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How to Install Python 3 and IDE or Anaconda Distribution on Windows 10


What is Python, Python Distribution, and IDE - In this post, we will discuss the tutorial on Installing Python 3 and IDE or Anaconda Distribution on Windows 10. Because it is quite long, this tutorial will be divided into several parts.

The ability to install computer programming software is the most basic thing that you must have if you want to become a programmer, scientist (in some research fields), engineer (in some research fields), or a career in data as a data engineer; data scientist; or data analyst.

But before following this tutorial, we hope you have:

  1. Ability to operate internet browser software (browser),
  2. Basic knowledge regarding the Windows 10 operating system regarding the software installation process.
  3. You can choose the Python-only installation or use the Anaconda (Python) Distribution.

In this first part, we will discuss basic knowledge such as Python, Python distribution, and IDE (integrated development environment), followed by Installing Python 3 and Installing Anaconda Python Distribution the Windows 10 operating system.

What is Python?

Python is a programming language made for the first time by Guido van Rossum, a researcher at the University of Amsterdam, the Netherlands. Python was released to the public for the first time in the early 1990s. The open-source Python license is held by the Python Software Foundation (PSF), an institution founded by Guido and his associates in the early 2000s.

What makes Python more than other programming languages:

  1. Open source, of course, you don't have to pay for a Python license either to use or create Python-based applications for commercial purposes.
  2. Easy to write and read (easy to write and read), Python's syntax, which is almost close to human language, namely English, makes writing program code easy. For those who read program code, even though they are not programmers, it will also be easy to understand the program code that has been written.
  3. Programming languages ​​are interpreted, unlike C / C ++ or Fortran, as compiled languages.
  4. Supports object-oriented programming (OOP for short) in addition to functional programming
  5. Because of its easy to write and read nature, Python is used as a command language to accommodate applications created in other programming languages.
  6. It has quite a number of packages (known as Python packages) aimed at scientific computing by scientists and engineers, artificial intelligence (AI for short), machine learning, and data science.
  7. Google uses them as the core of its search engine (search engine), Dropbox, Youtube, NASA, Lucas Film, and other large companies.

Python version

Currently, Python has two major versions, namely Python 2 and Python 3. In general, Python is released in a version with the code major.minor.micro. Major is a major version of Python, which is marked by major changes in the language. Minor is a minor change in the language, for example, to improve writing and improve execution capabilities. Sedagkan micro is intended for bug-fixed releases. In general, Python end-users use stable releases of Python from the naming of this version of major.minor.micro.

Python Distribution

Because Python has a large number of packages in various areas, some of the world's technology companies bundle Python with certain packages to be distributed to end-users. The main goal is that users are not too bothered by doing additional installations after Python has finished installing.

What Python packages are distributed to these end-users? In general, they are:

  1. Scientific Python Stacks (scipy stacks), which is a collection of packages containing libraries for scientific purposes such as NumPy (Numerical Python) for array data types such as Matlab, Scipy (scientific Python) for scientific calculations, Matplotlib for plotting, SymPy (Symbolic Python) for computing symbolic such as Maple or Mathematica, Pandas for data manipulation and data analysis. Finally, IPython is an interactive Python command editor and is also the base building block for Jupyter Notebook.
  2. Databases, like SQL Alchemy, besides Python's own default, SQLite.
  3. An IDE like Spyder should be a replica of Matlab's interface (commercial application).
  4. Notebooks such as Jupyter Notebook or JupyterLab, namely integration of code, text, and visualization on one page using a browser such as Chrome, Firefox, or Safari. This package is like using Mathematica (commercial application)
  5. Plotting or visualization, such as vtk, MayaVi, Bokeh, HoloView, Seaborn, and Matplotlib.
  6. Scientific applications for certain domains such as bioinformatics (biopython), machine learning (Scikit-Learn), image processing (scikit-image), astrophysics astropy). Unfortunately for AI (such as Keras and TensorFlow) to the best of my knowledge it is not bundled but can be installed later.
  7. To create a graphical user interface (GUI for short), users can use pyqt (Qt-based). The default Python for this GUI is tk.
  8. Package management, such as conda and an established deployment manager (EDM) in addition to Python's default, namely pip.

Who are the technology companies in the world that distribute Python with several packages? In general, for the purposes of scientific computing and data science, there are two technology companies, namely:

1. Anaconda Inc.

Anaconda Distribution

Anaconda Inc. formerly the name Continuum Analytic Inc. headquartered in Texas, United States. This is a large company that provides Python distribution for data science (as well as scientific computing) on ​​an open-source and enterprise scale. For open-source, the python distribution is the Anaconda Distribution ( which is available for Windows, macOS, and Linux / PowerPC operating systems. Meanwhile, Anaconda Enterprise has a commercial license aimed at the company.

2. Enthought Inc.

Enthought Canopy Python distribution

Enthought Inc., which is also headquartered in Texas, United States of America, provides the Python distribution for scientific and analytic computing. The open-source distribution of Python released is Enthought Canopy ( which is available for Windows, macOS, and Linux operating systems as shown on its website.

Apart from the two companies above, there are three other companies:

1. Intel Corp.

Intel Distribution for Python

Through the Intel Distribution for Python ( which is open source. Intel also provides a Python distribution for the Windows, macOS, and Linux operating systems, as shown on its website.

2. Activestate Software Inc.

ActivePython Community Edition

Through ActivePython Community Edition ( which is open source on the official website for Windows, Linux and Mac operating systems.

3. Microsoft Inc.

Visual Studio with Python versi Community

Via the Community version of Visual Studio with Python at

IDE (integrated development environment)

Integrated development environment or abbreviated as IDE is an integrated computer program development environment because there are quite a lot of facilities available. This can make it easier for computer program developers to develop software either individually or in teams to increase productivity in managing software development.

What IDEs are used in the Python programming language? These IDEs include:


default Python IDE

IDLE (integrated development environment) as the default Python IDE after the installation process is complete on each operating system.

2. Spyder

Spyder IDE

Spyder (Scientific Python Development Environment) written in Python can be installed via pip, a built-in Python package management. Spyder has an MIT license (an open-source license) with a GUI like Matlab.

3. PyCharm

PyCharm Community IDE

PyCharm released by JetBrains Inc. which provides a community (PyCharm Community) and professional (PyCharm Professional) version. PyCharm Community is free for general users, while PyCharm Professional is paid. For academics/researchers, PyCharm Professional is free for one year by registration via the institution's email and can be extended. Both have the same interface, with the only difference being the features provided.

4. Visual Studio Code


Visual Studio Code (abbreviated as VS Code) is an open-source IDE from Microsoft that supports various types of programming languages ​​through the installation of certain extensions for each programming language. In order to be used for python programming, there are several VS Code extensions for Python that must be installed first.

Package Management

Package management is a Python library that is intended to manage packages that will be installed into the Python environment related to dependencies with other packages or Python itself. Generally, this engagement is expressed by the compatibility of the version developed by the developer with Python and a particular package.

The two management packages in Python are:

  1. pip (Pip Install Packages) comes with every time you install Python from the official website or via a Python distribution.
  2. Conda package manager developed by Anaconda Inc. to manage Python packages such as installing packages, removing packages, creating/removing certain environments (create/remove environments), looking for suitable packages, cleaning packages and caches from the Python environment, updating packages, and so on. Overall, conda has the ability above the pip.

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