Saravanan666/pypi-org huggingface dataset:
Package: emsal
emsâl ⚖︎[TR]Yargıtay karar aramaarayüzündenkararların, yıl ve karar numarası temelinde yarı otomatik olarak indirilmesini sağlayan Python kütüphanesi.[EN]A Python library that enables semi-automatic downloading of decisions based on year and decision number from the Supreme Court decision searchinterface.➥Yükleme / Installationemsâl, pip paket yönetim sistemi kullanarak yüklenebilir.You can use pip package manager system to installemsâl.pipinstallemsal➥Kullanım / Usageimport emsal

emsal.get_decisions(driver_path, '2019', last_no='1978')➥Nasıl çalışır? / How does it work?[TR]emsâlkütüphanesi temel olarak girdi olarak verilen yılda, belirtilen karar numarası aralığındaki, ilgili anahtar kelimeyi geçiren kararları (en fazla bin adet olmak üzere) bulunulan dizine metin belgesi olarak kaydeder.Programı çalıştırdığınızda aşağıdaki gif'te görüleceği üzere program otomatik olarak anahtar kelime, tarih ve karar numarası kutularını doldurur ve ardından Captcha'yı girmeniz için 10 saniye bekler. Ardından kararları tek tek ilgili dizine kaydeder. Bu noktadan sonra bir şey yapmanıza gerek yoktur. Sistem kararları biner biner getirdiği için, 1000 karar sonra program otomatik olarak durur. Eğer devam etmek istiyorsanız kaldığınız karar numarasından tekrar başlamanız gerekir.[EN]Theemsâllibrary basically saves the decisions (maximum one thousand) that include the relevant keyword in the specified decision number range and in the given year as a text document in the current directory.When you run the program, the program automatically fills in the keyword, date and decision number boxes, as can be seen in the gif below, and then waits 10 seconds for you to enter the Captcha. Then it saves the decisions one by one in the relevant directory. You don't need to do anything after this point. The program stops automatically after 1000 decisions, as the system fetches the decisions one thousand at a time. If you want to continue, you have to start again from the decision number where you left off.
Package: emsarray
emsarrayTheemsarraypackage provides a common interface
for working with the many model geometry conventions used at CSIRO.
It enhancesxarrayDatasets
and provides a set of common operations for manipulating datasets.To use, open the dataset using theemsarray.open_dataset()function
and use thedataset.emsattribute:importemsarrayfromshapely.geometryimportPointdataset=emsarray.tutorial.open_dataset('gbr4')capricorn_group=Point(151.869,-23.386)point_data=dataset.ems.select_point(capricorn_group)Some methods take a DataArray as a parameter:# Plot the sea surface temperature for time = 0temp=dataset['temp'].isel(time=0,k=-1)dataset.ems.plot(temp)A number of operations provide further functionality to manipulate datasets,
export geometry, and select subsets of data:fromemsarray.operationsimportgeometrygeometry.write_geojson(dataset,'./gbr4.geojson')geometry.write_shapefile(dataset,'./gbr4.shp')LinksSource code on GithubDocumentation on Read The Docsemsarray on PyPIemsarray on conda-forgeExamplesExamples of usingemsarrayare available in theemsarray-notebooksrepository.
You canexplore these notebooks onlinewith Binder.DevelopingTo get set up for development, make a virtual environment and install the dependencies:$python3-mvenv
$sourcevenv/bin/activate
$pipinstall--upgradepip>=21.3
$pipinstall-e.-rcontinuous-integration/requirements.txtTestsTo run the tests, install and runtox:$python3-mvenv
$sourcevenv/bin/activate
$pipinstall--upgradepip>=21.3tox
$toxDocumentationThe documentation for the current stable version of emsarray is available on Read The Docs.To build the documentation, install the development requirements as above and invoke Sphinx:$make-Cdocs/htmlWhile updating or adding to the documentation,
run thelivetarget to automatically rebuild the docs whenever anything changes.
This will serve the documentation via alivereloadserver.$make-Cdocs/liveYou can the view the docs athttp://localhost:5500
Package: ems-config
EMS-configThis project introduces a unified way of handling config files. The philosophy is having a text-based config file
(ini, yml or toml) and then perform parsing and sanity-checking in code afterwards. Moreover, a default layout is
encouraged.You need to provide three pathsAnapp_datadirectory. This is where you should put all your data and where your final config file should go.
This is set in an environmental variableAPP_DATA_PATH, which defaults toapp_data.A path to your final config file. This defaults to$APP_DATA_PATH/config.iniif your template file is calledconfig.example.ini(see below).
That is, it strips.examplefrom the filename of you template file.A path to the template file. This defaults toconfig.example.ini.Notice that 2 and 3 can both be set in the following parse-method or in environmental variables (CONFIG_PATHandCONFIG_TEMPLATE_PATH)The assumed layout of you directory would then be something likeproject
  - app_data/
    - config.ini
  - app.py
  - config.py
  - config.example.iniWhereconfig.pycontains the following,from ems_config import parse_config

config = parse_config()

URL = config["DEFAULT"]["URL"]and the templateconfig.ini.examplecontains an example of the configuration,[DEFAULT]
URL = http://google.comYou can then use the configuration in other python files like this,from config import URL
print(URL)  # do stuff with the URLNotice, if theconfig.iniinapp_data(or where ever you choose to place it), the template
will be copied to that location.Helper methodsThis library provides a few helper methods found inems.helpers# Get the path of p relative to the APP_DATA_DIRget_from_app_data(p)## Help to parse from .ini style filesparse_dt_or_none(...)parse_list_or_none(...)CustomizationIf you don't want your template to be named after the above scheme, you can pass another template
path into theparse_config()methods. Likewise, if you want you final config file to be located elsewhere,
you can also provide another pathfromems_configimportparse_config# config_path will default to $APP_DATA_PATH/cfg.iniconfig=parse_config(config_template='templates/cfg.example.ini')config=parse_config(config_template='templates/cfg.ini',config_path='/etc/app.ini')
Package: emscraper
EmscraperAn module which helps to scrape emails from Google Search and mail it to the given email address after email validation for getting deleverable email ids.BadgesFeaturesYou can build your own free email list.You can get valid emails from Google.We validate each emails before sending the list to your mail.Easy to use & free.InstallationInstall my-project with pippipinstallemscraperDependencyEmscraper requires following programs to run properly :requestsBeautifulSoupsmtplibInstall selenium using pip command :pipinstallrequestspipinstallBeautifulSouppipinstallsecure-smtplibUsage/Examplesfromemscraperimportscrapescrape('Your_Audience_Niche','Your Email ID')RoadmapAdd more feactures.Get HTML Page on Mail.Authors@zandora-spaceSupportFor support, emailprofessor@zandora.spaceor follow our Instagram Page@zanx.codersFeedback/IssuesIf you have any feedback, please reach out to us atprofessor@zandora.spaceIf you have facing any issues, please report viaReport IssuesLicenseMIT
Package: ems-dash-utils
Dash utilitiesdash_utilsThis module containes convient methods to typical dash related methods:Timezone relatedTo make the client timezone available in callbacks, invoke the following during you setupinit_client_tz_javascript(dashappp)This adds a small snippet of javascript, which sets a cookie with the timezone. After this, a couple of functions
has been implemented to conveniently deal withdatetimeobjects such asget_client_tz()to_client_tz(dt)format_client_date()parse_client_date()Notice the two last functions usesdash_utils.CLIENT_DATE_FORMATwhich defaults to%Y-%m-%d %H:%M:%S.Dash callback relatedTwo functions to deal with the trigger source of a callback has also been implementedwas_source(id_str)
get_source()keycloak_utilsThis module implements some convenient functions when integrating with dash-keycloak and dealing with roles.Firstly, one should set the client inkeycloak_utils.KEYCLOAK_CLIENT.It is now possible to check if a user has a given role or even decorate a flask route to abort with 401 if the user does not have a role from a given list.check_role("admin")@require_role(["READ","WRITE"])@app.route('/api/status',methods=["GET"])defdo_stuff():...Read and writeA small scheme to determine read and write access has also been implemented. In this scheme
a user can have either READ or WRITE access to asubject.The role names is thus defined as<subject>/READ,<subject>/WRITEor<subject>/ALL.
Theadminrole has special privileges, i.e. both READ and WRITE for all subjects.A users access for a subject can now be checked withhas_read_access(subject)has_read_write(subject)
Package: ems-dataflow-testframework
ems-dataflow-testframeworkPurpose of the projectThis framework aims to help test Google Cloud Platform dataflows in an end-to-end way.How to develop locallyUsevirtualenvpreferably to manage Python dependencies.pipinstall-rrequirements.txtHow to run unit testsmaketestHow to run statical code analysismakecheckHow to contributeFork the repository and apply your changes. Pull requests are welcome. Please pay attention on the commit messageconventions. Thanks in advance!How to releaseReleasing is managed bypython-semantic-releasewhich means your commit messages define the upgraded version number. Use the following convention during writing commit messages:fix({SCOPE}): {BODY} -> patchfeat({SCOPE}): {BODY} -> minorxxx({SCOPE}): {BODY} -> BREAKING CHANGE -> majorIf you are unsure how to write valid commit messages enforce yourself with using tools likecommitizen.To trigger a release mergemasterbranch intoreleaseand push it.LicenseMIT
Package: ems-deploy
EMS Deploy scriptThis project provides a general-purpose deploy script for the EMS projects. It runs the suitable docker-compose command based on the available docker-compose files located in the directory.Installpip install ems-deployDirectory structure and required filesDeploy concatenates adocker-composecommand.docker-compose.ymlRequired.docker-compose.deploy.ymlDefault if no tags are given when running the command.docker-compose.<tag1>.<tag2>.<etc>.ymlOptional. Notice there can be any number of tags.How to usedeploy [-h] [-d] [-v] [--dry-run] [--flags "<flag1> <flag2>"] [tag]If a tag is supplied, it will append all parent-tags too, and they are required. I.e. if we
run the commanddeploy debug.test, it will add (and require) the following three filesdocker-compose.yml
docker-compose.debug.yml
docker-compose.debug.test.ymlNotice one can also use the full file as a tag. That is, the following command will give the same resultdeploy docker-compose.debug.test.yml.The first level tag will be used as the project name, i.e. thedocker-compose -pcommand.Configuration fileAn argument string can be saved to a file named.ems-deploy.
The arguments in this string will then automatically be added to thedeploy-command.
Additional arguments to thedeploy-command will overwrite the commands from the configuration file.NotesThe following flags are always added to thedocker-composecommand:--force-recreate--renew-anon-volumes--buildIf the first level tag isdeploy, the-dis automatically added.DeployTo deploy the app withdocker-compose.ymlanddocker-compose.deploy.yml, simply rundeployAdditional flags-dDetaches the process (this is automatically done in deploy-mode, but not in debug-mode)-vWrites the resulting command to the terminal.--dry-runWill not execute the command--flagsChange default flags. Must specify a sting afterwards, e.g.--flags "--force-recreate --build"
Package: ems-eploy
EMS Deploy scriptThis project provides a general-purpose deploy script for the EMS projects. It runs the suitable docker-compose command based on the available docker-compose files located in the directory.Installpip install ems-eployDirectory structure and required filesDeploy concatenates adocker-composecommand. The following files are recognizeddocker-compose.ymlRequired: Base filedocker-compose.deploy.ymlRequired: This file is added as an additional docker-compose filedocker-compose.debug.ymlOptional: This files is used instead ofdocker-compose.deploy.ymlwhen using thedebugflagHow to useThe following flags are always added to thedocker-composecommand:--force-recreate--renew-anon-volumes--buildDeployTo deploy the app, simply rundeployNote that it will automatically add the-dflag which detaches from the process afterwards.DebugTo run in debug mode, rundeploy debugNote that it will NOT automatically detach - this can however be supplied. See the next section for additional flagsAdditional flags-dDetaches the process (this is automatically done in deploy-mode, but not in debug-mode)-vWrites the resulting command to the terminal.
Package: emsg
emsgAn ISO BMFF emsg atom generator.  This cli generates an emsg atom file with any given parameters.  You can insert it into an mp4 file by using an mp4 file editor such as Bento4'smp4editto deliver in-band media timed event data for MPEG-DASH, HLS, and so on.Installation$pipinstall--upgradeemsgUsage$emsg--help
usage:emsg[-h][-oOUT][-sSCHEME_ID_URI][--box_version{0,1}][-iID][--valueVALUE][-mMESSAGE_DATA][--presentation_timePRESENTATION_TIME][--presentation_time_deltaPRESENTATION_TIME_DELTA][--timescaleTIMESCALE][--event_durationEVENT_DURATION]options:-h,--helpshowthishelpmessageandexit-oOUT,--outOUTsetfilenametooutput(default=./emsg.atom)-sSCHEME_ID_URI,--scheme_id_uriSCHEME_ID_URIsetschemeiduritoidentifythemessagescheme(default=https://aomedia.org/emsg/ID3)--box_version{0,1}setemsgboxversion(default=1)-iID,--idIDsetid(default=0)--valueVALUEsetvalueforeventstreamelements(default=1)-mMESSAGE_DATA,--message_dataMESSAGE_DATAsetmessagedata--presentation_timePRESENTATION_TIMEsetpresentationtimeforemsgversion1(default=450000)--presentation_time_deltaPRESENTATION_TIME_DELTAsetpresentationtimedeltaforemsgversion0(default=450000)--timescaleTIMESCALEsettimescale(default=90000)--event_durationEVENT_DURATIONseteventduration(default=270000)ExamplesTo generate an emsg box file named "sample-emsg.atom" containing the metadata below:timescale = 90000presentation time = 270000event duration = 180000id = 0scheme id uri = "urn:mpeg:dash:event:2012"value = "1"message data = "A sample message data"Run the command below:$emsg-osample-emsg.atom--timescale90000--presentation_time270000--event_duration180000-i0-surn:mpeg:dash:event:2012--value1-m"A sample message data"Format supportFormatSupportsemsg version 0Yemsg version 1YID3 Metadata in emsg (version 1)Y
Package: emsigma
DescriptionSpectral Interpretation using Gaussian Mixtures and Autoencoder (SIGMA)is an open-source Python library for phase identification and spectrum analysis for energy dispersive x-ray spectroscopy (EDS) datasets. The library mainly builds on theHyperspy,Pytorch, andScikit-learn. The publication is availablehere.(UPDATE v0.2.0)SIGMA now supportsUMAPfor dimensionality reduction andHDBSCANfor clustering.Try your dataset on SIGMA with Colab in the cloud:Type of dataSupport formatColab linkSEM.bcf.hspyTEM.emi/.ser.emdImages.tif.pngThis project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101005611:The EXCITE Network. If analysis using SIGMA forms a part of published work please cite themanuscript.InstallationCreate aPython>=3.10environment withconda:condacreate-nsigmapython=3.10
condaactivatesigmaInstallSIGMAwithpip:pipinstallemsigmaUse the notebook in the tutorial folder to runSIGMA.jupyter-labWorkflow of SIGMAA neural network autoencoder is trained to learn good representations of elemental pixels in the 2D latent space.The trained encoder is then used to transform high-dimensional elemental pixels into low-dimensional representations, followed by clustering using Gaussian mixture modeling (GMM) in the informative latent space.Non-negative matrix factorization (NMF) is applied to unmix the single-phase spectra for all clusters.In such a way, the algorithm not only identifies the locations of all unknown phases but also isolates the background-subtracted EDS spectra of individual phases.User-friendly GUICheck .bcf fileAn example of checking the EDS dataset and the sum spectrum.Demo with ColabDimensionality reduction and clusteringAn example of analysing the latent space using the graphical widget.Demo with ColabFactor analysis on cluster-wise spectraA demo of acquiring Background-substracted spectrum using Factor Analysis (FA).Demo with Colab
Package: ems-logging
EMS loggingSetupEither import this as a git submodule package (for development) andimport emslogging, or simply import theems-logginglibrary from pypi and use the python get logger:importemsloggingimportlogginglogger=logging.getLogger("Zipping")Log level can be set with env variableEMS_LOG_LEVELusing the python logging library levels, e.g.INFO,DEBUG, etc.
Package: emsm
EMSMTheExtendable Minecraft Server Manager(EMSM) handlesmultiple minecraft worldsandserver versions. It is completly written
in Python and can be easily modified by the user.TheEMSMprovides a simple, but powerful and extensive command line interface,
which allows to manage your minecraft server easily and automize tasks.The separation of minecraft worlds and server executables allows to manage
several different versions of server (e.g. Vanilla and Bukkit in
multiple versions) for different worlds. TheEMSMcomes with a backup
mechanism as one of the core plugins, which can be automated to create
periodical backups. It also provides a plugin to check the availability
of the server and restart them, if its configured to do so. Another plugin aims
at integratingEMSMwithinit.dto start/stop the server on
(re-)boot/shutdown processes.Get startedPlease read theonline documentationfor
a full introduction. I tried to keep it simple and short. The EMSM will
be installed in less than 10 minutes.When you need help, don’t hesitate to create an issue.Contribution and New PluginsIf you have a good idea for a new plugin,let us know:).When you found a bug, please report it.VersioningTheEMSMuses semantic version numbers. Take a look athttp://semver.org/for further information.License0.0.0-beta - 2.0.0-beta:GNU GPL v32.0.1-beta - current release:MIT License.
Package: ems-simple-logger-config
ems-simple-logger-configThis is a simple (file) logger configuration for Python.Installation:pip install ems-simple-logger-configOn app level: Initialize logger with default values to get a common console output:from logger import logger

log = logger.setup_logger()
log.info('Some text')On app level: Alternatively initialize logger with some configuration. If file_name is added a log file will be created.from logger import logger

log = logger.setup_logger(logger_name = 'SomeLoggerName', log_level = logging.DEBUG, file_name = 'log.txt')
log.info('Some text')On module level get the logger byfrom logger import logger

log = logger.get_logger(__name__)
log.info('Some text')
Package: emtable
Emtable is a STAR file parser originally developed to simplify and speed up metadata conversion between Scipion and Relion. It is available as a small self-contained Python module (https://pypi.org/project/emtable/) and can be used to manipulate STAR files independently from Scipion.How to citePlease cite the code repository DOI:10.5281/zenodo.4303966AuthorsJose Miguel de la Rosa-Trevín, Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, SwedenGrigory Sharov, MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, EnglandTestingpython3-munittest discover emtable/testsExamplesTo start using the package, simply do:fromemtableimportTableEach table in STAR file usually has adata_prefix. You only need to specify the remaining table name:Table(fileName=modelStar,tableName='perframe_bfactors')Be aware that from Relion 3.1 particles table name has been changed from “data_Particles” to “data_particles”.ReadingFor example, we want to read the wholerlnMovieFrameNumbercolumn from modelStar file, tabledata_perframe_bfactors.The code below will return a list of column values from all rows:table=Table(fileName=modelStar,tableName='perframe_bfactors')frame=table.getColumnValues('rlnMovieFrameNumber')We can also iterate over rows from “data_particles” Table:table=Table(fileName=dataStar,tableName='particles')forrowintable:print(row.rlnRandomSubset,row.rlnClassNumber)Alternatively, you can useiterRowsmethod which also supports sorting by a column:mdIter=Table.iterRows('particles@'+fnStar,key='rlnImageId')If for some reason you need to clear all rows and keep just the Table structure, useclearRows()method on any table.WritingIf we want to create a new table with 3 pre-defined columns, add rows to it and save as a new file:tableShifts=Table(columns=['rlnCoordinateX','rlnCoordinateY','rlnAutopickFigureOfMerit','rlnClassNumber'])tableShifts.addRow(1024.54,2944.54,0.234,3)tableShifts.addRow(445.45,2345.54,0.266,3)tableShifts.write(f,tableName="test",singleRow=False)singleRowisFalseby default. IfsingleRowisTrue, we don’t write aloop_, just label-value pairs. This is used for “one-column” tables, such as below:data_general_rlnImageSizeX3710_rlnImageSizeY3838_rlnImageSizeZ24_rlnMicrographMovieNameMovies/20170629_00026_frameImage.tiff_rlnMicrographGainNameMovies/gain.mrc_rlnMicrographBinning1.000000_rlnMicrographOriginalPixelSize0.885000_rlnMicrographDoseRate1.277000_rlnMicrographPreExposure0.000000_rlnVoltage200.000000_rlnMicrographStartFrame1_rlnMotionModelVersion1
Package: emtex_common_utils
This contains utility like permissions, audit log etc.Detailed documentation is in the “docs” directory.How to installUsing pip:pip install emtex_common_utils==0.3
    or
Add emtex_common_utils==0.3 in your requirements.txt file and then run:
pip install -r requirements.txtQuick startAdd “emtex_common_utils” to your INSTALLED_APPS setting like this:INSTALLED_APPS = [
    ...
    'emtex_common_utils',
]Things availableDatabase Migrations:python manage.py emtex_migrate --for_date="YYYY-MM-DD"Logging:from emtex_common_utils.models import BaseModel, BaseLogModel
from emtex_common_utils.mixins import BaseModelMixin

...


class MyModelLog(BaseLogModel):
    """ Model to log changes for model MyModel """
    pass


class MyModel(BaseModel, BaseModelMixin):
    """ Model which changes needs to be tracked. """

    class Meta:
        log_fields = (
            my_field1, my_field2,
            ...
        )
        log_model_name = MyModelLog
Package: emt-madrid
EMTMadridPython wrapper for the Madrid EMT (Empresa Municipal de Transportes) API, providing easy access to real-time transportation data in Madrid.InstallInstall the package using pip:pipinstallemt-madridAuthentication InstructionsTo use the EMT Mobilitylabs API you need to register in theirwebsite. Once you are registered you will receive a confirmation email to activate your account. It will not work until you have completed all the steps.UsageimportasynciofromaiohttpimportClientSessionfromemt_madridimportEMTAPIAuthenticator,EMTAPIBusStopEMAIL="email-from-EMT"PASSWORD="password-from-EMT"STOP_ID="stop-id-from-EMT"# For example: "72"asyncdeffetch_bus_info():"""Fetches bus information from the EMT API."""asyncwithClientSession()assession:emt_api_authenticator=EMTAPIAuthenticator(session,EMAIL,PASSWORD)awaitemt_api_authenticator.authenticate()token=emt_api_authenticator.tokenemt_api_bus_stop=EMTAPIBusStop(session,token,STOP_ID)awaitemt_api_bus_stop.update_stop_info()awaitemt_api_bus_stop.update_bus_arrivals()returnemt_api_bus_stop.get_stop_info()asyncdefmain():"""Main function to execute the code."""bus_info=awaitfetch_bus_info()print(bus_info)asyncio.run(main())AttributionThanks toEMT Madrid MobilityLabsfor providing the data anddocumentation.
Package: emtools
Utilities for CryoEM data manipulation.InstallationpipinstallemtoolsOr for development:gitclonegit@github.com:3dem/emtools.gitcdemtoolspipinstall-e.UsageTestingpython-munittestemtools.tests.test_utilspython-munittestemtools.tests.test_metadatapython-munittestemtools.tests.test_pipelineHow to citePlease cite the code repository DOI: xxxAuthorsJose Miguel de la Rosa-Trevín, St.Jude Children’s Research Hospital, Memphis, TN