Saravanan666/pypi-org huggingface dataset:
Package: pynaive
pynaiveA toy project to demonstrate Python development environment and toolchain.The scripttools/docker.shcreates, runs and executes a docker container for
developing the project. The scripttools/full_check.shruns style checkes,
linters and tests. The project can be built withpython3 setup.py sdist bdist_wheelcommand.host> cd <project_root_dir>
host> ./tools/docker.sh
pynaive_focal
container> ./tools/full_check.sh
Success: no issues found in 2 source files

--------------------------------------------------------------------
Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

========================= test session starts ==========================
platform linux -- Python 3.8.5, pytest-4.6.9, py-1.8.1, pluggy-0.13.0
rootdir: /pynaive
plugins: flake8-1.0.6
collected 7 items

tests/test_math.py .......                                       [100%]

======================= 7 passed in 0.03 seconds =======================
container> python3 setup.py sdist bdist_wheel
<lots_of_output_here>
container> twine check dist/*
container> twine upload --repository-url https://test.pypi.org/legacy/ dist/*
container> twine upload dist/*InstanllationExectute the following in the command line:shell> pip3 install pynaiveExampleThe simplest snippet which uses the package:shell> python3
>>> from naive.math import average
>>> average([2.5, 0.0, -1.0, 3.5])
1.25
>>>
Package: pynaja
pynaja快速开始下载git clonehttps://github.com/xiaoxiamiya/naja.git安装pip install pynaja项目层级结构├── pynaja                                      项目目录
│    ├── cache                                  缓存层
│    │    ├── base                           	缓存工具集
│    │    └── redis                          	redis工具集
│    ├── common                                 通用工具层
│    │    ├── async_base                        异步工具集
│    │    ├── base                              通用工具集
│    │    ├── error                             异常工具集
│    │    ├── metaclass                         元类工具集
│    │    ├── process                          	进程类工具集
│    │    ├── struct                          	结构类工具集
│    │    └── task                          	任务类工具集	
│    ├── database                               数据库层
│    │    ├── mongo                           	mongo工具集
│    │    └── mysql                          	mysql工具集
│    ├── enum                                   枚举层
│    │    └── base_enum                         枚举类工具集
│    ├── event                                  事件层目录
│    │    ├── async_event                       异步事件工具集
│    │    └── event                          	同步事件工具集
│    ├── frame                                  框架层
│    │    ├── fastapi                          	fastapi工具集
│    │    │    ├── base                         基础工具集
│    │    │    └── response                     响应工具集
│    │    └── logging                           日志工具类
│    ├── net                                    网络层
│    │    ├── cacert                            根证书
└────└──  └── http                          	http工具集
Package: pynalytics
Trabalho individual de GCES 2022-2PynalyticsA biblioteca desenvolvida auxilia desenvolvedores a explorar os dados com funções essenciais para a identificação de outliers e anomalias e uma interface que auxilia a visualizar as informações de acordo com o arquivo de configuração.A biblioteca recebe um arquivo yaml com as configurações de cada etapa do pipeline de dados, e do endereço do banco de dados.
Após a execução do banco de dados, o banco de dados de dados é atualizado com os resultados da análise e os resultados podem ser visualizados por meio de dashboards no metabase.RequisitosPython 3.9.16Poetry 1.3.2Docker
Package: pynamecom
Overviewnamecomis a python library for the v4 api ofname.com, a domain name registrar.InstallationIf you haven’t already, start by installing it
withpip:pip install --upgrade pynamecomQuick StartUseDnsApito create a dns record:fromnamecomimportAuth,DnsApiauth=Auth('username','access_token')api=DnsApi(domainName='example.org',auth=auth)result=api.create_record(host='test',type='A',answer='10.0.0.1')DocumentationRead more about this project atreadthedocs:OverviewInstallatonQuick StartMore About APIMore ReferencesUsage ExampleHey, it’s not Snake Case!
Package: pynamedotcom
pynamedotcomA python library to interact with the name.com apiInstallation$pipinstallpynamedotcomAPI Usage>>># read authentication details...>>>importjson>>>withopen("tests/auth.json")asf:...auth=json.load(f)...>>># initialise api...>>>importpynamedotcom>>>host="api.dev.name.com">>># get domains...>>>withpynamedotcom.API(host=host,**auth)asapi:...fordomain_nameinapi.domains:...print(domain_name)...wolcomm.netmaddison.family>>>>>># fetch domain object...>>>withpynamedotcom.API(host=host,**auth)asapi:...domain=api.domain(name="maddison.family")...>>>domainDomain(maddison.family)>>>>>># get/set domain properties...>>>domain.nameu'maddison.family'>>>domain.nameservers[u'ns1.example.com',u'ns2.example.com']>>>domain.nameservers=['foo.example.org','bar.example.org']>>>domain.nameservers[u'foo.example.org',u'bar.example.org']CLI UsageSeenamedotcom --help
Package: pynamelix
API tonamelix.comInstallFrom PyPi:pipinstallpynamelixfrom source:gitclonehttps://github.com/axju/pynamelixpipinstall.Quick startAs a command line interface:python-mpynamelix-hor:pynamelix-hExample:python-mpynamelix-p-swordmix-lmediumpythonaxju
Package: pyNamespace
pyNamespacepyNamespace is an Application Framework supporting creation of the in-application data storage, simulating organization and behavior of the
Unix filesystem graph. You can create "directories" and data objects. Refer  those directories and data using Unix-like path. Also, you can create internal links between an objects and link one data object to more than one "directory".Creation of a namespacefrompyNamespaceimport*ns=Namespace()After you import pyNamespace module, you shall create an object of type Namespace. The "filesystem" root - "/" will be created automatically.Reading and writing into a namespacefrompyNamespaceimport*ns=Namespace()ns.set("home/answer",42)print(ns.get("home/answer")).set and .get methods will store and read objects from Namespace. Parameters for .set will be the path and a value which will be stored at that path. For .get it'll be a path, from which value will be retrieved.Removing objects from namespacefrompyNamespaceimport*ns=Namespace()ns.set("home/answer",42)ns.rm("home/answer").rm with path parameter will remove an object from the namespace. .rm also removes all "orphan" (nodes which do not have an incoming connections) nodes from the graph.Refer one node to another in the namespace.There are two types of the references Soft-reference assumes that the object will be created in the graph, which will have a reference to another object. Method .get will recognize the reference and return the value of the original (source) object. Hard-reference will actually link source object with destination object in the graph..link method will create a "soft-link" and .ref will create a hard-reference.frompyNamespaceimport*ns=Namespace()ns.set("home/answer",42)print(ns.link("home/answer","etc/answer"))print(ns.get("etc/answer"))This is an example of the soft-reference.frompyNamespaceimport*ns=Namespace()ns.set("home/answer",41)ns.ref("home/answer","etc")ns.set("home/answer",42)This is an example of the hard-reference
Package: py-namethatcolor
AboutThe script allows to get the closest known color to any given one and also generates its general shade (like Blue, Red, Black, etc)>>> from py_namethatcolor import get_color
>>> color = get_color("#336699")
>>> color.name
'Lochmara'
>>> color.shade.name
'Blue'CreditsIt’s a Python port of the “Name that Color”
script that was originally written by Chirag Mehta and also its improved
version developed for “Color Name & Hue”
by Daniel Flueck
Package: pynami
nami = not an mmlab implementation原先基于mmengine，现fork了mmengine并改为franky安装：pip install pynami模型需要继承自：HFModel，并实现forward方法预训练的模型使用pretrained关键字当子模块模型基于transformers时需要：type为NamiAutoModelmodel_type和config_type必须config_pretrained和model_pretrained优先级model_pretrainedconfig_pretrainedNone新增transformers保存模型和预处理对应钩子
Package: pynamical
pynamicalis a Python package for modeling, simulating, visualizing, and animating discrete
nonlinear dynamical systems and chaos. pynamical uses pandas, numpy, and numba for fast simulation,
and matplotlib for beautiful visualizations and animations to explore system behavior. Compatible
with Python 2 and 3. See the examples and demos onGitHub.You can read/cite the journal article about pynamical: Boeing, G. 2016.
“Visual Analysis of Nonlinear Dynamical Systems: Chaos, Fractals, Self-Similarity and the Limits of Prediction.”Systems, 4 (4), 37. doi:10.3390/systems4040037.
Package: pynamics365
pynamics365Python 3 connector to Dymanics 365 CRMFree software: MIT licenseDocumentation:https://pynamics365.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2017-09-06)Development Started
Package: pynamix
PynamiXDocumentation here, or compile it yourself following the details below).InstallationWork in progress. Hopefully viapip install pynamixbut YMMV. If installing from github, try cloning and then running:python3 setup.py build
python3 setup.py installIf you make any changes to the source code, re-run those two lines to have your changes reflected in your installed package.ExamplesTry out the included Jupyter notebook to see how to use the package.DependenciesShould be handled in pip install for you. Currently requires:python3matplotlibnumpyscipyimageioDocumentationWe usesphinxto manage the docs. Update documentation with:cd docs
make htmlOnce these are built, you can commit and push the changes to github to have them refreshed on github pages. You can also view them locally.RoadmapA sorted implementation list is as follows:1. Size measurement using the FFT technique
2. Option to choose between FFT and wavelet transform for size measurement
3. Wrapper for James's PIV code
4. Wrapper for James's fake radiograph generatorDeploying to PyPI (just a reminder for Benjy, please don't try this yourself)Run the following to make a new distribution and upload it to PyPI.Note: You first need to update the version number insetup.py.python3 setup.py sdist
twine upload dist/*
Package: pynamodb-attributes
This Python 3 library contains compound and high-level PynamoDB attributes:FloatAttribute– same asNumberAttributebut whose value is typed asfloatIntegerAttribute– same asNumberAttributebut whose value is typed asint(rather thanfloat)UnicodeDelimitedTupleAttribute- a delimiter-separated value, useful for storing composite keysUnicodeEnumAttribute- serializes a string-valuedEnuminto a Unicode (S-typed) attributeUnicodeProtobufEnumAttribute- serializes a Protobuf enum into a Unicode (S-typed) attributeIntegerEnumAttribute- serializes a int-valuedEnuminto a number (N-typed) attributeTimedeltaAttribute,TimedeltaMsAttribute,TimedeltaUsAttribute– serializestimedeltas as integer seconds, milliseconds (ms) or microseconds (µs)TimestampAttribute,TimestampMsAttribute,TimestampUsAttribute– serializesdatetimes as Unix epoch seconds, milliseconds (ms) or microseconds (µs)IntegerDateAttribute- serializesdateas an integer representing the Gregorian date (e.g.20181231)UUIDAttribute- serializes aUUIDPython object as aStype attribute (e.g.'a8098c1a-f86e-11da-bd1a-00112444be1e')UnicodeDatetimeAttribute- ISO8601 datetime strings with offset informationTestingThe tests in this repository use an in-memory implementation ofdynamodb. To run the tests locally, make sureDynamoDB Localis running. It is available as a standalone binary, through package managers (e.g.Homebrew) or as a Docker container:dockerrun-d-p8000:8000amazon/dynamodb-localAfterwards, run tests as usual:pytesttests
Package: pynamodb-encoder
pynamodb-encoderIntroductionpynamodb-encoderprovides helper classes that can convertPynamoDBModelobjects intoJSONserializabledict. It can also decode suchdictback into thoseModelobjects.Polymorphicmodels and attributes are also supported.Examplesdeftest_encode_complex_model(encoder:Encoder):classPet(DynamicMapAttribute):cls=DiscriminatorAttribute()name=UnicodeAttribute()classCat(Pet,discriminator="Cat"):passclassDog(Pet,discriminator="Dog"):passclassHuman(Model):name=UnicodeAttribute()pets=ListAttribute(of=Pet)jon=Human(name="Jon",pets=[Cat(name="Garfield",age=43),Dog(name="Odie")])assertencoder.encode(jon)=={"name":"Jon","pets":[{"cls":"Cat","name":"Garfield","age":43},{"cls":"Dog","name":"Odie"}],}deftest_decode_complex_model(decoder:Decoder):classPet(DynamicMapAttribute):cls=DiscriminatorAttribute()classCat(Pet,discriminator="Cat"):name=UnicodeAttribute()classDog(Pet,discriminator="Dog"):breed=UnicodeAttribute()classHuman(Model):name=UnicodeAttribute()age=NumberAttribute()pets=ListAttribute(of=Pet)jon=decoder.decode(Human,{"name":"Jon","age":70,"pets":[{"cls":"Cat","name":"Garfield"},{"cls":"Dog","breed":"Terrier"}],},)assertjon.name=="Jon"assertjon.age==70assertisinstance(jon.pets,list)assertlen(jon.pets)==2assertisinstance(jon.pets[0],Cat)assertjon.pets[0].name=="Garfield"assertisinstance(jon.pets[1],Dog)assertjon.pets[1].breed=="Terrier"More examples can be found inencoder_test.pyanddecoder_test.py
Package: pynamodb-mate
Welcome topynamodb_mateDocumentation📙Full Documentation is HereOverviewDisclaimerFeaturesDynamoDB PatternsInstallOverviewpynamodb_mateprovides advanced best practice using DynamoDB in python. Built on top ofpynamodbpython library. It maintain the compatibility to major version ofpynamodblibrary. For examplepynamodb_mate>=5.0.0,<6.0.0is compatible topynamodb>=5.0.0,<6.0.0.DisclaimerEven though the author is a Dynamodb Subject Matter Expert from AWS, but this project is NOT an AWS official project, and it is a personal open source project for the Python community.FeaturesClick on the link below to see detailed tutorial and examples.⭐Store Large Object in DynamoDB: This feature allows you to store any Python object and arbitrary big data in DynamoDB that can exceed the 400KB limit.⭐Client Side Encryption: This feature allows you to use your own encryption key to encrypt your data before it is sent to the DynamoDB.⭐Compressed Attribute: This feature can automatically compress the data before it is sent to the DynamoDB.⭐AWS DynamoDB Console Url: This feature can print the AWS DynamoDB console url for the table, items. You can use this in you log to quickly jump to the console to debug.DynamoDB Patternspynamodb_matealso provides some commonly used patterns. It is based on the author’s experience providing solutions to many customers from different industries. Click on the link below to see detailed tutorial and examples.🎉Cache: This feature gives you a “Redis” liked, serverless, Zero-ops, auto-scaling, high performance, pay-as-you-go cache layer based on DynamoDB.🎉Status Tracker: This feature gives you the ability to track status of each task, and error-handling, retry, concurrency control out-of-the-box.Installpynamodb_mateis released on PyPI, so all you need is:$pipinstallpynamodb_mateTo upgrade to latest version:$pipinstall--upgradepynamodb_mateIn order to use the following feature, you need to runpip install pynamodb_mate[encrypt]first:pynamodb_mate.EncryptedNumberAttributepynamodb_mate.EncryptedUnicodeAttributepynamodb_mate.EncryptedBinaryAttributepynamodb_mate.EncryptedJsonDictAttribute
Package: pynamodb-mypy
pynamodb-mypyA plugin for mypy which gives it deeper understanding of PynamoDB (beyond what's possible through type stubs).UsageAdd it to thepluginsoption of the[mypy]section in your mypy.ini:[mypy]plugins=pynamodb_mypyNullable attributesWhen declaring attributes withnull=True, the value types would become optional. For example:frompynamodb.attributesimportUnicodeAttributefrompynamodb.modelsimportModelclassMyModel(Model):my_key=UnicodeAttribute()my_value=UnicodeAttribute(null=True)...my_model=MyModel.get('key')ifmy_model.my_value.lower()=='foo':# error: Item "None" of "Optional[str]" has no attribute "lower"print("Value is foo")would have to be changed to, e.g.:ifmy_model.my_valueandmy_model.my_value.lower()=='foo':print("Value is foo")Typed model initializersWhen declaring models, the__init__method would be typed to accept only the attributes declared in the model. For example:frompynamodb.modelsimportModelfrompynamodb.attributesimportNumberAttributefrompynamodb.attributesimportUnicodeAttributeclassMyModel(Model):my_key=UnicodeAttribute(hash_key=True)my_value=NumberAttribute(null=True)# Existing attributes would be enforced:_=MyModel(my_key='key',my_value=42,my_other_value='other_value')# error: Unexpected keyword argument "my_other_value" for "MyModel"# Typing would be enforced:_=MyModel(my_key='key',my_value='42')# error: Argument 2 to "MyModel" has incompatible type "str"; expected "Optional[int]"# Nullability will be enforced::_=MyModel(my_key='key',my_value=None)_=MyModel(my_key=None,my_value=None)# error: Argument "my_key" to "MyModel" has incompatible type "None"; expected "str"# The hash key and range key can also be passed as positional arguments:_=MyModel('key')_=MyModel(42)# error: Argument 1 to "MyModel" has incompatible type "int"; expected "str"
Package: pynamodb-polymorph
PynamoDB PolymorphThis package has utilities that are useful when using PynamoDB with a
single-table (polymorphic) design and overloading Global Secondary Indexes.Take for example a Publisher class that needs to use a compound key of their
type prefix and their name. If you rely on callers doing the copy in code
there is possibility for them to update the name without also updating the
GSI sort key that contains the name. TheCompoundTemplateAttributeusesstring.Templatetemplating to fill unicode or numeric attributes into a
string template to build keys automatically.classPublisher(Base,discriminator="Publisher"):name=UnicodeAttribute()description=UnicodeAttribute(default="")gsi1_pk=CopiedDiscriminatorAttribute(source="cls")_slug="PUBLISHER"gsi1_sk=JoinedUnicodeAttribute(attrs=["_slug",'name'],sep='#')# Alternative way to specify gsi1_sk using a `string.Template`.# This is best for cases that aren't simply joining attrs with a character# gsi1_sk = CompoundTemplateAttribute(#     template="PUBLISHER#$name",#     attrs=["name"],# )The template above will take any value innameand fill it in to the
template, soname="Random Book Publishing House"will become agsi1_sk="PUBLISHER#Random Book Publishing House".
Package: pynamodb-rest
Pynamodb RestA Python based project to easily serve up serverless REST apis utilizing the wonderful Pynamodb packageFree software: MIT licenseDocumentation:https://pynamodb-rest.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.1 (2019-11-17)First release on PyPI.
Package: pynamodb-utils
IntroductionPynamodb Utils is a collection of small helper functions, utilities and classes which make common patterns easier. It helped me make my job easier in the past.Examples are:Models with automaticupdated_at,created_atanddeleted_atfieldsAttributes for enums and dynamic mappingsClass with methods that allow to generate from JSON/dict query/scan conditionsTo install:Runpip install pynamodb-utilsor executepython setup.py installin the source directoryExample of UsageTo setup pynamodb models with authomaticly generated timestamps and useful functions allowing serialization of scan conditions from JSON input from API.fromdatetimeimporttimezone,datetimefrompynamodb.attributesimportUnicodeAttributefrompynamodb_utilsimportDynamicMapAttribute,AsDictModel,JSONQueryModel,TimestampedModelclassCategoryEnum(enum.Enum):finance=enum.auto()politics=enum.auto()classPostCategoryCreatedAtGSI(GlobalSecondaryIndex):category=EnumAttribute(hash_key=True,enum=CategoryEnum)created_at=UTCDateTimeAttribute(range_key=True)classMeta:index_name="example-index-name"projection=AllProjectionclassPost(AsDictModel,JSONQueryModel,TimestampedModel):name=UnicodeAttribute(hash_key=True)sub_name=UnicodeAttribute(range_key=True)category=EnumAttribute(enum=CategoryEnum,default=CategoryEnum.finance)content=UnicodeAttribute()tags=DynamicMapAttribute(default={})category_created_at_gsi=PostCategoryCreatedAtGSI()classMeta:table_name='example-table-name'TZINFO=timezone.utcPost.create_table(read_capacity_units=10,write_capacity_units=10)post=Post(name='A weekly news.',sub_name='Shocking revelations',content='Last week took place...',category=CategoryEnum.finance,tags={"type":"news","topics":["stock exchange","NYSE"]})post.save()condition=Post.make_index_query(query={"created_at__lte":str(datetime.now()),"sub_name__exists":None,"category__equals":"finance","OR":{"tags.type__equals":"news","tags.topics__contains":["NYSE"]},})# class method executes query on the most optimal indexprint(next(results).as_dict())That lines of code should result with following output{
        'name': 'A weekly news.',
        'created_at': '2019-01-01 00:00:00+00:00',
        'updated_at': '2019-01-01 00:00:00+00:00',
        'deleted_at': None,
        'content': 'Last week took place...',
        'tags': {
            'type': 'news',
            'topics': ['stock exchange', 'NYSE']
        }
    }Linkshttps://github.com/pynamodb/PynamoDBhttps://pypi.org/project/pynamodb-utils/
Package: pynamoLogger
PynamoLoggerlog information into a dynamodb, with dax supportInstallpip install pynamologgerviewDocumentationUsagecreate a dynamodb tableindexKeyappNamerangeKeytimestampSam templateput this in your template.yaml file under properties sectionmake sure that the table name is the same in Meta declarationYourLogTable:Type:AWS::DynamoDB::TableProperties:AttributeDefinitions:-AttributeName:appNameAttributeType:S-AttributeName:timestampAttributeType:NBillingMode:PAY_PER_REQUESTTableName:<put your table name here>KeySchema:-AttributeName:appNameKeyType:HASH-AttributeName:timestampKeyType:RANGEcreate using pynamodb apiLogger.create_table()class meta definitionfrompynamoLogger.loggerimportPynamoLoggerclassLogger(PynamoLogger):classMeta:table_name='member-database-log-dev-manual'# put your table nameregion='ap-southeast-1'#put your region namebilling_mode='PAY_PER_REQUEST'# Logger.create_table()Logger.log(appName='test',message="this is crazy",responseObject={'response':'null response'}){'logId': 1603075789.054751,
 'saveResult': {'ConsumedCapacity': {'CapacityUnits': 1.0,
   'TableName': 'member-database-log-dev-manual'}}}Logger.checkLog(appName='test',logId='1603074235.103042')[{'appName': None,
  'timestamp': 1603074235.103042,
  'logMessage': 'this is crazy',
  'requestObject': {'noValue': 'noValue'},
  'responseObject': {'response': 'null response'}}]
Package: pynando
pynandowrapper for Nando (Nanbyo data ontology)from pynando.nando import Nando

# get nanbyo (指定難病)
nanbyo = Nando('nanbyo)

# get shoman (小児特定慢性疾病)
shoman = Nando('shoman')You can access each nando_node by idshoman_1 = shoman['1']
print(shoman_1)id: 1
name_ja: 球脊髄性筋萎縮症
synonyms_ja:
name_en: Spinal and bulbar muscular atrophy
synonyms_en:
children:
Package: pynano
National Novel Writing Monthis an annual event in
which the goal is generally to write 50,000 words of the first draft of a novel
in the 30 days of November.Naturally, the hosts have graciously supplied a website with various means of
updating and tracking one’s progress through this adventure, including anAPIto allow users to create their own
progress trackers.This is wherepynanocomes into play, providing a simple, Pythonic way to
acess this API and leverage its data in your own projects:>>> from pynano import User
>>> kromey = User('kromey')
>>> kromey.wordcount
64133
>>> kromey.name
'Kromey'Objects are provided to access data about Users, Regions, and the Site itself;
each also provides access to daily data to track progress through the month:>>> kromey.history[14].date # The sequence is 0-indexed, so index 14 is day 15
'2015-11-15'
>>> kromey.history[14].wordcount
10499Requirementspynanois supported on Python versions 2.7, 3.5, and 3.6, with these
additional packages:requests (version 2.9 or later)xmltodict (version 0.9 or later)Notepynanois also tested against Python versions 3.3, and 3.4, though
they are not officially supported. As a convenience, however, they remain
listed on PyPi as long as they continue to pass tests.