Saravanan666/pypi-org huggingface dataset:
Package: unidown
unidown manages downloads and will only download items again when they are newer or not downloaded yet.unidown is written with the main aspect on plugins. unidown itself can only manage the produced data from 3rd party plugins.unidown saves all downloaded files with their modifications time and and will only download updated or not already downloaded files.Find more information in the documentation atRead the Docs.Webhttps://github.com/IceflowRE/unidownPluginsmr_deCrawl through german ebooks from Mobileread.https://github.com/IceflowRE/unidown-mr_deCreditsDeveloperIceflower Siceflower@gmx.deThird PartyPackagingDonald Stufft and individual contributorshttps://github.com/pypa/packagingBSD-3-Clause, Apache-2.0tqdmnoamraphhttps://github.com/tqdm/tqdmMIT, MPL-2.0urllib3Andrey Petrov and contributorshttps://github.com/shazow/urllib3MITLicenseCopyright (C) 2015-present Iceflower SThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.
Package: unidump
A Unicode codepoint dump.Think of it as  hexdump(1)  for Unicode.  The command analyses  the input andprints then three columns:  the raw byte count of the first codepoint in thisrow,  codepoints in their hex notation,  and finally the raw input characterswith control and whitespace replaced by a dot.Invalid byte sequences are represented with an “X” and with the hex value en-closed in question marks, e.g., “?F5?”.You can pipe in  data from stdin,  select several files at once,  or even mixall those input methods together.Examples:* Basic usage with stdin:echo -n 'ABCDEFGHIJKLMNOP' | unidump -n 40    0041 0042 0043 0044    ABCD4    0045 0046 0047 0048    EFGH8    0049 004A 004B 004C    IJKL12    004D 004E 004F 0050    MNOP* Dump the code points translated from another encoding:unidump -c latin-1 some-legacy-file* Dump many files at the same time:unidump foo-*.txt* Control characters and whitespace are safely rendered:echo -n -e '\x01' | unidump -n 10    0001    .* Finally learn what your favorite Emoji is composed of:( echo -n -e '\xf0\x9f\xa7\x9d\xf0\x9f\x8f\xbd\xe2' ; \echo -n -e '\x80\x8d\xe2\x99\x82\xef\xb8\x8f' ; ) | \unidump -n 50    1F9DD 1F3FD 200D 2642 FE0F    .🏽.♂️See  <http://emojipedia.org/man-elf-medium-skin-tone/> for images.  The “elf”emoji (the first character) is replaced with a dot here,  because the currentversion of Python’s unicodedata doesn’t know of this character yet.* Use it like strings(1):unidump -e '{data}' some-file.binThis will replace  every unknown byte from the input file  with “X” and everycontrol and whitespace character with “.”.* Only print the code points of the input:unidump -e '{repr}'$'\n' -n 1 some-file.txtThis results in  a stream of codepoints in hex notation,  each on a new line,without byte counter  or rendering of actual data.  You can use this to countthe total amount of characters  (as opposed to raw bytes)  in a file,  if youpipe it through `wc -l`.This is version 1.1.2 of unidump, using Unicode 8.0.0 data.
Package: uniem
uniemuniem 项目的目标是创建中文最好的通用文本嵌入模型。本项目主要包括模型的训练，微调和评测代码，模型与数据集会在HuggingFace社区上进行开源。🌟 重要更新➿2023.07.11, 发布 uniem 0.3.0，FineTuner除 M3E 外，还支持sentence_transformers,text2vec等模型的微调，同时还支持SGPT的方式对 GPT 系列模型进行训练，以及 Prefix Tuning。FineTuner 初始化的 API 有小小的变化，无法兼容 0.2.0➿2023.06.17, 发布 uniem 0.2.1 ， 实现了FineTuner以原生支持模型微调，几行代码，即刻适配！📊2023.06.17, 发布MTEB-zh正式版 ， 支持 6 大类 Embedding 模型 ，支持 4 大类任务 ，共 9 种数据集的自动化评测🎉2023.06.08, 发布M3E models，在中文文本分类和文本检索上均优于openai text-embedding-ada-002，详请请参考M3E models README。🔧 使用 M3EM3E 系列模型完全兼容sentence-transformers，你可以通过替换模型名称的方式在所有支持 sentence-transformers 的项目中无缝使用 M3E Models，比如chroma,guidance,semantic-kernel。安装pipinstallsentence-transformers使用fromsentence_transformersimportSentenceTransformermodel=SentenceTransformer("moka-ai/m3e-base")embeddings=model.encode(['Hello World!','你好,世界!'])🎨 微调模型uniem提供了非常易用的 finetune 接口，几行代码，即刻适配！fromdatasetsimportload_datasetfromuniem.finetunerimportFineTunerdataset=load_dataset('shibing624/nli_zh','STS-B')# 指定训练的模型为 m3e-smallfinetuner=FineTuner.from_pretrained('moka-ai/m3e-small',dataset=dataset)finetuner.run(epochs=3)微调模型详见uniem 微调教程or如果您想要在本地运行，您需要运行如下命令，准备环境condacreate-nuniempython=3.10
pipinstalluniem💯 MTEB-zh中文 Embedding 模型缺少统一的评测标准，所以我们参考了MTEB，构建了中文评测标准 MTEB-zh，目前已经对 6 种模型在各种数据集上进行了横评，详细的评测方式和代码请参考MTEB-zh。文本分类数据集选择，选择开源在 HuggingFace 上的 6 种文本分类数据集，包括新闻、电商评论、股票评论、长文本等评测方式，使用 MTEB 的方式进行评测，报告 Accuracy。text2vecm3e-smallm3e-basem3e-large-0619openaiDMetaSouluererlangshenTNews0.430.44430.48270.48660.45940.30840.35390.4361JDIphone0.82140.82930.85330.86920.7460.79720.82830.8356GubaEastmony0.74720.7120.76210.76630.75740.7350.75340.7787TYQSentiment0.60990.65960.71880.72470.680.64370.66620.6444StockComSentiment0.43070.42910.43630.44750.48190.43090.45550.4482IFlyTek0.4140.42630.44090.44450.44860.39690.37620.4241Average0.57550.58340.61570.62310.59560.5520166670.572250.594516667检索排序数据集选择，使用T2Ranking数据集，由于 T2Ranking 的数据集太大，openai 评测起来的时间成本和 api 费用有些高，所以我们只选择了 T2Ranking 中的前 10000 篇文章评测方式，使用 MTEB 的方式进行评测，报告 map@1, map@10, mrr@1, mrr@10, ndcg@1, ndcg@10text2vecopenai-ada-002m3e-smallm3e-basem3e-large-0619DMetaSouluererlangshenmap@10.46840.61330.55740.6260.62560.252030.086470.25394map@100.58770.74230.68780.76560.76270.333120.130080.34714mrr@10.53450.69310.63240.70470.70630.292580.100670.29447mrr@100.62170.76680.7120.78410.78270.362870.145160.3751ndcg@10.52070.67640.61590.68810.68840.283580.097480.28578ndcg@100.63460.77860.72620.80040.79740.374680.157830.39329🤝 Contributing如果您想要在 MTEB-zh 中添加评测数据集或者模型，欢迎提 issue 或者 PR，我会在第一时间进行支持，期待您的贡献！📜 Licenseuniem is licensed under the Apache-2.0 License. See the LICENSE file for more details.
Package: unifactory
UnifactoryUnifactory is a spin off fromfastapi-overrider.
A simple tool to automatically choose a matching factory frompolyfactory's inventory.Installationpip install unifactoryExamplesfrompolyfactory.pytest_pluginimportregister_fixturefromunifactoryimportunifactory,build,batch,coverage@dataclassclassPerson:name:strage:floatheight:floatweight:floatsome_person=build(Person)five_persons=batch(Person,5)all_persons=coverage(Person)person_factory=register_fixture(unifactory(Person),name="person_factory")
Package: unifetch
Unifetchpython3 -m pip install unifetchUnifetch is a python script that will display the logo and motto of a UK university.It's main purpose is to be used as a welcome message on a University ssh server or maybe just a local vm you use for uni work.Feel free to add any Academic institution logo you feel like.ExampleUsageusage: unifetch [-h] [--num-cols NUM_COLS] [--show-unis [SHOW_UNIS]] [--logo-only [LOGO_ONLY]] [uni]

Take image for processing

positional arguments:
  uni                   University short name, for a list of universities type --show-unis

optional arguments:
  -h, --help            show this help message and exit
  --num-cols NUM_COLS   Width of logo in text columns
  --show-unis [SHOW_UNIS]
  --logo-only [LOGO_ONLY]Universitiesabdn - University of Aberdeen
bath - University of Bath
bham - University of Birmingham
bris - University of Bristol
cam - University of Cambridge
cf - Cardiff University
cov - Coventry University
dmu - De Montfort University
dundee - University of Dundee
dur - Durham University
ed - University of Edinburgh
essex - University of Essex
ex - University of Exeter
gla - University of Glasgow
harper-adams - Harper Adams University
hw - Herriot-Watt University
ic - Imperial College London
kcl - King's College London
lancs - Lancaster University
lboro - Loughborough University
le - University of Leicester
leeds - University of Leeds
liv - University of Liverpool
lse - London School of Economics and Political Science
man - University of Manchester
mmu - Manchester Metropolitan University
ncl - Newcastle University
northumbria - Northumbria University
nott - University of Nottingham
ntu - Nottingham Trent University
ox - University of Oxford
port - University of Portsmouth
qmw - Queen Mary University of London
qub - Queen's University Belfast
rdg - University of Reading
rhul - Royal Holloway, University of London
shef - University of Sheffield
shu - Sheffield Hallam University
soton - University of Southampton
st-and - University of St Andrews
stir - University of Stirling
strath - University of Strathclyde
sund - University of Sunderland
surrey - University of Surrey
susx - University of Sussex
swan - Swansea University
tees - Teesside University
ucl - University College London
uea - University of East Anglia
uwe - University of the West of England, Bristol
warwick - University of Warwick
york - University of York
Package: unifhy
The Python packageunifhy(Unified Framework for Hydrology) is a hydrological
modelling framework which combines interchangeable modelling components for the
surface layer, subsurface, and open water parts of the terrestrial water cycle.
By two-way coupling these three components, the framework provides a fully
functional model for simulating the terrestrial water cycle. It is designed to
foster collaborations between land surface, hydrological, and groundwater
modelling communities by structuring their interactions around standardised
interfaces between the components.More details can be found in the online documentation accessible athttps://unifhy-org.github.io/unifhy.
Package: unifhycontrib-artemis
Artemis provides a simple runoff production model designed to be
comparable with the runoff-production models typically embedded
within climate models.It is driven with precipitation, radiation,
temperature, humidity and wind speed on a daily time step and
calculates canopy interception, evaporation, snowmelt, infiltration,
and runoff. It uses a Rutter–Gash canopy formulation (Gash, 1979)
to represent interception, together with Penman–Monteith evaporation
calculated using available radiation data (Monteith, 1965). Soil
moisture is accounted for using a two-layer model with
saturation-excess runoff computed using a generalized TOPMODEL
(Clark and Gedney, 2008). The snowpack is represented using a
temperature-based model of accumulation and melt (Moore et al.,
1999,Hock, 2003,Beven, 2011). Snow accumulates when
precipitation falls while temperature is below a threshold
temperature. When temperature is above a threshold for melt, melting
occurs at a rate proportional to the difference between the current
temperature and the melting temperature. This conceptual model is
widely used (Hock, 2003,Zhang et al., 2006,Rango and
Martinec, 1995,Beven, 2011) and gives performance comparable
with that of more parameter rich energy balance models, despite
their greater complexity (Parajka et al., 2010).The surface layer component of Artemis comprises canopy interception,
evaporation, and snowmelt.The sub-surface component of Artemis comprises infiltration and runoff.contributors:Simon Dadson [1,2], Thibault Hallouin [3], Rich Ellis [1]affiliations:UK Centre for Ecology and HydrologySchool of Geography and the Environment, University of OxfordDepartment of Meteorology, University of Readinglicence:BSD-3-Clausecopyright:2020, University of Oxfordcodebase:https://github.com/unifhy-org/unifhycontrib-artemisHow to installThis package is available on PyPI, so you can simply run:pipinstallunifhycontrib-artemis
Package: unifhycontrib-gr4
The GR4 (“Génie Rural à 4 paramètres” [in French]) model is a
bucket-type rainfall-runoff model featuring four parameters.It is typically used as a daily model, i.e. GR4J model
(Perrin et al., 2003). It can also be used at other temporal resolutions,
e.g. hourly in GR4H model, provided an adjustment in its time-dependent
parameter and constant values is performed (Ficchì et al., 2016). The model
has recently been expressed in a state-space formulation
(Santos et al., 2018).This version of the GR4 model is based on its explicit state-space
formulation and its recommended temporal resolutions are daily or hourly.
With either of these resolutions, time-dependent parametersx2,x3,x4, and constantnuare expected for the daily case and they are
adjusted accordingly if temporal resolution is not daily.The surface layer component of the GR4 model comprises the interception scheme.The subsurface component of the GR4 model comprises the runoff generation
and the runoff routing using the Nash cascade.The openwater component of the GR4 model comprises the runoff routing
using the routing store, and the inter-catchment groundwater exchange.contributors:Thibault Hallouin [1,2]affiliations:Department of Meteorology, University of ReadingNational Centre for Atmospheric Sciencelicence:GPL-2.0codebase:https://github.com/unifhy-org/unifhycontrib-gr4How to installThis package is available on PyPI, so you can simply run:pipinstallunifhycontrib-gr4
Package: unifhycontrib-rfm
River Flow Model (RFM) is a runoff routing model based on a discrete
approximation of the one-directional kinematic wave with lateral
inflow (Bell et al., 2007,Dadson et al., 2011).The wave equation is parametrised differently for surface and
sub-surface pathways, themselves split into a land domain, and a
river domain. Return flow is also possible between surface and
sub-surface pathways in each domain.This Python implementation of RFM is based on the work by Huw Lewis.contributors:Huw Lewis [1], Thibault Hallouin [2]affiliations:UK Met OfficeDepartment of Meteorology, University of Readinglicence:UK Open Governmentcopyright:2020, UK Met Officecodebase:https://github.com/unifhy-org/unifhycontrib-rfmHow to installThis package is available on PyPI, so you can simply run:pipinstallunifhycontrib-rfm
Package: unifhycontrib-smart
The Soil Moisture Accounting and Routing for Transport [SMART] model
(Mockler et al., 2016) is a bucket-type rainfall-runoff model.SMART is an enhancement of the SMARG (Soil Moisture Accounting and
Routing with Groundwater) lumped, conceptual rainfall–runoff model
developed at National University of Ireland, Galway (Kachroo, 1992),
and based on the soil layers concept (O’Connell et al., 1970;Nash and Sutcliffe, 1970). Separate soil layers were introduced
to capture the decline with soil depth in the ability of plant roots
to extract water for evapotranspiration. SMARG was originally developed
for flow modelling and forecasting and was incorporated into the
Galway Real-Time River Flow Forecasting System [GFFS]
(Goswami et al., 2005). The SMART model reorganised and extended
SMARG to provide a basis for water quality modelling by separating
explicitly the important flow pathways in a catchment.The surface layer component of SMART consists in meeting the
potential evapotranspiration demand either with rainfall alone under
energy-limited conditions or with rainfall and soil moisture under
water-limited conditions – throughfall is only generated under
energy-limited conditions. Note, unlike the original SMART model,
this component calculates the available soil moisture from the soil
water stress coefficient provided by the sub-surface component – in
the original SMART model, the available soil moisture is iteratively
depreciated with soil layer depth. This unavoidable simplification
may overestimate the soil moisture available compared to the original
SMART model.The sub-surface component of SMART comprises the runoff generation
and land runoff routing processes. This sub-surface component is
made up of six soil layers of equal depth and five linear reservoirs.
The six soil layers are vertically connected to allow for percolation
and evaporation. The five linear reservoirs represent the different
pathways for land runoff. Note, the river routing of SMART is not
included in this component.The open water component of SMART consists in routing the streamflow
through the river network by means of a linear reservoir.contributors:Thibault Hallouin [1,2], Eva Mockler [1,3], Michael Bruen [1]affiliations:Dooge Centre for Water Resources Research, University College DublinDepartment of Meteorology, University of ReadingIreland’s Environmental Protection Agencylicence:GPL-3.0copyright:2020, University College Dublincodebase:https://github.com/unifhy-org/unifhycontrib-smartHow to installThis package is available on PyPI, so you can simply run:pipinstallunifhycontrib-smart
Package: unifi-ap
unifi_apPython API for UniFi accesspointsInstallationpip install unifi_apUsagecurrently this package can only be used by importing it into own python filesimport unifi_ap
ap = UniFiAP("10.0.0.253", "admin")
clients = ap.get_clients()
ssids = ap.get_ssids()
clients_for_ssid = ap.get_clients(for_ssids=["guest"])Address/hostname and username are mandatoryif you don't define a password, ssh keys from the local ssh authentication agent are usedin addition/alternative to a password you can also define a private key file to be used for the authenticationUniFiAP("10.0.0.253", "admin", keyfile="my-rsa.key")Featuresget a list of SSIDs that the accesspoint is servingget currently connected clients (you can specify the SSIDs for which you want to get the clients - default: all)Creditsinspired byhttps://pypi.org/project/unifi-tracker/LicenseMIT
Package: unifi-backup
Usageunifi-backupis a simple tool to fetch configuration backups from
the UniFi Network Application.Arguments-h,--helpshow the help message and exit.-cFILE,--configFILEthe configuration file (default:~/.config/unifi-backup/config.yml)-oFILE,--outputFILEthe output file. The file name can containstrftimedirectives. If the argument
is specified,directory,nameandkeepfields of the configuration
are ignored.Configuration fileTheunifi-backupneeds a configuration file
(default~/.config/unifi-backup/config.yml). As the file contains secrets,
take care to set reasonable permissions. The file is in
theYAMLformat.Configuration filecontroller:host:unifiport:8443user:adminpassword:...site:defaultssl_verify:true|false|/path/to/custom_cert.pemoutput:directory:.name:"unifi-%Y%m%d-%H%M.unf"keep:12All fields exceptpasswordare optional.hostis a host name or an IP address. The host has to be the same
as the network application is configured for; usingunifihere
andunifi.domain.lanwon’t work.namespecifies the name of the output file.strftimedirectives
are allowed.keepremoves all but the most recent*.unffiles from thedirectory,
that in this case has to be specified and has to be an absolute path.directoryhas to already exist. As the backup is not encrypted
and contains secrets the permissions should be set accordingly.
Package: unifi-cam-proxy
UniFi Camera ProxyAboutThis enables using non-Ubiquiti cameras within the UniFi Protect ecosystem. This is
particularly useful to use existing RTSP-enabled cameras in the same UI and
mobile app as your other Unifi devices.Things that work:Live streamingFull-time recordingMotion detection with certain camerasSmart Detections usingFrigateDocumentationView the documentation athttps://unifi-cam-proxy.comDonationsIf you would like to make a donation to support development, please useGithub Sponsors.
Package: unification
Straightforward Unification, extensible via dispatch.Examples>>>fromunificationimport*>>>unify(1,1){}>>>unify(1,2)False>>>x=var('x')>>>unify((1,x),(1,2)){~x:2}>>>unify((x,x),(1,2))False@unifiableclassAccount(object):def__init__(self,id,name,balance):self.id=idself.name=nameself.balance=balancedata=[Account(1,'Alice',100),Account(2,'Bob',0),Account(2,'Charlie',0),Account(2,'Denis',400),Account(2,'Edith',500)]id,name,balance=var('id'),var('name'),var('balance')>>>[unify(Account(id,name,balance),acct)foracctindata][{~name:'Alice',~balance:100,~id:1},{~name:'Bob',~balance:0,~id:2},{~name:'Charlie',~balance:0,~id:2},{~name:'Denis',~balance:400,~id:2},{~name:'Edith',~balance:500,~id:2}]>>>[unify(Account(id,name,0),acct)foracctindata][False,{~name:'Bob',~id:2},{~name:'Charlie',~id:2},False,False]Function DispatchUnification supports function dispatch through pattern matching.fromunification.matchimport*n=var('n')@match(0)deffib(n):return0@match(1)deffib(n):return1@match(n)deffib(n):returnfib(n-1)+fib(n-2)>>>map(fib,[0,1,2,3,4,5,6,7,8,0])[0,1,1,2,3,5,8,13,21,34]This patten matching can be fairly complexname,amount=var('name'),var('amount')@match({'status':200,'data':{'name':name,'credit':amount}})defrespond(name,amount):balance[name]+=amount@match({'status':200,'data':{'name':name,'debit':amount}})defrespond(name,amount):balance[name]-=amount@match({'status':404})defrespond():print("Bad Request")See full example in the examples directory.Performance and ReliabilityThis was hacked together.  Unification stresses extensibility over performance,
preliminary benchmarks show that this is 2-5x slower than straight tuple-based
unification.This is somewhat reliable, the only caveat is on set unification which is
challenging to do generally within this framework.  It should work well in
moderately complex cases but break down under very complex ones.HistoryThis was carved out from theLogPyandMultiple Dispatchprojects.AuthorMatthew Rocklin
Package: unifi-client
# unifi_clientInstall it via```bashpip install unifi_client```## Usage```pythonfrom unifi_client import AirMaxAPIClientunifi = AirMaxAPIClient(url="https://air.max.example.com",username="username",password="password",verify=False,proxy="socks5h://localhost:5050")unifi.login() # Login to deviceunifi.statistics() # Get all the statistics from deviceunifi.logout() # Logout from device```
Package: unificontrol
unificontrol is a rich and full-featured Python interface to the
Ubiquiti Unifi software defined network controller. Goals of this package
include:A clean interface that supports introspection and self-documentation.A complete implementation of the Unifi controller API. Currently it supports over 100 API calls to the Unifi controller.Proper handling of SSL connections to allow secure access to the controller even when the controller uses a [self-signed certificate](ssl_self_signed.md).A concise, readable internal representation of the Unifi API, so that new API calls can easily be added as new features are added to the controller.Python 3 only, since it’s the way of the future.InstallationTo install the most recent release use:pip install unificontrolTo install the latest version of the code from GitHub use:pip install -e git+https://github.com/nickovs/unificontrol.git@master#egg=unificontrolDocumentationTheunificontrolcode aims to be self-documenting as far as possible so if you are using it in an interactive environment the built in Pythonhelp()function will often tell you what you need.There is also documentation that can be built using Sphynx in thedocsdirectory and a built version of these docs ishosted on ReadTheDocs.
Package: unifi-discovery
Unifi DiscoveryDiscover Unifi DevicesInstallationInstall this via pip (or your favourite package manager):pip install unifi-discoveryExample usageaioscanner.pyContributors ✨Thanks goes to these wonderful people (emoji key):Floris Van der krieken💻💡This project follows theall-contributorsspecification. Contributions of any kind welcome!CreditsThis package was created withCookiecutterand thebrowniebroke/cookiecutter-pypackageproject template.