semvec/pypi-packages huggingface dataset:
any4robot 0.1.2
Foundation dataset tooling for VLA model training
Requires Python: >=3.8
Keywords: robotics, dataset, lerobot, vla, data-tools

# Any4Robot

`any4robot` provides dataset conversion and management utilities for training VLA / WM / VAM robot control models. Data preparation is crucial for robot model development. Any4Robot provides a standardized, verified way to produce the right data so you can focus on model design.

## Install

```bash
pip install any4robot
```

## Quick start (LeRobot editor)

```python
from any4robot import LeRobotDatasetEditor

editor = LeRobotDatasetEditor("/path/to/lerobot-dataset")
editor.list_episodes(0, 5)
editor.delete_episode(12, dry_run=True)
```

## Combine datasets

```python
from any4robot.combine import merge_lerobot_datasets

merge_lerobot_datasets(
    ["/path/to/dataset_a", "/path/to/dataset_b"],
    "/path/to/output_dataset",
)
```

## Quality check (LeRobot v2.1 layout)

```python
from any4robot.qualitycheck import validate_lerobot_v2_1

result = validate_lerobot_v2_1("/path/to/lerobot-dataset")
print(result)
```

## Modules

- `any4robot.editing`: LeRobot dataset editing helpers (delete episode, copy episode, list episodes)
- `any4robot.combine`: Merge multiple LeRobot datasets into a single dataset
- `any4robot.qualitycheck`: Validate datasets (LeRobot v2.1 layout)
- `any4robot.conversion`: Placeholder for future dataset conversion pipelines

## Notes

- The LeRobot editor code is copied from `vendor/lero` and organized under `any4robot/lerobot_editor`.
- Optional GUI dependencies are available with `pip install any4robot[gui]`.
echo 0.12.1
Callback Properties in Python
Requires Python: >=3.10

|Azure Status| |Coverage status|

echo: Callback Properties in Python
===================================

Echo is a small library for attaching callback functions to property
state changes. For example:

::

    class Switch(object):
        state = CallbackProperty('off')

    def report_change(state):
        print 'the switch is %s' % state

    s = Switch()
    add_callback(s, 'state', report_change)

    s.state = 'on'  # prints 'the switch is on'

CalllbackProperties can also be built using decorators

::

    class Switch(object):

          @callback_property
          def state(self):
            return self._state

          @state.setter
          def state(self, value):
              if value not in ['on', 'off']:
                  raise ValueError("invalid setting")
              self._state = value

Full documentation is avilable `here <http://echo.readthedocs.org/>`__

.. |Azure Status| image:: https://dev.azure.com/glue-viz/echo/_apis/build/status/glue-viz.echo?branchName=master
   :target: https://dev.azure.com/glue-viz/echo/_build/latest?definitionId=4&branchName=master
.. |Coverage Status| image:: https://codecov.io/gh/glue-viz/echo/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/glue-viz/echo
worktrees 0.1.0
Add your description here
Requires Python: >=3.11

# worktrees

Initial PyPI package scaffold for `worktrees`, using `uv` for build and publish.

## Local workflow

```bash
uv build
uv publish
```

`uv publish` reads `UV_PUBLISH_TOKEN` automatically.

If your token is stored as `PYPI_TOKEN`, run:

```bash
export UV_PUBLISH_TOKEN="$PYPI_TOKEN"
uv publish
```

## TestPyPI

```bash
uv publish --publish-url https://test.pypi.org/legacy/
```
monorepos 0.1.0
Add your description here
Requires Python: >=3.11

# monorepos

Initial PyPI package scaffold for `monorepos`, using `uv` for build and publish.

## Local workflow

```bash
uv build
uv publish
```

`uv publish` reads `UV_PUBLISH_TOKEN` automatically.

If your token is stored as `PYPI_TOKEN`, run:

```bash
export UV_PUBLISH_TOKEN="$PYPI_TOKEN"
uv publish
```

## TestPyPI

```bash
uv publish --publish-url https://test.pypi.org/legacy/
```
gpustack-runtime 0.1.42.post5
GPUStack Runtime is library for detecting GPU resources and launching GPU workloads.
Requires Python: >=3.10

# GPUStack Runtime

GPUStack Runtime offers a unified interface for detecting GPU resources and managing GPU workloads.

It supports detection of a wide range of GPU and accelerator resources, including:

- AMD GPU
- Ascend NPU
- Cambricon MLU
- Hygon DCU
- Iluvatar GPU
- MetaX GPU
- Moore Threads GPU
- NVIDIA GPU
- T-Head PPU

Contributions to support additional GPU resources are welcome!

GPUStack Runtime enables GPU workload management on the following platforms:

- Docker
- Kubernetes
- Podman (>=4.9, Experimental support via `CONTAINER_HOST=http+unix:///path/to/podman/socket` environment variable)

## License

Copyright (c) 2025 The GPUStack authors

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at [LICENSE](./LICENSE) file for details.

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.