semvec/pypi-packages huggingface dataset:
django2-alexa 0.1.4
Django app for easily creating Amazon Alexa Skills


# Django2 app for creating Alexa Skills
Django app for easily creating Amazon Alexa Skills. *By Tim Woocker & Malte Mosler*

## Table of Content
1. [Prerequisites](#1-prerequisites)
2. [Getting Started](#2-getting-started)
3. [Settings](#3-settings)
4. [Examples](#4-examples)
5. [Support](#3-support)

## 1. Prerequisites
If you're using Apache HTTP Server, **use v2.4.10 or later**!
From [Amazon's Docs](https://developer.amazon.com/de/docs/custom-skills/request-and-response-json-reference.html):
> Note: if you are using Apache HTTP Server to host your web service, use version 2.4.10 or later. Earlier versions of Apache HTTP Server send an "unrecognized name" warning if the server is not configured with a ServerName or ServerAlias in the configuration files. This prevents the Alexa service from sending the customer's request to your server. To address this, either upgrade to 2.4.10 or later, or add ServerName / ServerAlias to your server's configuration file.

## 2. Getting Started
You can use pip to install this app:

	pip install django2-alexa

In your django *settings.py* add `"django2_alexa"` to `INSTALLED_APPS`:
```python
INSTALLED_APPS = [
	...
    'django2_alexa',
	...
]
```
In your current path create a django app with:
```python
python manage.py startapp YourAppName
```

Import & create the `Skill` object in your *views.py*:
```python
from django2_alexa.interfaces.alexa import Skill

skill = Skill()
```

Import the `skill` in your *urls.py*  and add the view to your urlpatterns:
```python
from YourAppName.views import skill

urlpatterns = [
	...
    path('', skill.view)
	...
]
```

You can use this library with `DEBUG` mode on in *settings.py*. The amazon server verification for timestamps however will be skipped. This will cause amazon to not accept your skill if you try to publish your skill in `DEBUG` mode.

Now you are ready to develope your own skill for alexa! You can find a few examples  [here](#4-examples).

## 3. Settings
This django app adds some settings to your project:

|Name|Type|Default|Description|
|--|--|--|--|
|`ALEXA_VERIFY_CONN`|`bool`|`True`|This setting specifies if every request to an alexa skill should be verified against the amazon servers. This is useful when testing your skill without Amazon's service.|

## 4. Examples
[Audio Response](https://github.com/timwoocker/django2-alexa/blob/master/examples/audio/views.py)

[Card Response](https://github.com/timwoocker/django2-alexa/blob/master/examples/card/views.py)

[Slots](https://github.com/timwoocker/django2-alexa/blob/master/examples/slots/views.py)
## 5. Support

Twitter: [@Tim Woocker](https://twitter.com/crey4fun) [@DeemonRider](https://twitter.com/DeemonRider)
Clumsy 0.0.5
A collection of scripts used in the Computational Memory Lab for timeseries analysis
Requires Python: >=3.6.0


# Clumsy
Clumsy (originally cml_lib) is a collection of various scripts used in the computational memory lab's python analysis.

What is Clumsy?
-------------

more details about it here blah blah blah:

```python

from Clumsy.signal import rolling_window
from typing import Iterator

def fib(n: int) -> Iterator[int]:
    a, b = 0, 1
    while a < n:
        yield a
        a, b = b, a + b
```
See the documentation for more examples.

Clumsy is in development; some features are missing and there are bugs.
See 'Development status' below.

Requirements
------------
pyedflib

mne

ptsa

scipy

numpy

xarray

pandas

six

cmlreaders

numba

visbrain


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

Clumsy can be installed using pip:

    $ pip install Clumsy

If you want to run the latest version of the code, you can install from git:

    $mkdir Clumsy
    $cd Clumsy
    $git clone https://github.com/LoganJF/Clumsy.git .
    $python setup.py install


Development status
------------------
Beta testing currently 0.0.4
parapy 0.0.3
An automatic handling of parameter passing to python programs.

# parapy
An automatic handling of parameter passing to python programs

## Usage
Import the script. Then in the top of your own document, define a list of tuples of all your parameters of the form ('name', 'prefix'/position, type), and then call the library using `params.params(Your_Parameters)`. This will return a dictionary of all the parameters of the form {'name' : value}.

The library supports prefixed parameters (i.e. whatever comes after '-i'), boolean parameters (i.e. if '-a' is passed) and positional parameters (i.e. the second parameter without a prefix).

Currently supported types are str, int, float and bool. Multi-word parameters _must_ be enclosed in quotes.

## Example
```
import params

parameters = [('output', '-o', str),   # A string parameter with prefix '-o'
              ('amount', '-n', int),   # An integer parameter with prefix '-n'
              ('verbose', '-v', bool), # A boolean parameter with name '-v'
              ('eggs', '-e', float),   # A float parameter with prefix '-e'
              ('input', 0, str),       # A string parameter position 0
              ('spam', 1, int),        # An integer parameter position 1
              ('message', '-m', str)]  # A string parameter with prefix '-m'


p = (params.params(parameters))

print(p)
```
Then calling the program with the parameters as such: ` python program.py -v gov_secrets.db -o elvis.mp3 4 -n 10 -m "Listen to this cool track!"`, will result in the following output:
```
{'output': 'elvis.mp3',
 'amount': 10,
 'verbose': True,
 'eggs': None,
 'input': 'gov_secrets.db',
 'spam': 4,
 'message': 'Listen to this cool track!'}
```

## TODO
- Add default values