Saravanan666/pypi-org huggingface dataset:
Package: creepy
[![PyPI Version](https://img.shields.io/pypi/v/creepy.svg?style=flat)](https://pypi.python.org/pypi/creepy/)[![PyPI Download](https://img.shields.io/pypi/dm/creepy.svg?style=flat)](https://pypi.python.org/pypi/creepy/)# CreepyDead simple web crawler for PythonThere are already a lot of web crawlers for Python, such as Scrapy. Creepy isyet another web crawler for Python, which ains to provide a simple and light wayto write web crawlers.## Example usage```pythonfrom creepy import Crawlerclass MyCrawler(Crawler):def process_document(self, doc):if doc.status == 200:print '[%d] %s' % (doc.status, doc.url)# Do something with doc.text (the content of the page)else:passcrawler = MyCrawler()crawler.set_follow_mode(Crawler.F_SAME_HOST)crawler.add_url_filter('\.(jpg|jpeg|gif|png|js|css|swf)$')crawler.crawl('http://www.example.com/')```## Installation1. Install from PyPI:`pip install creepy`2. Arch Linux users can find it on AUR or using [Yaourt](https://wiki.archlinux.org/index.php/Yaourt):`yaourt -S python2-creepy-git`## Bugs* Please report bugs to the github issure tracker.## Contributing1. Fork it2. Create your feature branch (`git checkout -b my-new-feature`)3. Commit your changes (`git commit -am 'Add some feature'`)4. Push to the branch (`git push origin my-new-feature`)5. Create new Pull Request
Package: cree-sro-syllabics
Cree SRO/SyllabicsPython 3 library to convert between Western Creestandard Roman
Orthography(SRO) tosyllabicsand back again!Can be used for:nêhiyawêwin/ᓀᐦᐃᔭᐍᐏᐣ/Cree Y-dialectnīhithawīwin/ᓃᐦᐃᖬᐑᐏᐣ/Cree Th-dialectnēhinawēwin/ᓀᐦᐃᓇᐍᐏᐣ/Cree N-dialectInstallUsingpip:pip install cree-sro-syllabicsOr, you can copy-paste or downloadcree_sro_syllabics.pyinto
your own Python 3 project!UsageVisit the full documentation here! Wondering about
words like "syllabics", "transliterator", or "orthography"? Visitthe glossary!Convert SRO to syllabics:>>>fromcree_sro_syllabicsimportsro2syllabics>>>sro2syllabics('nêhiyawêwin')'ᓀᐦᔭᐍᐏᐣ'>>>sro2syllabics('write nêhiyawêwin')'write ᓀᐦᐃᔭᐍᐏᐣ'Convert syllabics to SRO:>>>fromcree_sro_syllabicsimportsyllabics2sro>>>syllabics2sro('ᐊᒋᒧᓯᐢ')'acimosis'>>>syllabics2sro(' → ᒪᐢᑫᑯᓯᕽ  ᑎᕒᐁᐩᓬ ')' → maskêkosihk  tireyl 'See alsonêhiyawêwin syllabicsLicenseCopyright © 2018–2021 National Research Council Canada.Licensed under the MIT license.
Package: creevey
CreeveyNote 6/15/20:Our team previously had a tradition of naming projects with terms or characters from the Harry Potter series, but we are disappointed by J.K. Rowling’s persistent transphobic comments. In response, we will be renaming this repository, and are working to develop an inclusive solution that minimizes disruption to our users.Creevey is a file processing framework. It is designed for IO-bound workflows that involve reading files into memory, doing some processing on their contents, and writing out the results. It makes running those workflows faster and more reliable by parallelizing them across files, optional skipping files that have already been processed, handling errors, and keeping organized records of what happened.Creevey was developed for deep learning computer vision projects, so in addition to the general framework it also provides predefined components for image processing. However, it can be used for any project that involves processing data from many sources.Seethe docsfor more details.
Package: creh-logs
=====Creh Logs=====Creh-logs is a simple Django app to conduct Web-based polls. For eachquestion, visitors can choose between a fixed number of answers.Detailed documentation is in the "docs" directory.Quick start-----------1. creh-logs can be obtained directly from PyPI, and can be installed with pip:pip install creh-logs1. Add "polls" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'logs',]2. Run "python manage.py migrate" to create the log models.3. Usefrom creh-logs.actions import registerfrom creh-logs.utils import get_locationregister.create_by_exception(exception=exception, message='message', location=get_location(), tag='Tag')
Package: crehpages
=====Creh Pages=====Creh-pages is a simple Django app allow you to manage sections ofyour django pages quickly and by any administrator userDetailed documentation is in the "docs" directory.Quick start-----------1. creh-pages can be obtained directly from PyPI, and can be installed with pip:pip install crehpages1. Add "polls" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'pages',]2. Run "python manage.py migrate" to create the log models.3. Use--- Uploadpython runtests.pypython setup.py sdistpython setup.py sdist upload -r pypitwine upload dist/*---
Package: creh-pages
=====Creh Pages=====Creh-pages is a simple Django app allow you to manage sections ofyour django pages quickly and by any administrator userDetailed documentation is in the "docs" directory.Quick start-----------1. creh-pages can be obtained directly from PyPI, and can be installed with pip:pip install creh-pages1. Add "polls" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'pages',]2. Run "python manage.py migrate" to create the log models.3. Use
Package: creh-urls
=====Creh Urls=====Creh-urls is a simple Django app redirect inactive urls in web page.Detailed documentation is in the "docs" directory.Quick start-----------1. creh-urls can be obtained directly from PyPI, and can be installed with pip:pip install creh-urls1. Add "urls" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'urls',...]2. Run "python manage.py migrate" to create the log models.3. UseMIDDLEWARE_CLASSES = (...'urls.middleware.UrlRedirectMiddleware',...)
Package: creh-urls-redirec
=====Creh Urls=====Creh-urls is a simple Django app redirect inactive urls in web page.Detailed documentation is in the "docs" directory.Quick start-----------1. creh-urls can be obtained directly from PyPI, and can be installed with pip:pip install creh-urls1. Add "urls" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'urls',...]2. Run "python manage.py migrate" to create the log models.3. UseMIDDLEWARE_CLASSES = (...'urls.middleware.UrlRedirectMiddleware',...)
Package: creh-urltrace
=====Creh Url Trace=====Creh-urltrace is a simple Django app, get the url reference  and insert in a group of url's.Detailed documentation is in the "docs" directory.Quick start-----------1. creh-urltrace can be obtained directly from PyPI, and can be installed with pip:pip install creh-urltrace1. Add "urltrace" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'urltrace',...]2. Run "python manage.py migrate" to create the log models.3. UseMIDDLEWARE_CLASSES = (...'urltrace.middleware.UrlTraceMiddleware',...)
Package: creig
creig概要英語学習支援アプリケーションGUI単語リストやAPIキーなどの各種データは~/.creig_dataに存在しているインストールpip install -U creig使用法Listリストに登録されている単語の表示、単語をリストに登録Testリストに登録されている単語を出題、意味を4択から回答ReadingChatGPTを使って以下の情報を提供する英文に含まれる単語、熟語とその意味の表示英文の翻訳と主語動詞の表示HistoryTestで正解した回数のグラフを表示apikeyapikeyの入力依存関係openai ~= 0.28wxPython ~= 4.2.1plotly ~= 5.16.1ライセンスMITライセンス
Package: crelm
CrelmThe Crelm package provides a relatively simple API around the CFFI system. Give it C code or source files, it gives you a package with bindings to functions andstructs. Easiest way to get started is hack up the examples inthe repo.Installationpip3 install crelmSimple Demofrom crelm import Factory

paste = Factory(debug=False, verbose=True).create_Tube('add2') \
    .add_source_text('int add2(int a, int b) { return a + b; }') \
    .squeeze()

print(f'2 + 3 = {paste.add2(2, 3)}')
Package: crema
cremaconvolutional and recurrent estimators for music analysisUsage optionsFrom the command-line, print to the screen inJAMSformat:python -m crema.analyze file.mp3or save to a file:python -m crema.analyze file.mp3 -o file.jamsFrom within python:fromcrema.analyzeimportanalyzejam=analyze(filename='/path/to/file.mp3')or if you have an audio buffer in memory, librosa-style:jam=analyze(y=y,sr=sr)
Package: crema-ms
Confidence Estimation for Mass Spectrometry Proteomicscremais a Python package that implements various methods to estimate false discovery rates (FDR)
in mass spectrometry proteomics experiments. crema focuses on
methods that rely on the concept of "target-decoy competition." The sole purpose of crema is to do decoy-based FDR
estimation, and to do it well. As a result, crema is lightweight and flexible. It has minimal dependencies and
supports a wide range of input and output formats. On top of that, it is extremely simple to use.For more information, check out ourdocumentation.Installationcrema requires Python 3.6+ and can be installed with pip:$ pip3 install crema-msBasic UsageBefore using crema, you need one or more files, each containing a collection of
peptide-spectrum matches (PSMs) in tab-delimited format. Note that crema defaults
to reading files viacruxformat, but can easily be
manipulated to accept files in formats that use differing column headers.Simple crema calculations can be performed at the command line:$cremadata/tide-search.target.psms.txtdata/tide-search.decoy.psms.txtAlternatively, the Python API can be used to calculate confidence estimates in the Python
interpreter and affords greater flexibility:>>>importcrema>>>input_files=["data/tide-search.target.psms.txt","data/tide-search.decoy.psms.txt"]>>>psms=crema.read_tide(input_files)>>>results=psms.assign_confidence()>>>results.to_txt(ouput_dir="example_output_dir")Check out ourdocumentationfor more details
on how to make full use of crema.DisclaimerThis material was prepared as an account of work sponsored by an agency of the
United States Government.  Neither the United States Government nor the United
States Department of Energy, nor Battelle, nor any of their employees, nor any
jurisdiction or organization that has cooperated in the development of these
materials, makes any warranty, express or implied, or assumes any legal
liability or responsibility for the accuracy, completeness, or usefulness or any
information, apparatus, product, software, or process disclosed, or represents
that its use would not infringe privately owned rights.
Reference herein to any specific commercial product, process, or service by
trade name, trademark, manufacturer, or otherwise does not necessarily
constitute or imply its endorsement, recommendation, or favoring by the United
States Government or any agency thereof, or Battelle Memorial Institute. The
views and opinions of authors expressed herein do not necessarily state or
reflect those of the United States Government or any agency thereof.PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830
Package: cremerlab-utils
cremerlab-utilsThis is a package holding a variety of functions used by members of the Jonas
Cremer  Lab at Stanford University. This is very much in development and  will
be expanded as the utilities for the lab expandsInstallationIf you are interested in contributing to the development, it can be installed
locally via thePython Package installerpipvia the command line.$ pip install cremerlab-utilsIf you are interested in contributing to the development of the software,
you can clone or fork theGitHub Repositoryand install the package locally as follows:$ git clone git@github.com:cremerlab/cremerlab-utils
$ cd cremerlab-utils
$ pip install -e ./If you don't want to clone the source repository, you can install the development
version directly from GitHub:$ pip install -e git+https://github.com/cremerlab/cremerlab-utils.gitLicenseThe software is released under a standard MIT license which reads as follows:MIT License

Copyright (c) 2021 The Authors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: crengine
Change Ringing Engine is a method ringing application for church bell
ringers. It works out all the rows of a method (plain course or touch,
displays them in a variety of formats and even rings them audibly on a
set of bell sample sound files. Change Ringing Engine uses a
traditional command line interface, but may be embedded as an API in
another application such as Bell View.Installation instructions and a user manual are available on the
Harrogate Bell Ringers' websitehttps://harrogatebellringers.org/bellview/
Package: creole
Creole wiki markup parserSee http://wikicreole.org/ for latest specs.Notes:* No markup allowed in headings.Creole 1.0 does not require us to support this.* No markup allowed in table headings.Creole 1.0 does not require us to support this.* No (non-bracketed) generic url recognition: this is "mission impossible"except if you want to risk lots of false positives. Only known protocolsare recognized.* We do not allow ":" before "//" italic markup to avoid urls withunrecognized schemes (like wtf://server/path) triggering italic renderingfor the rest of the paragraph.@copyright: 2007 MoinMoin:RadomirDopieralski (creole 0.5 implementation),2007 MoinMoin:ThomasWaldmann (updates)@license: GNU GPL, see COPYING for details.@license: BSD, see COPYING for details.
Package: creolenltk
CreoleNLTK: Creole Natural Language ToolkitCreoleNLTK is a Python library designed for preprocessing Creole text. The library includes various functions and tools to prepare text data for natural language processing (NLP) tasks. It provides functionality for cleaning, tokenization, lowercasing, stopword removal, contraction to expansion, and spelling checking.FeaturesSpelling Check:Identify and correct spelling errors.Contraction to Expansion:Expand contractions in the text.Stopword Removal:Remove common words that do not contribute much to the meaning.Tokenization:Break the text into words or tokens.Text Cleaning:Remove unwanted characters and clean the text.InstallationYou can install CreoleNLTK using pip:pipinstallcreolenltkUsageSpelling Checker# -*- coding: utf-8 -*-fromcreolenltk.spelling_checkerimportSpellingChecker# Initialize the spelling checkerspell_checker=SpellingChecker()# Correct spelling errors in a wordcorrected_word=spell_checker.correction('Ã²tgraf')print(f"Original Word: Ã²tgraf, Corrected Word:{corrected_word}")# Ã²tografContraction to Expansionfromcreolenltk.contraction_expansionimportContractionToExpansion# Initialize the contraction expandercontraction_expander=ContractionToExpansion()# Expand contractions in a sentenceoriginal_sentence="L'ap manje. m'ap rete lakay mw."expanded_sentence=contraction_expander.expand_contractions(original_sentence)print(f"Original Sentence:{original_sentence}\nExpanded Sentence:{expanded_sentence}")# li ap manje. mwen ap rete lakay mwen.Stopword Removal# -*- coding: utf-8 -*-fromcreolenltk.stopwordimportStopword# Initialize the stopword handlerstopword_handler=Stopword()# Remove stopwords from a sentencesentence_with_stopwords="Sa se yon fraz tÃ¨s ak kÃ¨k stopwords nan KreyÃ²l Ayisyen."sentence_without_stopwords=stopword_handler.remove_stopwords(sentence_with_stopwords)print(f"Sentence with Stopwords:{sentence_with_stopwords}\nWithout Stopwords:{sentence_without_stopwords}")# fraz tÃ¨s stopwords KreyÃ²l Ayisyen.Tokenizerfromcreolenltk.tokenizerimportTokenizer# Initialize the tokenizertokenizer=Tokenizer()# Tokenize a sentencesentence="Sa se yon fraz senp"tokens=tokenizer.word_tokenize(sentence,expand_contractions=True,lowercase=True)print(f"Sentence:{sentence}\nTokens:{tokens}")# ["sa", "se", "yon", "fraz", "senp"]For more detailed usage and examples, refer to thedocumentation.LicenseMIT licensed. See the bundledLICENSEfile for more details.
Package: creon-api
creon-api대신증권 크레온 API반드시 python 32bit를 사용해야합니다.설치pip install creon-api사용 예시examples -> example_daily_routine.py 참고importcreon_api.utilsasutilsimportcreon_api.scripts.crawl_code_listimportcreon_api.scripts.crawl_daily_stock_adj_infoimportcreon_api.scripts.crawl_daily_priceimportcreon_api.scripts.crawl_daily_minute_priceimportcreon_api.scripts.processing_adj_infoif__name__=="__main__":# 주식시장 종목리스트 다운로드creon_api.scripts.crawl_code_list.save_recent_stock_code_list_file()code_list=[*utils.load_krx_code_list(),*utils.index_code_list]# 권리락 정보 다운로드creon_api.scripts.crawl_daily_stock_adj_info.update_stock_adj_info_file(code_list)# 일별데이터 다운로드creon_api.scripts.crawl_daily_price.update_daily_stock_file(code_list)# 분봉데이터 다운로드creon_api.scripts.crawl_daily_minute_price.save_daily_minute_price_file(code_list)# 수정주가 계산 및 저장code_list=utils.get_adj_file_code_list()fori,codeinenumerate(code_list):print(f"{code}{i+1}/{len(code_list)}")processed_adj_price_df=creon_api.scripts.processing_adj_info.get_processed_adj_price_df(code)creon_api.scripts.processing_adj_info.save_processed_df_to_file(processed_adj_price_df,code)사용자 저장 경로 지정하기(optional)main 프로그램 폴더 내에 creon_config.json 생성{"DATA_FOLDER_PATH":"./cybos_data","LOG_PATH":"./cybos_log"}
Package: creon-plus
Creon Plus대신증권에서 제공하는 Creon Plus API를 사용하기 쉽게 재구성한 패키지입니다.jihogrammer@gmail.com현재 이 패키지는 개발 중입니다.TODOrequirements.txt명시Windows에서 테스트 및 예제 개선pywin32종속성과 충돌 없는지 파악Creon Plus 자동 로그인Creon Plus 장애 발생 시 복구 및 예외처리Example - 실시간 가격 구독테스트 안 됨 - OSX에서 구현해서 Windows에서 확인해야 함패키지 내 examples 폴더에서 확인할 수 있으며, 주석은 pydoc이 익숙해지면 추가하겠습니다.현재 내용은 일종의 슈도코드(Pseudocode) 정도입니다.classMyHandler(LivePriceHandler):'''Creon Plus가 발생시키는 이벤트를 감지하는 함수 - 함수명은 반드시 "OnReceived"으로 고정'''defOnReceived(self)->None:dto=LivePrice(self.__module.GetHeaderValue(0),self.__module.GetHeaderValue(1),self.__module.GetHeaderValue(13),self.__module.GetHeaderValue(18),)print(dto)classSubscriber:__module:'Module'def__init__(self):# Creon 모듈 생성self.__module=get_stock_cur_module()# 이벤트 등록self.__handler=bind_module_with_eventhandler(self.__module,MyHandler)# 핸들러에 모듈 등록self.__handler.init(self.__module)defsubscribe(self):self.__handler.subscribe()defexample():'''실행 예시 - 실제로는 Creon 로그인과 pythoncom 핸들링이 필요함'''Subscriber().subscribe()
Package: crepex-django-util
CrepeX django util개발환경poetry를 사용해서 개발가상환경은poetry shell패키지 설치는poetry install최조 pre-commit 셋팅pre-commit install배포테스트TestPypi 계정준비, API 토큰 준비# test pypi repository 등록poetryconfigrepositories.testpypihttps://test.pypi.org/legacy/# poetry 에 토큰 등록poetryconfighttp-basic.testpypi__token__pypi-your-api-token-here# Build & Publishpoetrybuild
poetrypublish-rtestpypi# Get packagepipinstall-ihttps://test.pypi.org/simple/your-package-namePrivate 사용 (Now)# Clone 후 설치$pipinstallgit+https://[user-token]@github.com/[user-name]/[repo-name].git@[브랜치명|태그|해시]# Clone 없이 설치된 버전 사용$pipinstallhttps://[user-token]@raw.githubusercontent.com/[user-name]/[repo-name]/[branch]/dist/[package_name]-[version].tar.gz
Package: crepex-pyutil
CrepeX python util개발환경poetry를 사용해서 개발가상환경은poetry shell패키지 설치는poetry install최조 pre-commit 셋팅pre-commit install배포테스트TestPypi 계정준비, API 토큰 준비# test pypi repository 등록poetryconfigrepositories.testpypihttps://test.pypi.org/legacy/# poetry 에 토큰 등록poetryconfighttp-basic.testpypi__token__pypi-your-api-token-here# Build & Publishpoetrybuild
poetrypublish-rtestpypi# Get packagepipinstall-ihttps://test.pypi.org/.../your-package-name프로덕션Pypi 계정준비, API 토큰 준비# poetry 에 토큰 등록poetryconfigpypi-token.pypipypi-your-token-here# Build & Publishpoetrypublish--build
Package: crepr
creprCreate a__repr__for your python classes.A Python script that takes a file path as a command-line argument,
imports the specified file, and creates a__repr__method
for each class defined in the module.
It uses the definition found in the__init__method of the class.
It is pronounced /kɹeɪpr/, like 🇳🇿 crêpe.Have a look at the blog-postLove Your Representationfor the rationale of this package.InstallpipinstallcreprUsage❯crepr--help
Usage:crepr[OPTIONS]FILE_PATHCreatea__repr__methodforeachclassofapythonfile.

Arguments:FILE_PATH[required]Options:--install-completion[bash|zsh|fish|powershell|pwsh]Installcompletionforthespecifiedshell.--show-completion[bash|zsh|fish|powershell|pwsh]Showcompletionforthespecifiedshell,tocopyitorcustomizeExampleGiven the filetests/classes/kw_only_test.pywith the contents:classKwOnly:def__init__(self,name:str,*,age:int)->None:self.name=nameself.age=ageThe command:❯creprtests/kw_only_test.pyproducesclassKwOnly:def__init__(self,name:str,*,age:int)->None:self.name=nameself.age=agedef__repr__(self)->str:"""Create a string (c)representation for KwOnly."""return(f'{self.__class__.__module__}.{self.__class__.__name__}('f'name={self.name!r}, 'f'age={self.age!r}, '')')Therepr()of an instance of this class will be:>>>fromtests.classes.kw_only_testimportKwOnly>>>kwo=KwOnly('Christian',age=25)>>>kwotests.classes.kw_only_test.KwOnly(name='Christian',age=25,)Give your representations some love.❤️.__repr__(self) -> str:
Package: crescendo
CrescendoCrescendo provides a unified command line + API for training and evaluating Lightning models⚠️Crescendo is a work in progress and highly subject to change🙏 Some of our boilerplate is based on the wonderful template byashleve! Seehere.Summary⭐️ Crescendo leverages the power ofHydra,Lightningand the humble command line to make executing the training of neural networks as easy as possible.⭐️ Hydra supports an incredible suite of tools such as powerful approaches for hyperparameter tuning. These are built in and accessible.⭐️ Loading your models will be handled with thecrescendo.analysisAPI, so you can train your models via the command line on a supercomputer, then load the results in your local Jupyter notebook.Install⚠️Coming soon!You can easily install Crescendo via Pip!pipinstallcrescendoOf particular note, this not only installs thecrescendomodule, but also thecrcommand line executable. A simple example to test that everything is working properly:crmodel=mlpdata=california_housingAcknowledgementThis research is based upon work supported by the U.S. Department of Energy, Office of Science, Office Basic Energy Sciences, under Award Number FWP PS-030. This research used resources of the Center for Functional Nanomaterials (CFN), which is a U.S. Department of Energy Office of Science User Facility, at Brookhaven National Laboratory under Contract No. DE-SC0012704. This software is also based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Department of Energy Computational Science Graduate Fellowship under Award Number DE-FG02-97ER25308.The Software resulted from work developed under a U.S. Government Contract No. DE-SC0012704 and are subject to the following terms: the U.S. Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable worldwide license in this computer software and data to reproduce, prepare derivative works, and perform publicly and display publicly.THE SOFTWARE IS SUPPLIED "AS IS" WITHOUT WARRANTY OF ANY KIND. THE UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, AND THEIR EMPLOYEES: (1) DISCLAIM ANY WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE OR NON-INFRINGEMENT, (2) DO NOT ASSUME ANY LEGAL LIABILITY OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR USEFULNESS OF THE SOFTWARE, (3) DO NOT REPRESENT THAT USE OF THE SOFTWARE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS, (4) DO NOT WARRANT THAT THE SOFTWARE WILL FUNCTION UNINTERRUPTED, THAT IT IS ERROR-FREE OR THAT ANY ERRORS WILL BE CORRECTED.IN NO EVENT SHALL THE UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, OR THEIR EMPLOYEES BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, CONSEQUENTIAL, SPECIAL OR PUNITIVE DAMAGES OF ANY KIND OR NATURE RESULTING FROM EXERCISE OF THIS LICENSE AGREEMENT OR THE USE OF THE SOFTWARE.