semvec/pypi-packages huggingface dataset:
ros-kilted-ament-cmake-ros-core 0.14.5
Meta-package for ament_cmake_ros_core (ros-ament-cmake-ros-core) for ROS 2 kilted.

Meta-package for ament_cmake_ros_core (ros-ament-cmake-ros-core) for ROS 2 kilted. Built using https://github.com/ycheng517/ros-python-wheels
ros-kilted-ament-cmake-export-link-flags 2.7.3
Meta-package for ament_cmake_export_link_flags (ros-ament-cmake-export-link-flags) for ROS 2 kilted.

Meta-package for ament_cmake_export_link_flags (ros-ament-cmake-export-link-flags) for ROS 2 kilted. Built using https://github.com/ycheng517/ros-python-wheels
ros-kilted-ament-cmake-export-targets 2.7.3
Meta-package for ament_cmake_export_targets (ros-ament-cmake-export-targets) for ROS 2 kilted.

Meta-package for ament_cmake_export_targets (ros-ament-cmake-export-targets) for ROS 2 kilted. Built using https://github.com/ycheng517/ros-python-wheels
ros-kilted-rosidl-typesupport-cpp 3.3.3
Meta-package for rosidl_typesupport_cpp (ros-rosidl-typesupport-cpp) for ROS 2 kilted.

Meta-package for rosidl_typesupport_cpp (ros-rosidl-typesupport-cpp) for ROS 2 kilted. Built using https://github.com/ycheng517/ros-python-wheels
ros-kilted-rosidl-typesupport-fastrtps-c 3.8.1
Meta-package for rosidl_typesupport_fastrtps_c (ros-rosidl-typesupport-fastrtps-c) for ROS 2 kilted.

Meta-package for rosidl_typesupport_fastrtps_c (ros-rosidl-typesupport-fastrtps-c) for ROS 2 kilted. Built using https://github.com/ycheng517/ros-python-wheels
smartwater 0.0.13
Python library to communicate with Smart Water servers
Requires Python: >=3.8

[![license](https://img.shields.io/github/license/toreamun/amshan-homeassistant?style=for-the-badge)](LICENSE)
[![buy_me_a_coffee](https://img.shields.io/badge/If%20you%20like%20it-Buy%20me%20a%20coffee-yellow.svg?style=for-the-badge)](https://www.buymeacoffee.com/ankohanse)


# smartwater

Python library for retrieving sensor information from Smart Water branded devices.
This component connects to the remote Smart Water Technology servers and automatically determines which gateways, tanks and pumps are available there.

The custom component is compatible with SW900 devices (Desk Mount Wifi LCD, Wall Mount WiFi LCD, Tank Level Sender and Wireless Pump Controllers).
Legacy SW800 devices are not supported as these do not have WiFi/internet connectivity.

Disclaimer: this library is NOT created by [Smart Water Technologies](https://www.smart-water-online.com)


# Prerequisites
This library depends on the backend servers for the Smart Water app to retrieve the device information from. Before using this library, the Smart Water app must have been setup on your phone and linked to the desktop or wall-mount WiFi LCD.

When using the free app, usage is limited to 1 tank and 1 pump controller. For the paid app version multiple tanks and pumps are supported.


# Usage

The library is available from PyPi using:
`pip install smartwater`

See example_api_use.py for an example of usage.
xarray-beam 0.11.5
Distributed Xarray with Apache Beam
Requires Python: >=3.10

# Xarray-Beam

Xarray-Beam is a Python library for building
[Apache Beam](https://beam.apache.org/) pipelines with
[Xarray](http://xarray.pydata.org/en/stable/) datasets.

The project aims to facilitate data transformations and analysis on large-scale
multi-dimensional labeled arrays, such as:

-   Ad-hoc computation on Xarray data, by dividing a `xarray.Dataset` into many
    smaller pieces ("chunks").
-   Adjusting array chunks, using the
    [Rechunker algorithm](https://rechunker.readthedocs.io/en/latest/algorithm.html).
-   Ingesting large, multi-dimensional array datasets into an analysis-ready,
    cloud-optimized format, namely [Zarr](https://zarr.readthedocs.io/) (see
    also [Pangeo Forge](https://github.com/pangeo-forge/pangeo-forge-recipes)).
-   Calculating statistics (e.g., "climatology") across distributed datasets
    with arbitrary groups.

For more about our approach and how to get started,
**[read the documentation](https://xarray-beam.readthedocs.io/)**!

**Warning: Xarray-Beam is a sharp tool 🔪**

Xarray-Beam is relatively new, and focused on expert users:

-   We use it extensively at Google for processing large-scale weather datasets,
    but there is not yet a vibrant external community.
-   It provides low-level abstractions that facilitate writing very large
    scale data pipelines (e.g., 100+ TB), but by design it requires explicitly
    thinking about how every operation is parallelized.

## Installation

Xarray-Beam requires recent versions of immutabledict, Xarray, Dask, Rechunker,
Zarr, and Apache Beam. For best performance when writing Zarr files, use Xarray
0.19.0 or later.

## Disclaimer

Xarray-Beam is an experiment that we are sharing with the outside world in the
hope that it will be useful. It is not a supported Google product. We welcome
feedback, bug reports and code contributions, but cannot guarantee they will be
addressed.

See the "Contribution guidelines" for more.

## Credits

Contributors:

-   Stephan Hoyer
-   Jason Hickey
-   Cenk Gazen
-   Alex Merose