semvec/pypi-packages huggingface dataset:
docker-printer 1.0.0
Composer for dockerfiles
Requires Python: >=3.7

[![Documentation Status](https://readthedocs.org/projects/docker-printer/badge/?version=latest)](https://docker-printer.readthedocs.io/en/latest/?badge=latest) ![PyPI](https://img.shields.io/pypi/v/docker-printer)

# Docker-Printer

`docker-printer` is a CLI for easily managing multistep and branching dockerfiles.

Regular multi-stage dockerfiles and `docker build` commands are incredibly powerful and useful; however, they are designed for building a single image. Multistage builds can be used to define multiple related images, but this quickly results in complicated dockerfiles, possibly duplicated instructions, and complicated collections of build commands.

`docker-printer` addresses this in two main ways:
- By allowing dockerfiles to be composed from re-usable modules.
- By building bake files for use by `docker buildx bake` that consolidate the build processes of multiple images in multiple environments into a single configuration file.

# Getting Started and Documentation

```
pip install docker-printer
docker-printer init
```

See the [documentation](https://docker-printer.readthedocs.io/en/latest/#) for how to get started.

There are also example docker constructs provided in the `/examples` folder.
attd 1.0
Dictionary with attribute access to keys
Requires Python: >=3.1.0

Attribute Dictionary
====================

[![Test](https://github.com/otsaloma/attd/workflows/Test/badge.svg)](https://github.com/otsaloma/attd/actions)
[![PyPI](https://img.shields.io/pypi/v/attd.svg)](https://pypi.org/project/attd/)
[![Downloads](https://pepy.tech/badge/attd/month)](https://pepy.tech/project/attd)

attd is a Python package that provides a dictionary with attribute
access to keys. It is especially convenient when working with deeply
nested data from JSON APIs.

## Installation

```bash
# Latest stable version
pip install -U attd

# Latest development version
pip install -U git+https://github.com/otsaloma/attd
```

## Documentation

```python
>>> from attd import AttributeDict
>>> data = AttributeDict({"a": {"b": {"c": 1}}})
>>> data["a"]["b"]["c"]
1
>>> data.a.b.c
1
>>> from attd import FallbackAttributeDict
>>> data = FallbackAttributeDict()
>>> data["a"]["b"]["c"]
{}
>>> data.a.b.c
{}
```
py3status-fbox 0.1.2
Python module to monitor your freebox in py3status bar
Requires Python: >=3.7, <4
Keywords: freebox,monitor,status,i3,py3status

# py3status-fbox

Python module to monitor freebox activity in py3status bars

## Prerequisites

This is an i3/py3status module and it uses requests.

## Installation

```console
pip install py3status-fbox
```

## Configuration

Available parameters:
- `refresh_delay` (default: 60s)
- `format` (default: `freebox: ↑ {fmt_rate_up} ↓ {fmt_rate_down}`)

Available format variables:
- `rate_up`: raw upload rate
- `rate_down`: raw download rate
- `fmt_rate_up`: human readable upload rate
- `fmt_rate_down`: human readable download rate
- `bw_up`: raw upload bandwidth
- `bw_down`: raw download bandwidth
- `fmt_bw_up`: human readable upload bandwidth
- `fmtbw_down`: human readable download bandwidth
- `percent_up`: upload bandwidth usage
- `percent_down`: download bandwidth usage
- `time`: time of last update

Example configuration:

```
fbox {
  color="#dcedc1"
  refresh_delay=10
  format = " ↑[\?color=lightgreen {fmt_rate_up}]↓[\?color=lightblue {fmt_rate_down}]"
}
```
lenskit-implicit 0.14.0
LensKit wrappers for the Implicit package.
Requires Python: >= 3.7

# LensKit wrapper for implicit

The `lenskit-implicit` package provides [LensKit][] wrappers for the implicit-feedback matrix factorization
algorithms found in Ben Frederickson's [implicit][] package.

[implicit]: https://pypi.org/project/implicit
[LensKit]: https://lkpy.lenskit.org