pythonnet 3.0.4

.NET Standard 2.0 This package targets .NET Standard 2.0. The package is compatible with this framework or higher.
There is a newer prerelease version of this package available.
See the version list below for details. 
dotnet add package pythonnet --version 3.0.4                

                    
                

            
NuGet\Install-Package pythonnet -Version 3.0.4
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="pythonnet" Version="3.0.4" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
paket add pythonnet --version 3.0.4                

                    
                

            
#r "nuget: pythonnet, 3.0.4"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
// Install pythonnet as a Cake Addin
#addin nuget:?package=pythonnet&version=3.0.4

// Install pythonnet as a Cake Tool
#tool nuget:?package=pythonnet&version=3.0.4

pythonnet is a package that gives .NET programmers ability to integrate Python engine and use Python libraries.

Embedding Python in .NET

  • You must set Runtime.PythonDLL property or PYTHONNET_PYDLL environment variable, otherwise you will receive BadPythonDllException (internal, derived from MissingMethodException) upon calling Initialize. Typical values are python38.dll (Windows), libpython3.8.dylib (Mac), libpython3.8.so (most other *nix). Full path may be required.
  • Then call PythonEngine.Initialize(). If you plan to use Python objects from multiple threads, also call PythonEngine.BeginAllowThreads().
  • All calls to Python should be inside a using (Py.GIL()) {/* Your code here */} block.
  • Import python modules using dynamic mod = Py.Import("mod"), then you can call functions as normal, eg mod.func(args). You can also access Python objects via PyObject and dervied types instead of using dynamic.
  • Use mod.func(args, Py.kw("keywordargname", keywordargvalue)) or mod.func(args, keywordargname: keywordargvalue) to apply keyword arguments.
  • Mathematical operations involving python and literal/managed types must have the python object first, eg. np.pi * 2 works, 2 * np.pi doesn't.

Example

using var _ = Py.GIL();

dynamic np = Py.Import("numpy");
Console.WriteLine(np.cos(np.pi * 2));

dynamic sin = np.sin;
Console.WriteLine(sin(5));

double c = (double)(np.cos(5) + sin(5));
Console.WriteLine(c);

dynamic a = np.array(new List<float> { 1, 2, 3 });
Console.WriteLine(a.dtype);

dynamic b = np.array(new List<float> { 6, 5, 4 }, dtype: np.int32);
Console.WriteLine(b.dtype);

Console.WriteLine(a * b);
Console.ReadKey();

Output:

1.0
-0.958924274663
-0.6752620892
float64
int32
[  6.  10.  12.]

Resources

Information on installation, FAQ, troubleshooting, debugging, and projects using pythonnet can be found in the Wiki:

https://github.com/pythonnet/pythonnet/wiki

Mailing list https://mail.python.org/mailman/listinfo/pythondotnet Chat https://gitter.im/pythonnet/pythonnet

.NET Foundation

This project is supported by the .NET Foundation.

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (41)

Showing the top 5 NuGet packages that depend on pythonnet:

Package Downloads
Python.Included

Python.Included is an automatic deployment mechanism for .NET packages which depend on the embedded Python distribution. This allows libraries depending on Python and/or Python packages to be deployed via Nuget without having to worry about any local Python installations.
Numpy.Bare

C# bindings for NumPy on Win64 - a fundamental library for scientific computing, machine learning and AI. Does require Python 3.7 with NumPy 1.16 installed!
Gradient.Runtime

Core runtime components for Gradient
LostTech.NumPy

.NET bindings for NumPy. Requires the actual Python with NumPy installed.
LostTech.TensorFlow

FULL TensorFlow 2.5+ for .NET with Keras. Build, train, checkpoint, execute models. Samples: https://github.com/losttech/Gradient-Samples, https://github.com/losttech/YOLOv4, https://github.com/losttech/Siren Deep learning with .NET blog: https://ml.blogs.losttech.software/ Comparison with TensorFlowSharp: https://github.com/losttech/Gradient/#why-not-tensorflowsharp Comparison with TensorFlow.NET: https://github.com/losttech/Gradient/#why-not-tensorflow-net Allows building arbitrary machine learning models, training them, and loading and executing pre-trained models using the most popular machine learning framework out there: TensorFlow. All from your favorite comfy .NET language. Supports both CPU and GPU training (the later requires CUDA or a special build of TensorFlow). Provides access to full tf.keras, estimators and many more APIs. Free for non-commercial use. For licensing options see https://losttech.software/buy_gradient.html !!NOTE!! This version requires Python 3.x x64 to be installed with TensorFlow 2.5.x. See the official installation instructions in https://www.tensorflow.org/install/ (ensure you are installing version 2.5 to avoid hard-to-debug issues). Please, report any issues to https://github.com/losttech/Gradient/issues For community support use https://stackoverflow.com/ with tags (must be all 3 together) tensorflow, gradient, and .net. For support email contact@losttech.software . More information in NuGet package release notes and on the project web page: https://github.com/losttech/Gradient . TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

GitHub repositories (9)

Showing the top 5 popular GitHub repositories that depend on pythonnet:

Repository Stars
elsa-workflows/elsa-core
A .NET workflows library
LykosAI/StabilityMatrix
Multi-Platform Package Manager for Stable Diffusion
Danily07/Translumo
Advanced real-time screen translator for games, hardcoded subtitles in videos, static text and etc.
SciSharp/BotSharp
AI Multi-Agent Framework in .NET
SciSharp/Numpy.NET
C#/F# bindings for NumPy - a fundamental library for scientific computing, machine learning and AI
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3.0.3 332,997 10/11/2023
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3.0.1 335,947 11/2/2022
3.0.0 33,644 9/29/2022
2.3.0-py35-dotnet 3,758 3/16/2017
2.3.0-py27-dotnet 1,989 3/16/2017