semvec/pypi-packages huggingface dataset:
human-time 1.0.6
Converts digit based time formats to the english language equivalent
License: MIT
Requires Python: >=3.6
Keywords: talking clock human time

# HumanTime

Convert numerical times to their human readable English language equivalent.

Examples: 

`15:00` becomes `"Three o'clock"`

`15:15` becomes `"Quarter past three"`

`15:27` becomes `"Twenty seven minutes past three"`

Distributed on PyPI - https://pypi.org/project/human-time/

## System requirements

Python >= 3.6 is required. The instructions below are focused on creating a Python 3 virtual environment in order to
ringfence the dependencies. 

## Running the application

The package can be installed from source:
```bash
cd human-time
python3 -m venv venv
source venv/bin/activate

python -m pip install -r requirements.txt

python -m pip install -e . --upgrade
```

Alternatively the package can be pulled from PyPi:
```bash
python3 -m pip install human-time
```

The installed application can then be invoked in two says, either as command line tool, which simply performs a single
time conversion, or as a server, which provides a REST API with single endpoint `api/humantime` to convert the time.

`humantime-server` starts by default on port 5000, this can be changed by setting the `HUMANTIME_PORT` environment variable.
```bash
humantime -t 15:00
humantime-server
```
Both methods either return the human time corresponding to the current time, or if the `numeric_time` parameter is
provided, the human time for the given numeric time.

If using `humantime-server`, an OpenAPI user interface is available to test it's endpoint, which can be found at

## Testing

Before testing ensure that the Python virtual environment is set up, and both unit test and application dependencies 
are installed by running `python3 -m pip install -r requirements.txt -r test/requirements.txt`

To run the tests run `python3 -m pytest --cov=src --pyargs test`

## Build and Publish

The package is built, and deployed to PyPi via `twine`, as shown below.

```bash
python3 -m pip install setuptools twine
python3 -m setup sdist
twine upload dist/*
```
clear-cut 1.4.2
Number crunching backend to extract edges from a provided image
License: MIT
Requires Python: >=3.6

# Clear Cut

This package is intended to serve as a tool to sketch out the edges of any provided image. This is a personal project which I am - to use an appropriate term - *channeling* my number crunching desire into.

Refer to [this repo](https://github.com/chrispdharman/clear-cut) if you would like to play around with the source code.

# To run locally

1. Pick a new folder location, e.g. `~/Desktop/mock`
1. In a terminal, go into this folder `cd [absolute_path]/mock/`
1. Create a new Python3 virtual environment `python3 -m venv venv`
1. Activate this virtual environment: `source venv/bin/activate`
1. Install the latest (or specific) verion of the ClearCut python module: `pip install clear-cut(==1.3.1)`
1. Run Python in shell: `python`
1. Excecute the following Python script (tailoring the paths to your local set up):
```
from clear_cut.clear_cutter import ClearCut

image_filepath = '/Users/christopherharman/Desktop/mock/clear-cut-mock-logo.jpg'
results_path = '/Users/myusername/Desktop/mock/'

# All kwargs are optional
#   param debug: toggles on/off output to terminal
#   param results_path: sets results directory. Omitting this parameter will write results to current working directory
#   param image_filepath: location to image. Omitting this parameter will use a default Bob Ross image instead
clear_cut = ClearCut(debug=True, image_filepath=image_filepath, results_path=results_path)
clear_cut.run()
```

On completion, you should have a set of ClearCut processed images in a `/results/` directory
winrmmanager 1.1.0
A project to create winrm sessions via python utilizing the pywinrm library
License: MIT
Keywords: winrmmanager winrm pywinrm

============
winrmmanager
============

A project to create winrm sessions via python utilizing the pywinrm library


* Documentation:

Features
--------

* Return a winrm session in order of most secure to least secure.

Todo
----

* Certificate authentication across winrm currently not supported




History
-------

0.1 (2018-07-06)
---------------------

* First release


1.0.0 (17-10-2018)
------------------

* Ported the template part to python 3.7 and dropped support for python 2.7


1.0.1 (15-01-2019)
------------------

* Updated requests module


1.1.0 (28-08-2020)
------------------

* bumped pywinrm
django-gridfs-storage 0.0.2
Django GridFS Storage Engine
License: MIT
Requires Python: >3.6

# django-gridfs-storage

### Simple django GridFS storage engine


## Usage:
<ol>
<li> 
Install <code>django_gridfs_storage</code>:

```
pip install django_gridfs_storage
```
</li>
<li> 
Into settings.py file of your project, add <code>gridfs_storage</code> to <code>INSTALLED_APPS</code>:

```python
INSTALLED_APPS = [
    ...,
    'gridfs_storage',
]
```
</li>   
<li> 
add the following variables to your settings:

```python
# defaults to default local mongodb server
DEFAULT_GRIDFS_URL = 'mongodb://127.0.0.1:27017' 
# if set to None, it will refuse to serve files and raise an Exception
DEFAULT_GRIDFS_SERVE_URL = None  
DEFAULT_GRIDFS_COLLECTION = 'storage'
```
</li>
<li> 
To serve files through django (not recommended) you can use this in urls.py:

```python
urlpatterns = [
    path('admin/', admin.site.urls),
    ...,
    path('media/', include('gridfs_storage.urls')),
]
```
and set the <code>DEFAULT_GRIDFS_SERVE_URL</code> to the prefix you specified in the path. in this case its <code>/media/</code>
</li>

<li> 
If you wish to use it on all <code>FileField</code> and <code>ImageField</code> set it as the default Storage:

```python
DEFAULT_FILE_STORAGE = 'gridfs_storage.storage.GridFSStorage'
```
</li>

<li>
 If you wish to use on individual field bases set it as the field storage:

```python
from django.db import models
from gridfs_storage.storage import GridFSStorage

class SampleModel(models.Model):
    attachment = models.FileField(storage=GridFSStorage())
    first_pic = models.ImageField(storage=GridFSStorage(location='sample/images'))
    
    # To store in a different collection than "storage"
    another_pic = models.ImageField(storage=GridFSStorage(collection='image_storage'))
    
    # Serve through custom cdn connected to the same gridfs or similar, the limit is the sky :)
    served_outside = models.ImageField(storage=GridFSStorage(base_url='https://img.cdn/serve/'))
```
</li>
</ol>

## Requirements:

  1. Python 3.6 or higher.
  2. Django 2.2 or higher.
  3. MongoDB 3.4 or higher.


## Tests? None.
<code>We crash production like real men</code>