What systems is Python suitable for?

Python environment construction is suitable for many systems such as: Linux and Mac OS X, Unix (Solaris, Linux, FreeBSD, AIX, HP/UX, SunOS, IRIX, etc.), Win 9x/NT/2000, Macintosh (Intel, PPC, 68K), OS/2, DOS (multiple DOS versions), PalmOS, Nokia mobile phones, Windows CE, Acorn/RISC OS, BeOS, Amiga, VMS/OpenVMS, QNX, VxWorks, Psion

Python can also be ported to Java and .NET virtual machines. (Recommended learning: Python video tutorial)

Python uses the same virtual machine mechanism as Java. This construction idea can fully satisfy the same code on different operating systems. Operational needs; therefore, the applicability of the language on the operating system is determined only by the needs of the application itself. As a python developer, from experience, python is suitable for any operating system it supports. But in terms of the breadth of applications, most python commercial applications exist on Linux. Mainly used for testing, back-end functions and data mining.

In addition, I hope you will not stick to operating systems and languages. After all, they are just bridges for human-computer interaction. Being able to make full use of hardware performance and deliver tasks regularly is the top priority.

Python's latest source code, binary documents, news information, etc. can be viewed on Python's official website. You can download Python's documents on the official Python website. I personally recommend downloading HTML, PDF, PostScript and other formats. documentation.

Check whether the Python environment is installed on the system you are using. You can enter the "python" command through the terminal window to check whether Python has been installed locally and the installation version of Python.

Python has been ported to many platforms (with modifications to enable it to work on different platforms). You need to download the appropriate binaries for your platform and then install Python. If binaries for your platform are not available, you will need to manually compile the source code using a C compiler. Compiled source code is more selective in functionality and provides more flexibility for python installation.

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