Embedding .NET into Python#

Getting Started#

A key goal for this project has been that Python.NET should “work just the way you’d expect in Python”, except for cases that are .NET-specific (in which case the goal is to work “just the way you’d expect in C#”).

A good way to start is to interactively explore .NET usage in python interpreter by following along with the examples in this document. If you get stuck, there are also a number of demos and unit tests located in the source directory of the distribution that can be helpful as examples. Additionally, refer to the wiki on GitHub, especially the Tutorials there.

Installation#

Python.NET is available as a source release on GitHub and as a platform-independent binary wheel or source distribution from the Python Package Index.

Installing from PyPI can be done using pip install pythonnet.

To build from source (either the sdist or clone or snapshot of the repository), only the .NET6 SDK (or newer) and Python itself are required. If dotnet is on the PATH, building can be done using

python setup.py build

Loading a Runtime#

All runtimes supported by clr-loader can be used, which are

Mono (mono): Default on Linux and macOS, supported on all platforms.
.NET Framework (netfx): Default on Windows and also only supported there. Must be at least version 4.7.2.
.NET Core (coreclr): Self-contained is not supported, must be at least version 3.1.

The runtime must be configured before clr is imported, otherwise the default runtime will be initialized and used. Information on the runtime in use can be retrieved using pythonnet.get_runtime_info()).

A runtime can be selected in three different ways:

Calling `pythonnet.load`#

The function pythonnet.load() can be called explicitly. A single string parameter (like load("coreclr") will select the respective runtime. All keyword arguments are passed to the underlying clr_loader.get_<runtime-name> function.

from pythonnet import load

load("coreclr", runtime_config="/path/to/runtimeconfig.json")

Note

All runtime implementations can be initialized without additional parameters. While previous versions of clr_loader required a runtimeconfig.json to load .NET Core, this requirement was lifted for the version used in pythonnet.

Via Environment Variables#

The same configurability is exposed as environment variables.

PYTHONNET_RUNTIME: selects the runtime (e.g. PYTHONNET_RUNTIME=coreclr)
PYTHONNET_<RUNTIME>_<PARAM>: is passed on as a keyword argument (e.g. PYTHONNET_MONO_LIBMONO=/path/to/libmono.so)

The equivalent configuration to the load example would be

PYTHONNET_RUNTIME=coreclr
PYTHONNET_CORECLR_RUNTIME_CONFIG=/path/to/runtimeconfig.json

Note

Only string parameters are supported this way. It has the advantage, though, that the same configuration will be used for subprocesses as well.

Constructing a `Runtime` instance#

The runtime can also be explicitly constructed using using the clr_loader.get_* factory functions, and then set up using pythonnet.set_runtime():

from pythonnet import set_runtime
from clr_loader import get_coreclr

rt = get_coreclr(runtime_config="/path/to/runtimeconfig.json")
set_runtime(rt)

This method is only recommended, if very fine-grained control over the runtime construction is required.

Importing Modules#

Python.NET allows CLR namespaces to be treated essentially as Python packages.

from System import String
from System.Collections import *

Types from any loaded assembly may be imported and used in this manner. To load an assembly, use the AddReference function in the clr module:

import clr
clr.AddReference("System.Windows.Forms")
from System.Windows.Forms import Form

Note

Earlier releases of Python.NET relied on “implicit loading” to support automatic loading of assemblies whose names corresponded to an imported namespace. This is not supported anymore, all assemblies have to be loaded explicitly with AddReference.

Python.NET uses the PYTHONPATH (sys.path) to look for assemblies to load, in addition to the usual application base and the GAC (if applicable). To ensure that you can import an assembly, put the directory containing the assembly in sys.path.

Interacting with .NET#

Using Classes#

Python.NET allows you to use any non-private classes, structs, interfaces, enums or delegates from Python. To create an instance of a managed class, you use the standard instantiation syntax, passing a set of arguments that match one of its public constructors:

from System.Drawing import Point

p = Point(5, 5)

In many cases, Python.NET can determine the correct constructor to call automatically based on the arguments. In some cases, it may be necessary to call a particular overloaded constructor, which is supported by a special __overloads__ attribute.

Note

For compatibility with IronPython, the same functionality is available with the Overloads attribute.

from System import String, Char, Int32

s = String.Overloads[Char, Int32]('A', 10)
s = String.__overloads__[Char, Int32]('A', 10)

Using Generics#

Pythonnet also supports generic types. A generic type must be bound to create a concrete type before it can be instantiated. Generic types support the subscript syntax to create bound types:

from System.Collections.Generic import Dictionary
from System import *

dict1 = Dictionary[String, String]()
dict2 = Dictionary[String, Int32]()
dict3 = Dictionary[String, Type]()

Note

For backwards-compatibility reasons, this will also work with some native Python types which are mapped to corresponding .NET types (in particular str -> System.String and int -> System.Int32). Since these mappings are not really one-to-one and can lead to surprising results, use of this functionality is discouraged and will generate a warning in the future.

Managed classes can also be subclassed in Python, though members of the Python subclass are not visible to .NET code. See the helloform.py file in the /demo directory of the distribution for a simple Windows Forms example that demonstrates subclassing a managed class.

Fields and Properties#

You can get and set fields and properties of CLR objects just as if they were regular attributes:

from System import Environment

name = Environment.MachineName
Environment.ExitCode = 1

Using Indexers#

If a managed object implements one or more indexers, one can call the indexer using standard Python indexing syntax:

from System.Collections import Hashtable

table = Hashtable()
table["key 1"] = "value 1"

Overloaded indexers are supported, using the same notation one would use in C#:

items[0, 2]
items[0, 2, 3]

Using Methods#

Methods of CLR objects behave generally like normal Python methods. Static methods may be called either through the class or through an instance of the class. All public and protected methods of CLR objects are accessible to Python:

from System import Environment

drives = Environment.GetLogicalDrives()

It is also possible to call managed methods “unbound” (passing the instance as the first argument) just as with Python methods. This is most often used to explicitly call methods of a base class.

Note

There is one caveat related to calling unbound methods: it is possible for a managed class to declare a static method and an instance method with the same name. Since it is not possible for the runtime to know the intent when such a method is called unbound, the static method will always be called.

The docstring of CLR a method (__doc__) can be used to view the signature of the method, including overloads if the CLR method is overloaded. You can also use the Python help method to inspect a managed class:

from System import Environment

print(Environment.GetFolderPath.__doc__)

help(Environment)

Advanced Usage#

Overloaded and Generic Methods#

While Python.NET will generally be able to figure out the right version of an overloaded method to call automatically, there are cases where it is desirable to select a particular method overload explicitly.

Like constructors, all CLR methods have a __overloads__ property to allow selecting particular overloads explicitly.

Note

For compatibility with IronPython, the same functionality is available with the Overloads attribute.

from System import Console, Boolean, String, UInt32

Console.WriteLine.__overloads__[Boolean](True)
Console.WriteLine.Overloads[String]("string")
Console.WriteLine.__overloads__[UInt32](42)

Similarly, generic methods may be bound at runtime using the subscript syntax directly on the method:

someobject.SomeGenericMethod[UInt32](10)
someobject.SomeGenericMethod[String]("10")

Out and Ref parameters#

When a managed method has out or ref parameters, the arguments appear as normal arguments in Python, but the return value of the method is modified. There are 3 cases:

If the method is void and has one out or ref parameter, the method returns the value of that parameter to Python. For example, if someobject has a managed method with signature void SomeMethod1(out arg), it is called like so:

new_arg = someobject.SomeMethod1(arg)

where the value of arg is ignored, but its type is used for overload resolution.

If the method is void and has multiple out/ref parameters, the method returns a tuple containing the out/ref parameter values. For example, if someobject has a managed method with signature void SomeMethod2(out arg, ref arg2), it is called like so:

new_arg, new_arg2 = someobject.SomeMethod2(arg, arg2)

Otherwise, the method returns a tuple containing the return value followed by the out/ref parameter values. For example:

found, new_value = dictionary.TryGetValue(key, value)

Delegates and Events#

Delegates defined in managed code can be implemented in Python. A delegate type can be instantiated and passed a callable Python object to get a delegate instance. The resulting delegate instance is a true managed delegate that will invoke the given Python callable when it is called:

def my_handler(source, args):
    print('my_handler called!')

# instantiate a delegate
d = AssemblyLoadEventHandler(my_handler)

# use it as an event handler
AppDomain.CurrentDomain.AssemblyLoad += d

Delegates with out or ref parameters can be implemented in Python by following the convention described in Out and Ref parameters.

Multicast delegates can be implemented by adding more callable objects to a delegate instance:

d += self.method1
d += self.method2
d()

Events are treated as first-class objects in Python, and behave in many ways like methods. Python callbacks can be registered with event attributes, and an event can be called to fire the event.

Note that events support a convenience spelling similar to that used in C#. You do not need to pass an explicitly instantiated delegate instance to an event (though you can if you want). Events support the += and -= operators in a way very similar to the C# idiom:

def handler(source, args):
    print('my_handler called!')

# register event handler
object.SomeEvent += handler

# unregister event handler
object.SomeEvent -= handler

# fire the event
result = object.SomeEvent(...)

Exception Handling#

Managed exceptions can be raised and caught in the same way as ordinary Python exceptions:

from System import NullReferenceException

try:
    raise NullReferenceException("aiieee!")
except NullReferenceException as e:
    print(e.Message)
    print(e.Source)

Using Arrays#

The type System.Array supports the subscript syntax in order to make it easy to create managed arrays from Python:

from System import Array, Int32

myarray = Array[Int32](10)

Managed arrays support the standard Python sequence protocols:

items = SomeObject.GetArray()

# Get first item
v = items[0]
items[0] = v

# Get last item
v = items[-1]
items[-1] = v

# Get length
l = len(items)

# Containment test
test = v in items

Multidimensional arrays support indexing using the same notation one would use in C#:

items[0, 2]

items[0, 2, 3]

Using Collections#

Managed arrays and managed objects that implement the IEnumerable or IEnumerable<T> interface can be iterated over using the standard iteration Python idioms:

domain = System.AppDomain.CurrentDomain

for item in domain.GetAssemblies():
    name = item.GetName()

Type Conversion#

Type conversion under Python.NET is fairly straightforward - most elemental Python types (string, int, long, etc.) convert automatically to compatible managed equivalents (String, Int32, etc.) and vice-versa.

Custom type conversions can be implemented as Codecs.

Types that do not have a logical equivalent in Python are exposed as instances of managed classes or structs (System.Decimal is an example).

The .NET architecture makes a distinction between value types and reference types. Reference types are allocated on the heap, and value types are allocated either on the stack or in-line within an object.

A process called boxing is used in .NET to allow code to treat a value type as if it were a reference type. Boxing causes a separate copy of the value type object to be created on the heap, which then has reference type semantics.

Understanding boxing and the distinction between value types and reference types can be important when using Python.NET because the Python language has no value type semantics or syntax - in Python “everything is a reference”.

Here is a simple example that demonstrates an issue. If you are an experienced C# programmer, you might write the following code:

items = System.Array.CreateInstance(Point, 3)
for i in range(3):
    items[i] = Point(0, 0)

items[0].X = 1 # won't work!!

While the spelling of items[0].X = 1 is the same in C# and Python, there is an important and subtle semantic difference. In C# (and other compiled-to-IL languages), the compiler knows that Point is a value type and can do the Right Thing here, changing the value in place.

In Python however, “everything’s a reference”, and there is really no spelling or semantic to allow it to do the right thing dynamically. The specific reason that items[0] itself doesn’t change is that when you say items[0], that getitem operation creates a Python object that holds a reference to the object at items[0] via a GCHandle. That causes a ValueType (like Point) to be boxed, so the following setattr (.X = 1) changes the state of the boxed value, not the original unboxed value.

The rule in Python is essentially:

the result of any attribute or item access is a boxed value

and that can be important in how you approach your code.

Because there are no value type semantics or syntax in Python, you may need to modify your approach. To revisit the previous example, we can ensure that the changes we want to make to an array item aren’t “lost” by resetting an array member after making changes to it:

items = System.Array.CreateInstance(Point, 3)
for i in range(3):
    items[i] = Point(0, 0)

# This _will_ work. We get 'item' as a boxed copy of the Point
# object actually stored in the array. After making our changes
# we re-set the array item to update the bits in the array.

item = items[0]
item.X = 1
items[0] = item

This is not unlike some of the cases you can find in C# where you have to know about boxing behavior to avoid similar kinds of lost update problems (generally because an implicit boxing happened that was not taken into account in the code).

This is the same thing, just the manifestation is a little different in Python. See the .NET documentation for more details on boxing and the differences between value types and reference types.

Embedding .NET into Python#

Getting Started#

Installation#

Loading a Runtime#

Calling pythonnet.load#

Via Environment Variables#

Constructing a Runtime instance#

Importing Modules#

Interacting with .NET#

Using Classes#

Using Generics#

Fields and Properties#

Using Indexers#

Using Methods#

Advanced Usage#

Overloaded and Generic Methods#

Out and Ref parameters#

Delegates and Events#

Exception Handling#

Using Arrays#

Using Collections#

Type Conversion#

Calling `pythonnet.load`#

Constructing a `Runtime` instance#