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A Python execution engine based on FastAPI with a MinIO object storage. The app is designed to run algorithms written in Python on the server and report the results to the client application (e. g. Tescan 3D VIewer or Picannto)

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Compox

Compox is a simple Python execution engine for Tescan applications. It's purpose is to run data processing algorithms written in Python on the server and report the results to the client application such as Tescan 3D Viewer or Picannto.

See the GitHub pages for full python API reference, docs and tutorials!

Installation

Compox can be installed through PyPI:

pip install compox

You can also install the server by cloning this repository and installing it from source.

Note that some additional dependencies, such as MinIO executable for your operating system, will be downloaded on the first run of the server.

Running the server

Once installed into your Python environment, Compox can be run using the compox command. This command is available in the virtual environment created during the setup process. Run the following command to list the available commands:

compox --help

It's recommended to start with generating an initial configuration file with compox generate-config. See the configuration options section below. To see the usage of the generate-config command, you can run:

compox generate-config --help

To run the Compox, use the following command:

compox run --config /path/to/config.yaml

Deploying algorithms

See (Algorithm development tutorial) for information about target structure of the deployable algorithms.

Once your algorithm is ready, you can use the compox deploy-algorithms command to deploy it to your server. To see the usage of the deploy-algorithms command, you can run:

compox deploy-algorithms --help

This command will read the algorithm definitions from the folder specified in your configuration file with the deploy_algorithms_from key and deploy them to the server. For example:

compox deploy-algorithms --config /path/to/config.yaml

Note that the server does not need to be running in order to deploy the algorithms.

Configuration

The server uses pydantic settings for configuration. The options can be either set as runtime arguments, in a yaml file, or using the COMPOX__ environment variables, in corresponding order of precedence.

  • Ensure all paths and URLs are correctly set before running the application.
  • Adjust CUDA settings based on hardware capabilities.
  • Logging paths should be accessible by the application to prevent errors.
  • See the configuration reference below for detailed configuration options.
Configuration reference

Compox Configuration Reference

Section Field Default Description
port 5461 The main server port used to make requests
deploy_algorithms_from "./algorithms" Directory for algorithm deployment sources.
log_path "LOG_DEFAULT:compox.log" Path to the main log file (supports dynamic prefixes).
config None Optional config path override.
info product_name "TESCAN 3D Backend" Product display name.
info server_tags [] → auto appends "compox" Tags attached to the server. "compox" is added automatically.
info group_name "TESCAN GROUP, a.s." Name of the corporate group.
info organization_name "TESCAN 3DIM, s.r.o." Full name of the organization.
info organization_domain "tescan3dim.com" Domain used in server configuration.
gui algorithm_add_remove_in_menus False Enables/disables GUI menu for algorithm management.
gui use_systray False Enables/disables systray GUI integration.
gui icon_path Path to the installed package resource Path to the systray icon (supports dynamic prefixes)
inference device "cuda" Device used for model inference ("cpu", "cuda", "mps").
inference cuda_visible_devices "0" Comma-separated list of visible CUDA GPUs.
storage collection_prefix "" Prefix applied to object store collections. (useful for AWS s3 store, where unique bucket names are needed)
storage data_store_expire_days 1 Number of days until stored datasets expire.
storage access_key_id generated with UUIDv4 Generated access key for storage backend. If null is provided, random UUIDv4 is generated.
storage secret_access_key generated with UUIDv4 Generated secret key for storage backend. If null is provided, random UUIDv4 is generated.
storage.backend_settings (minio) provider "minio" Selected backend provider.
storage.backend_settings (minio) start_instance True Whether to start a local MinIO server.
storage.backend_settings (minio) port 9091 MinIO service port.
storage.backend_settings (minio) console_port 9090 MinIO admin console port.
storage.backend_settings (minio) executable_path "minio/minio_bin" Path to the MinIO binary (accepts dynamic prefixes).
storage.backend_settings (minio) storage_path "minio/compox_store" Storage directory used by MinIO (accepts dynamic prefixes).
storage.backend_settings (minio) aws_region None Optional AWS compatibility region.
storage.backend_settings (minio) s3_domain_name None Optional domain override for S3 compatibility.
storage.backend_settings (minio) s3_endpoint_url Derived from port Computed as http://localhost:{port}.
storage.backend_settings (aws) provider "aws" AWS backend selection.
storage.backend_settings (aws) s3_endpoint_url None Optional override for S3 endpoint URL.
storage.backend_settings (aws) aws_region None AWS region (e.g. us-east-1).
storage.backend_settings (aws) s3_domain_name None Domain used for S3-style URLs.

Some fields in the Compox configuration (such as log_path, icon_path, etc.) support dynamic prefixes that resolve to OS-specific or runtime-specific paths. This allows for portability across platforms (e.g., Windows, Linux) and between development and production environments.

Supported Prefixes

Prefix Meaning (Resolved To...)
LOG_DEFAULT: A platform-dependent log directory:
- Windows: %TEMP%/<organization>/<product>
- Linux/macOS: /var/log/<organization>/<product>
PROGRAMDATA_DEFAULT: A system-wide data directory (Windows only):
- e.g., %PROGRAMDATA%/<organization>/<product>
- On Linux/macOS, defaults to "." (current dir)

These are resolved at runtime in the Settings.parse_paths() validator method.

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A Python execution engine based on FastAPI with a MinIO object storage. The app is designed to run algorithms written in Python on the server and report the results to the client application (e. g. Tescan 3D VIewer or Picannto)

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