semvec/pypi-packages huggingface dataset:
mightyzap-17lf 0.2.0
Add your description here
Requires Python: >=3.13

# MightyZap 17Lf Python Library and CLI

A Python library to control the [MightyZap 17Lf
series](https://mightyzap.com/en/linear_actuator_intro/) of linear actuators.

## Installation

### As a CLI tool

```bash
uv tool install mightyzap-17lf
```

### As a Python library

```bash
mkdir project & cd project
uv init
uv add mightyzap-17lf
uv run python
>>> from mightyzap_17lf import MightyZap17Lf
>>> mighty = MightyZap17Lf("COM4")
>>> mighty.speed = 500
>>> mighty.position = 10000
```

## CLI usage

```bash
# Set position 8000
$ mz COM4 position 8000
# Set position 10000 with speed 500
$ mz COM4 position 10000 500
# Read current position
$ mz COM4 position
10000

# Set register 12 to 800 (long stroke limit)
$ mz COM4 register 12 800
# Read register 12
$ mz COM4 register 12

$ mz COM4 firmware_version
v1.2.3
$ mz COM4 serial_number
4752
```
plugboard-schemas 0.5.1
Schemas for the Plugboard framework
Requires Python: <4.0,>=3.12

# plugboard-schemas

Schemas for the Plugboard framework. This package provides Pydantic models and TypeDict definitions used throughout Plugboard.

## Installation

```bash
pip install plugboard-schemas
```

## Usage

```python
from plugboard_schemas import ComponentSpec, ConnectorSpec
```

This package is typically installed as a dependency of the main `plugboard` package.
Miracle-gro 0.0.1
Select and update across Github repositories and then push them out as branches!
Requires Python: >=3.10

# Miracle Gro

Copy select portions of a folder tree using only a `YAML` file!

## Installation

Find this tool on `PyPI`: `pip install miracle-gro`

## Usage

`Miracle Gro` is a command-line interface (CLI) tool. Invoke it:
```
mgro --dest "RELATIVE_PATH"
```
The CLI supports:
* `glob`-compatible regex patterns
* relative pathing
* ...and more!
databricks-tellr 0.1.21
Tellr deployment tooling for Databricks Apps
Requires Python: >=3.10

# databricks-tellr

Python deployment tooling for Tellr on Databricks Apps.

## Usage

```python
import databricks_tellr as tellr

!pip install --upgrade databricks-sdk==0.73.0

result = tellr.setup(
    lakebase_name="ai-slide-generator-db-dev",
    schema_name="app_data_dev",
    app_name="ai-slide-generator-dev",
    app_file_workspace_path="/Workspace/Users/you@example.com/.apps/dev/ai-slide-generator",
)

print(result["url"])
```