Some of its key distinguishing features include:
- very clear, readable syntax
- strong introspection capabilities
- intuitive object orientation
- natural expression of procedural code
- full modularity, supporting hierarchical packages
- exception-based error handling
- very high level dynamic data types
- extensive standard libraries and third party modules for virtually every task
- extensions and modules easily written in C, C++ (or Java for Jython, or .NET languages for IronPython)
- embeddable within applications as a scripting interface
Python is powerful... and fast
Fans of Python use the phrase "batteries included" to describe the standard library, which covers everything from asynchronous processing to zip files. The language itself is a flexible powerhouse that can handle practically any problem domain. Build your own web server in three lines of code. Build flexible data-driven code using Python's powerful and dynamic introspection capabilities and advanced language features such as meta-classes, duck typing and decorators.
Python lets you write the code you need, quickly. And, thanks to a highly optimized byte compiler and support libraries, Python code runs more than fast enough for most applications. The traditional implementation of CPython uses a bytecode virtual machine; PyPy supports just-in-time (JIT) compilation to machine code. Also, Jython and IronPython (see below) support JIT compilation on their respective virtual machine implementations.
Python plays well with others
Python can integrate with COM, .NET, and CORBA objects.
For Java libraries, use Jython, an implementation of Python for the Java Virtual Machine.
For .NET, try IronPython , Microsoft's new implementation of Python for .NET, or Python for .NET.
Python is also supported for the Internet Communications Engine (ICE) and many other integration technologies.
If you find something that Python cannot do, or if you need the performance advantage of low-level code, you can write extension modules in C or C++, or wrap existing code with SWIG or Boost.Python. Wrapped modules appear to your program exactly like native Python code. That's language integration made easy. You can also go the opposite route and embed Python in your own application, providing your users with a language they'll enjoy using.
Python runs everywhere
Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. There are even versions that run on .NET and the Java virtual machine. You'll be pleased to know that the same source code will run unchanged across all implementations.
Your favorite system isn't listed here? It may still support Python if there's a C compiler for it. Ask around on news:comp.lang.python - or just try compiling Python yourself.
Python is friendly... and easy to learn
The Python newsgroup is known as one of the friendliest around. The avid developer and user community maintains a wiki, hosts international and local conferences, runs development sprints, and contributes to online code repositories.
Python also comes with complete documentation, both integrated into the language and as separate web pages. Online tutorials target both the seasoned programmer and the newcomer. All are designed to make you productive quickly. The availability of first-rate books completes the learning package.
Python is Open
The Python implementation is under an open source license that makes it freely usable and distributable, even for commercial use. The Python license is administered by the Python Software Foundation.
Take a look at application domains where Python is used, or try the current download for yourself.
Python 3.7.4 is the fourth and most recent maintenance release of Python 3.7. The Python 3.7 series is the newest major release of the Python language and contains many new features and optimizations.
Among the major new features in Python 3.7 are:
- PEP 539, new C API for thread-local storage
- PEP 545, Python documentation translations
- New documentation translations: Japanese, French, and Korean.
- PEP 552, Deterministic pyc files
- PEP 553, Built-in breakpoint()
- PEP 557, Data Classes
- PEP 560, Core support for typing module and generic types
- PEP 562, Customization of access to module attributes
- PEP 563, Postponed evaluation of annotations
- PEP 564, Time functions with nanosecond resolution
- PEP 565, Improved DeprecationWarning handling
- PEP 567, Context Variables
- Avoiding the use of ASCII as a default text encoding (PEP 538, legacy C locale coercion and PEP 540, forced UTF-8 runtime mode)
- The insertion-order preservation nature of dict objects is now an official part of the Python language spec.
- Notable performance improvements in many areas.