Saravanan666/pypi-org huggingface dataset:
Package: classconvergence
classconvergencePlot the class distribution as a function of iteration from a Class2D or Class3D
job from RELION.This tool was tested with star files produced by RELION-3.1.0. Earlier versions
of RELION are not supported.AcknowledgmentsI would not have been able to put this tool together without thestarfilelibrary.InstallationI recommend to install this tool in a dedicated conda environment. You can
create one like so (replaceENV_NAMEwith the name you want to give to this
environment):$ conda deactivate
$ conda create --name ENV_NAME python=3.9
$ conda activate ENV_NAMEOnce the conda environment is active, you can install the tool with the
following command:$ pip install classconvergenceUsage$ classconvergence --help
Usage: classconvergence [OPTIONS] <job_directory>

  Plot the class distribution as a function of iteration from a Class2D or
  Class3D job from RELION.

Options:
  -c, --count        Plot particle counts per class (default, same effect as
                     not passing any option).

  -p, --percent      Plot percentages of particles per class (default:
                     counts).

  -o, --output TEXT  File name to save the plot (optional: with no file name,
                     simply display the plot on screen without saving it;
                     recommended file formats: .png, .pdf, .svg or any format
                     supported by matplotlib).

  -h, --help         Show this message and exit.
Package: classdiff
classdiff- Python Class DiffferThis is a small library to diff (data) classes or any other objects. It is
intended two work one obejcts of the same time orNoneType. Diffing different
classes is possible but might result in unexpected result. Different from most
existing diff tools that produce data structures that show adds, removes or
changes, this tool is intended to use for printing a dataclass and higlight the
diff with different color coding, similar to the output ofTerraformorPulumi.UsageJust pass your classes to the diff function to get back a representation of the
diff.Given the following two classes:new=SomeResource(name="my-data",price=2.3,quantity=4,dangerous=True,other=OtherClass(name="OA"),not_changed=OtherClass(name="Same"),)old=SomeResource(name="my-data",price=3.3,quantity=4,dangerous=False,other=OtherClass(name="OB"),not_changed=OtherClass(name="Same"),)Passing them toclassdiff.diffin combinations of(None, new),(old, new)and(old, None)and printing the lines in the returned value, the following
will be printed with colored output (green for added, red for removed and yellow
for changed). Note that each element in the returned list is of typeDiffInfowhich implements__repr__to print with proper prefix and color.>diff(None,new)----------------------------------------
+SomeResource(+dangerous=True
+name=my-data
+not_changed=OtherClass(+name=Same
+)+other=OtherClass(+name=OA
+)+price=2.3
+quantity=4+)>diff(old,new)----------------------------------------
~SomeResource(~dangerous=False=>Truename=my-datanot_changed=OtherClass(name=Same)~other=OtherClass(~name=OB=>OA
~)~price=3.3=>2.3quantity=4~)>diff(old,None)----------------------------------------
-SomeResource(-dangerous=False
-name=my-data
-not_changed=OtherClass(-name=Same
-)-other=OtherClass(-name=OB
-)-price=3.3
-quantity=4-)DevelopmentAll code is formatted and analyzed withblackandruff. Tests are run withpytest.›poetryrunruffcheck.
›poetryrunruffformat.
›poetryrunmypy.
›poetryrunpytesttests/
Package: class-doc
Class docSmall set of helpers aimed to extract class attributes documentation from the class definition. This stuff tries to mimicsphinx-autodoc behaviouras closely as possible (except instance attributes defined inside__init__function).The main advantage of this project oversphinx-autodocis that it is lightweight single-purpose dependency, whileautodocjust a small part of really heavy project.InstallationThis package is available onPyPIpipinstallclass-docExamplesShamely stolen fromsphinx-autodocdocsclassFoo:"""Docstring for class Foo."""#: Doc comment for class attribute Foo.bar.#: It can have multiple lines.bar=1flox=1.5#: Doc comment for Foo.flox. One line only.baz=2"""Docstring for class attribute Foo.baz."""baf=3"""Evenmultilinedocstringshandledproperly"""importclass_docassertclass_doc.extract_docs_from_cls_obj(Foo)=={"bar":["Doc comment for class attribute Foo.bar.","It can have multiple lines."],"flox":["Doc comment for Foo.flox. One line only."],"baz":["Docstring for class attribute Foo.baz."],"baf":["Even","multiline","docstrings","handled","properly"]}Development setupProject requiresPoetryfor development setup.If you aren't have it alreadypipinstallpoetryInstall project dependenciespoetryinstallRun testspoetryrunpytest.Great, all works!
Package: classdojo
Class DojoTools to get points from the classdojo point systemInstall using:pip3 install classdojoExample:import classdojo.classdojo as classdojo

classId = "<CLASS ID (Found in URL)"
cookie = "<Cookie (Found in developer console)

_class = classdojo.classDojo(classId, cookie)

print(_class.getPointsByCombinedName("KnowlesB")0.01 - Initial Upload
0.02 - Fixed Import Error
Package: class-d-oliversandli
class_dAn interactive utility for creating GitHub-style licenses locally with date and name.RequirementsPython version 3.6 or higherRequests*python-inquirer**pipwill install these automatically.Installationpython-mpipinstallclass-d-oliversandliNote that installation withsudowill addclass_dto/usr/local/bin. Withoutsudo,pipinstalls scripts to~/.local/bin. Many Linux distros do not have~/.local/binalready in their path, so to useclass_dafter asudo-less install, add~/.local/binto yourPATHvariable.Setupclass_dwill perform all necessary setup on first run.Usageclass_das a Programclass_d-f--favoriteCreate aLICENSEfile specified by"favorite"in~/.config/class_d/settings.json.class_das a Library#!/usr/bin/env python3"""example file"""importclass_dif__name__=="__main__":license_list=class_d.get_license_list()specific_license=class_d.get_license(license_list["MIT"])get_license_list()Return a dictionary of license names and GitHub API keys fromhttps://api.github.com/licenses.{'AGPL-3.0': 'agpl-3.0',
 'Apache-2.0': 'apache-2.0',
 'BSD-2-Clause': 'bsd-2-clause',
 'BSD-3-Clause': 'bsd-3-clause',
 'CC0-1.0': 'cc0-1.0',
 'EPL-2.0': 'epl-2.0',
 'GPL-2.0': 'gpl-2.0',
 'GPL-3.0': 'gpl-3.0',
 'LGPL-2.1': 'lgpl-2.1',
 'LGPL-3.0': 'lgpl-3.0',
 'MIT': 'mit',
 'MPL-2.0': 'mpl-2.0',
 'Unlicense': 'unlicense'}get_license(key)Return thebodyof a license fromhttps://api.github.com/licenses/{key}.get_license("mit")"MIT License\n\nCopyright (c) [year] [fullname]\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n"TODOAdd-fflag to use favorite license.Complete documentation in README.Complete PEP-8 compliance.Fullargparsefor--helpsupport.Provide library for useful functions.Distribute onpip.
Package: classeval
classevalThe libraryclassevalis developed to evaluate the models performance of any kind oftwo-classormulti-classmodel.classevalcomputes many scoring measures in case of a two-class clasification model. Some measures are utilized fromsklearn, among them AUC, MCC, Cohen kappa score, matthews correlation coefficient, whereas others are custom. This library can help to consistenly compare the output of various models. In addition, it can also give insights in tuning the models performance as the the threshold being used can be adjusted and evaluated. The output ofclassevalcan subsequently plotted in terms of ROC curves, confusion matrices, class distributions, and probability plots. Such plots can help in better understanding of the results.⭐️ Star this repo if you like it ⭐️Documentation pagesOn thedocumentation pagesyou can find more information aboutclassevalwith examples.Install classeval from PyPIpipinstallclasseval# normal installpipinstall-Uclasseval# update if neededImport classeval packageimportclassevalasclfExamplesExample: Evaluate Two-class modelExample: Evaluate multi-class modelExample: Model performance tweakingContributeAll kinds of contributions are welcome!CitationPlease citeclassevalin your publications if this is useful for your research. See column right for citation information.MaintainerErdogan Taskesen, github:erdogantContributions are welcome.If you wish to buy me aCoffeefor this work, it is very appreciated :)
Package: classevivaAPI
ClassevivaSlowAPIforClassevivabyGruppoSpaggiariParmaDownloadClassevivais available onPyPI$ python -m pip install classevivaAPIDocumentationYou can find the italian documentation onReadTheDocs.ioUsageYourYourFile.pycould be written as follows:#!\usr\bin\env python3fromclassevivaimportSession,Valutazioni,Note,Registrofromclasseviva.variablesimportNoteSortByif__name__=="__main__":s=Session("S<my-username>","<my-password>",hidden=False)s.login()print(s.user)v=Valutazioni(s)print(v.subjects)print(v.get_valutations_marks())print(v.get_valutations(False,False,False))n=Note(s)print(n.get_notes(NoteSortBy.TYPE))print(n.lenght)r=Registro(s)print(d:=r.Date.from_str("SABATO 31 GENNAIO 2022"))print(r.get_day_status(d))print(r.get_status(d,1))print(r.get_status(d,2))print(r.get_status(d,5))A sample output may be the following:DevTools listening on ws://127.0.0.1:63746/devtools/browser/25500ad4-68de-4f15-b52a-08068382f340
User: S<my-username> | <my-password> | 58733881
Time-left: 3598s
S<my-username> | <my-password> | 58733881
["RELIGIONE CATTOLICA O ATTIVITA' ALTERNATIVE", 'SCIENZE NATURALI', 'LINGUA E CULTURA STRANIERA (INGLESE)', 'LINGUA E LETTERATURA ITALIANA', 'SCIENZE MOTORIE E SPORTIVE', 'INFORMATICA', "DISEGNO E STORIA DELL'ARTE", 'FISICA', 'MATEMATICA', 'FILOSOFIA', 'STORIA', 'EDUCAZIONE CIVICA']
[8.0, 9.0, 8.5, 8.5, 8.0, 8.0, 8.0, 'g', 7.0, 8.5, 8.0, 9.5, 10.0, 9.5, 8.5, 9.0, 8.0, 8.5, 8.0, 8.0, 8.0, 8.0, 8.0, 7.0, 9.0, 8.5, 8.0, 8.0, 10.0, 10.0, 10.0, 8.0, 9.5, 9.5, 8.0, 8.5, 8.0, 9.0, 8.5, 8.5, 8.0, 8.0, 8.0, 'g', 7.0, 8.5, 8.0, 9.5, 10.0, 9.5, 8.5, 9.0, 8.0, 8.5, 8.0, 8.0, 8.0, 8.0, 8.0, 7.0, 9.0, 8.5, 8.0, 8.0, 10.0, 10.0, 10.0, 8.0, 9.5, 9.5, 8.0, 8.5]
[("RELIGIONE CATTOLICA O ATTIVITA' ALTERNATIVE", 10.0), ('SCIENZE NATURALI', 10.0), ('SCIENZE NATURALI', 9.5), ('SCIENZE NATURALI', 10.0), ('LINGUA E CULTURA STRANIERA (INGLESE)', 7.5), ('LINGUA E CULTURA STRANIERA (INGLESE)', 8.5), ('LINGUA E CULTURA STRANIERA (INGLESE)', 8.5), ('LINGUA E LETTERATURA ITALIANA', 8.0), ('LINGUA E LETTERATURA ITALIANA', 8.5), ('LINGUA E LETTERATURA ITALIANA', 7.0), ('LINGUA E LETTERATURA ITALIANA', 8.5), ('SCIENZE MOTORIE E SPORTIVE', 9.0), ('SCIENZE MOTORIE E SPORTIVE', 8.0), ('SCIENZE MOTORIE E SPORTIVE', 8.5), ('INFORMATICA', 10.0), ("DISEGNO E STORIA DELL'ARTE", 10.0), ("DISEGNO E STORIA DELL'ARTE", 7.0), ('FISICA', 7.0), ('FISICA', 9.5), ('FISICA', 6.0), ('MATEMATICA', 9.0), ('MATEMATICA', 8.0), ('MATEMATICA', 9.0), ('MATEMATICA', 8.0), ('FILOSOFIA', 8.0), ('STORIA', 9.0), ('STORIA', 8.5), ('STORIA', 8.5), ('EDUCAZIONE CIVICA', 10.0), ('EDUCAZIONE CIVICA', 8.5)]
[('La classe oggi 2/04/22, esce alle 11.50.', 'SOMEBODY', '02-04-2022', 'Annotazione del docente'), ("La classe esce alle ore 12:45 per l'assenza della prof.ssa SOMEBODY", 'SOMEBODY', '03-05-2022', 'Annotazione del docente'), ('Compiti di Geometria non svolti', 'SOMEBODY', '12-02-2022', 'Richiamo (Compiti)')]
3
SABATO 31 GENNAIO 2022
1.0
0.2
1.0
1.0The whole run should take around21s.
Package: classeviva-client
classeviva-clientclasseviva-client is a Python library and a CLI tool to access thehttps://web.spaggiari.eu, probably the most used portal for schools, students and families.Getting StartedSet your credentials as environment variables:export CLASSEVIVA_USERNAME="you@domain.com"
export CLASSEVIVA_PASSWORD="secret!"As a Python library$python
>>>
>>>fromclasseviva.clientimportClient
>>>fromclasseviva.credentialsimportEnvCredentialsProvider
>>>
>>>
>>>withClient(EnvCredentialsProvider())asclient:
...print(client.grades()[:1])...[Grade(value=7.25,display_value='7+',subject='ITALIANO',date='2021-10-11',color='green',comment='')]As a CLI toolList your grades:$classevivalist-grades2022-03-30
-MUSICA,72022-03-28
-MATEMATICA,7½2022-02-22
-MUSICA,9½
-RELIGIONE,8½List your agenda entries for homework assignments:$classevivalist-agenda2022-04-07
-TEACHERA,Geometria:pagina42n.90-91-96-100.
-TEACHERB,leggereetradurreoralmenteidialogodip.130ecopiareunavoltasulquaderno.RefsSpecial thanks to@michelangelomofor providing good API docs atmichelangelomo/Classeviva-Official-Endpoints.
Package: class_extension
# class_extensionA mechanism for extending python classes.Code for adding methods to classes outside of class definitions.For reference: another version of the same idea was found,proposed by GVR himself:https://mail.python.org/pipermail/python-dev/2008-January/076194.htmlI'm providing this version as a slightly safer alternative.It has various extra checks that avoid issues.Pros:* Promotes functional cohesion;Cross-class inter-dependant code can stay together,easing understanding (only need to refer to one file tosee how something works or make changes).* Actually safer than python's class definition mechanism dueto the existing-name-check assertion. i.e. we can't definesomething twice with extensions, but we can with ordinaryclasses.* Provides a way to avoid circular imports when adding methods.This can be a huge benefit for a large project.* Provides a good way to extend classes from external libraries.This can also be a nice benefit, as sometimes it's notpossible to use your subclass inside an external library.Cons:* Methods don't appear to metaclasses at class instantiation time.This shouldn't be a problem, as the metaclasses shouldn'tbe concerned with methods added in this way anyway.* Surprises developers who expect all methods to be inside a class definition.Notes:Monkey-patching is expressly disallowed.This means you can't replace an attribute on an existing class.However, you can override a superclass method, like an ordinary class canand you can always create a subclass and extend that.
Package: classfig
classfigComfortable figure handling in Python3 / Matplotlibwritten by Fabian Stutzki,fast@fast-apps.delicensed under MITUsageThe package has to be imported:fromclassfigimportclassfigA very simple example is:fig=classfig()fig.plot()fig.show()classfig allows for more complex behavior with multiple subplots, legend, grid and saving to multiple files at once.fig=classfig('PPT',nrows=2)# create figurefig.plot([1,2,3,1,2,3,4,1,1])# plot first data setfig.title('First data set')# set title for subplotfig.subplot()# set focus to next subplot/axisfig.plot([0,1,2,3,4],[0,1,1,2,3],label="random")# plot second data setfig.legend()# generate legendfig.grid()# show translucent grid to highlight major ticksfig.xlabel('Data')# create xlabel for second axisfig.save('test_fig1.png','pdf')# save figure to png and pdf
Package: classGenerator
classGeneratorThis is a package that helps to generate classes in an easy and fast wayInstallationInstall the package with pippipinstallclassGeneratorVariables ReferenceParameterTypeDescriptionnombreArchivostringRequired. It is the name of the file where the class will be added. If the file does not exist, it will be generated with that namenombreClasestringRequired. It is the name with which the class will be generatedvariablesstringRequired. They are the variables that the class will haveGettersAndSettersboolIf this parameter is not specified, the default will beFalse. SetTrueto generate the getters and setters in case you don't want them to setFalsedireccionstringIf this parameter is not specified, the file will be generated on thedesktop. Put the address where you want to generate the fileUsage/ExamplesEstructurefromclassGenerator.generateClassimportcreateClasscreateClass(nombreArchivo,nombreClase,variables,False,direccion)Example 1It will create a class on the desktop without getters and settersfromclassGenerator.generateClassimportcreateClasscreateClass("People","Person","first_name, last_name, email, address")Example 2It will create a class on the desktop with getters and settersfromclassGenerator.generateClassimportcreateClasscreateClass("People","Person","first_name, last_name, email, address",True)Example 3It will create a class at a specific address without getters and settersfromclassGenerator.generateClassimportcreateClasscreateClass("People","Person","first_name, last_name, email, address",False,"c:\\Users\user\Desktop")Screenshots
Package: classh
classh is yet another wrapper around ssh for running jobs on multipletargets.  It can support tens of thousands of targets (tested on over
25,000 at once) and runs a configurable number of jobs concurrently.
It separately gathers results, output and error messages, displaying
summary/status information it comes in (asynchronously) and more
detailed data after all jobs have completed.classh provides an SSHJobMan class which can be imported into your own
Python code and easily used to handle specialized display or other
disposition of results.  (For example the names of all hosts on which
the job succeeded can be fed into another process while various failure
modes can be tested and fed into other processes).
Package: classical
Convenience tools for working with Python classes.Simplified subclassing:classMyClass:def__init__(self,*args,**kwargs):pass# do whatever# subclass with presetsMySubClass=argumented_subclass(MyClass,'MySubClass',arg1='value',arg2=4)Various descriptors:classThing:Red=ArgumentedSubclass(color='red')book=AutoProperty(has='pages')def__init__(self,color=None,has=None):self.color=colorself.has=hasThing.Red# is a subclass of Thing and is 'red'Thing.Red.book# is an instance of Thing (and Thing.Red), is 'red' and has 'pages'See the full documentation athttp://classical.readthedocs.io/en/latest/InstallationpipinstallclassicalTestingmaketestYou may need to install[fielded,testing]extras to run testsGenerating docsmakedocsYou may need to install[fielded,docs]extras to generate docs
Package: classical-doa
Classical DOAClassical DOA Estimation algorithms implemented in Python.Getting StartedInstallationpipinstallclassical_doaor install from sourcegitclonehttps://github.com/zhiim/classical_doa.gitcdclassical_doa
pipinstall.UsageA sample example of DOA estimation using MUSIC algorithm.importnumpyasnpfromclassical_doaimportarrays,signalsfromclassical_doa.algorithm.musicimportmusicfromclassical_doa.plotimportplot_spatial_specturm# Create a 8-element ULA with 0.5m spacingula=arrays.UniformLinearArray(m=8,dd=0.5)# Create a complex stochastic signalsource=signals.ComplexStochasticSignal(nsamples=1000,fre=3e8,fs=1e9)# Simulate the received datareceived_data=ula.received_signal(signal=source,snr=0,angle_incidence=np.array([0,30]),unit="deg")# Calculate the MUSIC spectrumangle_grids=np.arange(-90,90,1)spectrum=music(received_data=received_data,num_signal=2,array_position=np.arange(0,4,0.5),signal_fre=3e8,angle_grids=angle_grids,unit="deg")# Plot the spatial spectrumplot_spatial_specturm(spectrum=spectrum,ground_truth=np.array([0,30]),angle_grids=angle_grids)You will a get a figure like this:Checkexamplesfor more examples.What's implementedArray StructuresUniform Linear Array (ULA)Signal ModelsNarrowbandcomplex stochastic signalBroadbandchirp signalAlgorithmsULAMUSICESPRITRoot-MUSICOMPl1-SVDUCAUCA-RB-MUSICUCA-ESPRITBroadbandISSMCSSMTOPSLicenseThis project is licensed under theMITLicense - see the LICENSE file for details.
Package: classicalguitar
Link:https://www.youtube.com/watch?v=8IEezGQwgZkPyPi:https://pypi.org/project/classicalguitar/สวัสดีจ้าาาา
แพ็คนี้คือแพ็คเกจที่อธิบายเรื่องราวเกี่ยวกับกีตาร์คลาสสิคแบบย่อๆ
โดยมีประวัติ การเล่นกีตาร์ และรูปภาพแอสกีวิธีติดตั้งเปิด CMD / Terminalpipinstallclassicalguitarวิธีใช้งานแพ็คเพจนี้เปิด IDLE ขึ้นมาแล้วพิมพ์…fromclassicalguitar.classicgtimportClassicalGTgt=ClassicalGT()gt.show_name()#ทักทายกันหน่อยgt.show_youtube()#แสดงยูทูปการเล่นกีตาร์คลาสสิคgt.about()#รู้จักกับกีตาร์คลาสสิคgt.show_art()#แสดงภาพแอสกีพัฒนาโดย: Doraeboy
Package: classical-logic
classical-logic - Tools for Classical Logicclassical-logicis a Python package that allows you to work with logical
propositions as Python objects.It's extremely simple to use:fromclassical_logicimportpropp=prop('P & Q')assertp(P=True,Q=True)isTrueassertp(P=True,Q=False)isFalseFeaturesParse proposition objects:fromclassical_logicimportprop# Can parse simple propositions:p=prop('P | Q')# As well as complex ones!p=prop('P & (Q | (Q -> R)) <-> S')Compose proposition objects:p=prop('P')q=prop('Q')# Create conjunctions and disjunctions with & and |:u=p&(q|p)# P & (Q | P)# Create conditionals and biconditionals as well:u=p.implies(q)# P -> Qu=p.iff(q)# P <-> QDecompose propositions:u=prop('P & Q')# Use indexing toassertu[0]==prop('P')assertu[1]==prop('Q')# You can also use Python's unpacking feature!p,q=uassertp==prop('P')assertq==prop('Q')Interpret propositions (assign truth values):u=prop('P <-> Q')# Call the proposition like a function to interpret itassertu(P=True,Q=True)isTrueassertu(P=True,Q=False)isFalseassertu(P=False,Q=False)isTrueNo dependencies.This package doesn't use any dependencies.Want to use this package? See thedocumentation!LinksDocumentation @ ReadTheDocsGithub RepositoryPyPI PageInstallationThis package can be installed using Pip:pipinstallclassical-logicPlease make sure you use a dash (-) instead of an underscore (_).Bug Reports and Feature RequestsYou can report a bug or suggest a feature on the Github repo.See theIssues page on Github.ContributionsContributions to this project are welcome. :)See thepull requests page on Github.