Top 10 Python Projects in the Year 2018

Top 10 python projects in the year 2018

Hello readers, welcome to the top 10 new python projects in the year 2018. Here are the few good projects are considered by the checking quality and credibility in the year 2018. The listed projects are developed with all open source libraries and tools. You can choose the project based on how big and effective it is and be the competence in the industry.
These are interesting and challenging projects to choose. All these projects were interesting and challenging, plays a very prominent role when building up your skill set, team skill set, level of competence and has the best chance to get success with the first step.

Top 10 Python Projects

Python Projects

Top 10 Python Projects List:

  • Home Assistant
  • PyTorch
  • Sanic
  • Pipenv
  • MicroPython
  • Prophet
  • SerpentAI
  • Python-Fire
  • SpaCy

Brief about the new python projects

Home Assistant:

It is an open source automation, allows to control the home devices remotely and puts privacy first. Can control and track multiple devices in the home with one interface, interacts with the things easily and it is good than other home automation tools. It allows checking cross-device notification and automation. For an example, you can check the temperature of your home in compare of outside and alerts you with notification using email service.


It is a deep Learning library in Python. It allows working on GPU’s and CPU’s like tensor operations. It involves working in Autograd Mechanics, Broadcasting Semantics, and CUDA semantics. Majorly it involves in computing Graphical processing unit operations.
PyTorch library is also used in the Machine Learning concepts and algorithms. Involves in deep neural networks type of work and so on.
Please click here for the tutorial


It is one of the big web framework written to go fast. It really handles the fast asynchronous and ‘wait’ based operations and came out pretty recently. It is developed on GitHub.
It works fine with Python 3.5+, The semantics and syntax are very simple than other web frameworks.
Please click here for tutorial


It is a tool to get all the required packages to the Python. It automatically creates virtual environments to your project and allows to manage easily.
You can create a new project, can install all dependencies for a project, can remove project virtualenv, create a lockfile, and can Check your installed dependencies for security vulnerabilities. You can create all the project dependencies at one go in the project folder and develop applications easily.
Pipenv is mainly used to provide an easy method to set up a working environment for users and developers for developing applications.
please click here for tutorial


It is a full Python compiler and runtime that runs on the bare metal and it is optimized to run on microcontrollers and in constrained environments. It is also called as a software implementation of Python3. It is also called as a Pyboard (compact electronic board circuit) that runs on MicroPython on the metal acts like a low-level Python Operating System that can be used to control the electronic projects.
It is available in the market. With the plain python, it allows transferring the information from desktop to embedded systems.
Please click here for tutorial


It’s a tool and API for producing high-quality forecasts for time series data that has multiple seasonality with linear and nonlinear growth.
The prophet is fast and provides automated data that can be used by data scientist and data analyst. Mainly used in predicting and analyzing the data. A prophet is a forecasting tool which is implemented in R and Python.
Please click here for tutorial


It is framework allows creating game agents with using python code. It can turn any video game to ‘Sandbox’ environment with familiar python code. It supports python scripting easily.
It is a valuable tool for Machine Learning and AI Research. It helps to create AI’s and bots to play any game using python.


It is a library which automatically generates command line interfaces. We can generate as a command line using any of the Python code which is written using objects, classes, and scripting.
The fire() function which is written in the python program will turn as a command line interface. We don’t have defined or write the arguments. We can call the ‘fire’ function from the main module and next is handled automatically.
GitHub link, please click here
Please click for the tutorial


It is a library which is written in a combination of Python and Cython and used for advance Natural Processing Language. We can work on machine learning concepts using SpaCy, it involves in deep learning.
With help of SpaCy we can build real products and real data analytics. Develop large scale projects easily. In Artificial Intelligence projects mainly considers natural language processing techniques.
spaCy provides a concise API to access its methods and properties governed by the trained machine (and deep) learning models
Please click for tutorial

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