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172 changes: 42 additions & 130 deletions README.md
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# Open Job Description - Adaptor Runtime
# Open Job Description - Adaptor Runtime Library

[![pypi](https://img.shields.io/pypi/v/openjd-adaptor-runtime.svg?style=flat)](https://pypi.python.org/pypi/openjd-adaptor-runtime)
[![python](https://img.shields.io/pypi/pyversions/openjd-adaptor-runtime.svg?style=flat)](https://pypi.python.org/pypi/openjd-adaptor-runtime)
[![license](https://img.shields.io/pypi/l/openjd-adaptor-runtime.svg?style=flat)](https://github.com/OpenJobDescription/openjd-adaptor-runtime/blob/mainline/LICENSE)

This package provides a runtime library for creating a command-line Adaptor to assist with
integrating an existing application, such as a rendering application, into batch computing systems
that run Jobs in a way that is compatible with [Open Job Description Sessions]. That is, when running
a Job on a host consists of a phase to initialize a local compute environment, then running one
or more Tasks that each run the same application for the Job on the host, and finally tearing down
the initialized compute environment when complete.

Some of the reasons that you should consider creating an Adaptor are if you want to:

1. Optimize the runtime of your Job on a compute host by loading the application once and dynamically running
many units of work with that single application instance before shutting down the application;
2. Programmatically respond to signals that the application provides, such as stopping the application early
if it prints a message to stdout that indicates that the run may produce undesirable results like watermarks
due to missing a floating license, or a bad image render due to missing textures;
3. Dynamically select which version of an application to run based on what is available and modify the
command-line options provided to the application based on which version will be run;
4. Emit [Open Job Description Stdout Messages], or equivalent, to update the batch computing system on the
status or progress of the running unit of work; and/or
5. Integrate [Open Job Description Path Mapping] information into the application in the format that it is expecting.
This package provides a runtime library to help build application interfaces that simplify
Open Job Description job templates. When implemented by a third party on behalf of
an application, the result is a CLI command that acts as an adaptor. Application
developers can also implement support for these CLI patterns directly in their
applications, potentially using this library to simplify the work.

Interface features that this library can assist with include:

1. Run as a background daemon to amortize application startup and scene load time.
* Tasks run in the context of [Open Job Description Sessions], and this pattern lets a
scheduling engine sequentially dispatch tasks to a single process that retains the
application, loaded scene, and any acceleration data structures in memory.
2. Report progress and status messages.
* Applications write progress information and status messages in many different ways.
An adaptor can scan the output of an application and report it in the format specified
for [Open Job Description Stdout Messages].
3. Map file system paths in input data.
* When running tasks on a different operating system, or when files are located at
different locations compared to where they were at creation, an adaptor can take
path mapping rules and perform [Open Job Description Path Mapping].
4. Transform signals like cancelation requests from the Open Job Description runtime into
the signal needed by the application.
* Applications may require different mechanisms to receive these messages, an adaptor
can handle any differences with what Open Job Description provides to give full
feature support.
5. Adjust application default behaviors for batch processing.
* When running applications that were built for interactive use within a batch processing
system, some default behaviors may lead to unreliability of workload completion, such
as using watermarks when a license could not be acquired or returning a success exit
code when an input data file could not be read. The adaptor can monitor and detect
these cases.

[Open Job Description Sessions]: https://github.com/OpenJobDescription/openjd-specifications/wiki/How-Jobs-Are-Run#sessions
[Open Job Description Stdout Messages]: https://github.com/OpenJobDescription/openjd-specifications/wiki/How-Jobs-Are-Run#stdoutstderr-messages
[Open Job Description Path Mapping]: https://github.com/OpenJobDescription/openjd-specifications/wiki/How-Jobs-Are-Run#path-mapping

Read the [Library Documentation](docs/README.md) to learn more.

## Compatibility

This library requires:
Expand All @@ -37,13 +51,13 @@ This library requires:

## Versioning

This package's version follows [Semantic Versioning 2.0](https://semver.org/), but is still considered to be in its
This package's version follows [Semantic Versioning 2.0](https://semver.org/), but is still considered to be in its
initial development, thus backwards incompatible versions are denoted by minor version bumps. To help illustrate how
versions will increment during this initial development stage, they are described below:

1. The MAJOR version is currently 0, indicating initial development.
2. The MINOR version is currently incremented when backwards incompatible changes are introduced to the public API.
3. The PATCH version is currently incremented when bug fixes or backwards compatible changes are introduced to the public API.
1. The MAJOR version is currently 0, indicating initial development.
2. The MINOR version is currently incremented when backwards incompatible changes are introduced to the public API.
3. The PATCH version is currently incremented when bug fixes or backwards compatible changes are introduced to the public API.

## Downloading

Expand All @@ -55,115 +69,13 @@ You can download this package from:

See [VERIFYING_PGP_SIGNATURE](VERIFYING_PGP_SIGNATURE.md) for more information.

## Usage

To create your own Adaptor you create a Python application that uses this package and consists of:

1. A console script entrypoint that passes control flow to an instance of this runtime's **EntryPoint** class;
2. A JSON file for configuration options of your Adaptor; and
3. An Adaptor class derived from either the **CommandAdaptor** or **Adaptor** class.
- **CommandAdaptor** is ideal for applications where you do not need to initialize the local compute environment by, say,
preloading your application, and simply need to run a single commandline for each Task that is run on the compute host.
Please see [CommandAdaptorExample] in this GitHub repository for a simple example.
- **Adaptor** exposes callbacks for every stage of an Adaptor's lifecycle, and is is suited for Adaptors where you want full control.
Please see [AdaptorExample] in this GitHub repository for a simple example.

You can also find many more examples within the [AWS Deadline Cloud Organization] on GitHub.

[CommandAdaptorExample]: https://github.com/OpenJobDescription/openjd-adaptor-runtime-for-python/tree/release/test/openjd/adaptor_runtime/integ/CommandAdaptorExample
[AdaptorExample]: https://github.com/OpenJobDescription/openjd-adaptor-runtime-for-python/tree/mainline/test/openjd/adaptor_runtime/integ/AdaptorExample
[AWS Deadline Cloud Organization]: https://github.com/aws-deadline

### Adaptor Lifecycle

All Adaptors undergo a lifecycle consisting of the following stages:

1. **start**: Occurs once during construction and initialization of the Adaptor. This is the stage where
your Adaptor should perform any expensive initialization actions for the local compute environment; such
as starting and loading an application in the background for use in later stages of the Adaptor's lifecycle.
- Runs the `on_start()` method of Adaptors derived from the **Adaptor** base class.
2. **run**: May occur one or more times for a single running Adaptor. This is the stage where your Adaptor is
performing the work required of a Task that is being run.
- Run the `on_run()` method of Adaptors derived from the **Adaptor** base class.
- Run the `on_prerun()` then `get_managed_process()` then `on_postrun()` methods of Adaptors derived from the
**CommandAdaptor** base class.
3. **stop**: Occurs once as part of shutting down the Adaptor. This stage is the inverse of the **start**
stage and should undo the actions done in that phase; such as stopping any background processes that are
still running.
- Runs the `on_stop()` method of Adaptors derived from the **Adaptor** base class.
4. **cleanup**: A final opportunity to cleanup any remaining processes and data left behind by the Adaptor.
- Runs the `on_cleanup()` method of Adaptors derived from the **Adaptor** base class.

A running Adaptor can also be canceled by sending the Adaptor process a signal (SIGINT/SIGTERM on posix, or
CTRL-C/CTRL-BREAK on Windows). This will call the `on_cancel()` method of your Adaptor, if one is defined.
You should ensure that the design of your Adaptor allows this cancelation to interrupt any actions that may
be running, and gracefully exit any running background processes.

### Running an Adaptor

The **EntryPoint** provided by this runtime allows for an Adaptor to be run directly through its
entire lifecycle in a single command, or to be run as a background daemon that lets you drive the lifecycle
of the Adaptor yourself.

#### The `run` Subcommand

The `run` subcommand of an Adaptor will run it through its entire lifecycle (**start**, then **run**, then
**stop**, and finally **cleanup**), and then exit. This is useful for initial development and testing, and
for running Adaptors created from the **CommandAdaptor** base class.

To see this in action install the openjd-adaptor-runtime package into your Python environment, and then
within your local clone of this repository:

```bash
cd test/openjd
python3 -m integ.AdaptorExample run --init-data '{"name": "MyAdaptor"}' --run-data '{"hello": "world"}'
```

The arguments to the `run` subcommand are:

- **`--init-data`** is a JSON-encoded dictionary either inline or in a given file (`file://<path-to-file>`). This data is
decoded and automatically stored in the `self.init_data` member of the running Adaptor.
- **`--run-data`** is, similarly, a JSON-encoded dictionary either inline or in a given file (`file://<path-to-file>`).
This data is passed as the argument to the `on_run()` method of an **Adaptor** or the `get_managed_process()`
method of a **CommandAdaptor**.

#### The `daemon` Subcommand

With the `daemon` subcommand, you must transition the Adaptor through its lifecycle yourself by running the
subcommands of the `daemon` subcommand in order.

1. Start the Adaptor: Initializes the Adaptor as a background daemon subprocess and leaves it running.
This runs the `on_start()` method of your **Adaptor**-derived Adaptor if the method is available.
```
python -m integ.AdaptorExample daemon start --connection-file ./AdaptorExampleConnection.json --init-data '{"name": "MyAdaptor"}'
```
- **`--init-data`** is as described in the `run` subcommand, above.
- **`--connection-file`** provide a path to a JSON file for the Adaptor to create. This file contains information
on how to connect to the daemon subprocess remains running, and you must provide it to all subsequent runs of the
Adaptor until you have stopped it.
2. Run the Adaptor: Connects to the daemon subprocess that is running the Adaptor and instructs it to perform its **run**
lifecycle phase. The command remains connected to the daemon subprocess for the entire duration of this **run** phase,
and forwards all data logged by the Adaptor to stdout or stderr. This step can be repeated multiple times.
```
python -m integ.AdaptorExample daemon run --connection-file ./AdaptorExampleConnection.json --run-data '{"hello": "world"}'
```
- **`--run-data`** is as described in the `run` subcommand, above.
- **`--connection-file`** is as described in above.
3. Stop the Adaptor: Connects to the daemon subprocess that is running the Adaptor and instructs it to transition to the
**stop** then **cleanup** lifecycle phases, and then instructs the daemon subprocess to exit when complete. The command
remains connected to the daemon subprocess for the entire duration, and forwards all data logged by the Adaptor to stdout
or stderr.
```
python -m integ.AdaptorExample daemon stop --connection-file ./AdaptorExampleConnection.json
```

## Security

We take all security reports seriously. When we receive such reports, we will
investigate and subsequently address any potential vulnerabilities as quickly
as possible. If you discover a potential security issue in this project, please
We take all security reports seriously. When we receive such reports, we will
investigate and subsequently address any potential vulnerabilities as quickly
as possible. If you discover a potential security issue in this project, please
notify AWS/Amazon Security via our [vulnerability reporting page](http://aws.amazon.com/security/vulnerability-reporting/)
or directly via email to [AWS Security](aws-security@amazon.com). Please do not
or directly via email to [AWS Security](aws-security@amazon.com). Please do not
create a public GitHub issue in this project.

## License
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