Saravanan666/pypi-org huggingface dataset:
Package: negima
NegimaNegima is a Python package to extract phrases in Japanese text by using the part-of-speeches based rules you defined.Negimaは日本語の文章の中から定義した品詞のルールにあてはまるフレーズを抽出するPythonパッケージです。InstallingInstall and update using pip:$pipinstall-UnegimaInstall usingsetup.py:$pythonsetup.pyinstallDependenciesmecab:http://taku910.github.io/mecab/A Simple Examplesample.pyfromnegimaimportMorphemeMergermm=MorphemeMerger()# csvmm.set_rule_from_csv('rules/1_noun.csv')# tsv# mm.set_rule_from_csv('rules/1_noun.tsv', sep='\t')# # excel# mm.set_rule_from_excel('rules/rules.xlsx', sheet_name='1_noun')words,_=mm.get_rule_pattern('今日はいい天気')print(words)$pythonsample.py['今日','天気']RuleYou can define　rules in a csv, tsv or excel format.A rule file requires following 9 columns.Define one of part-of-speeches each row.*ルールはcsv, tsv, excelファイルの形式で定義することができるます。ルールには以下の9種のカラムが必要になります。また、1行には1形態素の品詞の情報を定義します。
*idA rule starts with non-empty id column.idが空でなければ、ルールのスタートを示すid has to be unique.idはユニークである必要があるRules are applied in ascendings order of id (ids are compared as UTF-8 strings, not as byte arrays).ex: id:000_XXX has priority over id:999_ZZZidは文字列としてsortされて小さい順にそのルールの優先度が定義される例: id:000_XXXのルールはid:999_ZZZのルールよりも優先度が高いminMinimum repeat number. 0 means that morpheme is optional.形態素の最小繰り返し回数。0に設定するとそのパーツはあってもなくても良いdefault=1maxMaximum repeat number形態素の最大繰り返し回数default=1pos0, pos1, pos2, pos3, pos4, pos5Part of speeches of morphemes parsed by mecab.mecabでparseされた形態素の品詞や活用の名前pos0: 表層  (ex: 名詞)pos1: 品詞1 (ex: 副詞可能)pos2: 品詞2pos3: 品詞3pos4: 活用1pos5: 活用2To represent OR condition, concatenate part-of-speeches with|as a separator.|で品詞を接続することでOR条件の定義が可能であるYou can add arbitrary columns to your rule file. other columns are just ignored.
An example is available atrule/3_independent_phrase.csv, which has a row example that describes an example sentence for the rule.上記以外にも任意の列の追加が可能です。rule/3_independent_phrase.csvではexampleという列を追加し、ルールにあてはまるサンプルを記述しています。Simple rule (csv)A rule to extract compound noun.このようなルールを定義することで、複合名詞を抽出できますidminmaxpos0pos1pos2pos3pos4pos5102接頭詞14名詞一般|サ変接続|数02名詞接尾CautionDon't insert empty row between rules.注意ルール同士の間に空行をはさまないようにすることRule samplesrule/1_noun.csvExtract nouns.名詞の抽出約5000人が国立競技場に駆けつけた->5000人国立競技場場所がわかりにくいのでたどり着けなかった->場所rule/2_nouns.csvExtract compound nouns.複合名詞の抽出約5000人が国立競技場に駆けつけた->約5000人国立競技場場所がわかりにくいのでたどり着けなかった->場所rule/3_independent_phrase.csvExtract a little complex phrase.形容詞や否定の「ない」を含んだ少し複雑なルールのフェーズの抽出新人研修のレベルは高い->新人研修レベルは高いあのサイトはホテルの比較がしやすくないので好きではない->サイトホテル比較がしやすくない好きではない
Package: neglect
NeglectExecution formateneglect( file_name.py,current_file.py )Functionalities of the NeglectIgnores logical program errorsHelps to run python file by avoiding compilation of mistaken linesindicates error lines inside the program/code itselfminimise unnecessary usage of try & exceptUsageMake sure you have installed Python in your system.Run Following command in the CMD.pip install neglect
Package: negotiate
Smart, simple content negotiation for Python web applications.Content negotiation can be difficult to do well. Ideally, your code should be
DRY, and you wouldn’t be repeating the same old boilerplate in multiple view
methods in order to emit the same domain object in different formats.negotiatehelps make your life even easier by allowing you to decorate
your view methods with formatters that automatically translate your domain
objects into the format requested by the client.It’s really simple to use. Hopefully this example (for a Flask application)
makes the main points clear:# First, we write a couple of formatters that specify how to translate the
# output of the view function into a particular format. Here we define a
# JSON formatter and an HTML formatter that takes a template parameter.

from negotiate.flask import Formatter

class JSONFormatter(Formatter):
    format = 'json'
    mimetypes = ['application/json']

    def render(self, obj):
        return json.dumps(obj)

class HTMLFormatter(Formatter):
    format = 'json'
    mimetypes = ['text/html']

    def configure(self, template):
        self.template = template

    def render(self, obj):
        return render(self.template, **obj)

# Then, when building the application, we decorate the view function with the
# "negotiate" decorator, listing the formats in which this view is available.

from negotiate.flask import negotiate

@app.route('/posts/<id>')
@app.route('/posts/<id>.<format>')
@negotiate(JSONFormatter)
@negotiate(HTMLFormatter, template='post.html')
def view_post(id, format=None):
    post = Posts.by_id(id)

    if post is None:
        abort(404)
    if not g.user.authorize('read', post):
        abort(401)

    return {'post': post}The result is a view action that will return an HTML version of the post by default (i.e. withAccept: */*and no explicit format), or if the.htmlextension is explicitly specified, or a JSON version of the post if the.jsonextension is given orAccept: application/jsonis sent with the request.Supportnegotiatecurrently supportsFlaskandPylons, although adding support for other web frameworks should be pretty easy. Have a look atnegotiate/flask.pyandnegotiate/pylons.pyto see the small amount of integration code required.
Package: nehushtan
Nehushtan (נְחֻשְׁתָּן)A toolkit for projects in Pythonipse dissipavit excelsa et contrivit statuas et succidit lucos confregitque serpentem aeneum quem fecerat Moses siquidem usque ad illud tempus filii Israhel adolebant ei incensum vocavitque eum NaasthanLicense: MITCategoryCLIHelp to handle the command line parameters.HelperProvide an easier way to access to class, data, etc.LoggingProvide a solution for logging, other than the default.MailA package to support EMail related tasks.MySQLProvide a high-to-low solution on MySQL access, with Model support.QueueA designed framework for queue usingsubprocess.Multi-ProcessingSupport for multiprocessing queue.
Package: neighborhood
Travis CI:Python 3 implementation of “neighborhood algorithm” direct-search
optimization and Bayesian ensemble appraisal. In short, a
nearest-neighbor interpolant based on Voronoi polygons is used to
interpolate the misfit (search) and posterior probability (appraisal) to
allow efficient sampling and integration for high-dimensional problems.
Details on theory and implementation are supplied in the references.Example search population for 4D Rosenbrock objective function. Image
include 10,000 samples collected in 1,000 iterations of the neighborhood
algorithm direct search, withnum_samp=10andnum_resamp=5. The
true minimum is0at(1, 1, 1, 1), while the best sample is0.0113at((0.976, 0.953, 0.908, 0.824). This result continues
to converge for larger sample size (but the plot is less interesting since
the density converges to a point!)To generate the example figure above, you can run the internal demo,
like so:importneighborhoodasnbrnbr.demo_search(ndim=4,nsamp=10,nresamp=5,niter=500)Equivalently, you can do the following:importneighborhoodasnbrnum_dim=4srch=nbr.Searcher(objective=nbr.rosenbrock,limits=[(-1.5,1.5)for_inrange(num_dim)],num_samp=10,num_resamp=5,maximize=False,verbose=True)srch.update(500)srch.plot()StatusOptimization is implemented, ensemble appraisal is in progress.TestingThis project usespytestfor
unit testing. The aim is not to be exhuastive, but to provide reasonable
assurances that everything works as advertised. To run, simply callpytest--verbosefrom somewhere in this package.ReleaseRelease versions are tagged in the repository, built as distributions,
and uploaded to PyPI. The minimal commands to do this are:# update PyPI-readable READMEpandoc--from=markdown--to=rst--output=README.rstREADME.md# build with setuptoolspython3setup.pysdistbdist_wheel# upload to PyPI test server (then check it out)twineupload--repository-urlhttps://test.pypi.org/legacy/dist/*# upload to PyPItwineuploaddist/*# tag release in git repogittag-aX.X.X-m"vX.X.X"gitpushorigin--tagsReferencesSambridge, M. (1999). Geophysical inversion with a neighbourhood
algorithm - I. Searching a parameter space. Geophysical Journal
International, 138(2), 479–494.http://doi.org/10.1046/j.1365-246X.1999.00876.xSambridge, M. (1999). Geophysical inversion with a neighborhood
algorithm -Appraising the ensemble. Geophys, J. Int., 138, 727–746.http://doi.org/10.1046/j.1365-246x.1999.00900.x
Package: neighbours-python
neighbours-python PackageThis is a package modified fromNearPy 1.0.0.I removed normalization for feature vectors to make it find true neighbours when using Euclidian Distance.I upload it for my own convenience as well as for others who use NearPy in their projects.The structures and names all remain the same as NearPy. So you can use it exactly the same way asnearpyin your python scripts.For example, you should import this package as:importnearpy
Package: neighpy
neighpyneighphyis a Python implementation of the Neighbourhood Algorithm for the optimisation and appraisal of high-dimensional loss surfaces.
First presented in two papers by M. Sambridge at the Australian National University in 1999, it has since been widely used, particularly in the geophysical community, for the optimisation of complex, high-dimensional functions.This implementation hopes to replace the original Fortran code with a more modern, user-friendly and flexible Python package.
It is a very simple implementation, with just two classes to implement the two phases of the algorithm: theneighpy.search.NASearcherclass for the optimisation phase, and theneighpy.appraise.NAAppraiserclass for the appraisal phaseInstallationpipinstallneighpyBasic UsageimportnumpyasnpfromneighpyimportNASearcher,NAAppraiserdefobjective(x):# Objective function to be minimisedreturnnp.linalg.norm(data-predict_data(x))# Bounds of the parameter spacebounds=((-5,5),(-5,5))# Initialise direct search phasesearcher=NASearcher(objective,ns=100,# number of samples per iterationnr=10,# number of cells to resampleni=100,# size of initial random searchn=20,# number of iterationsbounds=bounds)# Run the direct search phasesearcher.run()# results stored in searcher.samples and searcher.objectives# Initialise the appraisal phaseappraiser=NAAppraiser(searcher.samples,# points of parameter space already samplednp.exp(-searcher.objectives),# objective function values (as a probability distribution)bounds=bounds,n_resample=500000,# number of desired new samplesn_walkers=10# number of parallel walkers)# Run the appraisal phaseappraiser.run()# Results stored in appraiser.samplesLicenceThis code is distributed under aGNU General Public License.ContributingIf you have any questions, please to open an issue in this repository.
Package: neil-vst-gui
py-neil-vst-guiGUI application based on py-neil-vst package (Cython-based simple VST 2.4 Host and VST Plugins wrapper)Supported platforms:Windows 64bitSupported python versions:3.7,3.8,3.9Supported VST Plugins: only64-bit/VST2Multiply files work on the one click.VST 64-bit plugin chain support - add, remove, change "on the fly".VST Plugins self GUI on separate windows.Multithreading support for proccessing, one file - one thread.Fast work with minimum memory required for the one working thread.Play any file with VST plugin chain "as is" - some as the output result.ASIO, WASAPI, WDM audio streams supportSave/Open projects files in readable json formatOptional log window with four levels (DEBUG, INFO, WARNING, ERROR)GUI based on PyQt5Full open source project
Package: neinsum
Neinsum (Named Einsum)NumPy's Einsum, but with named subscripts.Installationpip install neinsumUsageimportnumpyasnpfromneinsumimportnamed_einsumx=np.eye(3)y=named_einsum("A_ij,B_kl")(A=x,B=x)# this is equal toz=np.einsum("ij,kl",x,x)
Package: neirogenius
NeirogeniusPYNeirogeniusPY is a Python wrapper for the Neirogenius API.Neurogenius is a Discord bot created by@Pelfoxthat entertains people. It generates funny
sentences using words from server members' messages.InstallationUsing PyPipip install neirogeniusExample usage# Import the API class.fromneirogeniusimportAPI# Create an instance of the API class.api=API()# Get the ID of the first guild.guild=api.get_statistic().guilds[0].name# Some name.# Get the first message.message=api.get_messages(677481923995500566).messages[0]# Instance of Message class.# Print message content.print(message.content)LicenseThis project is licensed under
theApache License Version 2.0.
Package: nejimaki
generating file tree from one yamle file.exampledata.yaml./conf:./base:base.yaml:logging:asctime:2013-04-10 15:39:26,014created:1365604766.014612levelname:INFOmessage:test messagename:logger_namedev.yaml:debug:true$inherits:"./base/base.yaml"staging.yaml:debug:false$inherits:"./base/base.yaml"production.yaml:$inherits:"./staging.yaml"$nejimakiexamples/readme/data.yaml--position=examples/readmeINFOnejimakiemit:conf/base/base.yamlINFOnejimakiemit:conf/dev.yamlINFOnejimakiemit:conf/staging.yamlINFOnejimakiemit:conf/production.yaml$treeexamples/readme/confexamples/readme/conf├──base│└──base.yaml├──dev.yaml├──production.yaml└──staging.yaml1directory,4files0.1.1raw format0.1.0initial release
Package: nejma
⭐ Nejma ⭐Nejma ⭐ allows you to manage multiple realtime connections and send messages to groups or a user multiple tabs...Take a look at this examplenejma-chat, a simple chat application built usingnejmaandstarlette.Installation$pipinstallnejmaGetting startedHere's an example of usingnejmawith websockets.First import Channel and channel_layer from nejmafromnejmaimportChannel,channel_layerCreate a channel on connectasyncdefon_connect(self,websocket,**kwargs):awaitsuper().on_connect(websocket,**kwargs)self.channel=Channel(send=websocket.send)Add groups, channels or send messagesasyncdefon_receive(self,websocket,data):# Adds a channel to a giving groupself.channel_layer.add(group,self.channel)# Removes a channel from a given groupself.channel_layer.remove(group,self.channel)# Removes a channel from all the groupsself.channel_layer.remove_channel(self.channel)# Reset all the groupsself.channel_layer.flush()awaitself.channel_layer.group_send(group,"Welcome !")Finnaly, remove the channel once the connection is closedasyncdefon_disconnect(self,websocket,close_code):self.channel_layer.remove_channel(self.channel)StarletteTo usenejmawithstarlette, simply import the WebSocketEndpoint from nejmafromchannels.ext.starletteimportWebSocketEndpoint@app.websocket_route("/ws")classChat(WebSocketEndpoint):encoding="json"asyncdefon_receive(self,websocket,data):room_id=data['room_id']message=data['message']username=data['username']ifmessage.strip():group=f"group_{room_id}"self.channel_layer.add(group,self.channel)payload={"username":username,"message":message,"room_id":room_id}awaitself.channel_layer.group_send(group,payload)DocsTheChannelLayerclass provided bynejmaexposes the following methods :add(group, channel)Adds a channel to a giving group.self.channel_layer.add(group,self.channel)remove(group, channel)Removes a channel from a given groupself.channel_layer.remove(group,self.channel)remove_channel(channel)Removes a channel from all the groupsself.channel_layer.remove_channel(self.channel)flush()Reset all the groupsself.channel_layer.flush()
Package: nekbot.plugins.geo
geo plugin. Nekbot, a modular and multiprotocol bot written in Python.Usage:!geo <place or coordinates>
Return coordinates, place, and extra information.

!geodistance <place or coordinates 1> <place or coordinates 2>
Return distance between places.Example:!geo Madrid
40.4167047,-3.7035825 Madrid, Área metropolitana de Madrid y Corredor del Henares, Madrid, Comunidad de Madrid, España [city] https://www.openstreetmap.org/relation/4844521

!geo 40.4167047,-3.7035825
Plaza de la Puerta del Sol, Barrio de las Letras, Centro, Madrid, Área metropolitana de Madrid y Corredor del Henares, Madrid, Comunidad de Madrid, 28080, España https://www.openstreetmap.org/way/4263034

!geo 40.4167047,-3.7035825 Sevilla
Vicenty distance: 390.503168km Great-circle distance: 390.839770kmPlease! You need NekBot for use this plugin. This plugin not works without NekBot.https://bitbucket.org/Nekmo/nekbot-mirai/
Package: nekbot.plugins.random
Randomness plugin for Nekbot, a modular and multiprotocol bot written in Python.Usage:!random – Random number between 1 and 6.!random <number> – Number between 1 and <number>!random <number A> <number B> – Number between <number A> and <number B>!random <word 1> <word 2>[ <word 3>…] – Random word.!veryrandom – Random.org commandYou need NekBot to use this plugin. This plugin does not work without NekBot.https://bitbucket.org/Nekmo/nekbot-mirai/
Package: nekbot.plugins.weather
weather plugin. Nekbot, a modular and multiprotocol bot written in Python.Usage:!weather <place or coordinates>[ <moment: now, today, tomorrow... or datetime>]
Return weather for now, today and tomorrow if moment is not given.Moment keys options:now (or n).today (or ty).tomorrow (or tw).after-tomorrow (or aw).Examples:!weather Madrid
Now: Clear 18.9ºc ⚫ Today: Partly cloudy until evening. 16.8ºc min. 30.9ºc max. ⚫ Tomorrow: Clear throughout the day. 16.0ºc min. 34.1ºc max.

!weather Madrid 01/02/1987
Clear 6.7ºc 6.7ºc RealFeel 0% humid.

!weather Barcelona "20/10/2006 10:15"
Partly Cloudy 20.3ºc 20.3ºc RealFeel 0% humid. wind 3.47km/h

!weather Torrelodones tomorrow
Clear throughout the day. 15.2ºc min. 33.9ºc max. 0% humid. wind 0.63km/hYou need NekBot to use this plugin. This plugin does not work without NekBot.https://bitbucket.org/Nekmo/nekbot-mirai/
Package: neko233-sugar
sugar@author SolarisNekoWhat is itUse Python in Decorator / Annotation Like Java Lombok / C# Annotation / TypeScript Decorator作者是写 Java / TypeScript 习惯了注解Use Like Other Language:Java Lombok @DataTypeScript  @AsyncC#  [Required(ErrorMessage = "{0} is required")]顺手写How to use 如何使用install 安装依赖pipinstallsugar@string |str@stringclassMockData:def__init__(self,age):self.age=agedata=MockData(18)# Output = "MockData(age=18)"print(data)@csv | CSV@csvclassMockData:def__init__(self,name,age):self.name=nameself.age=ageself.emptyTips=''classTest(TestCase):deftest_csv(self):data=MockData(name='neko',age=18)# csv 输出文本print(data.csv_str())# csv 的格式print(data.csv_format())# 示例中，有个字段为空# neko,18,# name,age,emptyTipsmy project initgitinitgitremoteaddgithubhttps://github.com/SolarisNeko/neko233-python-sugar.gitgitremoteaddoriginhttps://gitee.com/SolarisNeko/neko233-python-sugar.git
Package: nekobin
🐱 Nekobin API Wrapper⬇️ Installing nekobin via 🐍 pip:pip install nekobin🆕 Upgrading nekobin via 🐍 pip:pip install -U nekobin⬇️ Installing nekobin via 🌐 source:git clone https://github.com/OpenRestfulAPI/nekobinpy
cd nekobinpy
make install📖 Example Usage:from nekobin import NekoBin, errors
import asyncio

nekobin = NekoBin()


async def main():
    try:
        neko = await nekobin.nekofy(
            content="Hello World",
            title="example",  # Optional
            author="pokurt"  # Optional
        )
    except errors.HostDownError:
        return print("Host is down at the moment")
    output = "Nekofy Content:\n-----------\n"
    output += "Key: " + neko.key + "\n"
    output += "URL: " + neko.url + "\n"
    output += "Raw URL: " + neko.raw + "\n"
    if neko.title:
        output += "Title: " + neko.title + "\n"
    if neko.author:
        output += "Author: " + neko.author + "\n"
    output += "Date: " + str(neko.date) + "\n"
    output += "Views: " + str(neko.views) + "\n"
    output += "Length: " + str(neko.length) + "\n"
    output += "Content: " + neko.content + "\n"
    print(output)


if __name__ == "__main__":
    asyncio.run(main())©️ CopyrightsThis Project was made by an indivial onTelegram. The person who made this API wrapper has nothing to do withNekobinor the base source of the paste service. Therefore All rights reserved toNekobinPaste Service's Rightful OwnerDanHimself.
Package: nekodict
Neko DictionaryNeko Dictionary 是一款轻量级命令行中英文词典。安装pipinstallnekodict使用ndic <word>直接查询单词，或ndic进入交互模式查询单词。直接查询单词例如:ndicgrammar进入交互模式查询单词例如:ndic在交互模式下输入q退出支持模糊搜索，选取最接近的词条:ndiclexem支持阅读单词(未经跨平台测试):ndic-r显示帮助:ndic-h其它本程序基于GPLv3分发本程序词典源来自有道词典本程序模仿了termdic建议使用yakuake启动 Neko Dictionary
Package: nekofun
NekofunGithubHow to useInstallpip install nekofunExample[async]fromnekofunimportclientimportasyncioasyncdefmain():# 클래스를 정의해줍니다.get=client.Get()result=awaitget.cry()# 우는 그림(or gif)를 가져옵니다.result=result.content# 링크형태로 반환합니다.print(result)loop=asyncio.get_event_loop()loop.run_until_complete(main())loop.close()[sync]fromnekofunimportsyncsync=sync.Get()# 클래스를 정의해줍니다.result=sync.cry()# 우는 그림(or gif)를 가져옵니다.print(result.content)# 링크형태로 반환하여 출력합니다.
Package: nekograd
nekogradFast & Flexible(just like a catgirl)deep learning framework.All frameworks require vast manuscripts of code to be written in order to
create the simplest trainable model configuration.
We proposenekogradas a convenient way of creating such pipelines
with the least amount of code needed to be written.Installationpipinstallnekogradorgitclonehttps://github.com/arseniybelkov/nekograd.gitcdnekograd&&pipinstall-e.ExampleCoreModelinherits everything fromLightningModuleand just implements it basic methods so you don't have to.importtorchimporttorch.nnasnnimportpytorch_lightningasplfromnekograd.modelimportCoreModelfromnekograd.model.policyimportMultiplyfromsklearn.metricsimportaccuracy_score# Simplest use case, which covers many DL tasks.# You just define architecture, loss function, metrics,# optimizer and lr_scheduler.architecture:nn.Module=nn.Sequential(nn.Flatten(),nn.Linear(28*28,10))criterion:Callable=nn.CrossEntropyLoss()metrics:Dict[str,Callable]={"accuracy":accuracy_score}optimizer=torch.optim.Adam(architecture.parameters())lr_scheduler=torch.optim.lr_scheduler.LambdaLR(optimizer,Multiply({10:0.1}))model=CoreModel(architecture,criterion,metrics,optimizer=optimizer,lr_scheduler=lr_scheduler)device="gpu"iftorch.cuda.is_available()else"cpu"trainer=pl.Trainer(max_epochs=20,accelerator=device)trainer.fit(model,datamodule=...)trainer.test(model,datamodule=...)
Package: nekoite-be-core
Nekoite Backend CoreUsageRequires python 3.7 or newer.pip install nekoite-be-coreThere are someexamplesto look at.Basically, choose an adapter (or build on your own), create
some views and routes, and give it to the functionregister_routes.routes={"/a":AView,...}adapter=SomeAdapter(*args)register_routes(adapter,routes)ModulesViewExtend the classViewBase. Override the functionhandle_req.
You can specify therequest_schemaandresponse_schema, and if they
are not specified orNone, then the request or response format will
not be checked.methodcan be a string or list of strings indicating
the HTTP methods accepted by this view.classTestView(ViewBase):request_schema={"id":fields.Integer(required=True)}response_schema={"id":fields.Integer(),"timestamp":fields.Integer()}methods=["GET","POST"]defhandle_req(self,req:t.Dict[str,t.Any])->t.Any:return{"id":req["id"],"timestamp":int(time()),}FieldsYou can importfieldsfrom this package. It includes some field type
defined inmarshmallow, and theNestedtype is rewritten to accept dict
as parameter.The detailed usage of the types infieldscan be found onthe homepage of marshmallow.fromnekoite_be_coreimportfields# ...request_schema={"id":fields.Integer(required=True),...}