# napari-result-stack
[](https://github.com/hanjinliu/napari-result-stack/raw/main/LICENSE)
[](https://pypi.org/project/napari-result-stack)
[](https://python.org)
[](https://github.com/hanjinliu/napari-result-stack/actions)
[](https://codecov.io/gh/hanjinliu/napari-result-stack)
[](https://napari-hub.org/plugins/napari-result-stack)
Widgets and type annotations for storing function results of any types.
## `Stored` type
Type `Stored[T]` is equivalent to `T` for the type checker, but `magicgui` is aware of this annotation and behaves as a "storage" for the `T` instances.
```python
from pathlib import Path
import pandas as pd
from magicgui import magicgui
from napari_result_stack import Stored
# Returned values will be stored in a result stack.
@magicgui
def provide_data(path: Path) -> Stored[pd.DataFrame]:
return pd.read_csv(path)
# You can choose one of the values stored in the result stack
# for the argument `df` from a ComboBox widget.
@magicgui
def print_data(df: Stored[pd.DataFrame]):
print(df)
```
- Different types use different storage. e.g. `Stored[int]` and `Stored[str]` do not share the same place.
- Even for the same type, you can specify the second key to split the storage. e.g. `Stored[int]`, `Stored[int, 0]` and `Stored[int, "my-plugin-name"]` use the distinct storages.
## Manually store variables
`Stored.valuesof[T]` is a `list`-like object that returns a view of the values stored in `Stored[T]`. This value view is useful if you want to store values outside `@magicgui`.
```python
from magicgui.widgets import PushButton
from datetime import datetime
from napari_result_stack import Stored
button = PushButton(text="Click!")
@button.changed.connect
def _record_now():
Stored.valuesof[datetime].append(datetime.now())
```
## Result stack widget
`napari-result-stack` provides a plugin widget that is helpful to inspect all the stored values.
<details><summary>Show code</summary><div>
```python
from napari_result_stack import Stored
from magicgui import magicgui
import numpy as np
import pandas as pd
@magicgui
def f0() -> Stored[pd.DataFrame]:
return pd.DataFrame(np.random.random((4, 3)))
@magicgui
def f1(x: Stored[pd.DataFrame]) -> Stored[float]:
return np.mean(np.array(x))
viewer.window.add_dock_widget(f0, name="returns a DataFrame")
viewer.window.add_dock_widget(f1, name="mean of a DataFrame")
```
---
</div></details>
----------------------------------
This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.
<!--
Don't miss the full getting started guide to set up your new package:
https://github.com/napari/cookiecutter-napari-plugin#getting-started
and review the napari docs for plugin developers:
https://napari.org/stable/plugins/index.html
-->
## Installation
You can install `napari-result-stack` via [pip]:
pip install napari-result-stack
To install latest development version :
pip install git+https://github.com/hanjinliu/napari-result-stack.git
## Contributing
Contributions are very welcome. Tests can be run with [tox], please ensure
the coverage at least stays the same before you submit a pull request.
## License
Distributed under the terms of the [BSD-3] license,
"napari-result-stack" is free and open source software
## Issues
If you encounter any problems, please [file an issue] along with a detailed description.
[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin
[file an issue]: https://github.com/hanjinliu/napari-result-stack/issues
[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
Raw data
{
"_id": null,
"home_page": "https://github.com/hanjinliu/napari-result-stack",
"name": "napari-result-stack",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "",
"author": "Hanjin Liu",
"author_email": "liuhanjin-sc@g.ecc.u-tokyo.ac.jp",
"download_url": "https://files.pythonhosted.org/packages/ca/73/be8386ee628eb7ba2c2c91a8e239761a25a3c36b33445000898555d3a755/napari-result-stack-0.0.1.tar.gz",
"platform": null,
"description": "# napari-result-stack\n\n[](https://github.com/hanjinliu/napari-result-stack/raw/main/LICENSE)\n[](https://pypi.org/project/napari-result-stack)\n[](https://python.org)\n[](https://github.com/hanjinliu/napari-result-stack/actions)\n[](https://codecov.io/gh/hanjinliu/napari-result-stack)\n[](https://napari-hub.org/plugins/napari-result-stack)\n\nWidgets and type annotations for storing function results of any types.\n\n## `Stored` type\n\nType `Stored[T]` is equivalent to `T` for the type checker, but `magicgui` is aware of this annotation and behaves as a \"storage\" for the `T` instances.\n\n```python\nfrom pathlib import Path\nimport pandas as pd\nfrom magicgui import magicgui\nfrom napari_result_stack import Stored\n\n# Returned values will be stored in a result stack.\n@magicgui\ndef provide_data(path: Path) -> Stored[pd.DataFrame]:\n return pd.read_csv(path)\n\n# You can choose one of the values stored in the result stack\n# for the argument `df` from a ComboBox widget.\n@magicgui\ndef print_data(df: Stored[pd.DataFrame]):\n print(df)\n```\n\n\n\n- Different types use different storage. e.g. `Stored[int]` and `Stored[str]` do not share the same place.\n- Even for the same type, you can specify the second key to split the storage. e.g. `Stored[int]`, `Stored[int, 0]` and `Stored[int, \"my-plugin-name\"]` use the distinct storages.\n\n## Manually store variables\n\n`Stored.valuesof[T]` is a `list`-like object that returns a view of the values stored in `Stored[T]`. This value view is useful if you want to store values outside `@magicgui`.\n\n```python\nfrom magicgui.widgets import PushButton\nfrom datetime import datetime\nfrom napari_result_stack import Stored\n\nbutton = PushButton(text=\"Click!\")\n\n@button.changed.connect\ndef _record_now():\n Stored.valuesof[datetime].append(datetime.now())\n\n```\n\n## Result stack widget\n\n`napari-result-stack` provides a plugin widget that is helpful to inspect all the stored values.\n\n\n\n\n<details><summary>Show code</summary><div>\n\n```python\nfrom napari_result_stack import Stored\nfrom magicgui import magicgui\nimport numpy as np\nimport pandas as pd\n\n@magicgui\ndef f0() -> Stored[pd.DataFrame]:\n return pd.DataFrame(np.random.random((4, 3)))\n\n@magicgui\ndef f1(x: Stored[pd.DataFrame]) -> Stored[float]:\n return np.mean(np.array(x))\n\nviewer.window.add_dock_widget(f0, name=\"returns a DataFrame\")\nviewer.window.add_dock_widget(f1, name=\"mean of a DataFrame\")\n```\n\n---\n</div></details>\n\n\n\n----------------------------------\n\nThis [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.\n\n<!--\nDon't miss the full getting started guide to set up your new package:\nhttps://github.com/napari/cookiecutter-napari-plugin#getting-started\n\nand review the napari docs for plugin developers:\nhttps://napari.org/stable/plugins/index.html\n-->\n\n## Installation\n\nYou can install `napari-result-stack` via [pip]:\n\n pip install napari-result-stack\n\n\n\nTo install latest development version :\n\n pip install git+https://github.com/hanjinliu/napari-result-stack.git\n\n\n## Contributing\n\nContributions are very welcome. Tests can be run with [tox], please ensure\nthe coverage at least stays the same before you submit a pull request.\n\n## License\n\nDistributed under the terms of the [BSD-3] license,\n\"napari-result-stack\" is free and open source software\n\n## Issues\n\nIf you encounter any problems, please [file an issue] along with a detailed description.\n\n[napari]: https://github.com/napari/napari\n[Cookiecutter]: https://github.com/audreyr/cookiecutter\n[@napari]: https://github.com/napari\n[MIT]: http://opensource.org/licenses/MIT\n[BSD-3]: http://opensource.org/licenses/BSD-3-Clause\n[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt\n[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt\n[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0\n[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt\n[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin\n\n[file an issue]: https://github.com/hanjinliu/napari-result-stack/issues\n\n[napari]: https://github.com/napari/napari\n[tox]: https://tox.readthedocs.io/en/latest/\n[pip]: https://pypi.org/project/pip/\n[PyPI]: https://pypi.org/\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "Widgets and type annotations for storing function results of any types",
"version": "0.0.1",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "7563940ead571d53688a6374a947d375f62888d27283eedb58b8d128f5c6d9c6",
"md5": "3c14e657e9cea7eea9056e2a59d5c69b",
"sha256": "eb5fc1e215a24bb644c2ed4210a2de7f93688cc22d5001f815e460ca552addcc"
},
"downloads": -1,
"filename": "napari_result_stack-0.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "3c14e657e9cea7eea9056e2a59d5c69b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 23400,
"upload_time": "2023-01-27T12:34:21",
"upload_time_iso_8601": "2023-01-27T12:34:21.726357Z",
"url": "https://files.pythonhosted.org/packages/75/63/940ead571d53688a6374a947d375f62888d27283eedb58b8d128f5c6d9c6/napari_result_stack-0.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ca73be8386ee628eb7ba2c2c91a8e239761a25a3c36b33445000898555d3a755",
"md5": "2928b2d5553b94a1c54b2ee5fc0f5701",
"sha256": "2952bfe0313d350dbd15f2e09e889eca8965a1f7ad7b1de18856acb411d17eaf"
},
"downloads": -1,
"filename": "napari-result-stack-0.0.1.tar.gz",
"has_sig": false,
"md5_digest": "2928b2d5553b94a1c54b2ee5fc0f5701",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 19480,
"upload_time": "2023-01-27T12:34:24",
"upload_time_iso_8601": "2023-01-27T12:34:24.005057Z",
"url": "https://files.pythonhosted.org/packages/ca/73/be8386ee628eb7ba2c2c91a8e239761a25a3c36b33445000898555d3a755/napari-result-stack-0.0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-27 12:34:24",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "hanjinliu",
"github_project": "napari-result-stack",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"tox": true,
"lcname": "napari-result-stack"
}
JSON
