semvec/pypi-packages huggingface dataset:
equestions-pkg-joanclopezm 0.0.1
Depression test to calculate depression
Requires Python: >=3.6

         ___        ______     ____ _                 _  ___  
        / \ \      / / ___|   / ___| | ___  _   _  __| |/ _ \ 
       / _ \ \ /\ / /\___ \  | |   | |/ _ \| | | |/ _` | (_) |
      / ___ \ V  V /  ___) | | |___| | (_) | |_| | (_| |\__, |
     /_/   \_\_/\_/  |____/   \____|_|\___/ \__,_|\__,_|  /_/ 
 -----------------------------------------------------------------
time-ms 0.0.1
Variable time formats in one package
Keywords: python,time,tools,utils,formats,seconds

# time-ms

Use this package to easily convert various time formats to seconds.


## What is it?

```py
from time-ms import ms

ms('2w') # 1209600
ms('1m') # 60
```

## How to use?

```py
from time-ms import ms
import asyncio

asyncio.sleep(ms('1h')) # sleeping 3600 sec. / 1h
```

## Formats

```
m, min, minute, h, ho, hour, d, day, w, week, y, year, mon, month, y, year
```

## Find a Bug?

Report it [here](https://github.com/AlmondPark/time-ms.py/issues)
crabkevin 2.0.0
A sample Python project
Requires Python: >=3.6, <4
Keywords: sample,setuptools,development

# A sample Python project

![Python Logo](https://www.python.org/static/community_logos/python-logo.png "Sample inline image")

A sample project that exists as an aid to the [Python Packaging User
Guide][packaging guide]'s [Tutorial on Packaging and Distributing
Projects][distribution tutorial].

This project does not aim to cover best practices for Python project
development as a whole. For example, it does not provide guidance or tool
recommendations for version control, documentation, or testing.

[The source for this project is available here][src].

Most of the configuration for a Python project is done in the `setup.py` file,
an example of which is included in this project. You should edit this file
accordingly to adapt this sample project to your needs.

----

This is the README file for the project.

The file should use UTF-8 encoding and can be written using
[reStructuredText][rst] or [markdown][md use] with the appropriate [key set][md
use]. It will be used to generate the project webpage on PyPI and will be
displayed as the project homepage on common code-hosting services, and should be
written for that purpose.

Typical contents for this file would include an overview of the project, basic
usage examples, etc. Generally, including the project changelog in here is not a
good idea, although a simple “What's New” section for the most recent version
may be appropriate.

[packaging guide]: https://packaging.python.org
[distribution tutorial]: https://packaging.python.org/tutorials/packaging-projects/
[src]: https://github.com/pypa/sampleproject
[rst]: http://docutils.sourceforge.net/rst.html
[md]: https://tools.ietf.org/html/rfc7764#section-3.5 "CommonMark variant"
[md use]: https://packaging.python.org/specifications/core-metadata/#description-content-type-optional
jangl-toolbox 1.0.1
Common utilities for Python 3.9+ to interact with Jangl environment.
Requires Python: >=3.9
Keywords: jangl-toolbox

=============
Jangl Toolbox
=============

Common utilities for Python 3.9+ to interact with Jangl environment.



=======
History
=======

1.0.1 (2021-12-14)
------------------

* Update backend_api for new httpx version

1.0.0 (2021-06-03)
------------------

* First release on PyPI.
yourbase 7.1.3
Automatically skip tests that don't need to run
Requires Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*

A test accelerator.

# Setup

You can install this package using pip:

```sh
pip install yourbase
```

# Documentation

Please see the official YourBase documentation:

- https://docs.yourbase.io/python
bubbletree 1.2
Bubble plot or heatmap ordered by phylogenetic tree

# Bubble Tree

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5114948.svg)](https://doi.org/10.5281/zenodo.5114948)

![example](img/figexample.png)

BubbleTree generates a Cleveland dot plot or heatmap ordered by a corresponding phylogenetic tree. Required input: a tab separated frequency table (i.e., with taxa as rows and samples as columns), a newick, nexus, nexml, phyloxml, or cdao formated tree, and a tab separated file with sample metdata. See example files for formatting requirements.

### Prerequisites

Bubble tree is written with python 3+ and relies on the following packages:

* [BioPython](https://biopython.org/) 
* [Matplotlib](https://matplotlib.org/)
* [Pandas](https://pandas.pydata.org/)
* [Numpy](http://www.numpy.org/)
* [Seaborn](https://seaborn.pydata.org/)

### Install with pip

```
pip install bubbletree
```

### Install with conda

```
conda install -c aemann01 bubbletree
```

### Examples
Generate a heatmap figure ordered by the mapping.txt column Habitat2
```
bubbletree.py -i examples/biom.txt -t examples/tree.tre -m examples/map.txt -c Habitat2 -d heatmap -s sampleID -a ASVID
```

Generate a bubble chart figure colored and ordered by the mapping.txt column Species and view the tree structure in ASCII format to screen
```
bubbletree.py -i examples/biom.txt -t examples/tree.tre -m examples/map.txt -c Species -d bubblechart -p True -s sampleID -a ASVID
```

Generate a bubble chart figure colored and ordered by the mapping.txt column Genus on a remote cluster (Disables the automatic $DISPLAY environment varible used by matplotlib)
```
bubbletree.py -i examples/biom.txt -t examples/tree.tre -m examples/map.txt -c Genus -d bubblechart -r True -s sampleID -a ASVID
```

Help and parameter description
```
bubbletree.py -h
```
snitch-ai 1.1.13
Client library for using Snitch AI's model validation platform

# Snitch AI Python Client Library

This library is used to perform Snitch AI analyses in a programmatic manner. This allows for easier upload
to the Snitch AI platform without having to use the UI. Additionally, this library can facilitate integration
with existing MLOps pipelines and external reporting tools.

## Usage:

### Generate a quality report

```
import snitch_ai

# you can specify the access_token in code or set the SNITCH_ACCESS_TOKEN environment variable 
snitch_ai.access_token = "VGhpcyBpcyBub3QgYW4gYWN0dWFsIGFjY2VzcyB0b2tlbi4gVG8gZ2V0I..."

project = snitch_ai.select_project("My First Project")

quality = project.run_quality_analysis(model, train_x, train_y, test_x, test_y)

json = quality.get_json()
quality.save_pdf("My Quality Report.pdf")
```

### Generate a drift report

```
import snitch_ai

# you can specify the access_token in code or set the SNITCH_ACCESS_TOKEN environment variable
snitch_ai.access_token = "VGhpcyBpcyBub3QgYW4gYWN0dWFsIGFjY2VzcyB0b2tlbi4gVG8gZ2V0I..."

project = snitch_ai.select_project("My First Project")

drift = project.run_drift_analysis(train_x, updated_x)

json = drift.get_json()
drift.save_pdf("My Drift Report.pdf")
```

### Usage within a hybrid environment

Snitch AI can also be used in a hybrid environment. This gives you the full power of Snitch AI's analysis
engine without needing to upload your models or datasets to the cloud. If your internal security policy
forbids uploading your data to a public cloud, this will likely be your preferred method of using Snitch AI.

You can learn more about Snitch AI Hybrid here: https://www.snit.ch/hybrid/
```
import snitch_ai

# replace this address with the address of your on-premises Snitch AI environment
# you can also set this in the SNITCH_ENDPOINT_ADDRESS environment variable
snitch_ai.endpoint_address = "https://localhost:5443/"

# you can specify the access_token in code or set the SNITCH_ACCESS_TOKEN environment variable
snitch_ai.access_token = "VGhpcyBpcyBub3QgYW4gYWN0dWFsIGFjY2VzcyB0b2tlbi4gVG8gZ2V0I..."

# perform quality or drift analysis per usual

```

Full product documentation can be found at https://help.snit.ch/