Saravanan666/pypi-org huggingface dataset:
Package: exsu
exsuExperiment support tools prepared for computer vision experiments.
Output directory and spreadsheet file is managed by package.Spreadsheet data and report images are stored into output directoryImages are reported according a selected severityCommon spreadseet containing complete history from all output directories can be producedVersion of particular python package can be reported in the spreadsheetRepository status, git hash and dirty files can be reported in the spreadsheetWrite spreadsheet datafrompathlibimportPathimportexsuoutputdir=Path("./test_report/")commonsheet=Path("./test_report_common_spreadsheet.xlsx")report=exsu.report.Report(outputdir=outputdir,additional_spreadsheet_fn=commonsheet)report.add_cols_to_actual_row({"Col1":25,"Col2":"test string","Col5":5})report.add_cols_to_actual_row({"Col2":"prepsanu","Col1":26,"Col4":"ctyrka"})report.finish_actual_row()report.add_cols_to_actual_row({"Col1":27,"Col2":"test string","Col3":"trojka"})report.finish_actual_row()# Save all into `outputdir` and also into `commonsheet`report.dump()# new write to common excelreport.init()report.add_cols_to_actual_row({"Col1":28,"Col2":"new line to common","Col7":77})report.finish_actual_row()report.dump()Write image dataWrite image data into output directoryfrompathlibimportPathimportnumpyasnpimportexsuoutputdir=Path("./test_report/")commonsheet=Path("./test_report_common_spreadsheet.xlsx")fn="test_image.png"img=50+np.random.rand(100,100)*30img[20:60,20:60]+=100img=img.astype(np.uint8)report=exsu.report.Report(outputdir=outputdir,additional_spreadsheet_fn=commonsheet)report.imsave(fn,img)Git repository infofrompathlibimportPathimportnumpyasnpimportexsureport=exsu.report.Report(repodir=Path(__file__).parent.resolve())report.finish_actual_row()report.dfOutput DataFramerepo exsu id  ...  repo exsu dirty files
0  1da301da36cec0fb931f60dd9acca790ec715892  ...      exsu/git_tools.pyMore than one repositories can be added withreport.add_repo(repodir, reponame=None).Automatically report versions of selected packagesThe version of crucial packages can be reported with the data.importexsureport=exsu.report.Report(check_version_of=["numpy","scipy"])report.finish_actual_row()report.df
Package: ext
This python module makes it possible to add new attributes to built-in
types, enabling the user to modify types implemented in C, which is not
possible from Python code.The code doing the monkey patching is in ext/_ext.c. It basically adds
a new attribute to a built-in type’s __dict__, and then calls
PyType_Modified on the type. This way it is possible to add new methods
(implemented in Python or C) or other class attributes to built-in types
(like list).
The module is experimental. I’m not sure which problems can result from
modifying the dict of a built-in type.
The module doesn’t allow replacing an existing attribute of a type, so it
is harder to render unusable the built-in types. The monkey patching also
works on types implemented in Python (it just calls setattr after checking
if there is already an attribute with the given name).
Package: extarc
extarc - Utility functions forarcpyThis repository contains python functions for commonly repeated tasks, e.g. getting new scratch feature classes in a scratch gdb, or getting certain projections. It's named extarc because it...extendsarcpy. It also sounds like a cool ship fromThe Expansewhich you should really watch. It utilizes thearcpymodule which ships with ArcMap Desktop / ArcGIS Pro and so it's assumed that your python environment has access to these modules. That is, if you can'timport arcpyalready, why are you trying to use a helper library? Currently, arcpy isnotpart of requirements.txt because it's not clear whether it will pass a CI check.InstallationWhile you can always just clone this repository into your project, or add it as a submodule via:>gitsubmoduleaddhttps://github.com/joshpsawyer/extarc.git...it's a much better practice to install it as a module in your python environment - less maintenance, no unnecessary packages in your code. While structured for pypi, it's currentlynotin the index. You need to install a development build. Anaonda is recommended for environment management, but because Anaconda doesn'tdirectlysupport this - you need to use pip.Assuming you have anaconda installed and a target environment, open your command prompt / terminal. If you're installing it to the conda environmentcool-env, switch to that environment now:(base)>condaenvactivatecool-env(cool-env)>condaenvactivatecool-envFrom the prompt, type:(cool-env)>pipinstall--editable=git+https://github.com/joshpsawyer/extarc.git#egg=extarcThe latest master commit will be installed under the package namedextarc-joshpsawyer. To uninstall, type:(cool-env)>pipuninstallextarc-joshpsawyerUsageimportextarcasea
Package: extasy
EXTasy=======EXTasy is a Cucumber-like BDD tool for ExtJS developers. It is written in python and built on top of Pycukes.Installation=====You can install it using Python's easy_install::$ easy_install extasyOr You can download source code and install using setup.py script::$ python setup.py installUsage=====First, make sure you have installed story_runner, pyhistorian, pycukes and extasy.By default, if you just call ``extasy`` from your command line into some dir, it will look for a ``stories`` dir (expecting your stories files are there).Each story file by convention ends with .story, like ``calculator.story``.So, lets say you have the directory tree::|-- calculator|-- stories|-- calculator.storyTo run your stories, you can simple call::$ extasyOr if you can specify exactly what stories run::$ extasy stories/calculator.storyGet in touch with the team=====If you have further questions, please contact the team:snit-ram: http://github.com/snit-ram, http://twitter.com/snit_ram
Package: extasy.wrappers
# ExTASY Wrappers #A library to simplify the construction of ExTASY simulation-analysis workflows.### What is this repository for? ###* *ExTASY wrappers* provide a consistent API for launching command line applications (such as MD simulations or simulation analysis jobs) from python scripts. Though designed originally with ExTASY simulation-analysis workflows in mind, they are extensible to many other possible applications.In a nutshell, the construction and execution of a complete simulation or analysis job is reduced to a python function call of the form:```#!pythonresults = kernel.run(inputs)```where "kernel" might be pmemd, grompp, pyCoCo, LSDMap, etc.See the Wiki for more details.* Version 0.0.1### How do I get set up? ###* Clone the repository and then run setup.py:```git clone https://bitbucket.org/extasy-project/wrappers.gitcd wrapperspython setup.py install --user```* Dependencies: *ExTASY wrappers* itself has no dependencies outside the standard python libraries. To run the examples though will require:1. An MD code: Amber (or Ambertools) and/or GROMACS2. A sampling analysis package: [ExTASY CoCo](https://bitbucket.org/extasy-project/coco) and/or [ExTASY-compliant LSDMap](https://github.com/ClementiGroup/LSDMap)Running the parallel examples will additionally require:[Dask](https://github.com/blaze/dask) and/or [mpipool](https://github.com/adrn/mpipool/tree/master/mpipool)* How to run tests: See the README files in the folders under ./examples.### Who do I talk to? ###* Charlie Laughton
Package: ext-auth
User External AuthUser External Auth is a wrapper Django app for 3rd Party token auth, and convert it to Django OAuth2 token (django-oauth-toolkit).For now only focus on Firebase Auth ID Token.More feature and convenient methods will include in the future.Register and Login Apiview is ready and it is using Django Rest Framework library.Requirementsdjango >= 1.7.7django-oauth-toolkit >= 0.10.0django-rest-framework >= 3.1.1firebase-adminInstallationInstall using pippip install ext-authUsageAddext_authto your INSTALLED_APPS.INSTALLED_APPS = [
...
'ext_auth',
]Runpython manage.py migrateto create the ext_auth models.** The register and login Apiview sample is underext_auth.rest-framework.firebase
Package: extaxsi
ExTaxsI functionsLibrary overviewExTaxsI functions can be used separately from the ExTaxsI tool. In general, there are 6 main functions for the following tasks:load_configurations() -mandatory before using ExTaxsi functions- setting NCBI API key to allow data querydb_creation() - create FASTA, accession with taxonomy or enriched databasetaxonomyID_converter() - convert taxid into organism taxonomy and viceversasunburst_plot() - create sunburst plotscatterplot() - create scatterplotworldmap_plot() - create worldmap plotIn the [github](https://github.com/qLSLab/ExTaxsI/blob/master/library/functions_installation_and_tutorial.ipynb) notebook installation and tutorials for configuration and usage are provided.Input files used are available in theexamplesdirectory.For any doubt, please write tog.agostinetto@campus.unimib.it
Package: extBrightness
Copyright Jörg Mäder - 2016-05-05 - Version 1.0.4 -http://www.toolcase.org/app/linux/extBrightnessThis tool allows to control brightness and gamma for all connected
screens on a X11 system (which is the case for the most linux systems).
extBrightness can be used using the terminal or the implemented GUI.HINT: This tool is a software solution and works additional to the
hardware settings of your screens. The hardware settings will not be changed!
(I simply don’t know how)Command line options-h,--helpshow this help message and exit-bNUMset brightness (float between 0.0 - 1.999 or integer
between 2 - 200)-BNUMset brightness by increment. Hint: To small changes
may not work-c,--countcount the connected screens-dDISPLAYLimit action to this Screen. Use ‘a’ for all, ‘p’ for
primary and ‘np’ for non-primary-gGAMMAset gamma correction. Either one or three float values
between 0 and 10 separated by ‘:’-llist screens, together with ‘-v’ the current values
are shown.-pshow key of primary screen, use -v for more details-rreset (set brightness to 100% and gamma to 1)-tTEMPset gamma using a temperature in Kelvin-uundo last changes (saved in profile [last])-Dset the brightness to 0 or to the last value if it is
already 0-vverbose output including thexrandrcommand which
was used to set the new values.--guishow user interface after processing the other options
(default if no option is present)--versionshow current version--hardApply changes usingxrandreven nothing has changed--virtualdo not apply changes but show potential results--fileFILEfile used for saving profiles and other settings
(default: ~/.extBrightness.xml)-PNAME,--profile-loadNAMEload profile--profile-saveNAMEsave current values as profile. If option –gui is
used too, the final values of it will be saved!--profile-deleteNAMEdelete profile--profile-showNAMEshow profile--profile-listlist all profiles. Use ‘-v’ too for displaying the
saved values.TipsThis program may set all your screens to complete darkness (brightness = 0). For such a situation it is a good idea
to have a key binding on your system to the gui of extBrightness. After it is started you just have to hit[r]and  all screens are set to 100% brightness and gamma 1.If you use option--profile-saveNAMEand--guitogether, the final values from the gui
are saved to the profileNAME.WithextBrightness-dnp-Dyou can switch all external screensoffandonagain. Please check before,
if one of your screens is set as primary! If you are not sure useextBrightness-p. If the output is empty,
you have to define a screen as primary first (typically using your OS settings > screens > select one > set primary).The values applied (byxrandr) to your system are not necessary exactly the same as you use in the options. Therefore small
changes may not have always an effect. Of course, you can bidn this command to a key using your OS to make it even more easy.
Package: extcats
tools to organize and query astronomical catalogsThis modules provides classes to import astronomical catalogs into
amongodbdatabase, and to efficiently query this database for
positional matches.Description:The two main classes of this module are:CatalogPusher: will process the raw files with the catalog sources and creates a database. Seeinsert_examplenotebook for more details and usage instruction.CatalogQuery: will perform queries on the catalogs. Seequery_examplefor examples and benchmarking.Supported queries includes:all the sources with a certain distance.closest source at a given position.binary search: return yes/no if anything is around the positon.user defined queries.The first item on the above list (cone search around target) provides the basic block for the other two types of positional-based queries. The code supports tree types of basic
cone-search queries, depending on the indexing strategy of the database.usingHEALPix: if the catalog sources have been assigned an HEALPix index (usinghealpy).usingGeoJSON(or ‘legacy coordinates’): if the catalog documents have the
position arranged in one of these two formats (example), the query is based on
the$geoWithinand$centerSpheremongo operators.raw: this method uses the$wherekeyword to evaluate on each document ajavascriptfunction computing the angular distance between each source and the target. This method
does not require any additional field to be added to the catalog but has, in general,
poorer performances with respect to the methods above.All the core functions are defined in thecatquery_utilsmodule. In all cases the
results of the queries will be return anastropy.table.Tableobjects.Notes on indexing and query performances:The recommended method to index and query catalogs is based on the GeoJSON coorinate type.
See theexample_insertnotebook for how this can be implemented.Performant queries requires the database indexes to reside in the RAM. The indexes are
efficiently compressed by mongodb default engine (WiredTiger), however there is little
redundant (and hence compressible) information in accurately measured coordinate pairs.
As a consequence, GeoJSON type indexes tends to require fair amount of free memory (of
the order 40 MB for 2M entries). For large catalogs (and / or small RAM) indexing on
coordinates might not be feasible. In this case, the HEALPix based indexing should
be used. As (possibly) many sources shares the same HEALPix index, compression is
more efficient into moderating RAM usage.Installation:The easiest way to install the Python library is with pip:pip install extcatsIf you want do modifyextcatsitself, you’ll need an editable installation.
After cloning this Git repository:poetry installUsefull links:mongodb installationhealpyastropy
Package: extclass
Ext-ClassAdding fields/methods to existing classes.A Python approach to the greatextensionsfeature in C# and Kotlin, and probably the closest.How to usepip install extclassSuppose you have aPersonclass in an already installed package:fromdataclassesimportdataclass@dataclassclassPerson:first_name:strlast_name:strThen, you could add an extra method outside the source package somewhere in your project.fromextclassimportextension@extensionclassPersonExt(Person):age:int=10deffull_name(self):returnf'{self.first_name}{self.last_name}'With the help of the@extensiondecorator, new fieldageandfull_nameare added to the originPersonclass. You can just call them as usual.if__name__=='__main__':person=Person(first_name='rick',last_name='sanchez')print(person.full_name())print(person.age)which print asrick sanchez
10However, the IDE cannot know the dynamic informations of the added attributes, so there would be a warning message:Unresolved attribute reference 'full_name' for class 'Person'And no autocomplete for the attributes in the IDE.To handle the warnings also enabling autocomplete, you can simplytyping.castthe origin object to the new extended type.fromtypingimportcastperson=cast(PersonExt,person)In this case,personis still the old object but only marked as the extended type in order to cheat the IDE for better programming experiences.No OverrideSame method/field name in the extending class will not affect the origin class. So this package is very safe in any use-cases.Pydantic issuesClasses ofpydantic.BaseModelcan only attach new methods. Dynamic fields are internally forbidden by the pydantic package. So please doNOTextend fields for pydantic models, or anAttributeErrorwould be raised during runtime.Full examplesSeetest.py
Package: ext-distributions
##ext-distributionsPackage currently supports calculation and visualization of binomial and gaussian distributionsInstallationUse the package managerpipto install ext_distributions.pipinstallext-distributionsUsage Gaussian distributionfromext_distributionsimportGaussiangaussian=Gaussian()gaussian.read_data_file('filename')#The txt file should have one number (float) per linegaussian.plot_histogram()#Output's a histogram of current data filegaussian.plot_histogram_pdf()#plot the normalized histogram of the data and a plot of the probability density function along the same rangeUsage Binomial distributionfromext_distributionsimportBinomialbinomial=Binomial()binomial.read_data_file('filename')#The txt file should should contain only 0 or 1 per line(1=positive case)binomial.replace_stats_with_data()#updates mean and standard deviation(do use it after reading a text file)binomial.plot_bar()#Output's a bargraph of current data filebinomial.plot_bar_pdf()#Plot's the pdf of the binomial distributionUsage Other#Adding of two gaussian objectsgaussian_three=gaussian_one+gaussian_two#Adding of two binomial objects with same probability(p) valuebinomial_three=binomial_one+binomial_twoLicenseMIT
Package: extendable-pydantic
Extendable PydanticThis addons provides a new type used to declarePydanticmodel asExtendableclass.From release 1.0.0 it only supports Pydantic >= 2.0.0.frompydanticimportBaseModelfromextendable_pydanticimportExtendableModelMetafromextendableimportcontext,registryclassLocation(BaseModel,metaclass=ExtendableModelMeta):lat=0.1lng=10.1classExtendedLocation(Location,extends=Location):name:str_registry=registry.ExtendableClassesRegistry()context.extendable_registry.set(_registry)_registry.init_registry()loc=Location(**{"lat":12.3,"lng":13.2,"name":"My Loc"})loc.model_dump()=={"lat":12.3,"lng":13.2,"name":"My Loc"}#> Trueloc.model_json_schema()#> {'title': 'Location', 'type': 'object', 'properties': {'lat': {'title': 'Lat', 'default': 0.1, 'type': 'number'}, 'lng': {'title': 'Lng', 'default': 10.1, 'type': 'number'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['name']}Developmentpip install -e .Then, copyextendable_pydantic_patcher.pthto$VIRTUAL_ENV/lib/python3.10/site-packages.Releaserun ``bumpversion patch|minor|major --listCheck the new_version value returned by the previous commandrun towncrier build.Inspect and commit the updated HISTORY.rst.git tag {new_version} ; git push --tags.
Package: extended-enum
extended-enumIntroductionPackage that expands the capabilities of the standard Enum.Featuresstore additional information inside Enum memberInstallpipinstallextended-enumUsageQuick Startfromdataclassesimportdataclass,fieldfromenumimportuniquefromtypingimportOptionalfromuuidimportUUIDfromextended_enumimportExtendedEnum,ValueWithDescription,BaseExtendedEnumValue,EnumField@dataclass(frozen=True)classSomeExtendedEnumValue(BaseExtendedEnumValue):display_name:str=field(compare=False)description:Optional[str]=field(default=None,compare=False)classMixedEnum(ExtendedEnum):"""A combined enumeration in which member values are of different types."""CONST1=EnumField('const1')CONST2=EnumField(1)CONST3=EnumField(UUID('79ff3431-3e98-4bec-9a4c-63ede2580f83'))NOT_DUPLICATE_CONST3=EnumField('79ff3431-3e98-4bec-9a4c-63ede2580f83')CONST4=EnumField(BaseExtendedEnumValue(value='const4'))CONST5=EnumField(BaseExtendedEnumValue(value=2))CONST6=EnumField(BaseExtendedEnumValue(value=UUID('e7b4b8ae-2224-47ec-afce-40aeb10b85e2')))CONST7=EnumField(ValueWithDescription(value='const7'))CONST8=EnumField(ValueWithDescription(value=3,description='some const8 description'))CONST9=EnumField(SomeExtendedEnumValue(value='const9',display_name='some display name',description='some const9 description'))unique(MixedEnum)>>>MixedEnum.CONST9<MixedEnum.CONST9: SomeExtendedEnumValue(value='const9', display_name='some display name', description='some const9 description')>>>>MixedEnum.CONST9.value'const9'>>>MixedEnum.CONST9.extended_valueSomeExtendedEnumValue(value='const9', display_name='some display name', description='some const9 description')>>>MixedEnum.get_values()Tuple('const1',1,UUID('79ff3431-3e98-4bec-9a4c-63ede2580f83'),'79ff3431-3e98-4bec-9a4c-63ede2580f83','const4',2,UUID('e7b4b8ae-2224-47ec-afce-40aeb10b85e2'),'const7',3,'const9')>>>MixedEnum.get_extended_values()Tuple(BaseExtendedEnumValue(value='const1'),BaseExtendedEnumValue(value=1),BaseExtendedEnumValue(value=UUID('79ff3431-3e98-4bec-9a4c-63ede2580f83')),BaseExtendedEnumValue(value='79ff3431-3e98-4bec-9a4c-63ede2580f83'),BaseExtendedEnumValue(value='const4'),BaseExtendedEnumValue(value=2),BaseExtendedEnumValue(value=UUID('e7b4b8ae-2224-47ec-afce-40aeb10b85e2')),ValueWithDescription(value='const7', description=None),ValueWithDescription(value=3, description='some const8 description'),SomeExtendedEnumValue(value='const9', display_name='some display name', description='some const9 description'))LicenseThis project is licensed under theApache-2.0License.
Package: extended-int
This repository provides a Python base class that implements extended integers.ExampleIn[1]:fromnumbersimportReal,IntegralIn[2]:fromextended_intimportExtendedIntegral,int_infIn[3]:float(int_inf)Out[3]:infIn[4]:print(int_inf)infIn[5]:int(int_inf)---------------------------------------------------------------------------OverflowErrorTraceback(mostrecentcalllast)In[6]:isinstance(int_inf,Real)Out[6]:TrueIn[7]:isinstance(int_inf,Integral)Out[7]:FalseIn[8]:isinstance(2.5,ExtendedIntegral)Out[8]:FalseIn[9]:isinstance(int_inf,ExtendedIntegral)Out[9]:TrueIn[10]:isinstance(2,ExtendedIntegral)Out[10]:True
Package: extendedjson
extendedjsonEasily extend JSON to encode and decode arbitrary Python objects.Getting startedYou cangetextendedjsonfrom PyPI,
which means it's easily installable withpip:python-mpipinstallextendedjsonExample usageSuppose you want to extend the JSON format to handle complex numbers,
which corresponds to the typecomplexin Python.To do that, you need to:Determine how a complex number could look like as a JSON dictionary.
For example, a dictionary with keys"real"and"imag"is enough to determine what complex number we are talking about.SubclassExtendedEncoderand implement the methodencode_complexthat accepts a complex number and returns a dictionary with the format you defined.SubclassExtendedDecoderand implement a methoddecode_complexthat accepts a dictionary with the format you described and returns an instance of acomplexnumber.Here is the code:importextendedjsonasxjsonclassMyEncoder(xjson.ExtendedEncoder):defencode_complex(self,c):return{"real":c.real,"imag":c.imag}classMyDecoder(xjson.ExtendedDecoder):defdecode_complex(self,dict_):returncomplex(dict_["real"],dict_["imag"])Then, you can use your classes with the standard modulejson,
by specifying theclskeyword argument in the functionsjson.load,json.loads,json.dump, andjson.dumps:importjsonc=complex(1,2)c_json=json.dumps(c,cls=MyEncoder)c_=json.loads(c_json,cls=MyDecoder)print(c_)# (1+2j)print(c_==c)# TrueRefer tothis articleto learn more about the internal details ofextendedjson.ChangelogRefer to theCHANGELOG.mdfile.
Package: extended-jsonschema
Extended JSON SchemaA fastJSON Schemavalidator with extensions.Warning: This packages is early stage in active development.DO NOT use it in production yet.FeaturesNo any other programming languages like C/C++ or Rust for speedy execution. Just pure Python and a little Cython magic under the hood.Basic UsagefromextendedjsonschemaimportValidatorvalidator=Validator({"type":"string"})errors=validator(3.14)print(errors)>>>[{'path':[],'keyword':'type','value':'string'}]Licenseextendedjsonschemais offered under the MIT license.