Saravanan666/pypi-org huggingface dataset:
Package: eve-optimizer
EVE: The EVer Evolving Deep Learning OptimizerEVE is a new optimizer library built on top of PyTorch that combines the best of multiple state-of-the-art optimizer algorithms into one flexible, infinitely customizable super-optimizer.The goal of EVE is not to provide one final, static optimizer, but rather an interface to a PyTorch optimizer that will continue to implement the latest, well-tested methods from modern research.In preliminary testing, the current implementation of EVE was able to beat Adam and other near state-of-the-art optimizers without a significant increase in compute time. Here are some inital results from training a ResNet18 on the ImageNette (subset of ImageNet that encompasses a few hard to classify classes) 5 epoch challenge.Adam (Final Accuracy = 40.00%)epochtrain_lossvalid_lossaccuracytime02.4795579.5228480.12993600:3312.2232022.0419430.43312100:3322.5293002.3001900.21299400:3432.0182341.8665970.34726100:3541.7809241.7322650.40000000:35EVE (Final Accuracy = 70.62%)epochtrain_lossvalid_lossaccuracytime02.3968122.6173680.33528700:3912.1704821.6265440.47872600:3921.5260031.6721560.50114600:3930.9561250.9496520.69630600:3940.5675830.9493950.70624200:39Here are a few animations demonstrating EVE's convergence properties on simple functions:2D Convex Surface2D Non-Convex Surface3D Surface with Saddle PointInstallation and Getting StartedThe simplest way to use EVE in your PyTorch models is to install it using pip:pip install eve-optimizerThen, the main EVE optimizer can be imported as follows:from eve.optimizers import eveo3This will import a function that returns atorch.optim.Optimizerobject, which can be used in the usual way.The EVE library also provides a direct interface to other optimizers (like Ranger, RAdam, etc.) that were used in part or were built upon to create the main EVE optimizer. These can also be accessed fromeve.optimizersin the same way.What Exactly is EVE?At present, EVE implements (and combines) the following algorithms:AdamRAdamLARSLAMBLookAheadDiffGradWe are currently working on adding in the following variants as well:AdaModDeepMemoryMarina
Package: eve-panel
Dynamically create an httpx based client for any Eve api. Uses Param + Cerberus for type enforcement and Panel for GUIs.
This is just a prototype package,features will slowly be added as i need them for my own purposes.
The api is expected to change without warning based on my needs but feel free to fork or copy parts and adapt to your own needs.To view the widgets in a notebook you will need to install the pyviz plugin. For details, see panel docs.Usageimportevefromeve_panelimportEveClientapp=eve.Eve()api=eve_panel.EveClient.from_app(app)# optionalapi.set_token("my-secret-token")# show a resources guiapi.resource_name# get a specific itemapi.resource_name["item_id"]# get current pageapi.resource_name.current_page()# get next pageapi.resource_name.next_page()# get previous pageapi.resource_name.previous_page()# insert new documentsdocs=[{"name":"new document"}]api.resource_name.insert_documents(docs)Free software: MITDocumentation:https://eve-panel.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template.
Package: eveparse
Eve ParseParser for Eve Online - extract item name and quantity from a string, and return values with type_idInstallpipinstalleveparseUsageTheparse()function takes a single-line string. It is designed to fail fast and will raise ParserError if it is unable to parse the string.importeveparsestring="Ragnarok 1"try:type_id,name,quantity=eveparse.parse(string)excepteveparse.ParserErroraserror:print(error)else:print(type_id,name,quantity)
Package: eveparser
Eve PasteA Python library to help parse various things that are copy/pastable from the Eve Online UI.This is currently awork in progress. Interfaces can and will change from version to version.LicensePermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.CCP Copyright NoticeEVE Online and the EVE logo are the registered trademarks of CCP hf. All rights are reserved worldwide. All other trademarks are the property of their respective owners. EVE Online, the EVE logo, EVE and all associated logos and designs are the intellectual property of CCP hf. All artwork, screenshots, characters, vehicles, storylines, world facts or other recognizable features of the intellectual property relating to these trademarks are likewise the intellectual property of CCP hf. CCP hf. has granted permission to eveparser to use EVE Online and all associated logos and designs for promotional and information purposes on its website but does not endorse, and is not in any way affiliated with, eveparser. CCP is in no way responsible for the content on or functioning of this website, nor can it be liable for any damage arising from the use of this website.
Package: evepaste
Eve PasteA Python library to help parse various things that are copy/pastable from the Eve Online UI.This is currently awork in progress. Interfaces can and will change from version to version.LicensePermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.CCP Copyright NoticeEVE Online and the EVE logo are the registered trademarks of CCP hf. All rights are reserved worldwide. All other trademarks are the property of their respective owners. EVE Online, the EVE logo, EVE and all associated logos and designs are the intellectual property of CCP hf. All artwork, screenshots, characters, vehicles, storylines, world facts or other recognizable features of the intellectual property relating to these trademarks are likewise the intellectual property of CCP hf. CCP hf. has granted permission to evepaste to use EVE Online and all associated logos and designs for promotional and information purposes on its website but does not endorse, and is not in any way affiliated with, evepaste. CCP is in no way responsible for the content on or functioning of this website, nor can it be liable for any damage arising from the use of this website.
Package: eve-peewee
|Build Status|A WIP data layer forEveusingpeeweeCurrently peewee creates tables based on settings.py DOMAIN declarations
during start-up and basic Eve CRUD methods work.Instuctionspython setup.py installorpip installeve-peeweedefine DATABASE_URI in settings.py (see examples)Eve(data=EvePeewee).run()Testedpostgres 9.x, sqlite3python 2.7, 3.5basic eve functionality (filtering, sorting, pagination, timestamps,
etag/if-match, soft delete)1:m data relationshipsUntested/TBDmysqlcustom validatorconstraints (unique)m:m data relationships (atm creates link tables but likely fails to
query for embedding)versioning fieldsNotable caveatspeewee doesn’t do auto-migration (if you change domain models, drop
the tables to get them recreated or apply changes in db manually)peewee specific field properties can be defined in DOMAIN schema
(requires “transparent_schema_rules”), e.g.'_peewee': { 'primary_key': True }not all possible error cases are captured to json/xml document,
default 500 response may happenobjectid and media types are unsupported (list and dict types are
saved as jsonb)many of the mongo centric field properties of eve (anyof, allof etc)
are silently ignored
Package: ever2text
ever2textConvert Evernote exports to plain text files.The goal is to export Evernote notes to raw text files for use with any
text editor, such asAtomorSublime Text.GitHub for ever2text:https://github.com/nicholaskuechler/ever2textIf you are looking to export Evernote notes for use with SimpleNote, have a
look atever2simple.InstallationInstall usingpip(preferably in a virtualenv):$ pip install -U ever2textDevelopment InstallationClone this repository withgit:$ git clone https://github.com/nicholaskuechler/ever2text.git
$ cd ever2text
$ python setup.py installUsageFirst you will need to export your notes from inside of the Evernote
application. For each notebook, right click the notebook name and select the
“Export Notes” option. Make sure to select theenexformat.IMPORTANT: You need to export each notebook individually. I could not find an
option to export all notebooks in to a single Evernote export file. Make sure
to give each exported notebook a unique name. I used the notebook name as the
basis for the exported enex dump file.Once you have created an export file, you can run the script on the file
setting the--outputto a directory:$ ever2text my_notebook.enex --output output_directory --format textYou can export notes to either plain text or markdown format. The default is
plain text. For markdown formatted notes, use--formatmarkdown.$ ever2text my_notebook.enex --output output_directory --format markdownNotes and CaveatsEach Evernote notebook needs to be exported individually. It does not appear
you can export all notebooks in to a single export file.Notes are created with a number suffix to avoid collisions when multiple
notes have the same title.If a title cannot be sanitized, the note will have a default title oftitle_fail-NUMBER.txtConverting notes to text will not preserve tags in the notes.This does not handle any attachments.CreditsBased on ever2simple by Clayton Parker:https://github.com/claytron/ever2simpleChanges0.3 (2016-07-29)Include future package0.2 (2016-07-29)PyPI package release0.1 (2016-07-29)Initial release
Package: everbug
The Everbug is a lightweight Django middleware for Chrome extension with easy install. One of the advantages: the response body of target page remains clean
and unchanged.Special summary:
* Database queries with explains (Multiple database support)
* Context variables
* Profiles functions (cProfile through decorator)
* Support ajax requestsInstallingFor Django:Run "pip install everbug".
Add "everbug" to your INSTALLED_APPS in settings.py.
Append "everbug.middleware.Tracer" to MIDDLEWARE or MIDDLEWARE_CLASSES in settings.py.For Chrome: _chrome_ext_
For Firefox: _firefox_ext_Usage“Context” works for any view which has a “context_data”. “Queries” works
as-is for all databases in “DATABASES” section. “Profile” works through
decorator (based on builtin cProfile). By default, profile output is
truncated to 20 lines.Example usage:from everbug.shortcuts import profile

@profile
def sample_method():
    // some code here ...Call @profile with argument for full view, for example:@profile(short=False)
def sample_method():
    // some code here ...Running the testsdocker-compose  up -d
docker exec -it everbug toxRequirementsPython >= 3.5Django >= 1.11LicenseThis project is licensed under the MIT License - see theLICENSEfile
for details
Package: eve_resource
EveResourceResource utilities for EveFree software: MIT licenseDocumentation:https://eve-resource.readthedocs.io.FeaturesResource level utilities for Eve api’sCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0First release on PyPI.0.1.5Resource keys is now a kwarg on instantiation
Package: everest
everestis an extension of the popularPyramidframework aimed at simplifying the
development of REST applications inPython.everestfeatures in a nutshell:A resource declaration framework that allows you to expose an entity domain
model through a REST application;Extensible views for performing standard CRUD operations on resources in
response to REST requests;Representers that convert resources to string representations and vice versa
for a number of MIME types (XML, ATOM, CSV, JSON);A repository layer permitting per-resource configuration of the storage
backend to use (memory for testing, file system for small data volumes,
relational database for large data volumes);A query language for expressing complex hierarchical queries on the resource
object tree through URLs;A Flex client
(distributed separately);InstallationInstallingeverestis simple. You needA recent version of Python (2.7.x). Seeherefor instructions;The pip Python package installer. Install in a shell with the command> easy_install pipWith these requirements in place, all you need to do to installeverestis
to issue the command> pip install everestDocumentationAPI documentationAdemo application.Developmenteverestis hosted ongithub. To
contribute, please fork the project and submit a pull request. Please adhere to
PEP8 in your code and ensure 100% test coverage. We recommend configuring
pylint with the configuration file supplied in thesupportdirectory.
Package: everest-pipeline
EPIC Variability Extraction and Removal for Exoplanet Science Targets:
A pipeline for de-trendingK2,Kepler, andTESSlight curves with
pixel level decorrelation and Gaussian processes. The Python interface
allows easy access to the online EVEREST de-trended light curve catalog;
alternatively, users can de-trend their own light curves with customized
settings. Read the documentation athttps://github.com/rodluger/everest
Package: evergreen
OverviewEvergreen is a cooperative multitasking and i/o library for Python. It provides equivalent primitives to
those for thread programming, but uses a cooperative model instead.Operations are driven by an event loop which will run the given tasks and i/o operations in a non-blocking
manner while presenting the user a synchronous, blocking API.Features:Cooperative multitaskingCooperative synchronization primitives: locks, events, queues, channelsFutures API (almost) compatible with the standard libraryCooperative versions of several standard library modulesAbility to monkey patch standard library modules to make them
cooperativeRunning the test suiteThere are several ways of running the test suite:Running individual tests:Go inside the tests/ directory and run each individual testRun the test with the current Python interpreter:From the toplevel directory, run:nosetests-v-wtests/Use Tox to run the test suite in several virtualenvs with several interpretersFrom the toplevel directory, run:tox-epy26,py27,py32, py33this will run the test suite
on Python 2.6, 2.7, 3.2 and 3.3 (you’ll need to have them installed beforehand)CI statusDocumentationhttp://readthedocs.org/docs/evergreen/AuthorSaúl Ibarra Corretgé <saghul@gmail.com>Code written by other authors has been adapted for use with Evergreen, check
the NOTICE file.LicenseUnless stated otherwise on-file Evergreen uses the MIT license, check LICENSE and NOTICE files.ContributingIf you’d like to contribute, fork the project, make a patch and send a pull
request. Have a look at the surrounding code and please, make yours look
alike :-) If you intend to contribute a new feature please contact the maintainer
beforehand in order to discuss the design.
Package: evergy
⚡Evergy ClientA simple utility that you can use to login to your Evergy account and retrieve you meter readings.DocumentationSource CodeNote: This is an unofficial utility that uses Evergy's non-public API.Previously known as "KCPL"Installpip install evergyUsagefromevergy.evergyimportEvergyevergy=Evergy("<evergy-username>","<evergy-password>")data=evergy.get_usage()print("Today's kWh: "+str(data[-1]["usage"]))OutputThe last element from theget_usage()will be the latest data. Theusageis in kilowatt-hours. I believe thepeakDateTimeis thetime during that day when your usage was the highest and thepeakDemandis how many kilowatts you were drawing at that time.Latest data:

{

    'period': 'Saturday',

    'billStart': '0001-01-01T00:00:00',

    'billEnd': '0001-01-01T00:00:00',

    'billDate': '2021-09-18T00:00:00',

    'date': '9/18/2021',

    'usage': 14.7756,

    'demand': 3.7992,

    'avgDemand': 0.0,

    'peakDemand': 3.7992,

    'peakDateTime': '12:45 p.m.',

    'maxTemp': 71.0,

    'minTemp': 71.0,

    'avgTemp': 71.0,

    'cost': 18.5748, 

    'isPartial': False

}Related ProjectsKC Water: A similar project developed byPatrick McDonagh. Check it out!DevelopmentSetuppython-mpipinstall--upgradevirtualenvvirtualenvvenv.\venv\Scripts\activate.ps1Code FormattingInstall the dev dependencies and runisortandflake8to properly format the code.pipinstall-rrequirements_dev.txt

isortevergy/

flake8evergy/Build DocsWindows PowerShell:pipinstall-rdocs/requirements_docs.txtdocs\make.batclean;docs\make.bathtmlRelease New VersionBump__version__inevergy/__init__.pygitcommit-m"Bump version"gittag-av1.0.1-m"v1.0.1"gitpush--tagsBuild WheelThe--no-isolationflag tells it to use the existing virtual envpython-mbuild--no-isolation--wheelUpload to PyPiTesttwineupload--verbose--repositorytestpypidist/*Prodtwineupload--verbose--repositorypypidist/*
Package: everinfer
Everinfer ClientEverinfer client to run scalable distributed ML inference with low latency.Free software: MIT licenseDocumentation:https://everinfer.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.1 (2022-11-26)First release on PyPI.
Package: evermore
evermoreDifferentiable (binned) likelihoods in JAX.Installationpython-mpipinstallevermoreFrom source:gitclonehttps://github.com/pfackeldey/evermorecdevermore
python-mpipinstall.Usage - Model definition and fittingSee more inexamples/evermorein a nutshell:importequinoxaseqximportjaximportjax.numpyasjnpimportevermoreasevmjax.config.update("jax_enable_x64",True)# define a simple model with two processes and two parametersclassMyModel(evm.Model):def__call__(self,processes:dict,parameters:dict)->evm.Result:res=evm.Result()# signalmu_mod=evm.modifier(name="mu",parameter=parameters["mu"],effect=evm.effect.unconstrained())res.add(process="signal",expectation=mu_mod(processes["signal"]))# backgroundbkg_mod=evm.modifier(name="sigma",parameter=parameters["sigma"],effect=evm.effect.gauss(0.2))res.add(process="background",expectation=bkg_mod(processes["background"]))returnres# setup modelprocesses={"signal":jnp.array([10.0]),"background":jnp.array([50.0])}parameters={"mu":evm.Parameter(value=jnp.array([1.0]),bounds=(0.0,jnp.inf)),"sigma":evm.Parameter(value=jnp.array([0.0])),}model=MyModel(processes=processes,parameters=parameters)# define negative log-likelihood with data (observation)nll=evm.likelihood.NLL(model=model,observation=jnp.array([64.0]))# jit it!fast_nll=eqx.filter_jit(nll)# setup fit: initial values of parameters and a suitable optimizerinit_values=model.parameter_valuesoptimizer=evm.optimizer.JaxOptimizer.make(name="ScipyMinimize",settings={"method":"trust-constr"})# fitvalues,state=optimizer.fit(fun=fast_nll,init_values=init_values)print(values)# -> {'mu': Array([1.4], dtype=float64),#     'sigma': Array([4.04723836e-14], dtype=float64)}# eval model with fitted valuesprint(model.update(values=values).evaluate().expectation())# -> Array([64.], dtype=float64)# gradients of "prefit" model:print(eqx.filter_grad(nll)({"sigma":jnp.array([0.2])}))# -> {'sigma': Array([-0.12258065], dtype=float64)}# gradients of "postfit" model:@eqx.filter_grad@eqx.filter_jitdefgrad_postfit_nll(where:dict[str,jax.Array])->dict[str,jax.Array]:nll=evm.likelihood.NLL(model=model.update(values=values),observation=jnp.array([64.0]))returnnll(where)print(grad_postfit_nll({"sigma":jnp.array([0.2])}))# -> {'sigma': Array([0.5030303], dtype=float64)}ContributingSeeCONTRIBUTING.mdfor instructions on how to contribute.LicenseDistributed under the terms of theBSD license.
Package: evernode
EverNode
===
[![Build Status](https://travis-ci.org/AtomHash/evernode.svg?branch=dev-1.0.0)](https://travis-ci.org/AtomHash/evernode) [![Pypi Package](https://badge.fury.io/py/evernode.svg)](https://pypi.org/project/evernode) [![Docs](https://readthedocs.org/projects/evernode/badge/)](http://evernode.readthedocs.io/en/latest/)EverNode for fast beautiful APIs
—
EverNode adds enhanced features to [Flask](https://github.com/pallets/flask) out of the box for rapid API development. Support for [Flask-SQLAlchemy](https://github.com/mitsuhiko/flask-sqlalchemy) model serialization, internationalization, easy to handle form data, JWT Bearer Authorization, authorized emails and more. Our primary focus for EverNode is modular based API development and to remain as light weight and fast as possible.Fair Warning
—
EverNode is currently developed in my spare time and used in my personal applications used in a production environment.
So any features that I deem useful get added to EverNode without much notice, while also trying to keep bulk down.
This warning is to warn people that I do not plan on having stable release timeframes until EverNode v2.
At that time a new release schedule will be created, along with much, much better unit tests. ThanksGet it now
—$ pip install evernodeProject Links
—
- Travis [https://travis-ci.org/AtomHash/evernode](https://travis-ci.org/AtomHash/evernode)
- PyPI: [https://pypi.python.org/pypi/evernode](https://pypi.python.org/pypi/evernode)
- Issues: [https://github.com/AtomHash/evernode/issues](https://github.com/AtomHash/evernode/issues)Getting Started
—
- Docs: [http://evernode.readthedocs.io/en/latest/](http://evernode.readthedocs.io/en/latest/)License
—
MIT licensed. See the bundled [LICENSE](https://github.com/AtomHash/evernode/blob/master/LICENSE) file for more details.