Saravanan666/pypi-org huggingface dataset:
Package: pollination-ladybug-radiance
Pollination Ladybug RadiancePollination ladybug-radiance adds daylight simulation functions to Pollination.This plugin takes advantage of Ladybug Toolsladybug-radiancePython package.
For more information see:PyPIandGitHub.For running all the functionalities on your local machine you need to installRadiance. You can download the latest official
release of Radiance fromGitHub.FunctionsYou can see the list of available functions in ladybug-radiance pluginhereon Pollination.
Package: pollination-lbt-honeybee
Pollination lbt-honeybeeThe lbt-honeybee plugin provides access to the honeybee-core library and all
honeybee extensions simultaneously. This includes:honeybee-energyhoneybee-radianceNote that the plugin does not include any simulation engines and only contains
the Python libraries.Sourceslbt-honeybeePython package.PyPI,sourceThis package includes the following extensions for honeybee:honeybee-radiancePython package.PyPI,sourcehoneybee-energyPython package.PyPI,sourcehoneybee-displayPython package.PyPI,source
Package: pollination-pmv-comfort-map
PMV Comfort MapPMV thermal comfort map recipe for Pollination.Compute spatially-resolved PMV thermal comfort from a Honeybee model and EPW.
This recipe also computes operative temperature or (optionally) Standard
Effective Temperature (SET). Raw results are written into aresults/folder and
include CSV matrices of hourly temperatures, thermal conditions and PMV. Processed
metrics of Thermal Comfort Percent (TCP) can be found in themetrics/folder.
Input conditions to the comfort model are written to aninitial_results/conditionsfolder.MethodsThis recipe uses EnergyPlus to obtain surface temperatures and indoor air
temperatures + humidities. Outdoor air temperatures, relative humidities, and
air speeds are taken directly from the EPW. All outdoor points are assumed to be
at one half of the EPW meteorological wind speed (effectively representing wind
speed at ground/human height).Longwave radiant temperatures are achieved by computing spherical view factors
from each sensor to the surfaces of the model using Radiance. These view factors
are then multiplied by the surface temperatures output by EnergyPlus to yield
longwave MRT at each sensor. All indoor shades (eg. those representing furniture)
are assumed to be at the room-average MRT. For outdoor sensors, the EnergyPlus
outdoor surface temperatures are used and each sensor's sky view is multiplied by
the EPW sky temperature to account for longwave radiant exchange with the sky.
All outdoor context shades and the ground are assumed to be at the EPW air
temperature unless they have been modeled as Honeybee rooms.A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations,
which precisely represents direct sun by tracing a ray from each sensor to the
solar position. The energy properties of the model geometry are what determine
the reflectance and transmittance of the Radiance materials in this shortwave
calculation.To determine Thermal Comfort Percent (TCP), the occupancy schedules of the energy
model are used. Any hour of the occupancy schedule that is 0.1 or greater will be
considered occupied. For outdoor sensors, all hours are considered occupied.
Package: pollination-point-in-time-grid
point_in_time_gridPoint-in-time grid-based recipe for Pollination.Use this recipe to calculate illuminance or irradiance for a single point in time,
given a HBJSON model and a sky condition. This recipe can also compute luminance
and radiance, though these will interpret the sensors as individual rays.Skies can be either CIE, ClimateBased/Custom, or for a specific
Illuminance/Irradiance. This input can also just be a text definition
of a sky's parameters. Examples include:cie 21 Mar 9:00 -lat 41.78 -lon -87.75 -tz 5 -type 0climate-based 21 Jun 12:00 -lat 41.78 -lon -87.75 -tz 5 -dni 800 -dhi 120irradiance 0
Package: pollination-point-in-time-view
point_in_time_viewPoint-in-time view-based recipe for Pollination.Use this recipe to get a High Dynamic Range (HDR) view of illuminance, irradiance,
luminance or radiance for a single point in time, given a HBJSON model.Theview-countinput can be used to split each view for parallel processing, producing
multiple images that are recombined into a single .HDR for the view at the end of the
recipe. The recombination process automatically includes an anti-aliasing pass that
smooths and improves the quality of the image.By default, the recipe will also perform an overture calculation prior to splitting
each view, which results in an image with better interpolation between neighboring pixels.
However, for parallelized simulations with a highview-count, this overture calculation
can account for a significant fraction of the run time. Accordingly theskip-overtureinput can be used to skip the overture calculation in these circumstances.
Package: pollination-radiation
RadiationRadiation recipe for PollinationThis recipe calculates average irradiance (W/m2) and cumulative radiation (kWh/m2)
over the time period of a specified Wea.LimitationsThis recipe uses Radiance'sgendaymtxto generate the sky instead of directly
tracing the line of sight from sensors to the solar position.Gendaymtx takes a weather tape as input and produces a matrix of sky patch valuesusing the Perez all weather model. If there is a sun in the description, gendaymtxwill include its contribution in the four nearest sky patches, distributing energyaccording to centroid proximity.This means that the direct sun is diffused between several sky patches and so the
precise line between shadow and sun for each hour is blurred. This approximation
is fine for studies where the timestep-by-timestep irradiance values do not need
to be exact. For accurate modeling of direct irradiance on a timestep-by-timestep
basis, see theIrradiancerecipe.
Package: pollination-radiation.express
Radiation ExpressRadiation Express recipe for PollinationThis recipe calculates average irradiance (W/m2) or cumulative radiation (kWh/m2)
over the time period of a specified Wea.LimitationsThis recipe uses the ladybug-radianceRadiationStudy.Such studies of incident radiation can be used to approximate the energy that canbe collected from photovoltaic or solar thermal systems. They are also usefulfor evaluating the impact of a building's orientation on both energy use and thesize/cost of cooling systems. For studies of photovoltaic potential or buildingenergy use impact, a sky matrix from EPW radiation should be used. For studiesof cooling system size/cost, a sky matrix derived from the STAT file's clear skyradiation should be used.Note that no reflections of solar energy are included in the analysis performed bythis class. Ground reflected irradiance is crudely accounted for by means of anemissive "ground hemisphere," which is like the sky dome hemisphere and is derivedfrom the ground reflectance that is associated with the connected sky_matrix. Thismeans that including geometry that represents the ground surface will effectivelyblock such crude ground reflection.
Package: pollination-radiation.viz
RadiationRadiation recipe for PollinationThis recipe calculates average irradiance (W/m2) and cumulative radiation (kWh/m2)
over the time period of a specified Wea.LimitationsThis recipe uses Radiance'sgendaymtxto generate the sky instead of directly
tracing the line of sight from sensors to the solar position.Gendaymtx takes a weather tape as input and produces a matrix of sky patch valuesusing the Perez all weather model. If there is a sun in the description, gendaymtxwill include its contribution in the four nearest sky patches, distributing energyaccording to centroid proximity.This means that the direct sun is diffused between several sky patches and so the
precise line between shadow and sun for each hour is blurred. This approximation
is fine for studies where the timestep-by-timestep irradiance values do not need
to be exact. For accurate modeling of direct irradiance on a timestep-by-timestep
basis, see theIrradiancerecipe.
Package: pollinations
🌸pollinations.aiPollinations are an effort to make generative art more approachable.A frontend hosting a set ofcurated notebooksthat allow creating and experimenting with generative art.The Interplanetary Filesystem (IPFS) for decentralized censorship-resistant storage of models, code and generated contentPollinations are run on Google Colab at the moment (for the free cloud GPUs)Instructionson using Pollinations.AI.🐍 Python Package# Usage Exampleimportpollinationsasaimodel:object=ai.Model()image:object=model.generate(prompt=f'Golden retriever puppy playing in the rain{ai.realistic}',model=ai.turbo,height=512,seed=57184)image.save('image-output.jpg')print(image.url)// >>> https://image.pollinations.ai/prompt/Golden%20retriever%20puppy%20playing%20in%20the%20rain%20realistic,%20realism,%20real%20life,%20ultra%20realistic,%20high%20quality,%20real?model=turbo&width=1024&height=512&seed=57184�👩‍💻 Development (outdated)Development of Pollinations.AI Web App`make dev` to start the development server of web app.% 

Enable logging:
`localStorage.debug = "*"`

If logs don't appear in Chrome enable logging "All Aevels" (including Verbose)


## Optionally it is possible to develop with a local IPFS node

Enable connect to local IPFS:
`localStorage.localIFS = true

`make up` to start the releant services. See next section for detailsDevelopment of NotebooksAll notebooks atpollinations/hiveare automatically deployed to Pollinations.We will add an easy way to include custom notebooks. For now, to use an external notebook it needs to be uploaded to IPFS wrapped in a folder in the forminput/notebook.ipynb. The resulting IPFS hash can be used directly like so:https://pollinations.ai/p/[hash]Development with Local IPFS nodeDevelopment environment requires `docker` & `docker-compose` for running a loca IPFS node. For docker installation, please navigate to https://docs.docker.com/get-docker/.

After docker is setup, `make` is used for managing the IPFS and development environment.

## 🟡 Initialization

To run pollinations development environment first time,

- Run `make init`, this will initialize start the IPFS docker image and fill `tmp/ipfs` folder by migrating IPFS.

## 🟢 Running

After IPFS migrated, to start development environment,
- Run `make up`, this will start the dockerized IPFS instance and detach.
- Run `make dev` to start the react application living under `/app`

## 🔴 Stopping

- Run `make down` to stop running IPFS instance.
- Run `make clean` to remove the `tmp` folder and its contents.

## ⚙️ Configuration

IPFS configuration can be found and updated in `docker/ipfs/config.json`. Every time the docker containers are started, the config file under `tmp/ipfs/config` is overwritten with this json file.Architecture DiagramThe following diagram has an editable copy embedded. Usehttps://draw.io/#Hpollinations/pollinations/master/pollinations_architecture.pngto edit the file.Export the results as PNG with "Include a copy of my diagram" option selected and replace the current diagram.🔗 LinksFrontend:https://pollinations.ai/Instructions:docs/instructions.mdDiscord:https://discord.gg/azGuNpvPu8
Package: pollinations.ai
🌸pollinations.aiPollinations are an effort to make generative art more approachable.A frontend hosting a set ofcurated notebooksthat allow creating and experimenting with generative art.The Interplanetary Filesystem (IPFS) for decentralized censorship-resistant storage of models, code and generated contentPollinations are run on Google Colab at the moment (for the free cloud GPUs)Instructionson using Pollinations.AI.🐍 Python Package# Usage Exampleimportpollinationsasaimodel:object=ai.Model()image:object=model.generate(prompt=f'Golden retriever puppy playing in the rain{ai.realistic}',model=ai.turbo,height=512,seed=57184)image.save('image-output.jpg')print(image.url)// >>> https://image.pollinations.ai/prompt/Golden%20retriever%20puppy%20playing%20in%20the%20rain%20realistic,%20realism,%20real%20life,%20ultra%20realistic,%20high%20quality,%20real?model=turbo&width=1024&height=512&seed=57184�👩‍💻 Development (outdated)Development of Pollinations.AI Web App`make dev` to start the development server of web app.% 

Enable logging:
`localStorage.debug = "*"`

If logs don't appear in Chrome enable logging "All Aevels" (including Verbose)


## Optionally it is possible to develop with a local IPFS node

Enable connect to local IPFS:
`localStorage.localIFS = true

`make up` to start the releant services. See next section for detailsDevelopment of NotebooksAll notebooks atpollinations/hiveare automatically deployed to Pollinations.We will add an easy way to include custom notebooks. For now, to use an external notebook it needs to be uploaded to IPFS wrapped in a folder in the forminput/notebook.ipynb. The resulting IPFS hash can be used directly like so:https://pollinations.ai/p/[hash]Development with Local IPFS nodeDevelopment environment requires `docker` & `docker-compose` for running a loca IPFS node. For docker installation, please navigate to https://docs.docker.com/get-docker/.

After docker is setup, `make` is used for managing the IPFS and development environment.

## 🟡 Initialization

To run pollinations development environment first time,

- Run `make init`, this will initialize start the IPFS docker image and fill `tmp/ipfs` folder by migrating IPFS.

## 🟢 Running

After IPFS migrated, to start development environment,
- Run `make up`, this will start the dockerized IPFS instance and detach.
- Run `make dev` to start the react application living under `/app`

## 🔴 Stopping

- Run `make down` to stop running IPFS instance.
- Run `make clean` to remove the `tmp` folder and its contents.

## ⚙️ Configuration

IPFS configuration can be found and updated in `docker/ipfs/config.json`. Every time the docker containers are started, the config file under `tmp/ipfs/config` is overwritten with this json file.Architecture DiagramThe following diagram has an editable copy embedded. Usehttps://draw.io/#Hpollinations/pollinations/master/pollinations_architecture.pngto edit the file.Export the results as PNG with "Include a copy of my diagram" option selected and replace the current diagram.🔗 LinksFrontend:https://pollinations.ai/Instructions:docs/instructions.mdDiscord:https://discord.gg/azGuNpvPu8
Package: pollination-sandbox-solar-irradiance
Incident IrradianceA recipe to assess average solar irradiance beneath Sandbox Solar agrivoltaic panels.MethodsThis recipe calculates the total amount of irradiance by calculating the direct solar
irradiance from sun disks and adding them to the contribution from indirect sky irradiance.incident_irradiance = direct_sun_irradiance + indirect_sky_irradianceThe recipe is structured in a manner that ambient bounces are NOT included.
Package: pollination-sky-irradiance
Annual Sky RadiationAnnual Sky Radiation recipe for PollinationThis recipe calculate the annual sky radiation for each timestep provided in the wea
file. Nigh-time hours are filtered before running the simulation. To match the results
for each hours see the list of hours in sun-up-hours.txt.LimitationsThis recipe uses Radiance'sgendaymtxto generate the sky. "Gendaymtx takes a weather
tape as input and produces a matrix of sky patch values using the Perez all weather
model". "If there is a sun in the description, gendaymtx will include its contribution
in the four nearest sky patches, distributing energy according to centroid proximity".
This means that the value of direct sun is diffused between these patches. This
approximation is fine for studies such as cumulative radiation or for outdoor studies
where the amount of exact direct radiation is not critical. For accurate direct radiation
seeannual_radiationrecipe.
Package: pollination-sky-view
sky-viewRecipe for computing Sky View (aka. Sky Component).Sky View is defined as the percent of the sky dome seen by a surface. This can
be computed either using a uniform (default) sky or a cloudy sky. Note that sky
view's definition means that sky regions directly in front of the surface carry
more weight than those at the sides.Note that computing cloudy Sky View for a vertically-oriented geometry (horizontal
sensor direction) will yield Vertical Sky Component (VSC) as described by the UK
Building Research Establishment (BRE). VSC is defined as the ratio of cloudy sky
illuminance falling on a vertical wall to the simultaneous horizontal illuminance
under an unobstructed sky [Littlefair, 1991].Also note that this recipe still respects the transparency of objects, reducing
the percentage of the sky visible through a certain geometry by the transmittance
of that geometry.
Package: pollination-streamlit
Pollination StreamlitAPollinationextension to facilitate working with
Pollination inStreamlitapps.Many thanks to the Streamlit team for developingStreamlit app framework! :balloon: :balloon: :balloon:You can build custom apps for environmental building simulation by bringing the power of
Pollination and Ladybug Tools to Streamlit apps!Getting StartedSeethis repositoryfor several sample
pollination sample apps.If you are new Streamlit see Streamlitget started documentation.Installationpython -m pip install -U pollination-streamlitLocal DevelopmentClone this repo locallygit clone git@github.com:ladybug-tools/pollination-streamlit#orgit clone https://github.com/ladybug-tools/pollination-streamlitInstall dependencies:cd pollination-streamlitpip install -r dev-requirements.txtpip install -r requirements.txtRun Tests:python -m pytest tests/
Package: pollination-utci-comfort-map
UTCI Comfort MapUTCI thermal comfort map recipe for Pollination.Compute spatially-resolved Universal Thermal Climate Index (UTCI) and heat/cold stress
conditions an EPW and Honeybee model. Raw results are written into aresults/folder and
include CSV matrices of hourly UTCI temperatures, thermal conditions and heat stress
classifications. Processed metrics of Thermal Comfort Percent (TCP) can be found
in themetrics/folder.MethodsThis recipe uses EnergyPlus to obtain longwave radiant temperatures and indoor air
temperatures. The outdoor air temperature and air speed are taken directly from the EPW.
A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations,
which includes an accurate direct sun calculation using precise solar positions. The
energy properties of the model geometry are what determine the outcome of the
simulation and the model's SensorGrids are what determine where the comfort
mapping occurs.To determine Thermal Comfort Percent (TCP), all hours of the outdoors are considered
occupied. For any indoor sensor, the occupancy schedules of the energy model are used.
Any hour of the occupancy schedule that is 0.1 or greater will be considered occupied.
Package: polling2
polling2Never write another polling function again!Documentation available atRead the DocsYou can install the package fromPypiPolling2 is a powerful python utility used to wait for a function to return a certain expected condition.Some possible uses cases include:Wait for API response to return with code 200Wait for a file to exist (or not exist)Wait for a thread lock on a resource to expirePolling2 is handy for getting rid of all that duplicated polling-code. Often, applications require retrying until the correct response is returned. Why re-implement the ability to poll again and again? Use Polling2!Polling2 is a fork of the originalpolling. It was forked when the original maintainer failed to respond to issues or PRs.Polling2 isunder active development. Would you like to see a particular feature? Ask and thou shall recieve.Installationpip install polling2Development installation# install lib, but use system links from the repo into sitepackages.pythonsetup.pydevelop# install test dependenices.pythonsetup.pytest# run the testspytesttestsExample:# This call will wait until the file exists, checking every 0.1 seconds and stopping after 3 seconds have elapsedfile_handle=polling2.poll(lambda:open('/tmp/myfile.txt'),ignore_exceptions=(IOError,),timeout=3,step=0.1)# Polling will return the value of your polling function, so you can now interact with itfile_handle.close()There aremore examplesin the documentation.API and user guide atRead the Docs
Package: polls-epsilon-deltta
Polls is a Django app to conduct Web-based polls. For each question,
visitors can choose between a fixed number of answers.Detailed documentation is in the “docs” directory.Quick startAdd “polls” to your INSTALLED_APPS setting like this:INSTALLED_APPS = [
    ...
    'polls',
]Include the polls URLconf in your project urls.py like this:path('polls/', include('polls.urls')),Runpython manage.py migrateto create the polls models.Start the development server and visithttp://127.0.0.1:8000/admin/to create a poll (you’ll need the Admin app enabled).Visithttp://127.0.0.1:8000/polls/to participate in the poll.
Package: pollstats
=====
pollstatsPollstats is a Django app which display the entire number of Voters, calculates the percentage of voters who took part in the
online poll. This library is exclusively designed for a college project and may not have all the dynamic features.Quick startAdd "pollstats.apps.PollstatsConfig" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [
...
'pollstats.apps.PollstatsConfig',
]Include the polls URLconf in your project urls.py like this::
path('pollstats/',include("pollstats.urls")),This library uses Django's default User Object and the data in it is accessed by using from django.contrib.auth.models import UserThis library strictly uses the following models to calculate the data:class Events(models.Model):
event_name = models.CharField(max_length=200)
event_code = models.CharField(max_length=20)
referal_code = models.CharField(max_length=20)
hosted_by = models.ForeignKey(User, default=1, on_delete=models.CASCADE)
event_description = models.TextField()
event_status = models.IntegerField(default=0)
starting_date = models.DateField(default=None)
ending_date = models.DateField(default=None)class Options(models.Model):
option_name = models.CharField(max_length=100)
count = models.IntegerField(default=0)
event_code = models.CharField(max_length=200)class Transactions(models.Model):
voter = models.ForeignKey(User, default=1, on_delete=models.CASCADE)
voting_time = models.DateTimeField(auto_now_add=True)
option_name = models.CharField(max_length=150)
event_name = models.CharField(max_length=150)event_code = models.CharField(max_length=70)
referal_code = models.CharField(max_length=70)Django admin can be used to insert the data in to Events table and also to insert initial data in to Options table with
count as 0Then the count should be updated when a user votes/unvotes, the data in Transactions table must be inserted and deleted
during the vote/unvote process
Package: pollute
A decorator and context manager for temporarily modifyingos.environ.# as a context managerwithmodified_environ(added={...},absent=[...]):...# as a decorator@modified_environ(added={...},absent=[...])Installation:$pipinstallpollutemodified_environmodifiesos.environin-place, ensuring that all
references to it in the code are updated. All changes made bymodified_environare reversed when exiting the context or decorator.Exampleimportosfrompolluteimportmodified_environassert'HELLO'notinos.environassert'PATH'inos.environwithmodified_environ(added={'HELLO':'WORLD'},absent=['PATH']):assertos.environ['HELLO']=='WORLD'assert'PATH'notinos.environassert'HELLO'notinos.environassert'PATH'inos.environ