Do not recommend beginners to choose AnacondaPython and ActivePython, in my opinion they provide convenience to the user than learning so much trouble,
Retaining
Retaining belongs to Python reference implementation scheme, is all other Python distribution of a set of standardized versions, retaining written using C language, and the authors contains a number of the core staff in Python language top decision-makers, retaining in terms of optimizing the most conservative, of course, this is not a defect, but the design orientation, Python advocates hope will retaining into Python most widely compatibility and standardized implementation scheme, retaining the most suitable for Python standard should have good compatibility and consistency of users, in addition, retaining the same applies to hope in the most basic way to use Python and are willing to give up some convenience of professionals,
Anaconda Python
Hand Anaconda derived from Anaconda company (formerly known as Continuum Analytics), its design goal is to serve those needs by commercial suppliers support Python developers and business support services, Anaconda Python's main use cases including mathematics, statistics, engineering, data analysis, machine learning, and other related applications, Anaconda bundles have Python commercial and scientific usage scenarios of all kinds of commonly used libraries - including SciPy, NumPy and Numba, etc., at the same time, through a set of customized package management system to provide more access ability,
ActivePython
Similar to the Anaconda ActivePython, also by the profit-making enterprises create and maintain - ActiveState company, the company also in selling a variety of common language runtime and multilingual Komodo IDE, ActivePython for enterprise users with data scientists - that is, want to use the Python language, but don't want to waste a lot of energy on assembly and management aspects of Python, ActivePython using conventional PIP in Python package manager, but also in the form of a certification package to provide hundreds of common libraries, plus Intel mathematics has some core library and other third-party dependencies of the public library,
PyPy
PyPy belongs to substitute for retaining the interpreter, the use of instant (JIT) compiler to speed up the process of execution, a Python program according to the actual execution of task, its performance can be very significant, for Python - especially retaining sound of complaints, mainly revolves around the speed performance, by default, the running speed of Python than C language - gap may even reach hundreds of times, PyPy JIT will compile Python code into machine language, resulting in an average of 7.7 times the speed of retaining, in some specific task, the acceleration effect can reach 50 times,
Jython
JVM (Java virtual machine) can be used as a multiple languages except the Java runtime options, this long list includes Groovy, Scala and Clojure, Kotlin, Python, and - yes, of course, Jython, Jython's biggest drawbacks is its only supports the Python 2 x version, currently in Python 3. X version support ability is still in development, but still need quite a long time, now, don't have any relevant version released,
IronPython
Similar to Python implementation scheme on the JVM Jython positioning, IronPython belongs to a foothold. The.net runtime - or CLR (common language runtime) - Python implementation scheme of IronPython use CLR DLR (dynamic language runtime) to allow a Python program to equal to realize dynamic level of retaining operation, similar to Jython, IronPython currently only supports the Python 2 x version, but IronPython 3 x implementation scheme is in intensive development of
Install Python
From Python's official website to download, please pay attention to choose the right version, if it is used for learning, download the latest version there is no problem, if it is used in the production, is to consider whether you development requires third-party modules to support the latest version of Python, do not forget to check the installed at the bottom of two checkboxes, otherwise can bring some trouble to subsequent modules installed, it is recommended to use the default installation way,
My colleagues are also young IDE fans, pycharm initial use, later is now hot vscode,
I love to use python IDLE, and even take it when the calculation is used, most of the time, I use the IDLE written validation code is correct, check whether the module as well as the version number, the success of the installation IDLE support the TAB key to auto-complete, I often use this function to view an object's methods and properties,
Tip
1. The TAB key to auto-complete
2. Move the cursor to the execution of the statement on the hit return, can repeat the order
3. The underscore (_) can get the last execution results
In fact, the IDLE is an IDE, you can use it to create or open. Py script file, you can edit, run, and debug,
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