semvec/pypi-packages huggingface dataset:
Djheroku 0.6.1
Some helper functionality for binding Heroku configuration to Django

Djheroku
========

Djheroku is a helper script that reads Heroku configuration from environment
variables and injects them to Django configuration.


.. image:: https://secure.travis-ci.org/fubaz/djheroku.png?branch=master
    :target: http://travis-ci.org/fubaz/djheroku
    :alt: Build Status

.. image:: https://coveralls.io/repos/ferrix/djheroku/badge.png
    :target: https://coveralls.io/r/ferrix/djheroku
    :alt: Test Coverage

.. image:: https://requires.io/github/fubaz/djheroku/requirements.svg?branch=master
     :target: https://requires.io/github/fubaz/djheroku/requirements/?branch=master
     :alt: Requirements Status

.. image:: https://img.shields.io/pypi/v/djheroku.svg
    :target: https://pypi.python.org/pypi/djheroku/
    :alt: Latest Version

.. image:: https://img.shields.io/pypi/wheel/djheroku.svg
    :target: https://pypi.python.org/pypi/djheroku/
    :alt: Wheel Status

.. image:: https://img.shields.io/pypi/l/djheroku.svg
    :target: https://pypi.python.org/pypi/djheroku/
    :alt: License

Autopilot for Heroku settings
-----------------------------

This is an easier way to control what Django does. Just add
a few lines to your settings.py::

    from djheroku import autopilot
    autopilot(vars())

Then you can make runtime changes to your application settings::

    heroku addons:add sendgrid
    heroku config:set ADDONS=sendgrid
    heroku addons:add memcachier
    heroku config:set ADDONS=sendgrid,memcachier

Djheroku will change the variables accordingly.

Configuration helpers
---------------------

Example::

    # settings.py
    from djheroku import sendgrid
    vars().update(sendgrid())

This is equivalent of typing in::

    # settings.py
    import os

    if 'SENDGRID_USERNAME' in os.environ and 'SENDGRID_PASSWORD' in os.environ:
        EMAIL_HOST = 'smtp.sendgrid.net'
        EMAIL_HOST_USER = os.environ['SENDGRID_USERNAME']
        EMAIL_HOST_PASSWORD = os.environ['SENDGRID_PASSWORD']
        EMAIL_PORT = 587
        EMAIL_USE_TLS = True

If any of the variables are not present, the configuration will be left as it
is. Currently there are two helpers: ``sendgrid()`` and ``mailgun()``.

Middleware
----------

There are three middleware classes in Djheroku. They are used to redirect
permanently from one URL to another.

* ``NoWwwMiddleware`` removed www. from URLs of incoming requests.
  The opposite is built-in functionality of Django. Enable this Middleware
  and set NO_WWW = True in settings.py to activate.
* ``PreferredDomainMiddleware`` redirects all domains directed to the
  application to a preferred one.
* ``ForceSSLMiddleware`` redirects all non-SSL connections to a secure
  connection.

Each of these middlewares does one thing only and combined they will lead
into three separate redirects or even a eternal loop if configured
properly wrong.
dbt-accelerator 0.0.1
Package which generates schema.yml and columns.md from Excel Sheet
Requires Python: >=3.6

# dbt_schema_md_generator
This code automatically produces schema.yml and columns.md file with input from xlsx file.


Please follow the Steps below:
1. Input the program with your xlsx filename and model_name_to_append
2. Each Sheet Name will represent a Table and contains the Column_Name, Column_Description and tests if any.
3. Each sheet must contain 'Column_Name' and 'Column_Description' as Headers in them 
4. If you want to add Test you need to add 'Yes' respectively under the test column.
5. Make Sure you have a Table_Descriptions Sheet present in your xlsx file
6. Ensure you have entries for all the Tables in Table_Descriptions Sheet
7. The Sheet Name must match with the Column_Name given in the Table_Descriptions Sheet
8. Please refer to the Sample_File provided for more clarity.
SweeplineVT 0.0.8
Voronoi Tessellation using Sweep-line algorithm
Requires Python: >=3.6

# SweeplineVT -- Voronoi Tessellation using sweep-line algorithm

[SweeplineVT github](https://github.com/lewtonstein/SweeplineVT)

```
pip install SweeplineVT
```

## Description
* Voronoi Tessellation on the basis of the sweep-line algorithm developed by Steven Fortune in 1986
* Make centroidal Voronoi Tessellation (CVT)
* Make Delaunay triangulation
* Take accurate positions of points with no need of pixelation / binning.
* Confine Voronoi diagram to a rectangular region
## Examples
### Make Voronoi Tessellation for a list of points
* The content of "example.dat"

```
-0.5 1.5
1.1 3.3
2.9 5.7
3.1 4.3
5.4 2.6
6.3 3.1
```

```
slvt.py example.dat --calCentroid
pl_VT.py example_VT.dat example_ctd.dat -s
```

The red points are the Voronoi sites (input points from "example.dat"). The green lines connect each sites with the corresponding cell centroid.

![example](https://github.com/lewtonstein/SweeplineVT/blob/master/SweeplineVT/doc/example_VT.png?raw=true)

### Make centroidal Voronoi Tessellation (CVT) of 14 points in 0<x<7, 0<y<5.
```
slvt.py --makeCVT 14 --border 0,7,0,5 -s
pl_VT.py CVT14_VT.dat -s
```

"-s" of slvt.py means "silent". "-s" of pl_VT.py means "step".

* One possible result you might see:   
![CVT14](https://github.com/lewtonstein/SweeplineVT/blob/master/SweeplineVT/doc/CVT14_VT.png?raw=true)


### Show the distribution of cell area

```
from SweeplineVT import Voronoi
import pylab as pl
x=np.random.random(size=10)
y=np.random.random(size=10)
vor=Voronoi(events=np.vstack((x,y)).T,calArea=True,autoscale=False)
Area,ind,cts=vor.getarealist()
Area/=np.array(cts)
pl.hist(Area)
```


## Output files
* {FileName}_VT.dat: each item corresponds to one cell edge. The 9 columns are:
 + 1: index of edge
 + 2-3 and 3-4: coordinates of the two Voronoi vertices (nodes) of the edge
 + 5-6 and 7-8: coordiantes of the two nearest Voronoi sites (The Delaunay diagram)

* With "--calCentroid", {FileName}_ctd.dat: each item corresponds to one cell. The 6 columns are:
 + 1: index of cell / site.
 + 2-3: Voronoi site of the cell
 + 4-5: centroid of the cell
 + 6: area of the cell
 + 7: site duplication number (>1 means duplicated)

* With "--calArea", {FileName}_area.dat: each item corresponds to one cell. The 6 columns are:
 + 1: index of cell / site.
 + 2-3: Voronoi site of the cell
 + 4: area of the cell
 + 5: site duplication number (>1 means duplicated)