doc: minicline pass at improving environment docs

Author: satra

docs/source/explanation/environments.rst

@@ -13,20 +13,111 @@ to the execution call (e.g. ``my_task(worker="cf", environment="docker")``) or i
 Specifying at execution
 -----------------------
 
-Work in progress...
+The environment for a task can be specified at execution time by passing the ``environment`` argument to the task call.
+This can be an instance of `pydra.environments.native.Environment` (for the host system),
+`pydra.environments.docker.Environment` (for Docker containers), or
+`pydra.environments.singularity.Environment` (for Singularity containers), or a custom environment.
+
+Example:
+
+.. code-block:: python
+
+    from pydra.environments import native, docker, singularity
+    from pydra.compose import shell
+    # Define a simple shell task
+    shelly = shell.fuse("echo hello")
+
+    # Execute with a native environment
+    outputs_native = shelly(environment=native.Environment())
+
+    # Execute with a Docker environment (assuming busybox image is available)
+    outputs_docker = shelly(environment=docker.Environment(image="busybox"))
+
+    # Execute with a Singularity environment (assuming an image is available)
+    outputs_singularity = shelly(environment=singularity.Environment(image="/path/to/image.sif"))
+
+Alternatively, when using a `pydra.engine.submitter.Submitter`, the environment can be specified in the Submitter constructor:
+
+.. code-block:: python
+
+    from pydra.engine.submitter import Submitter
+    from pydra.environments import native
+    from pydra.compose import shell
+
+    shelly = shell.fuse("echo hello")
+    with Submitter(environment=native.Environment()) as sub:
+        result = sub(shelly)
 
 
 Specifying at workflow construction
 -----------------------------------
 
-Work in progress...
+When constructing a workflow, the environment can be specified in the ``workflow.add()`` call.
+This ensures that all tasks within that workflow branch will execute in the specified environment.
+
+Example:
+
+.. code-block:: python
+
+    from pydra.environments import singularity
+    from pydra.compose import workflow, shell
+    from fileformats.generic import File
 
+    image = "/path/to/my_singularity_image.sif" # Replace with your Singularity image path
+
+    Singu = shell.define("cat {file}")
+
+    def MyWorkflow(file: File) -> str:
+        singu_task = workflow.add(
+            Singu(file=file),
+            environment=singularity.Environment(image=image),
+        )
+        return singu_task.stdout
+
+    # Now you can use MyWorkflow, and the 'cat' task will run in the Singularity environment
 
 
 Implementing new environment types
 ----------------------------------
 
-Work in progress...
+Custom environment types can be implemented by creating a new class that inherits from `pydra.environments.Environment`.
+These custom environment classes are typically located in the `pydra/environments/` directory.
+
+Example (simplified custom environment):
+
+.. code-block:: python
+
+    from pydra.environments import Environment as PydraEnvironment
+
+    class MyCustomEnvironment(PydraEnvironment):
+        def __init__(self, some_config: str):
+            super().__init__()
+            self.some_config = some_config
+
+        def _setup(self):
+            # Logic to set up the custom environment
+            print(f"Setting up custom environment with config: {self.some_config}")
+
+        def _execute(self, command: list):
+            # Logic to execute a command within the custom environment
+            # This is where you would integrate with a custom execution system
+            print(f"Executing command: {' '.join(command)} in custom environment")
+            # For demonstration, just return a dummy result
+            return {"stdout": "Custom environment output", "return_code": 0}
+
+        def _tear_down(self):
+            # Logic to tear down the custom environment
+            print("Tearing down custom environment")
+
+Then, you can use your custom environment like any other built-in environment:
+
+.. code-block:: python
+
+    from pydra.compose import shell
+    # Assume MyCustomEnvironment is defined as above
+    my_task = shell.fuse("echo Hello from custom env")
+    outputs = my_task(environment=MyCustomEnvironment(some_config="test"))
+    print(outputs.stdout)
 
 
 .. _Docker: https://www.docker.com/