semvec/pypi-packages huggingface dataset:
sbcli-ref 0.0.6
CLI for managing SimplyBlock cluster


# Simply Block
[![Docker Image Build](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/docker-image.yml)

[![Python Unit Testing](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml/badge.svg)](https://github.com/simplyblock-io/sbcli/actions/workflows/python-testing.yml)


## Install
Add the package repo from AWS CodeArtifact using [awscli](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html)

```bash
aws codeartifact login --tool pip --repository sbcli --domain simplyblock --domain-owner 565979732541 --region eu-west-1
```
Install package
```bash
pip install --extra-index-url https://pypi.org/simple sbcli-dev
```

# Components

## Simply Block Core
Contains core logic and controllers for the simplyblock cluster

## Simply Block CLI
Please see this document
[README.md](../main/simplyblock_cli/README.md)


## Simply Block Web API
Please see this document
[README.md](../main/simplyblock_web/README.md)



### local development

FoundationDB requires a client library (libfdb_c.dylib) for the Python bindings to interact with the database.
Depending on the OS architecture, please install the appropriate version from the official github repo

```
wget https://github.com/apple/foundationdb/releases/download/7.3.3/FoundationDB-7.3.3_arm64.pkg
```

setup the code on a management node and the webApp code can be developed by building the `docker-compose-dev.yml` file.


```
sudo docker compose -f docker-compose-dev.yml up --build -d
```
harness-ar-python 1.0.0
Harness AR Python Package
Requires Python: >=3.6

# Harness AR Python

A Python package for Harness AR integration.

## Installation

You can install the package using pip:

```bash
pip install harness-ar-python
```

## Usage

```python
import harness_ar_python

# Add usage examples here
```

## License

This project is licensed under the MIT License.
ocs-rise-set 0.6.4
Routines for accurate rise/set/transit calculations
Requires Python: <3.13,>=3.9

# Rise-set Library

![Build](https://github.com/observatorycontrolsystem/rise_set/workflows/Build/badge.svg)
[![Coverage Status](https://coveralls.io/repos/github/observatorycontrolsystem/rise_set/badge.svg?branch=master)](https://coveralls.io/github/observatorycontrolsystem/rise_set?branch=master)
[![Codacy Badge](https://app.codacy.com/project/badge/Grade/8b05ac4107534c7297dfff464360af57)](https://www.codacy.com/gh/observatorycontrolsystem/rise_set/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=observatorycontrolsystem/rise_set&amp;utm_campaign=Badge_Grade)
[![PyPI](https://img.shields.io/pypi/v/ocs-rise-set?style=flat)](https://pypi.org/project/ocs-rise-set/)

***WARNING: The API of this library will be updated in the near future***

This library provides Python routines for finding the positions of astronomical bodies to reasonable precision. It is primarily used to calculate target uptime and sunrise, sunset and twilight times, accurate to 30s-1m. It also supports calculating target airmass over time. The library depends on Fortran SLALIB to perform the computations. The rise/set/transit algorithms are implementations of Astronomical Algorithms, Ch. 14 (Jean Meeus). This library was initially authored by [Eric Saunders](https://github.com/ire-and-curses).

## Prerequisites

-   Python >= 3.9
-   Ability to compile fortran (gfortran installed)

## Installation

It is highly recommended that you install and run your python code inside a dedicated python
[virtual environment](https://docs.python.org/3/tutorial/venv.html).

Add the `ocs_rise_set` package to your python environment (you may need to install numpy first):

```bash
(venv) $ pip install numpy; pip install ocs_rise_set
```

## For Developers

### Running the Tests

The unit tests are currently using nosetests, so there are a few tests dependencies to install. After cloning this project, from the project root and inside your virtual environment (using Poetry):

```bash
$ poetry env use python3.10
$ poetry install
$ poetry run pytest
```