Search results
IronPython
- IronPython is the code name for an implementation of the Python programming language written by the CLR team at Microsoft. IronPython runs on the Microsoft®.NET Framework and supports an interactive console with fully dynamic compilation.
learn.microsoft.com/en-us/archive/msdn-magazine/2006/october/clr-inside-out-ironpython
Oct 7, 2019 · IronPython is the code name for an implementation of the Python programming language written by the CLR team at Microsoft. IronPython runs on the Microsoft® .NET Framework and supports an interactive console with fully dynamic compilation.
Existing .NET developers can also use IronPython as a fast and expressive scripting language for embedding, testing, or writing a new application from scratch. The CLR is a great platform for creating programming languages, and the DLR makes it all the better for dynamic languages.
Oct 2, 2019 · And languages running on the CLR can integrate seamlessly. Sharing libraries and frameworks allows languages new to the CLR to build on the work of others. The CLR also includes support for dynamic languages, as IronPython 1.0 demonstrates ( www.codeplex.com/ironpython ).
Python.NET is a package that gives Python programmers nearly seamless integration with the .NET Common Language Runtime (CLR) and provides a powerful application scripting tool for .NET developers. It allows Python code to interact with the CLR, and may also be used to embed Python into a .NET application.
- Overview
- Primary DLR Advantages
- DLR Architecture
- DLR Documentation
- See also
The dynamic language runtime (DLR) is a runtime environment that adds a set of services for dynamic languages to the common language runtime (CLR). The DLR makes it easier to develop dynamic languages to run on the .NET Framework and to add dynamic features to statically typed languages.
Dynamic languages can identify the type of an object at run time, whereas in statically typed languages such as C# and Visual Basic (when you use Option Explicit On) you must specify object types at design time. Examples of dynamic languages are Lisp, Smalltalk, JavaScript, PHP, Ruby, Python, ColdFusion, Lua, Cobra, and Groovy.
Most dynamic languages provide the following advantages for developers:
•The ability to use a rapid feedback loop (REPL, or read-evaluate-print loop). This lets you enter several statements and immediately execute them to see the results.
•Support for both top-down development and more traditional bottom-up development. For example, when you use a top-down approach, you can call functions that are not yet implemented and then add underlying implementations when you need them.
•Easier refactoring and code modifications, because you do not have to change static type declarations throughout the code.
Simplifies Porting Dynamic Languages to the .NET Framework
The DLR allows language implementers to avoid creating lexical analyzers, parsers, semantic analyzers, code generators, and other tools that they traditionally had to create themselves. To use the DLR, a language needs to produce expression trees, which represent language-level code in a tree-shaped structure, runtime helper routines, and optional dynamic objects that implement the IDynamicMetaObjectProvider interface. The DLR and the .NET Framework automate a lot of code analysis and code generation tasks. This enables language implementers to concentrate on unique language features.
Enables Dynamic Features in Statically Typed Languages
Existing .NET Framework languages such as C# and Visual Basic can create dynamic objects and use them together with statically typed objects. For example, C# and Visual Basic can use dynamic objects for HTML, Document Object Model (DOM), and .NET reflection.
Provides Future Benefits of the DLR and .NET Framework
Languages implemented by using the DLR can benefit from future DLR and .NET Framework improvements. For example, if the .NET Framework releases a new version that has an improved garbage collector or faster assembly loading time, languages implemented by using the DLR immediately get the same benefit. If the DLR adds optimizations such as better compilation, the performance also improves for all languages implemented by using the DLR.
The following illustration shows the architecture of the dynamic language runtime.
DLR architecture
The DLR adds a set of services to the CLR for better supporting dynamic languages. These services include the following:
•Expression trees. The DLR uses expression trees to represent language semantics. For this purpose, the DLR has extended LINQ expression trees to include control flow, assignment, and other language-modeling nodes. For more information, see Expression Trees (C#) or Expression Trees (Visual Basic).
•Call site caching. A dynamic call site is a place in the code where you perform an operation like a + b or a.b() on dynamic objects. The DLR caches the characteristics of a and b (usually the types of these objects) and information about the operation. If such an operation has been performed previously, the DLR retrieves all the necessary information from the cache for fast dispatch.
•Dynamic object interoperability. The DLR provides a set of classes and interfaces that represent dynamic objects and operations and can be used by language implementers and authors of dynamic libraries. These classes and interfaces include IDynamicMetaObjectProvider, DynamicMetaObject, DynamicObject, and ExpandoObject.
For more information about how to use the open source version of the DLR to add dynamic behavior to a language, or about how to enable the use of a dynamic language with the .NET Framework, see the documentation on the IronLanguages/dlr repo on GitHub.
Mar 11, 2023 · As long as you write a program that takes ANY source code (e.g. Python, PHP, C++, etc.) and converts it to MSIL - you can have it run on CLR. And people actually did just that: IronPython compiles Python to CLR
People also ask
What is the Common Language Runtime (CLR)?
Does CLR support dynamic languages?
What is a Dynamic Language Runtime (DLR)?
What is IronPython and the Dynamic Language Runtime?
Which CLR namespaces can be treated as Python packages?
Is Clr better than DLR?
Oct 4, 2023 · IronPython uses the DLR (Dynamic Language Runtime) of the CLR to allow Python programs to run with the same degree of dynamism that they do in CPython. Use cases for IronPython Like Jython ...
