Saravanan666/pypi-org huggingface dataset:
Package: dectest
Improved TestCase Classdectest.TestCaseis a drop-in replacement forunittest.TestCasewith
a few added features.Tests, Setup, and Teardown with DecoratorsTests can optionally be marked using the@testdecorator, instead of
prefixing the method name withtest. The following test case class
contains two tests:fromdectestimportTestCase,testclassMyTest(TestCase):deftest_foo(self):pass@testdefbar(self):passSetup and teardown methods can be marked using the@beforeand@afterdecorators, respectively. A class can have multiple setup and teardown
methods:fromdectestimportTestCase,before,afterclassMyTest(TestCase):@beforedefsetup_stuff(self):pass@beforedefsetup_more_stuff(self):pass@afterdefteardown_all_stuff(self):passWhile the order of execution inside a class is undefined and should not be
relied upon, it is guaranteed that setup methods in super-classes are
executed before methods in sub-classes, and teardown methods in sub-classes
are executed before teardown method in super-classes:fromdectestimportTestCase,before,afterclassMySuperTest(TestCase):@beforedefsuper_setup(self):print("setup first")@afterdefsuper_teardown(self):print("teardown second")classMySubTest(MySuperTest):@beforedefsub_setup(self):print("setup second")@afterdefsub_teardown(self):print("teardown first")Patch Supportdectest.TestCasehas apatch()method to install a mock usingunittest.mock.patch(). This patch is removed during test
teardown:fromdectestimportTestCase,testclassMyPatchTest(TestCase):@testdeffoo(self):exit=self.patch("sys.exit")# will be stopped during teardown# call implementationexit.assert_called_with(1)
Package: decto
DectoCài đặt FasterRCNN sử dụng Feature Pyramid Network.Thư viện decto hướng tới việc đơn giản khi sử dụng, code ngắn gọn, dễ hiểu và độ chính xác tương tự như thư viện detectron2, đồng thời giúp cho các bạn có thể custom code cho các dự án khác.Thư viện này được áp dụng cho các dự án số hóa và đã đem lại kết quả rất tốt trên tập dữ liệu .Cài đặtĐể cài đặt các bạn chạy lệnh saupip install dectoKết quả thử nghiệmKết quả huấn luyện bằng decto có độ chính xác bằng với các thư viên khác nhưdetectron2, hoặcpytorch-faster-rcnnCài đặtVOC 2007Số hóadetectron20.750.decto0.750.81Train & InferenceCác bạn tham khảo notebook sauDatasetCác bạn chuẩn bị cấu trúc dataset dưới dạng sau├── img
│   ├── a.jpg
│   ├── b.jpg
├── test.json
└── train.jsonFile json train và test có định dạng như dưới:{
'class_names':['bird', 'car'],
'annotations':
[
  {'fname':'img/a.jpg', 'bbox':[[10, 20], [30, 40]], 'label':[0, 0]}
  {'fname':'img/b.jpg', 'bbox':[[20, 50], [40, 70]], 'label':[0, 1]}
]
}ProblemNếu bạn có bất kì vấn đề gì, vui lòng tạo issue hoặc liên hệ mình tạipbcquoc@gmail.com
Package: dectools
DecTools provides a library of tools for creating Python decorators.  It
unifies usage between class decorators, decorators requiring arguments,
and simple decorators.  It also provides correct names, doc, and function
signatures for decorated functions.  Typical usage often looks like this:@make_call_once
def register_callback(function):
      gui.callback_create(function.__name__, function)

@make_call_before
def require_login(function, args, kwargs, page_name):
     while not current_user_id():
        ...

@register
@require_login("Summary of Items")
def view_summary():
    ...You can find manuals in docs/index.html.
Package: decyclify
decyclifyGraph decyclify algorithm implementation as in Sandnes & Sinnen paper (2004) in Python."A new strategy for multiprocessor scheduling of cyclic task graphs", link toarticle in Research Gate.See open issues for current status of the project.decyclify algorithmThe algorithm uses two matrices,DandC.Dis theintraiteration dependenciesmatrix. It represents the dependencies
in the graph within a cycle.Cis theinteriteration dependenciesmatrix. It represents the dependencies
in the graph between cycles.Node IteratorsThis is not part of the paper. Here we show how the algorithm can be used to first remove the
cycles. Next, we use the matrices to decide how to traverse the graph.The first iterator, theCycleIteratorsimply goes through all the tasks in the cycles and executes
them in order. Thedecyclifyfunction is used to avoid repeating a node due to a cycle.The second iterator available is theTasksIterator. With this, for each cycle it returns the next tasks
available, as well as any tasks in the next cycles that can be returned.A task is considered ready to be returned when its sibling in the previous cycle has been executed, and after
its inter-cycle dependency (if any) has been satisfied as well.It should be possible to use these iterators, or create new ones, and apply it to tools
such as workflow managers that support only DAG scheduling, to schedule an infinite
graph, viagraph-unrolling. The next cycle is simply an integer counter incremented,
but could be an ISO8601 date-time function.NOTE: this part of the project was a summer holidays project, and is in need of documentation,
more tests, code review, etc. Feel free to submit pull requests.Changelog0.1 (2020-12-29)Added a couple of node iterators. With these, it is possible to iterate the graph per cycle, or per task. This latter enables a task to start as soon as its sibling in a previous cycle has been executed, as long as there are no inter-cycle dependencies.#3Implemented the algorithm to unroll a graph using the Decyclify algorithm#10Create intraiteration matrix (D) and interiteration matrix (C)#2Graph input#1Build and packagingLicenseLicensed under the Apache License. SeeLICENSEfor more.
Package: decy-tools
decy-toolsFeaturesProvides extensible CLI application with ability to easily add functionalityRequires Python 3.8.2 or higherTechThis application uses the following:Pytest- Unit testing libraryCoverage- Unit testing extension to test branch coverageRequests- Python HTTP libraryPrompt-Toolkit- Python Library to ease CLI buildoutGitlab CI- Used to build developement sdlc pipelineSetuptools-SCM- Python automated versioning libraryTwine- used to upload package to PyPiInstallationRunpip install decy-toolsEnsure that you haveDECY_GATEWAY_TOKENset as an environment variable. See ITG for the token. The application will use this to authenticate against our api gatewayUsage:Currently the usage in place is:usage:decy-tool[-h]{new-email-interactive}...

positionalarguments:{new-email-interactive}optionalarguments:-h,--helpshowthishelpmessageandexitTroubleshootingError:2021-12-03 12:00:20,831 :: root :: CRITICAL :: {"message":"Forbidden"}This means that the API key you have set to the env. variable ofDECY_GATEWAY_TOKENis incorrect.Timeout: This means that the api gateway is unreachable. Check the AWS console to validate the URLLicenseMIT
Package: ded
dedHelm dependency deduplication post-rendererInstallationpipinstalldedUsageThis program collects all pre-rendered manifests from Helm and post-renders only those unique amongst them.The uniqueness is determined based on the default or supplied YAML keys. The keys must exist in all of the supplied documents.Invoke as--post-rendererduring helm install/upgrade.deddetermines uniquiness based on values of thekindandmetadata.namefields of each manifests. You can specify non-default keys by which the pre-rendered manifests from helm must be deduplicated:ded--keymetadata.namespaceIMPORTANT: The keys used to determine uniquiness must be present in every manifest ordedwill exit with code 1 andhelm installorhelm upgradewill consequently fail.ExamplesThe example below will filter all manifests based on values ofkindandmetadata.namefields.helminstallrelease-nameyour-chart/--post-rendererdedSo, if there are 2 manifests in your Helm chart release with the same values on these fields, then only one of them will be left.Manifest A:apiVersion:v1kind:ConfigMapmetadata:name:foo-cmdata:onedata:testManifest B:apiVersion:v1kind:ConfigMapmetadata:name:foo-cmdata:twodata:test-testIn the example above only the first occuring manifest will make it to the output of the post-renderer.Or invoke with a different set of keys:helminstallrelease-nameyour-chart/--post-rendererded--keymetadata.nameMore keys:helminstallrelease-nameyour-chart/--post-rendererded-kmetadata.name--kdata.onedataWhyded?Because it's a shorthand fordeduplicationBecause"ded"means grandpa inRussian. And I was grumpy as hell when I was trying to deduplicate manifests generated by Helm.Because dealing with subcharts and dependencies in Helm makes you a littledeadinside.Helm is ❤️
Package: dedalov2
DedaloDedalo explains why a set of URIs belongs together.ExampleHave a look at the example below and get going in seconds!We'll use the fileabba.txtas input. Its contents are:1,http://dbpedia.org/resource/Benny_Andersson
1,http://dbpedia.org/resource/Björn_Ulvaeus
1,http://dbpedia.org/resource/Agnetha_Fältskog
1,http://dbpedia.org/resource/Anni-Frid_Lyngstad
2,http://dbpedia.org/resource/Linus_Torvalds
2,http://dbpedia.org/resource/Avicii
2,http://dbpedia.org/resource/Stellan_Skarsgård
2,http://dbpedia.org/resource/Markus_PerssonThe number at the start of each line indicates thegroupthe URI belongs to. You can use any number you like, as long as it's an integer.You can use the following code to explain group 1.importdedalov2asddlforexplanationinddl.explain("the-internet.hdt","abba.txt",minimum_score=1,groupid=1):print(explanation)The results depend on thehdtfile you're using. If it includes URIs from DBPedia, the results look something like this:http://dbpedia.org/property/label -| http://dbpedia.org/resource/Polar_Music
http://dbpedia.org/property/associatedActs -| http://dbpedia.org/resource/ABBA
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Anni-Frid_Lyngstad
http://www.w3.org/2004/02/skos/core#subject -| http://dbpedia.org/resource/Category:ABBA_members
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Cher
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Polar_Music
http://dbpedia.org/ontology/associatedBand -| http://dbpedia.org/resource/ABBA
http://dbpedia.org/ontology/associatedMusicalArtist -| http://dbpedia.org/resource/ABBA
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Svensktoppen
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Eurovision_Song_Contest
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/ABBA
http://dbpedia.org/property/wikiPageUsesTemplate -| http://dbpedia.org/resource/Template:infobox_musical_artist
http://dbpedia.org/property/wikilink -| http://dbpedia.org/resource/Rik_Mayall
http://dbpedia.org/ontology/label -| http://dbpedia.org/resource/Polar_MusicThese URIs are long and difficult to read.
Readthe docsto learn how to make the output look better.InstallationDedalov2 requires Python 3 and can be installed using Python's package manager, pip.pipinstalldedalov2Depending on your use case, you may want to pass the-Uflag or run this in a virtual environment.DocumentationSee thedocumentation pagefor more examples.
Package: dedalus
Dedalus ProjectDedalus is a flexible framework for solving partial differential equations using modern spectral methods.
The code is open-source and developed by a team of researchers studying astrophysical, geophysical, and biological fluid dynamics.Dedalus is written primarily in Python and features an easy-to-use interface with symbolic vectorial equation specification.
For example, to simulate incompressible hydrodynamics in a ball, you can symbolically enter the equations, includinggauge conditionsandboundary conditions enforced with the tau method, as:problem.add_equation("div(u) + tau_p = 0")problem.add_equation("dt(u) - nu*lap(u) + grad(p) + lift(tau_u) = - u@grad(u)")problem.add_equation("u(r=1) = 0")problem.add_equation("integ(p) = 0")Our numerical algorithms produce sparse and spectrally accurate discretizations of PDEs on simple domains, including Cartesian domains of any dimension, disks, annuli, spheres, spherical shells, and balls:KdV-Burgers equation (1D IVP)Rayleigh-Benard convection (2D IVP)Periodic shear flow (2D IVP)Poisson equation (2D LBVP)Librational instability (disk IVP)Spherical shallow water (sphere IVP)Spherical shell convection (shell IVP)Internally heated convection (ball IVP)The resulting systems are efficiently solved using compiled libraries and are automatically parallelized using MPI.
See thedocumentationfor tutorials and additional examples.LinksProject homepage:http://dedalus-project.orgCode repository:https://github.com/DedalusProject/dedalusDocumentation:http://dedalus-project.readthedocs.orgMailing list:https://groups.google.com/forum/#!forum/dedalus-usersDevelopersKeaton Burns (@kburns)Geoff Vasil (@geoffvasil)Jeff Oishi (@jsoishi)Daniel Lecoanet (@lecoanet)Ben Brown (@bpbrown)
Package: deddiag-loader
deddiag-loaderDataloader for DEDDIAG, a Domestic Energy Demand Dataset of Individual Appliances Germany.The dataset contains recordings of 15 homes over a period of up to 3.5 years, wherein total 50 appliances have been recorded at a frequency of 1 Hz. Recorded appliances are of significance for load-shifting purposes such as dishwashers, washing machines and refrigerators. One home also includes three-phase mains readings that can be used for disaggregation tasks. Additionally, DEDDIAG contains manual ground truth event annotations for 14 appliances, that provide precise start and stop timestamps.The dataset is available for download on Figshare:10.6084/m9.figshare.13615073.v1.
For a detailed description of the dataset please seethis publication.InstallThe deddiag-loader is available onpypipip install deddiag-loaderInstall from source (alternative)python setup.py installCLI UsageShow Dataset overviewpython-mdeddiag_loaderstats--host=localhost--password=<password>Save measurements with labels to numpy arraypython-mdeddiag_loadersave--host=localhost--password=<password>The database options can also be provided using environment variables:DEDDIAG_DB_PW=DEDDIAG_DB_USER=DEDDIAG_DB_HOST=DEDDIAG_DB_NAME=Code Examplefromdeddiag_loaderimportConnection,Annotations,MeasurementsExpandedWithLabelscon=Connection(password="password")item_id=10start_date="2016-11-30T20:24:05"stop_date="2019-06-02T17:56:17"annotations=Annotations(item_id,start_date=start_date,stop_date=stop_date).request(con)first_annotation=annotations.iloc[0]# Get Expanded Measurements for first annotationmeasurements=MeasurementsExpandedWithLabels(item_id,first_annotation['label_id'],first_annotation['start_date'],first_annotation['stop_date']).request(con)CitationWhen using the dataset in academic work please citethis paperas the reference.@article{DEDDIAG_2021,
  author = {Marc Wenninger and Andreas Maier and Jochen Schmidt},
  title = {{DEDDIAG}, a domestic electricity demand dataset of individual appliances in Germany},
  year = {2021},
  month = jul,
  publisher = {Springer Science and Business Media {LLC}},
  volume = {8},
  number = {1},
  journal = {Scientific Data},
  doi = {https://doi.org/10.1038/s41597-021-00963-2},
  url = {https://rdcu.be/coGqL},
}AcknowledgementsThe monitoring system and dataset were created as part of a research project of theTechnical University of Applied Sciences Rosenheim.The project was funded by theGerman Federal Ministry of Education and Research (BMBF), grant 01LY1506,
and supported by theBayerische Wissenschaftsforum (BayWISS).LicenseMIT licensed as found in theLICENSEfile.
Package: dedict
DedictDedict is a simple dependency-less library that allows you to create data objects from dictionaries. It currently works on Python 3.6 and 3.7Why Dedict?There's already a few libraries out there that allow you to create objects from json/dictionaries, such asjsonpickle. However these libraries usually rely on metadata stored in the input structure to create the object. That means the serialized object has noisy metadata in it and that the dictionary/json must have been generated with the library to be able to be transformed back into an object.There's alsojsonstructwhich fixes the metadata issue, but requires dataclasses to have "default" values defined for their parameters so that it can read the types at runtime and understand how to create the object.Dedict aims to strive away from these methods, and allow the creation of objects without relying on metadata inside the input data or arbitrary default values within the data class. Instead, dedict makes clever use oftype hintsandvariable annotationsthat were introduced with Python 3.6Installpip install dedictUsage exampleclassSomeDataClass(Dedictable):something:strwhatever:intsome_data_class=SomeDataClass.dedict({'something':'test','whatever':100})# output: SomeDataClass(something='test', whatever=100)Dedict also works recursively, meaning you can parse complex data structuresclassSomeChildClass(Dedictable):a:strb:strclassComplex(Dedictable):some_string:strchild:SomeChildClasscomplex=Complex.dedict({'some_string':'test','child':{'a':'hello','b':'world'}})Built-in object model validationDedict also ensures the data passed is actually a valid representation of the object you're trying to create, by checking whether your data structure has fields that do not belong in the target objectclassSample(Dedictable):something:strwhatever:strsample=Sample.dedict({'something':'else','whatever':'you want','hello':'world'})# raises: AttributeError('object Sample has no attribute named hello')By default, dedict will not care about missing attributes in the input data structure, and will consider them optional. However you can enforce full validation by instead using theDedictableStrictimplementation.classStrict(DedictableStrict):a:strb:strc:strs=Strict.dedict({'b':'hello','c':'world'})# raises: AttributeError('dictionary was missing mandatory attribute a to create an object of type Sample')However, if you want full validation but also need to set some attributes as optional, dedict provides a new type annotation to mark attributes as optional when using the strict implementation.classStrict(DedictableStrict):a:OptionalAttr[str]b:strc:strs=Strict.dedict({'b':'hello','c':'world'})
Package: dedis-cluster
dedis-clusterredis-cluster plugin for django基于redis-py-cluster,实现了使用redis集群作为django缓存的backend安装源码安装git clone https://github.com/feiwencaho/dedis-cluster.git
cd dedis-cluster
python setup.py installpip安装pip install dedis-cluster使用在settings.py中作如下配置CACHES={'default':{'BACKEND':'dedis_cluster.cache.RedisClusterCache',# your redis-cluster nodes"LOCATION":["redis://192.168.1.4:7000/0","redis://192.168.1.4:7001/0","redis://192.168.1.4:7002/0","redis://192.168.1.4:7003/0",],'OPTIONS':{"CLIENT_CLASS":"dedis_cluster.client.DefaultClient",}}}
Package: deDL
A Decentralized Middleware for Decentralized Deep LearningPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: Apache Software License 2.0Documentation:https://deDL.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.1 (2022-04-17)First release on PyPI.
Package: dedlin
dedlinDedlin is an interactive line-by-line text editor and a DSL, similar to edlin or ed. It is perfect for
letting AI chatbots edit documents without sending the whole document back and forth.It is scriptable making it similar tosedfor doing find, insert, replace, delete operations on existing files.Soon it will support non-line number ranges, e.g."/Done/ DELETEDedlin extends onedlinenough that it is not backwards compatible.I have made changes to make the app less user hostile than classic ed or edlin, but there is a--vim_modewhere all help, warnings, feedback will be suppressed.BadgesInstallationRequires python 3.11 or higher. Someday I'll write a standalone installer for it.Install globally in an isolated virtual environment. This is a good idea.pipxinstalldedlinRun pre-built image with docker. Painful, but you're using an edlin clone, so that is what you're looking for.# This is should work in powershell or linux bash. Not windows git-bash.dockerrun--rm-it-v"${PWD}/:/app"ghcr.io/matthewdeanmartin/dedlin:latestfile.txtUsageLaunch and edit file_name.txtIf you installed withpiporpipxdedlinfile_name.txtCommand line help> python -m dedlin --help
Dedlin.

An improved version of the edlin.

Usage:
  dedlin [<file>] [options]
  dedlin (-h | --help)
  dedlin --version

Options:
  -h --help          Show this screen.
  --version          Show version.
  --macro=<macro>    Run macro file.
  --echo             Echo commands.
  --halt_on_error    End program on error.
  --promptless_quit  Skip prompt on quit.
  --vim_mode         User hostile, no feedback.
  --verbose          Displaying all debugging info.
  --blind_mode       Optimize for blind users (experimental).Sample session_          _  _  _
 __| | ___  __| || |(_) _ _
/ _` |/ -_)/ _` || || || ' \
\__,_|\___|\__,_||_||_||_||_|


Editing /home/mmartin/github/dedlin/sample.txt
? * 1i
1 INSERT
Control C to exit insert mode
?    1 :  cabbage
?    2 :  bread
?    3 :  carrots
?    4 :  ghost peppers
?    5 :  coffee
?    6 :  tortillas
?    7 :

Exiting insert mode

? * SORT
 SORT
Sorted
? * LIST
1,6 LIST
   1 : bread
   2 : cabbage
   3 : carrots
   4 : coffee
   5 : ghost peppers
   6 : tortillas

? * EXIT
1,6 EXITDocumentationUser ManualDeveloper roadmapPrior Art
Package: dedl-stack-client
DestinE Data Lake (DEDL) Stack ClientPython client to facilitate the use of DestinE Data Lake Stack Service.InstallationTo install the latest version of the client library run:pipinstalldedl-stack-clientUsageDaskAn example notebook is providedhere.
The client will guide a user through the needed authentication flow and will automatically create dedicated Dask cluster on each DEDL bridge.fromdedl_stack_client.authnimportDaskOIDCfromdedl_stack_client.daskimportDaskMultiClusterfromrich.promptimportPromptmyAuth=DaskOIDC(username=Prompt.ask(prompt="Username"))myDEDLClusters=DaskMultiCluster(auth=myAuth)myDEDLClusters.new_cluster()The DaskMultiCluster class provides an abstraction layer to interact with the various clusters on each DEDL bridge. Computations can be directed to the different Dask clusters by making use of a context manager as given in the following.withmyDEDLClusters.as_current(location="central")asmyclient:myclient.compute(myarray)withmyDEDLClusters.as_current(location="lumi")asmyclient:myclient.compute(myarray)