semvec/pypi-packages huggingface dataset:
rouleur 0.0.3
Cycling performance modelling with Python
License: MIT
Keywords: cycling power modelling

# rouleur: Cycling performance modelling

Makes the physical modelling of cycling trivially easy.

For example, let's try and estimate the power required for Wiggo's current hour record:

```pycon
>>> from rouleur import CyclingParams, calculate_air_density
>>>
>>> record = 54.526          # km/h
>>> record *= 1000 / 60**2   # m/s
>>> rho = calculate_air_density(30, 777, 0.6)  # about right
>>> pars = CyclingParams(
>>>     rider_velocity=record,
>>>     air_density=rho,
>>>     CdA=0.19, Crr=0.0025, 
>>>     chain_efficiency_factor=0.98,
>>>     road_gradient=0,
>>>     mass_total=82)
>>>     
>>> pars.solve_for.power_output()
440.9565671224358
```

That's all there is to it. 

The API consists almost exclusively of the `CyclingParams` class, which holds all the parameters required for modelling a cyclist. The class constructor combines a number of sensible defaults with any (keyword) arguments passed. Details of recognised keyword arguments---i.e. model parameters---can be found in the class docstring (`help(CyclingParams)`).

Instances then have a number of solver methods accessible via `parameters.solve_for.*`. 

# References

This package is an implementation of a number of published algorithms. Important references are:

1. [Martin JC, Milliken DL, Cobb JE, McFadden KL, Coggan AR. Validation of a Mathematical Model for Road Cycling Power. Journal of Applied Biomechanics 14: 276--291, 1998.](http://journals.humankinetics.com/doi/10.1123/jab.14.3.276)

2. [Martin JC, Gardner AS, Barras M, Martin DT. Modeling sprint cycling using field-derived parameters and forward integration. Med Sci Sports Exerc 38: 592--597, 2006.](https://www.ncbi.nlm.nih.gov/pubmed/16540850)

3. [Atkinson G, Peacock O, Passfield L. Variable versus constant power strategies during cycling time-trials: Prediction of time savings using an up-to-date mathematical model. Journal of Sports Sciences 25: 1001--1009, 2007.](https://www.ncbi.nlm.nih.gov/pubmed/17497402)

4. [Wells MS, Marwood S. Effects of power variation on cycle performance during simulated hilly time-trials. European Journal of Sport Science 16: 912--918, 2016.](https://www.ncbi.nlm.nih.gov/pubmed/26949050)
django-celery-inspect 0.2.1
Django Reusable app that uses Celery Inspect command to monitor workers/tasks via the Django REST Framework
License: MIT
Keywords: django,django-rest-framework,celery,inspection,monitoring,python

# django-celery-inspect

Django reusable-app that uses Celery Inspect command to monitor workers via the [Django REST Framework](https://github.com/tomchristie/django-rest-framework).

The main idea is to be able to monitor celery workers from another external service or server via a REST API and figure out if they are running or not by using celery's own [Inspect API]
(http://docs.celeryproject.org/en/latest/userguide/workers.html#inspecting-workers).

## Quick start

1. Install:

		pip install django-celery-inspect

2. Add "celery_inspect" to your INSTALLED_APPS setting like this:

		INSTALLED_APPS = [

          ...
          'celery_inspect',
        ]

3. Add the following to your urls.py:

		url(r'^api/v1/celery-inspect/', include('celery_inspect.urls', namespace='celery_inspect')),

4. If you Desire to use DRF's Authentication to protect these endpoints (Optional).

		REST_FRAMEWORK = {
		    'DEFAULT_AUTHENTICATION_CLASSES': (
			'rest_framework.authentication.TokenAuthentication',
		    ),
		    'DEFAULT_PERMISSION_CLASSES': (
			'rest_framework.permissions.IsAuthenticated',
		    ),
		}

## Usage:

1. http://localhost:8000/api/v1/celery-inspect/ping/

		{
			"worker2@localhost:8000": {
			    "ok": "pong"
			},
			"worker1@localhost:8000": {
			    "ok": "pong"
			}
        	}

2. http://localhost:8000/api/v1/celery-inspect/active/

        {
            "worker2@localhost:8000": [],
            "worker1@localhost:8000": []
        }

3. http://localhost:8000/api/v1/celery-inspect/registered/

        {
            "worker2@localhost:8000": [
                "core.tasks.db_backup",
                "core.tasks.send_queued_emails",
                "yy.tasks.assign_to_mongo",
                "xx.tasks.check_for_new_registered",
                "xx.tasks.create_and_associate_manager",
                "qq.celery.debug_task"
            ],
            "worker1@localhost:8000": [
                "core.tasks.db_backup",
                "core.tasks.send_queued_emails",
                "yy.tasks.assign_to_mongo",
                "xx.tasks.check_for_new_registered",
                "xx.tasks.create_and_associate_manager",
                "qq.celery.debug_task"
            ]
        }

4. http://localhost:8000/api/v1/celery-inspect/scheduled/

        {
            "worker2@localhost:8000": [],
            "worker1@localhost:8000": []
        }



### If for some reason you can only deal with status codes (This feature will only work if you have django-celery installed)

1. http://localhost:8000/api/v1/celery-inspect/active-status/

    - Returns 200 if all workers in WorkerState are up.
    - Returns 404 if workers are down (WorkerState != then inspect()).
    - Returns 501 if djcelery a.k.a django-celery is not installed.
ripy 0.0.7
Parsing of refractive index data, designed to be used with the tmmpy package.
License: MIT

Ripy is a small project aiming to allow easy access to refractive index information on materials. Besides basic objects representing materials, bindings to various databases are provided. Currently the following databases are supported:

* The *http://refractiveindex.info/* database
* Exports from PV Lighthouse (experimental)

More databases will be added in the future if needed.
linked_list 0.0.7
Classes for linked lists and doubly linked lists
License: MIT
Keywords: linked list data structure

linked_list module
==================

This package currently supports singly linked lists and doubly linked lists. Push and pop and delete operations are supported.

Installation
------------

You can install the package via pip:

    pip install linked_list

Documentation
-------------

You can find the documentation on `Read the Docs <http://linked-list.readthedocs.io/en/latest/>`_