semvec/pypi-packages huggingface dataset:
tvmodels 0.0.7
Implementation of vision models with their pretrained weights

# tvmodels
The tvmodels library contains pretrained vision models in pytorch trained on ImageNet. Some of these models are available in [torchvision](https://pytorch.org/docs/stable/torchvision/index.html) but some are not, so you can load them for here.

## Installation
Run the following to install:
```python
pip install tvmodels
```

### Colab
If it shows `ModuleNotFoundError` on Google-colab use the following:
```python
!git clone https://github.com/rohitgr7/tvmodels.git
import sys
sys.path.append('/content/tvmodels')
```

## Usage
```python
from tvmodels.models import se_resnet50, resnet18

# Load the models
se_res_model = se_resnet50(pretrained=True)
res_model = resnet18(pretrained=True)
```

## Available models
- [x] ResNet(s)
- [x] ResNext(s)
- [x] SEResNet(s)
- [x] SEResNeXt(s)
- [x] SENet154
- [x] EfficientNets
customusers 1.0.3
A simple Django app to create custom users and their RESTful APIs.

=====
Users
=====

Users is a simple Django app that create own custom users and a RESTful API for the users that is allauth enabled.

Quick start
-----------

1. Add "users" to your INSTALLED_APPS setting like this::

	INSTALLED_APPS = [
		...
		'app_users',
		'rest_framework',

	]

2. Include the usres URLconf in your project urls.py like this::

    path('users/', include('app_users.urls')),

3. Run `python manage.py migrate` to create the users models.

4. Start the development server and visit http://127.0.0.1:8000/users/
   to view the users API
elisa-dnt 0.1.6
Do Not Translate for machine translation

# Do Not Translate [![Build Status](https://travis-ci.com/ChenghaoMou/elisa-dnt.svg?token=9nvvJ4htB9CrTskFFEhv&branch=master)](https://travis-ci.com/ChenghaoMou/elisa-dnt)

Find, remove and restore regex-matched language-independent tokens before and after translation.

## Usage

```shell
python -m elisa_dnt --help
```
unitrans-evalir 0.0.1.9
Parses a file with a certain structure and converts to the desired metric unit.

# UniversalTranslator

Final individual project for the "Tendencias en desarrollo de aplicaciones" class.

## App objective

This CLI (Command Line App) can be used to convert from one longitude unit from the International Unit System to another one.

## App installation

First, you need to have pip installed; it's the python package manager that you'll use to then install the application. You can get it [here](https://www.liquidweb.com/kb/install-pip-windows/), however, it should be preinstalled on your system; still, I recommend upgrading to the latest version to avoid conflicts.

After installing pip, you can just run this command: `pip install unitrans-evalir`

When you install it with pip (beware, this will also install all of the CLI dependencies), you can then use it by running `UniversalTranslator --help`: this will display the help file with all the command options.

Example:

```
pip install unitrans-evalir
UniversalTranslator --pathname input.txt --writepath output.txt
```

This example will take the input.txt file that you have created on the folder you're in, process the contents, and write to the `output.txt` file the converted units.

### Note for windows users

For using the command line app, you MUST have installed these 3 things:

- The latest version of Python 3.
- The latest version of PyPI.
- Git Bash.
  Using the normal windows prompt and powershell will not work. You MUST use the linux subsystem command line or the Git bash to use the application.

### Input Format example:

`1 m cm`: 1 meter to centimeters.
`2 dm km`: 2 decimeters to kilometers.
For further info about usage, please refer to [this table on wikipedia.](https://en.wikipedia.org/wiki/Metre)

## Contributing:

Please take a look at the CONTRIBUTING.MD file.

## Miscellaneous

- [CRC Cards](https://www.dropbox.com/s/ziuwpm2cyhquio0/CRC%20responsiblity.png?dl=0)
- [UML Diagram](https://www.dropbox.com/s/634thy9jduy5mgd/UML%20Diagram.png?dl=0)
py-emailprotections 0.8.5
Python library to interact with SPF and DMARC

# py-emailprotections
[![Build Status](https://travis-ci.com/poipoii/pyemailprotectionslib.svg?branch=master)](https://travis-ci.com/poipoii/pyemailprotectionslib)
[![Coverage Status](https://coveralls.io/repos/github/poipoii/pyemailprotectionslib/badge.svg?branch=master)](https://coveralls.io/github/poipoii/pyemailprotectionslib?branch=master)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/py-emailprotections.svg)
![PyPI - Wheel](https://img.shields.io/pypi/wheel/py-emailprotections.svg)
[![PyPI version](https://badge.fury.io/py/py-emailprotections.svg)](https://badge.fury.io/py/py-emailprotections)
![PyPI - Downloads](https://img.shields.io/pypi/dm/py-emailprotections.svg)

This is a simple library designed to assist people with finding email protections.

## Installing

``` python
pip install py-emailprotections
```

## Usage

The simplest use of this library is to find and process SPF and DMARC records for domains. This is easiest with the `SpfRecord.from_domain(domain)` and `DmarcRecord.from_domain(domain)` factory methods.

Example:

    import emailprotectionslib.spf as spf
    import emailprotectionslib.dmarc as dmarc

    spf_record = spf.SpfRecord.from_domain("google.com")
    dmarc_record = dmarc.DmarcRecord.from_domain("google.com")

    print spf_record.record
    print dmarc_record.policy
python-datetime-tz 0.5.4
A drop in replacement for Python's datetime module which cares deeply about timezones.

Home-page: http://github.com/mithro/python-datetime-tz
Author: Tim Ansell
Author-email: mithro@mithis.com
License: License :: OSI Approved :: Apache Software License
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Internationalization