling a frontend experience. It specifically functions for the database interactions, calculations, business logic, and overall performance of the website. Application codes are primarily made on the website’s backend.

An Overview of Python Backend Developer

Backend developers have a comprehensive understanding of the programming databases and languages as well as the server architecture since backend codes are primarily run on specific servers. Backend problems result in errors, crashing, and slowing down of applications thus you need a reliable backend developer to avoid these issues.

Python backend developer makes sure that clients do not experience web application problems through developing standardized styles and idioms that make enjoyable and more efficient reading and writing of application codes. Python offers readability, making it a popular option for web application building. It is one of the most popular backend languages in contemporary web development.

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