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Financial Analyst, python
Anil

Financial Analyst, python  


Python SciPy Python Developers Corporate Strategy 
$25 /hr
India
Programmer and Web Designer
May

Programmer and Web Designer  


Python PHP javascript 
$50 /hr
Pakistan
React /Python developer
Sweta Singh

React /Python developer  


Python React JS React Native 
$10 /hr
India
Full Stack Developer
Sumeet Kaura

Full Stack Developer  


Python PHP javascript 
$12 /hr
India
WordPress & E-Commerce Expert
Isaac

WordPress & E-Commerce Expert  


Python Shopify SEO 
$12 /hr
Nigeria
Full-Stack MeteorJS /ReactJS /NodeJS Developer
Rajat Pundir

Full-Stack MeteorJS /ReactJS /NodeJS Developer  


Python Ruby on Rails Developers Excel Experts 
$15 /hr
India
Freelancer
Jenit Patel

Freelancer  


Python Transcription javascript 
$7 /hr
India
Python Expert & Automator: Data Mining, Web Scraping, Crawling and Automation
Mora

Python Expert & Automator: Data Mining, Web Scraping, Crawling and Automation  


Python Python Pandas Python Developers 
$10 /hr
Egypt
Developer
Shraddha Patel

Developer  


Python Odoo 
$4 /hr
India
Software Developer
Ibrahim Hassaan

Software Developer  


Python PHP Web Scraping 
$3 /hr
Maldives
Data Scientist, Computer Vision Expert
Deepanshu Bhinda

Data Scientist, Computer Vision Expert  


Python Computer Vision OpenCV 
$35 /hr
India
Software developer
Vikram Verma

Software developer  


Python PHP Web Hosting 
$15 /hr
India
Developer
Akshay Kumar

Developer  


Python 
$0 /hr
India
DevOps Engineer and Software Development Engineer
Krishna Chaitanya

DevOps Engineer and Software Development Engineer  


Python Amazon S3 Automation 
$10 /hr
United States
Software Developer , Researcher
Issam

Software Developer , Researcher  


Python JSON javascript 
$60 /hr
Canada
Python developer
Saiteja Meka

Python developer  


Python 
$20 /hr
India
Freelance Developer
Keerthana Viyasarayan

Freelance Developer  


Python PHP ASP.NET Core 
$20 /hr
Czech Republic
Python Developer
Rohit Sanjay

Python Developer  


Python Python Numpy Data Science & Analytics 
$10 /hr
India
Honesty is first priority - Full money refunded back if not satisfied...
Shellcast

Honesty is first priority - Full money refunded back if not satisfied...  


Python javascript CakePHP 
$10 /hr
India
Data Scientist
Mathubalan Gopalan

Data Scientist  


Python Data Science & Analytics Machine Learning 
$14 /hr
India
Developer ,Business Analyst
Devi Padikkal

Developer ,Business Analyst  


Python PHP HTML 
$17 /hr
India
Python and machine Learning Specialist
Vidyacharan Kapalli

Python and machine Learning Specialist  


Python Machine Learning 
$20 /hr
India
Developer - Software, Firmware
Sai Bharadwaj Inemella

Developer - Software, Firmware  


Python javascript C Programming 
$4 /hr
India
Software Developer
Gaurav Dhiman

Software Developer  


Python PHP Bash Shell Scripting 
$10 /hr
India
Startup
Nikilesh

Startup  


Python Android Studio Android App Development 
$15 /hr
India
Freelance Developer
Dawson Dias

Freelance Developer  


Python Data Scraping Web Scraping 
$20 /hr
India
Developer
Shilpa Kumari

Developer  


Python Digital Electronics Core Java 
$5 /hr
India
Senior Software engineer
Vivek

Senior Software engineer  


Python javascript Microservices 
$12 /hr
India
Data Scientist
Ganesh Anbhule

Data Scientist  


Python SciPy Python Pandas Data Science & Analytics 
$80 /hr
India
Applied AI Practitioner
Rajyam Matcha

Applied AI Practitioner  


Python OpenCV Image Processing 
$35 /hr
India
Data Extraction Specialist
Victor

Data Extraction Specialist  


Python Scrapy Data Extraction 
/hr
Nigeria
Software engineer
Fred Eric

Software engineer  


Python MATLAB Script C Programming 
$2 /hr
India
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Popular How-To's in Python category


 
How to create a solver in python
Scripts & Utilities

Python scipy provides a good number of optimizers/solvers. You can use these optimizers to solve various non-linear and linear equations. However, sometimes things might get tricky...

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What is Python Script?

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.

What is a Python Script Freelancer?

Python is an interpreted, object-oriented and extensible programming language. Python can run on many different operating systems. A freelancer well versed in Python can handle your workload quite easily. To hire freelance programming help for Python post a job today!

What is a Freelancer?

A freelancer or freelance worker, is a term commonly used for a person who is self-employed and is not necessarily committed to a particular employer long-term.

Why hire a Freelancer instead of full time employee?

If there is a long lead time for them to get up and running, using that investment on a full-time employee might be a better option. And if the position requires oversight, hire an employee. A freelancer might choose to perform the work outside of normal business hours, when you're not able to monitor their progress.

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Skills related to Python

Articles Related To Python


Python is one of the fastest growing programming languages. It has undergone more than 28 years of the successful span. Python itself reveals its success story and a promising future ahead. Python programming language is presently being used by a number of high traffic websites including Google, Yahoo Groups, Yahoo Maps, Shopzilla, Web Therapy, Facebook, NASA, Nokia, IBM, SGI Inc, Quora, Dropbox, Instagram and Youtube. Similarly, Python also discovers a countless use for creating gaming, financial, scientific and instructive applications.

 

Python is a fast, flexible, and powerful programing language that's freely available and used in many application domains. Python is known for its clear syntax, concise code, fast process, and cross-platform compatibility.

 

Python is considered to be in the first place in the list of all AI and machine learning development languages due to the simplicity. The syntaxes belonging to python are terribly easy and can be easily learn. Therefore, several AI algorithms will be easily implemented in it. Python takes short development time as compared to different languages like Java, C++ or Ruby. Python supports object oriented, functional as well as procedure oriented styles of programming. There are lots of libraries in python that make our tasks easier.

 

Some technologies relying on python:

Python has become the core language as far as the success of following technologies is concerned. Let’s dive into the technologies which use python as a core element for research, production and further developments.

 

  1. Networking: Networking is another field in which python has a brighter scope in the future. Python programming language is used to read, write and configure routers and switches and perform other networking automation tasks in a cost-effective and secure manner.
  2. Big Data: The future scope of python programming language can also be predicted by the way it has helped big data technology to grow. Python has been successfully contributing in analyzing a large number of data sets across computer clusters through its high-performance toolkits and libraries.
  3. Artificial Intelligence (AI): There are plenty of python frameworks, libraries, and tools that are specifically developed to direct Artificial Intelligence to reduce human efforts with increased accuracy and efficiency for various development purposes. It is only the Artificial Intelligence that has made it possible to develop speech recognition system, interpreting data like images, videos etc.

 

Why Choose Python for Artificial Intelligence and Machine Learning?

Whether a startup or associate MNC, Python provides a large list of benefits to all. The usage of Python is specified it cannot be restricted to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complicated processes like artificial intelligence (AI), Machine Learning (ML), natural language process, data science etc. The question is why Python is gaining such momentum in AI? And therefore the answer lies below:

 

Flexibility: Flexibility is one of the core advantages of Python. With the option to choose between OOPs approach and scripting, Python is suitable for every purpose. It works as a perfect backend and it also suitable for linking different data structures together.

 

Platform agnostic: Python provides developer with the flexibility to provide an API from the existing programming language. Python is also platform independent, with just minor changes in the source codes, you can get your project or application up and running on different operating systems.

 

Support: Python is a completely open source with a great community. There is a host of resources available which can get any developer up to speed in no time. Not to forget, there is a huge community of active coders willing to help programmers in every stage of developing cycle.

 

Prebuilt Libraries: Python has a lot of libraries for every need of your AI project. Few names include Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning.

 

Less Code: Python provides ease of testing - one of the best among competitors. Python helps in easy writing and execution of codes. Python can implement the same logic with as much as 1/5th code as compared to other OOPs languages.

 

Applications of Python:

There are so many applications of Python in the real world. But over time we’ve seen that there are three main applications for Python

Web Development: Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

Data Science (including Machine Learning): Machine Learning with Python has made it possible to recognize images, videos, speech recognition and much more.

Data Analysis/Visualization: Python is also better for data manipulation and repeated tasks. Python helps in the analysis of a large amount of data through its high-performance libraries and tools. One of the most popular Python libraries for the data visualization is Matplotlib.

 

Now a days, the popularity of scientific computing environments such as IDL, Maple, Mathematica, Matlab and R has increased considerably. Engineer simply feel more productive in such environments. One reason is the simple and clean syntax of command languages in these environments. Another factor is tight integration of simulation and visualization in Maple, R and similar environments you can quickly and conveniently visualize what you just have computed. One problem with the mentioned environments is that they do not work, at least not in an easy way, with other types of numerical software and visualization systems. Many of the environment specific programming languages are also quite simple or primitive. At this point scripting in Python comes in.

 

Python offers the clean and simple syntax of the popular scientific computing environments, the language is very powerful, and there are lots of tools for simulation, visualization, and data analysis programs. Python allows you to build your own Matlab like scientific computing environment, tailored to your specific needs and based on your favorite high performance FORTRAN, C, or C++ codes.

 

Scientific Computing Is More Than Number Crunching: Many computational scientists work with their own numerical software development and realize that much of the work is not only writing computationally intensive number-crunching loops. Very often programming is about shuffling data in and out of different tools, converting one data format to another, extracting numerical data from a text, and administering numerical experiments involving a large number of data files and directories. Such tasks are much faster to accomplish in a language like Python than in FORTRAN, C, C++, and C#.

 

Scripting is particularly attractive for building demos related to teaching or project presentations. Such demos benefit greatly from a GUI, which offers input data specification, calls up a simulation code, and visualizes the results. The simple and intuitive syntax of Python encourages users to modify and extend demos on their own, even if you are newcomers to Python.

 

Python has some clear advantageous over Matlab and similar environments:

  • The Python programming language is more powerful.
  • The Python environment is completely open and made for integration with external tools.
  • A complete toolbox/module with lots of functions and classes can be contained in a single file.
  • Transferring functions as arguments to functions is simpler.
  • Nested, heterogeneous data structures are simple to construct and use.
  • Object-oriented programming is more convenient.
  • Interfacing C, C++, and FORTRAN code is better supported and therefore simpler.
  • Scalar functions work with array arguments to a larger extent (without modifications of arithmetic operators).
  • The source is free and runs on more platforms.

 

How to run Python script

One of the most important skills you need to build as a Python developer is to be able to run Python scripts and code. This is going to be the only way for you to know if your code works as you planned. It’s even the only way of knowing if your code works at all!

 

A Python script is a reusable set of code which is essentially a Python program or a sequence of Python instructions contained in a file. You can run the program by specifying the name of the script file to the interpreter. 

 

This step-by-step will guide you through a series of ways to run Python scripts, depending on your environment, platform, needs, and skills as a programmer. When you try to run Python scripts, a multi-step process begins. 

 

  1. Run Python Scripts Using the Command-Line: A Python interactive session will allow you to write a lot of lines of code, but once you close the session, you lose everything you’ve written. That’s why the usual way of writing Python programs is by using plain text files. By convention, those files will use the .py extension. Open a command-line and type in the word ‘python’ followed by the path to script file and press enter. You’ll see output on your screen.
  2. Run Python Scripts Interactively: It is also possible to run Python scripts and modules from an interactive session. This option offers you a variety of possibilities.
    • Taking advantage of import
    • Use importlib and imp
    • Use runpy.run_module()
    • Hacking exec()
    • Use execfile()
  3. Run Python Scripts from an IDE or a Text Editor: IDE offer the possibility of running your scripts from inside the environment itself. It is common for them to include a Run or Build command, which is usually available from the tool bar or from the main menu.
  4. Run Python Scripts From a File Manager: Running a script by double-clicking on its icon in a file manager is another possible way to run your Python scripts. This option may not be widely used in the development stage, but it may be used when you release your code for production.

 

After you play around with Python on your own or in an online tutorial, I highly recommend to you to write small scripts to strengthen your knowledge. To stay motivated, choose a program that is in some way useful to you, so you can gain insight while figuring out Python. Below are a few ways you can begin to build your expert level in Python script:

 

  • Python Documentation
  • Google and stackoverflow
  • Ask an experience person

 

First, create a very basic version end-to-end. It is much less frustrating than trying to build a super-duper version from scratch. A big plus is that you will have something you can use very fast. Then iterate and add more complex functionality one by one.

 

Second, decompose large problems to smaller ones by introducing functions. Small, cohesive functions are easy to understand, test and debug.

 

Last, but probably the most important thing to keep in mind, is practice makes perfect. Start small, be patient and practice. Happy coding!

Welcome to Python programming world! We presume you are trying to find information concerning why and how to get started with Python. Fortunately, an experienced coder in any programing language (whatever it's going to be) will pick up Python very quickly. It is also easy for beginners to learn and use.

 

Why you should learn Python

Python is one of the most popular general-purpose programming languages used for both large and small-scale applications. With Python, you can discover how to bridge web development and data analytics. Python’s widespread adoption is due to its large standard library, easy readability, and support of multiple paradigms such as functional, procedural and object-oriented programming styles. Python modules interact with a variety of databases, making it an excellent choice for large-scale data analysis. The Python programming language is often the best choice for introductory courses in data science and machine learning. If you've been wondering how to learn python online to advance your career, you've come to the right destination.

 

A popular Python slogan “life is happier without braces”.

 

Install Python

Installing Python is generally easy, and today several Linux and UNIX system distributions include a recent Python. Even some Windows computers currently go along with Python already installed. If you do need to install Python download from Python official website.

 

Learning Python

Before getting started, you may want to find out which IDEs and text editor are best, IDE usually has plenty of useful features such as autocomplete, debugger and refactoring tools. Some will even check your Python code for little mistakes and encourage best practices through warnings. IDE will help you to find bugs and develop code faster. Learn basics of Python programming and syntax from online Python tutorials.

 

What you need to learn

  1. Python Syntax
  2. String and Console output
  3. Conditionals and control flow
  4. Function
  5. List and Dictionaries
  6. Loops and array
  7. Classes
  8. File input and output
  9. Advanced topic in python

 

Here are some tips to help you make the new concepts you are learning as a beginner programmer:

  1. Code Everyday: Consistency is very important when you are learning a new language. We recommend making a commitment to code every day.
  2. Write it out: As you progress on your journey as a new programmer, you may wonder if you should be taking notes. This will be especially beneficial for those working towards the goal of becoming a full-time developer, as many interviews will involve writing code on a whiteboard.
  3. Go Interactive: Whether you are learning about basic Python data structures (strings, lists, dictionaries, etc.) for the first time, or you are debugging an application, the interactive Python shell will be one of your best learning tools.
  4. Become bug hunter: Once you begin writing complicated programs that you just can run into bugs in your code. It happens to all or any of us! Don’t let bugs frustrate you. Instead, embrace these moments proudly and consider yourself as a bug bounty hunter.
  5. Surround yourself with others: It is extremely important when you are learning to code in Python that you simply surround yourself with others who are learning additionally. This may allow you to share the information and tricks you learn on the approach.
  6. Teach: It is said that the most effective way to learn something is to teach it. This is often true once you are learning Python. There are many ways to try to do this: white boarding with other Python lovers, writing blog posts explaining recently learned ideas, recording videos during which you explain something you learned, or simply talking to yourself at your computer.
  7. Pair program: Pair programming is a technique that involves two developers working to complete a task. The two developers switch between them. One developer writes the code, while other helps guide the problem solving and reviews the code as it is written. Switch frequently to get the benefit of both sides.
  8. Build something: For beginners, there are many small exercises that will really help you become confident with Python.

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