Saravanan666/pypi-org huggingface dataset:
Package: duskcrawler
duskCrawlerduskCrawler is a Python program that crawls throught set horoscope url:https://www.astrology.com/horoscope/daily.html.InstallationUse the package manager [pip] or [poetry] to add this program to your enviromentpipinstallduskCrawler
poetryaddduskCrawlerRequirementsThis module requires the following packages:
lxml, pandas, pytest, requestsUsageprocess_page("https://www.astrology.com/horoscope/daily.html")After succesful program run, user gets prompted if they want the data saved to their computer.
If data is needed to be saved to users computer, program saves the data as a .csv fileContributingPull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.Example dataStart page:https://www.astrology.com/horoscope/daily.htmlArticle link:https://www.astrology.com/horoscope/daily/aries.htmlDecember 20, 2023An instinctive and impulsive energy flows through you this morning,
dear Aries, as the moon continues its journey through your sign.
Unfortunately, you may have trouble getting past stubborn behaviors as
Venus and Uranus face off, making it important that you don't get your
own way by clinging to tradition. A destructive element also comes
into play, and you'll want to avoid reacting hastily when confronted
with chaos or plot twists. Take a moment to acknowledge your basic
needs this evening when Chiron activates, offering healing and calm.
Inspiration strikes as the day comes to a close, and passionate Mars
triggers your solar ninth house.Daily Food HoroscopeYou'll feel uncharacteristically introverted today. Could a broken
heart be behind your blue mood? Doing something nice for yourself
could brighten your spirit. Soothe your soul with a thick piece of
cheesecake, a cup of mocha java and an upbeat movie.Daily Home HoroscopeBuying your elderly father a computer is not a complete gift unless
you or someone else is willing to spend a few hours showing him the
basics. Patience is the key if you are doing it yourself.Daily Dog HoroscopeDon't forget the surefire way to avoid a dogfight: make sure your bark
is worse than your bite. Keep it short and sweet, like the horn of a
semi. Once you get into the details, you're in trouble.Daily Teen HoroscopeYou can charm the birds out of the trees right now -- or your camp
counselor out of putting you on kitchen duty, if that's what you need
to do. Take advantage of your winsome wiles!Daily Cat HoroscopeYou need to let your human friends know what's important to you --
even though it might get pretty complicated! The day is just right for
showing your deepest feelings, though, so get to work.Daily Bonus HoroscopeYou can be forceful and tactful. Push a little harder, and you'll get
what you want.Article link:https://www.astrology.com/horoscope/daily/taurus.htmlDecember 20, 2023
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Package: duspider
duspider自用spider 多数为医药相关网站diseasesaskbobhttps://www.jk.cn/ab-special/#/baiduhttps://jiankang.baidu.com/widescreen/entitylistdayi_orghttps://www.dayi.org.cn/aboutdxyhttps://dxy.com/diseasesjbk39https://jbk.39.net/bw/t1/xywyhttp://jib.xywy.com/html/a.htmldrugsaskbobhttps://www.jk.cn/ab-special/#/drugbankhttps://go.drugbank.com/drugs/medlivehttps://drugs.medlive.cn/drugref/drugCate.do?treeCode=H010101medscapehttps://reference.medscape.com/drugsnmpa_govhttps://www.nmpa.gov.cn/datasearch/home-index.html#category=ypjbk39https://jbk.39.net/bw/t1/xywyhttp://jib.xywy.com/html/a.htmlguidemedlivehttps://drugs.medlive.cn/drugref/drugCate.do?treeCode=H010101proteinuniprothttps://www.uniprot.org/uniprotkb/A0A1B0GTW7/entrymedlive_login 医脉通登录
Package: dustapprox
This is a set of tools to compute photometric extinction coefficients in aquick and dirtyway.full documentation at:http://mfouesneau.github.io/dustapprox/Quick Startimportpandasaspdfromdustapproximportmodelsfromdustapprox.literatureimportedr3importpylabasplt# get Gaia modelslib=models.PrecomputedModel()r=lib.find(passband='Gaia')[0]# taking the first onemodel=lib.load_model(r,passband='GAIA_GAIA3.G')# get some datadata=pd.read_csv('models/precomputed/kurucs_gaiaedr3_small_a0_grid.csv')df=data[(data['passband']=='GAIA_GAIA3.G')&(data['A0']>0)]# valueskg_pred=model.predict(df)InstallationInstallation from PyPIpip install git+https://github.com/mfouesneau/gdr3_extinctionManual installationdownload the repository and run the setupgit clone https://github.com/mfouesneau/gdr3_extinction
python setup.py installContributorsMorgan Fouesneau (@mfouesneau)René AndraeRosanna SordoThavisha DharmawardenaContributingPlease open a new issue or new pull request for bugs, feedback, or new features
you would like to see. If there is an issue you would like to work on, please
leave a comment, and we will be happy to assist. New contributions and
contributors are very welcome!
Package: dusted
DustedAn offline editor for Dustforce replays, largely based on dustkid.com's replay composer.Installationpip install dustedFor extra features, copyplugin/tas.asto~dustforce/user/script_src, compile as an in-game plugin, and enable it.On linux, the programunbufferis required, which can be installed withsudo apt-get install expect(or equivalent depending on your distribution).UsageRun the editor withpython -m dustedor, if the python scripts directory is on the PATHdusted
Package: dust_emissivity
Simple tools built on astropy’s units & constants framework for computing the
mass / column of a given chunk of dust.Compare tohttps://code.google.com/p/agpy/source/browse/trunk/agpy/blackbody.pyandhttps://code.google.com/p/agpy/source/browse/trunk/agpy/dust.py, which are
standalone and do not make use of the units framework.InstallationInstallation is through normal pip:pipinstallhttps://github.com/keflavich/dust_emissivity/archive/master.zipThen, one can import:importdust_emissivityfromdust_emissivityimportblackbody,modified_blackbody,integrate_sedDocumentationThere is anexample notebookand docstringsGithub Things
Package: duster
Package DescriptionDuster is an IPython extension that selectively clears one’s IPython session
namespace while automatically ignoring specified variables to preserve and
reloading specified packages.InstallationThe package may be installed as follows:pip install dusterAfter installation, the extension may be loaded within an IPython
session with%load_ext dusterConfigurationModules to be reloaded when duster is invoked should each be listed as a tuple
containing the module name and the name to which it should be imported (or ‘’ if
it should be imported as-is). For example:c.DusterMagic.modules = [('numpy', 'np'), ('scipy', 'sp'), ('sys', '')]Variables to be ignored when resetting the IPython namespace should be listed
by name as follows:c.DusterMagic.ignore = ['varname0', 'varname1']The above settings may be viewed and/or modified within an IPython session using%config DusterMagicNotesDuster will automatically reloadpylabif pylab mode is active.DevelopmentThe latest release of the package may be obtained fromGitHub.AuthorSee the includedAUTHORS.rstfile for more information.LicenseThis software is licensed under theBSD License.
See the includedLICENSE.rstfile for more information.
Package: dust-extinction
This package provides astronomical interstellar dust extinction curves
implemented using the astropy.modeling framework.This package is anaffiliated packageofAstroPy.To install:pip install dust_extinctionBuild checks/statusPackagingDocumentationUsingreadthedocs.In Development!This code is currently in active development.
Contributions welcome (see below).ContributorsKarl Gordon (lead)All contributorsContributingPlease open a new issue or new pull request for bugs, feedback, or new features
you would like to see.   If there is an issue you would like to work on, please
leave a comment and we will be happy to assist.   New contributions and
contributors are very welcome!New to github or open source projects?  If you are unsure about where to start
or haven’t used github before, please feel free to contact@karllark.
Want more information about how to make a contribution?  Take a look at
the astropycontributinganddeveloperdocumentation.Feedback and feature requests?   Is there something missing you would like
to see?  Please open an issue or send an email to@karllark.
dust_extinction follows theAstropy Code of Conductand strives to provide a
welcoming community to all of our users and contributors.We love contributions! dust_extinction is open source,
built on open source, and we’d love to have you hang out in our community.Impostor syndrome disclaimer: We want your help. No, really.There may be a little voice inside your head that is telling you that you’re not
ready to be an open source contributor; that your skills aren’t nearly good
enough to contribute. What could you possibly offer a project like this one?We assure you - the little voice in your head is wrong. If you can write code at
all, you can contribute code to open source. Contributing to open source
projects is a fantastic way to advance one’s coding skills. Writing perfect code
isn’t the measure of a good developer (that would disqualify all of us!); it’s
trying to create something, making mistakes, and learning from those
mistakes. That’s how we all improve, and we are happy to help others learn.Being an open source contributor doesn’t just mean writing code, either. You can
help out by writing documentation, tests, or even giving feedback about the
project (and yes - that includes giving feedback about the contribution
process). Some of these contributions may be the most valuable to the project as
a whole, because you’re coming to the project with fresh eyes, so you can see
the errors and assumptions that seasoned contributors have glossed over.This disclaimer was originally written byAdrienne Lowefor aPyCon talk, and was adapted by
dust_extinction based on its use in the README file for theMetPy project.LicenseThis project is Copyright (c) Karl Gordon and Kristen Larson and licensed under
the terms of the BSD 3-Clause license. This package is based upon
theAstropy package templatewhich is licensed under the BSD 3-clause licence. See the licenses folder for
more information.
Package: dustmaker
DustmakerDustmaker is a Python library for reading, manipulation, and writing
binary files used by Dustforce, primarily level files.DocumentationDocumentation can be found athttps://dustmaker.readthedocs.io/en/latest/.InstallationInstall with pip through PyPi usingpython -m pip install dustmakeror clone this repository and install using./setup.py installCommand Line ToolDustmaker comes with a few command line tools that can be accessed through
running the dustmaker module.$python-mdustmaker--help
...listingofavailableutilities
$python-mdustmakertransform--upscale2downhillbig_downhill
...createsupscaledversionofdownhillandsavesto"big_downhill"Example: Creating a new level from scratchfromdustmaker.levelimportLevelfromdustmaker.tileimportTile,TileShapefromdustmaker.dfwriterimportDFWriter# Create a new empty level and add some tiles.level=Level()level.name=b"my level!"level.virtual_character=Truefori,shapeinenumerate(TileShape):level.tiles[(19,2*i,i)]=Tile(shape)# Automatically figure out edge solidity and connectivity flagslevel.calculate_edge_visibility()level.calculate_edge_caps()# Write level to a filewithDFWriter(open("mylevel.dflevel","wb"))aswriter:writer.write_level(level)Example: Counting how many apples are in a levelfromdustmaker.dfreaderimportDFReaderfromdustmaker.entityimportApplewithDFReader(open("mylevel.dflevel","rb"))asreader:level=reader.read_level()apples=0forx,y,entityinlevel.entities.values():ifisinstance(entity,Apple):apples+=1print(f"Level has{apples}apples")
Package: dustpan
dustpanDescriptionClean up your workspace by removing extraneous files and directories.InstallationWithPythoninstalled, simply run the following command to add the package to your project.python-mpipinstalldustpanUsageThis is a command-line program, and can be executed as follows:dustpan[-h][-pPATTERNS[PATTERNS...]][-iIGNORE[IGNORE...]][--remove-empty-directories][-q|-v|-vv]directories[directories...]Positional arguments:directories           Root directories to searchOptional arguments:-h, --help            show this help message and exit
  -p PATTERNS [PATTERNS ...], --patterns PATTERNS [PATTERNS ...]
                        Additional path patterns to queue for removal
  -i IGNORE [IGNORE ...], --ignore IGNORE [IGNORE ...]
                        Path patterns to exclude from removal
  --remove-empty-directories
                        Remove all childless directories
  -q, --quiet           Be quiet
  -v, --verbose         Be more verbose
  -vv, --very-verbose   Be very verboseFeel free tocheck out the docsfor more information on how to use this package.LicenseThis software is released under the terms ofMIT license.
Package: dustpy
DustPyDust Coagulation and Evolution in Protoplanetary DisksDustPyis a Python package to simulate the evolution of dust in protoplanetary disks.DustPysimulates the radial evolution of gas and dust in a protoplanetary disk, involving viscous evolution the the gas disk, advection and diffusion of the dust disk, as well as dust growth by solving the Smoluchowski equation.Please read thedocumentationfor a detailed description.
By using any version ofDustPyyou agree to these terms of usage.InstallationDustPycan be installed via the Python Package Indexpip install dustpyRequirementsDustPyneeds a Python3 distribution and a Fortran compiler installed on your system.Documentationhttps://stammler.github.io/dustpy/1. Basics2. Simple Customization3. Advanced Customization4. The Standard Model5. Dust Coagulation6. Dust Evolution7. Gas EvolutionLibrary: dustpylibTest: Analytical Coagulation KernelsTest: Gas EvolutionExample: Ice LinesExample: Planetary GapsExample: Planetesimal FormationA. CitationB. List of PublicationsC. Contributing/Bugs/FeaturesD. DustPy DiscussionsE. ChangelogModule ReferenceFrameworkDustPyis using theSimframeframework for scientific simulations (Stammler & Birnstiel 2022)AcknowledgementsDustPyhas received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 714769.DustPywas developed at theUniversity Observatoryof theLudwig Maximilian University of Munich.
Package: dustpylib
DustPyLibDustPyLibis a library that contains auxiliary modules for the dust evolution softwareDustPy, for example interfaces to radiative transfer codes or modules with extensions to theDustPydefaults.For information about the usage ofDustPy, please have a look at theDustPy documentation.InstallationDustPyLibcan be installed via PyPI.pip install dustpylibDocumentationFor the usage ofDustPyLibplease have a look at itsdocumentation.GridGrid refinementPlanetesimalsPlanetesimal formationRadiative transferRADMC-3DSubstructuresPlanetary gapsA. Contributing / Bug reports / Features requests
Package: dutch-boy
dutch-boyMock and memory leak detector library.  Right now this just features a plugin
for Nose 1.x and is inbeta.This plugin:
- Detects mocks that are not reset between tests.
- Detects mocks created during tests that are not deleted by the end of the test.
- Reports memory delta between tests.  Optional.To learn the story of the name, visithttps://en.wikipedia.org/wiki/Hans_Brinker,_or_The_Silver_Skates.Pull requests are welcome.  In particular, area I’m looking to improve are:
- adding a pytest test runner
- improving memory delta reportingDjango SetupTo use this plugin with django nose runner, just include the following in your settings file:NOSE_PLUGINS = [
    'dutch_boy.nose.LeakDetectorPlugin']
NOSE_ARGS = ['--with-leak-detector', '--leak-detector-level=3']
Package: dutch-text-analytics
Dutch Text AnalyticsDutch Text Analytics is a versatile toolkit designed to facilitate the exploration, execution, and validation of a diverse range of Natural Language Processing (NLP) tasks specifically tailored for the Dutch language. This repository provides a comprehensive set of tools, including code examples, scripts, and resources, to enhance and streamline your Dutch NLP projects.Getting StartedPrerequisitesEnsure you have Python version 3.8.10 installed on your system.InstallationTo install theDutch Text Analyticspackage, open a command prompt and run:pipinstalldutch_text_analyticsUsageIn your Python script or Jupyter Notebook, import the library as follows:importdutch_text_analytics.text_analyticsastaTo access modules and leverage the functionalities provided by the toolkit, instantiate the TextProcessing class:text_processor=ta.TextProcessing()For detailed usage examples and demonstrations, refer to the demo scripts available in thedemosfolder.Modules OverviewText ProcessingThe TextProcessing module provides powerful tools for working with Dutch text, including lemmatization, handling separable verbs, and displaying dependency trees.# Example: Instantiate TextProcessingtext_processor=ta.TextProcessing()# Example: Lemmatize a sentencelemmatized_sentence=text_processor.lemmatize("Your Dutch sentence here.")# Example: Handle separable verbs in a sentenceprocessed_sentence=text_processor.handle_separable_verbs("Your Dutch sentence here.")# Example: Display dependency tree of a sentencetext_processor.display_dependency("Your Dutch sentence here.")Explore the module for additional functionalities to enhance your Dutch text processing workflows.Tip: The TextProcessing takes in language argument. For english:# Example: Instantiate TextProcessingtext_processor=ta.TextProcessing(language='en')DemosCheck out thedemosfolder for hands-on demonstrations and code examples showcasing the capabilities of Dutch Text Analytics across various NLP tasks.Feel free to contribute, report issues, or suggest improvements. Happy coding with Dutch Text Analytics!
Package: dutch-words
A simple python package that exports a list of almost 10,000 Dutch words ranked by usage.Usageimport dutch_words
words = dutch_words.get_ranked()ThanksThanks toSasha Romijnfor the inspiration and the University of
Leipzig for theDutch word list.LicenseThe word list provided by the University of Leipzig and the python code are available under theCC BY 4.0license.
Package: dutch-workdays
A very small library that handles with Dutch calendars and holidays 🇳🇱Installing` pip installdutch-workdays`Usage`python from dutch_workdays import Calendar cal = Calendar() cal.get_king_queen_day(2018) # (datetime.date(2018, 4, 27), "King's day") `dutch-workdaysworks as a drop-in replacement ofworkalendar, so for the
rest of the API please refer to
theworkdays documentation.Why not just using Workalendar instead?Workalendar is an awesome library, it’s very complete and very well maintained
but it’s, unfortunately, quite a big dependency as well. It not only includes
Python code to handle calendars from most of the world, but it also requires C
libraries to calculate high-precision astronomy computations. It’s an overkill
if you only need to know about Dutch holidays.Differences from WorkalendarAll the codebase is type annotated.Zero dependenciesDateutil easter calculation is vendorized.
Package: dutc-rwatch
### Disclaimerdutc = Don't Use This Code (!!)# Compatibility* Python 3.5 or higher* Linux or OS X* need build toolchain (prob. need `gcc`)# Read Watches in Python```python>>> import rwatch # enable functionality>>> from sys import setrwatch, getrwatch>>> x, y, z = object(), object(), object()>>> def view(frame, obj):...     print(frame, obj)...     return obj...>>> setrwatch({id(x): view, id(y): view})>>> getrwatch(){139825758638208: <function view at 0x7f2bb89a59d8>, 139825758638224: <function view at 0x7f2bb89a59d8>}>>> x<frame object at 0x7f2bb8ad9ba8> <object object at 0x7f2bb8ac9080><object object at 0x7f2bb8ac9080>>>> y<frame object at 0x7f2bb8ad9d48> <object object at 0x7f2bb8ac9090><object object at 0x7f2bb8ac9090>>>> z<object object at 0x7f2bb8ac90a0>```# Lessons:* read watches are a very useful tool for debugging* it's actually very useful for a language to have a runtime* there are some hidden equivalencies between, e.g., read watches and perfect proxy objects
Package: dutest-trac
Advanced testing framework for Trac and BloodhoundThis library offers a set of tools supporting best practices
gathered throughout the development of test suites for
Trac and Apache(TM) Bloodhound issue trackers. This includes
(but is not limited to):writing doctests,specialized unittest test case classes,advanced functional testing environments and testers.Notice: Most of the classes offered in this module have been imported fromTracGViz plugin; created in 2009Copyright 2009-2018 Olemis Lang <olemis at gmail.com>
Licensed under the Apache LicenseWhat’s new in version 0.1.0
Package: dutil
dutilA few data utilities to make life of a data scientist easierInstallationpipinstalldutilModulespipeline(data caching and pipelines)stats(statistical functions)string(string manipulations)transform(data transformations)jupyter(tools for jupyter notebooks)Pipelineimportdutil.pipelineasdpipeimportpandasaspdimportnumpyasnpfromloguruimportlogger# --- Define data transformations via step functions (similar to dask.delayed)@dpipe.delayed_cached()# lazy computation + caching on diskdefload_1():df=pd.DataFrame({'a':[1.,2.],'b':[0.1,np.nan]})logger.info('Loaded{}records'.format(len(df)))returndf@dpipe.delayed_cached()# lazy computation + caching on diskdefload_2(timestamp):df=pd.DataFrame({'a':[0.9,3.],'b':[0.001,1.]})logger.info('Loaded{}records'.format(len(df)))returndf@dpipe.delayed_cached()# lazy computation + caching on diskdefcompute(x,y,eps):assertx.shape==y.shapediff=((x-y).abs()/(y.abs()+eps)).mean().mean()logger.info('Difference is computed')returndiff# Define pipeline dependenciests=pd.Timestamp(2019,1,1)eps=0.01s1=load_1()s2=load_2(ts)diff=compute(s1,s2,eps)# Trigger pipeline executionprint('diff:{:.3f}'.format(dpipe.delayed_compute((diff,))[0]))Statsfromdutil.statsimportmean_lower,mean_upperimportpandasaspdss=pd.Series([0,1,5,-1])mean_lower(ss)# Compute mean among 50% smallest elementsmean_upper(ss)# Compute mean among 50% biggest elementsStringfromdutil.stringimportcompare_companiescompare_companies("Aarons Holdings Company Inc.","Aaron's, Inc.")# Give match rating for two company namesTransformfromdutil.transformimporthtimportpandasaspddf=pd.DataFrame({'a':[0,2,2,4,6],'b':[1,1,1,1,1]})ht(df)# Return first and last rows of a DataFrame, a Series, or an arrayJupyterfromdutil.jupyterimportdhtimportpandasaspddf=pd.DataFrame({'a':[0,2,2,4,6],'b':[1,1,1,1,1]})dht(df)# Display first and last rows of a DataFrame, a Series, or an array in a Jupyter notebook