Saravanan666/pypi-org huggingface dataset:
Package: gooder
GOOgle spiDERGoogle search engine parser on python3InstructionRequirement python 3.10+pip install gooderfromgooderimportGoodergooder=Gooder()# Make request on google.com/search?q=Hello+Worldparsed=gooder.parse(query="Hello World")# Print only result linksprint(gooder.get_links())# Print only result titlesprint(gooder.get_titles())# Print all results list[tuple[link,title]]print(gooder.raw_results)# If TRUE = parsed, else = captcha/rate limitif(parsed)# Save urls to json filegooder.save_to_file(only_urls=True,to_json=True,override=True,file="results.json")Methods & FieldsMethod/FieldArgsExampleResultGooder.parsequery: str, page: int=0, ignore_google: bool=True, clear_old: bool=Truegooder.parse("hello",  clear_old=False)True | FalseGooder.raw_resultsFieldField[[link, title], ...]Gooder.get_linksrepeats: bool = Falsegooder.get_links()[unique_link, ...]Gooder.get_titlesNonegooder.get_titles()[title, title, ...]Gooder.save_to_fileonly_urls: bool = True override: bool = True to_json: bool = False file: str = "urls.txt"gooder.save_to_file()New file with urlsGooder.get_hostnamelinks: str | listgooder.get_hostname(https://google.com/)google.comGooder.get_captcha_urlNonegooder.get_captcha_url()None| google.com/sorry/...Gooder.get_headersNonegooder.get_headers()None| HTTPHeaderDict({...})Todo:Add proxy managerReplaceraw_results: list(list())todict()
Package: gooder-cv
gooder-cv基于python-opencv2查找图像中对象位置Find object position based on python-opencv2for python2.7+Usageimport gooder_cv as ac
imsrc = ac.imread('youimage.png') # 原始图像
imsch = ac.imread('searched.png') # 带查找的部分SIFT查找图像print ac.find_sift(imsrc, imsch)
# - when Not found
@return None 
# 之前是返回的 []

# - when found
@return {'point': (203, 245), 'rectangle': [(160, 24), (161, 66), (270, 66), (269, 24)], 'confidence': 0.09}
# point: 查找到的点
# rectangle： 目标图像周围四个点的坐标
# confidence: 查找图片匹配成功的特征点 除以 总的特征点SIFT多个相同的部分查找print ac.find_all_sift(imsrc, imsch, maxcnt = 0)
# - when not found
@return []
# - when found
@return [{..}, {..}]
# {..}的内容跟SIFT查找到单个图像的格式一样maxcnt是可选参数，限制最多匹配的数量。直接匹配查找图像print ac.find_template(imsrc, imsch)期望输出 (目标图片的中心点，相似度)， 相似度是电脑计算出来的一个值，跟平常所说的相似97%不是一个意思。对于这个值，达到0.999以上才算是图片一样。(294, 13), 0.9715查找多个相同的图片，如在图形中查找print ac.find_all_template(imsrc, imsch)期望输出 (目标图片的中心点，相似度)[((294, 13), 0.9715), ...]效果开发规范开发规范LICENSELICENCE underMITSome other idea. Not implementedexampleimportgooder_cvimsrc=gooder_cv.Image('demo.png')imobj=gooder_cv.Image('object.png')print(imsrc.find(imobj,method=gooder_cv.FIND_TMPL))# or method=gooder_cv.FIND_SIFT# expect gooder_cv.Position(x=10, y=20, extra={'method': gooder_cv.FIND\_TMPL, 'result': 0.98})print(imobj.find_in(imsrc,method=gooder_cv.FIND_TMPL))# expect gooder_cv.Position(x=10, y=20)rect=gooder_cv.Rect(left=80,top=10,width=50,height=90)# Rect define: Rect(left=0, top=0, right=None, bottom=None, width='100%', height='100%')pos=imsrc.find(imobj,rect=rect,method=gooder_cv.FIND_TMPL)print(pos)# expect gooder_cv.Position(x=10, y=20)print(imsrc.draw_point(pos))# .draw_point(pos2)# expect gooder_cv.Image objectprint(imsrc.draw_rectangle(gooder_cv.Rect(left=80)))# expect gooder_cv.Image objectprint(imsrc.draw_circle('??'))print(imsrc.cv_object)# expect numpy objectimsrc.save('source.png')# An Exception raised when file existsprint(imsrc.rect()==imobj.rect())# expect True or Falseprint(imsrc.percent(imobj))
Package: gooderror
GoodError DocumentationThe GoodError library provides an improved exception handling mechanism in Python. It allows you to enhance the output of exceptions, including sending them to GPT-3 for additional context.InstallationTo install GoodError, use pip:pipinstallgooderrorExampleHere's an example of how to use GoodError:fromgooderrorimportGoodErrorGoodError()x="SADfsadf"+5# GoodError will enhance the exception output and will add COLORS!# OUTPUT:#<module>, TypeError(Can only concatenate str (not "int") to str)#main, Line 82 -> m = "SADfsadf" + 5Class: GoodErrorThe GoodError class provides the following attributes and methods:Attributesgpt_key(str): Your GPT API key.use_colors(bool): Whether to use colors in the output.GPT3.5 UsageImport the GoodError class and initialize it with your GPT API key.fromgooderrorimportGoodError# Initialize GoodError with your GPT API keyGoodError(gpt_key="YOUR_GPT_API_KEY")result=0/0# OUTPUT:#<module>, ZeroDivisionError(Division by zero)#main, Line 80 -> result = 0/0#Waiting for GPT to respond...#The error "ZeroDivisionError" is raised when you try to divide a number by zero in Python. Division by zero is not defined in mathematics, hence this error is generated to indicate an invalid operation.#To fix this error, you need to make sure you do not divide a number by zero. If the denominator can potentially be zero in your code, you can add a check to handle this scenario using an if condition. For example:#try:#    result = 0/0#except ZeroDivisionError:#    print("Cannot divide by zero")#In this case, if the division operation encounters a ZeroDivisionError, it will be caught by the except block, which will then print the error message.
Package: good-first-issues
Good First IssuesFind good first issues right from your CLI!Install Good First IssuesRequires Python 3.6.1 or higher.$pip3installgood-first-issues--upgradeThe CLI uses the aliasgfito run commands.ContentsInstall Good First IssuesContentsCreate GitHub Personal Access TokenUsageSearch for issuesQuery all repos in an organizationQuery a single repo in an organizationQuery all repos in a user profileQuery a single repo in a user profile.Search for Hacktoberfest approved issuesQuery all repos with topichacktoberfestQuery all repos with topic 'hacktoberfest' in an organization or in a user profileChanging output limitsViewing issues on browserContributingCreate GitHub Personal Access TokenThe CLI requires GitHub Personal Access Token to make requests to the GitHub API.GetGitHub Personal Access TokenYou don't have to select any scopes, add a Note for your token and selectGenerate token.Provide token to CLI:$gficonfigToken is stored locally on/home/<username>/.gfi/good-first-issuesfile.Token in envrionment variable:Store the token with the nameGFITOKENin your environment.UsageGitHub provides API to fetch user and organization data.Personal Access Tokenis required for authentication and data fetching.Search for issuesTo look for issues, use thegfi searchcommand.Query all repos in an organization$gfisearch"rust-lang"DemoQuery a single repo in an organization$gfisearch"facebook"--repo"jest"DemoQuery all repos in a user profile$gfisearch"yankeexe"--userDemoQuery a single repo in a user profile.--userflag not required here.$gfisearch"yankeexe"--repo"good-first-issues"DemoSearch for Hacktoberfest approved issuesQuery all repos with topichacktoberfest$gfisearch--hacktoberfest

$gfisearch-hfDemoQuery all repos with topic 'hacktoberfest' in an organization or in a user profileQuery all repos with topic 'hacktoberfest' in an organization.$gfisearch"facebook"--hacktoberfestDemoQuery all repos with topic 'hacktoberfest' in a user profile.--userflag not required here.$gfisearch"yankeexe"--hacktoberfestDemoChanging output limitsThe output is limited to display 10 issues by default. Use--limitflag to set the number of issues for output or--allfor no limits.Limit the issues to 12$gfisearch"facebook"--limit12DemoView all issues found.$gfisearch"rust-lang"--allViewing issues on browserIt's hard to navigate through all the issues when you have the--allflag enabled, you can view the issues on your browser with ease using the--webflag.$gfisearch"facebook"--all--webDemoContributingFor guidance on setting up a development environment and how to make a contribution togood-first-issues, see thecontributing guidelines.
Package: goodgit
GoodGit: Git, but with a Human Touch 🎉It only takes 4 minutes, not 4 years to master git! 😎https://github.com/brainspoof/goodgit/assets/78320447/e8115809-c000-4f19-a941-e606a0cca711GoodGit is the brainchild of community frustrations – a chorus of developers who wanted Git to be friendlier. We listened. We coded. Now, we present to you GoodGit: Git, as it should be - intuitive, quick, and with a human touch.Features 🌟Simplified Commands: Because 'intuitive' is not just a buzzword.AI-Powered Commit Messages: Say goodbye to commit message writer's block.SSH Setup in a Snap: We value your time. Setting up SSH keys is now a breeze.Multi-Account Flow: Effortlessly juggle between work and personal Git accounts.Effortless Search: Zero in on that elusive commit or branch with ease.Branching Simplified: Focus on your work, not on stashing and managing branches.Direct Publish: Seamlessly push your projects to GitHub. No more context switching.Upcoming Features 🚀AI Merge Conflict Resolution: Let AI handle the tough parts of merging.GUI: For when you want to point-and-click instead of type-and-peck.Prerequisites 🛠PythonPipInternet Connection (It's the digital era, after all!)A Pair of Hands (Preferably attached to a human who can type.)Installation 💻Jump into GoodGit goodness with:pipinstallgoodgitUsage 🛠️Simplified Git Commands
Forget the convoluted commands. With GoodGit, you get the power without the complexity.Add Filesadd files like you're used toggadd<files-to-add>CommitYou write code; AI writes the commit message for you!ggcommitUncommitUncommit the oops commitsgguncommitTime TravelTime-Travel through your history, make it your present if you like itggtimetravelorggttBring the time-travelled commit to the present.ggttapplysearchWhat you want is just a search awayggsearchbranchNo stashing; no worries! Just start branchingggbranchorggbsetupNo more irritating SSH, set it it in T-10 seconds.Have multiple accounts? Set them up too!ggsearchpublishJust started a project? Don't leave your terminal to add it to github!ggpublishwebopen your repo in the browser from the terminalggwebContributing 🤝Join the crew! Your expertise is the secret sauce to make GoodGit even better.Got an idea?Open an issue.Got code?Pull, request it.Found a bug?We're on it, just let us know.Become a part of the GoodGit story athttps://goodgit.io/- where we're turning'dang it, Git!'into'Yay, Good Git!'
Package: goodhound
GoodHound______                ____  __                      __
  / ____/___  ____  ____/ / / / /___  __  ______  ____/ /
 / / __/ __ \/ __ \/ __  / /_/ / __ \/ / / / __ \/ __  / 
/ /_/ / /_/ / /_/ / /_/ / __  / /_/ / /_/ / / / / /_/ /  
\____/\____/\____/\__,_/_/ /_/\____/\__,_/_/ /_/\__,_/Attackers think in graphs, defenders think in actions, management think in charts.GoodHound operationalises Bloodhound by determining the busiest paths to high value targets and creating actionable output to prioritise remediation of attack paths.I'm lucky enough to do this for a living. Any donations will be passed on to my local foodbank, animal sanctuary and animal rescue centres.UsageQuick StartFor a very quick start with most of the default options, make sure you have your neo4j server running and loaded with SharpHound data and run:pip install goodhound
goodhound -p "neo4jpassword"This will process the data in neo4j and output 3 csv reports in the current working directory.DocumentationAll documentation can be found in thewikiAcknowledgmentsThepy2neoproject which makes this possible.ThePlumHoundproject which gave me the idea of creating something similar which suited my needs.Theaclpwnfor the idea around exploit cost.TheBloodhound Gang Slack channelfor Cypher help.TheBloodHound projectfor changing the world and for continuing their support for the Open-Source community even when having a commercial offering.
Package: good-interface
good_interfaceProvides the Interface class and other utilities which can define method "interfaces" which automatically check method implementation in classes and objects.InterfacesAn Interface is a collection of methods that are to be implemented in classes that implement this Interface. The Interface class can define Interfaces from a class skeleton.fromgood_interfaceimportInterface@InterfaceclassMyInterface:defmethod1(self,arg1,arg2):passdefmethod2(self,arg2):passSince the interface is callable, you can call the new Interface object as a decorator on a class, which provides a check on the given class, ensuring that it implements the defined methods in the given interface.fromgood_interfaceimportInterface@InterfaceclassMyInterface:defmethod1(self,arg1,arg2):passdefmethod2(self,arg2):pass@MyInterfaceclassMyClass:defmethod1(self,arg1,arg2):passdefmethod2(self,arg2):passCalling the interface on another interface will extends the interface, adding the methods of this current interface to the new interfacefromgood_interfaceimportInterface@InterfaceclassMyInterface1:defmethod1(self):pass@MyInterface1@InterfaceclassMyInterface2:defmethod2(self,arg1,arg2):passdefmethod3(self,arg2):pass# Creates:## @Interface# class MyInterface2:#     def method1(self):#         pass##     def method2(self, arg1, arg2):#         pass##     def method3(self, arg2):#         pass
Package: goodlibs
goodlibsDownload books from a Goodreads shelf using Library Genesis.:books: BackgroundGoodreadsis a social cataloging website that allows you to search for books and save them to reading lists, known as "shelves".Library Genesis(Libgen) is a file-sharing website for scholarly journal articles, academic and general-interest books, images, comics, and magazines.goodlibsis a simple utility that searches for and downloads all items from a Goodreads shelf using Libgen.
It was built usingbetterreadsand a modified fork oflibgen.py.In solidarity with Library Genesis. In memory of Aaron Swartz.:hammer_and_wrench: InstallationInstall usingpip:pip3installgoodlibsGoodreads setupRegister for aGoodreads API keyin order to access your list of books.Ensure yourGoodreads account privacy settingsallow for access to your shelves via the API.SetWho can view my profile:toanyone (including search engines)Check the boxAllow partners of Goodreads to display my reviews:computer: Usage:heavy_dollar_sign: From the command lineFor basic usage, start with thedownloadcommand:goodlibsdownload--helpIf you want to save your options for later, use theconfigurecommand:goodlibsconfigure--helpTypical usage:goodlibsdownload-kyourgoodreadsapikey-uyourgoodreadsusername-emobi-eepub-epdf:page_with_curl: From a scriptfromgoodlibsimportgoodreads,libgen# Get the list of books from Goodreads.books=goodreads.get_books(api_key="yourgoodreadsapikey",username="yourgoodreadsusername",shelf_name="to-read")# Optional.# Query Libgen with the list of books.libgen.download_books(books=books,language="English",# Optional.extensions=("mobi","epub","pdf"))# Optional.:balance_scale: LicenseThis code is licensed under the GNU General Public License v3.0.
For more details, please take a look at theLICENSEfile.:handshake: ContributingContributions are welcome!
Please feel free to open an issue or submit a pull request.
Package: goodlogging
This logging package provides some additional functionality
to command line utilities allowing for good-looking terminal
displays. These include:Easy indentation of displayed linesConfigurable verbosity levelsOptional identifying tags on every messageEasily trigger ERROR or FATAL messages (where fatal exits the program)Input method for getting user response from the command lineAdd consistent seperators or newlines to the displayed outputRequirementsThis is a python package and requires the following:Python 3.4+InstallationInstall using pip:$pipinstallgoodloggingRequests, Issues, Bugs or SuggestionsAdd any feature requests, issues, bugs or suggestions here:https://github.com/davgeo/goodlogging/issuesPlease give as much detail as possible.
Package: goodman-pipeline
Goodman High Throughput Spectrograph Data Reduction PipelineOverviewThe Goodman High Throughput Spectrograph (Goodman HTS) Data-Reduction Pipeline
is the SOAR Telescope's official data reduction pipeline forGoodman HTS.It has been fully developed in Python and uses mostly astropy affiliated packages
with the exception ofdcrwhich is an external tool
that does cosmic ray identification and correction. The reason for using it
instead of LACosmic is that it works very well for spectroscopic data and the
results are evidently superior. Some of the negative aspects of using this
external (meaning outside of Python domains) software were: The integration into
the pipeline's workflow and the use of an externaldcr.parparameter file.
Such parameters have to be changed by hand and can't be integrated into the
pipeline's workflow itself. In particular for binning 2x2 and custom ROI those
parameters contained indcr.parhas to be specifically tuned.DocumentationYou will find a user manual ongoodman.readthedocs.orgIf you wish to know more about the instrument please check theSOAR websiteHaving trouble?If you are having trouble operating the Goodman Pipeline we suggest the following
procedure.Checkexisting issuesor
open anew Issueon GitHub.Development TeamSimón Torres(NOIRLab Software Engineer - main code developer)César Briceño(SOAR Telescope Scientist - team lead)Bruno Quint(Brazil Support Astronomer - code development adviser)AcknowledgementsWe acknowledge the important contribution ofDavid Sanmartim, who developed
the initial incarnation of the redccd module. We thankTina Armondfor her
invaluable help in adding calibrated comparison lamps to thelibraryof
reference comparison lamps for wavelength solution.Our work would not be possible without the friendly work atmosphere at CTIO
headquarters in La Serena, were we can interact with our SOAR and CTIO
colleagues in lively and useful discussions that have been important in making
the Goodman pipeline possible.  We also acknowledge fruitful discussions and
suggestions from our colleagues Bart Dunlop, Chris Clemens, and Erik Dennihy,
at University of North Carolina at Chapel Hill.Citations:This pipeline makes extensive use of Astropy therefore you should cite as suggested
onAstropy Citation Pageas follows:This research made use of Astropy, a community-developed core Python package
for Astronomy (Astropy Collaboration, 2013, 2018).It also usesDCRfor cosmic rays identification
and removal. You should citethis paperPych, W., 2004, PASP, 116, 148
Package: goodmap
Good MapMap engine to serve all the people ;)SetupUse python 3.10, install poetry:pip install poetryand then install dependencies:poetry installRunning App locallyTL;DRIf you don't want to go through all the configuration, e.g. you just simply want to test if everything works,
you can simply run app with test dataset provided intests/e2e_testsdirectory:poetry run flask --app 'goodmap.goodmap:create_app(config_path="./tests/e2e_tests/e2e_test_config.yml")' runConfigurationIf you want to serve app with your configuration rename config-template.yml to config.yml and change its contents according to your needs.
Values descriptions you can find inside config-template.yml.Afterwards run it with:poetry run flask --app 'goodmap.goodmap:create_app(config_path="/PATH/TO/YOUR/CONFIG")' --debug runDatabaseDatabase consists of three sections:categories- which informs on what categories data of points is dividedvisible_data- list of categories which will be visible by application usersdata- actual data split intocategoriescategoriesFully configurable map where key is name of category and value is list of allowed types. E.g."car_elements": ["mirror", "wheel", "steering wheel"]"color": ["red", "blue", "green"]dataData consists of two parts:obligatory and constantname- name of the objectposition- coordinates of objectcategory dependent - depending on yourcategoriessetup it varies. See example of config below.custom dataYou can define your own, more complex data types as dictionary.obligatory fields in dictionary:type- type of datavalue- value of dataoptional fields in dictionary:displayValue- value to display instead ofvalueExamplesYou can find examples of working configuration and database intests/e2e_testsnamed:e2e_test_config.ymle2e_test_data.json
Package: goodmock
goodmock - A Good Mock Library for PythonThis repository is for activate development of goodmock.DisclaimerThis module makes no claims of mock magic, but it's goodGetting StartedAll source code for this project is located in goodmock.pyPrerequisitesgoodmock relies on features introduced inPEP 612, and only supports Python 3.10+InstallationPyPi: TODOManual Installation:navigate to the root directory of the project and runpython -m pip install .How to use goodmockGiven a class definition like:classClassA:defmethod(inti)->int:...You can set a return value for a class method:classa_mock=Mock.of(ClassA)Mock.when(classa_mock.method).takes(1).returns=2assertclassa_mock.method(1)==2Or you can set an expected exception for a class method:classa_mock=Mock.of(ClassA)Mock.when(classa_mock.method).takes(1).raises=Exception()withpytest.raises(Exception):classa_mock.method(1)That's it!Need help?For more examples see theunit testsFile an issue viaGithub IssuesContributingThis project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution.
Package: goodmodslab-api
О проектеПроект содан для разработчиков работующим сhttp://goodmodslab.ru/Проект не поддерживает асинхронность. Но в скором времени будет)Синхронное использованиеИмпортируйте библиотеку и создайте переменную чтобы пользоваться библиотекойfromgoodmodslab_apiimportGoodModsLabapi=GoodModsLab()Асинхронное использование[Данные удалены]
Package: goodness-of-fit
# Goodness of fitgoodness_of_fit is a python language software package that provide a set of function
for goodness of fit measure between two signals.While most of these functions are available in packages such as [Scipy](https://github.com/scipy/scipy), [Spotpy](https://github.com/thouska/spotpy), etc…
this package brings together all these functions and provides a unified interface for their use.## Content of the packageThe package provides the following functions :
* Mean Error
* Mean Absolute Error
* Root Mean Square Error
* Normalized Root Mean Square Error
* Pearson product-moment correlation coefficient
* Coefficient of Determination
* Index of Agreement
* Modified Index of Agreement
* Relative Index of Agreement
* Ratio of Standard Deviations
* Nash-sutcliffe Efficiency
* Modified Nash-sutcliffe Efficiency
* Relative Nash-sutcliffe Efficiency
* Kling Gupta Efficiency
* Deviation of gain
* Standard deviation of residual## Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.### Prerequisitesgoodness_of_fit requires :Python 3[Numpy](https://github.com/numpy/numpy) for efficient computation on array.### InstallingTo install the package, clone or download the repository and use the setup.py :`bash git clonehttps://github.com/SimonDelmas/goodness_of_fit.gitcd goodness_of_fit python ./setup.py install `### Building the documentationThe documentation could be generated using the command :`bash python ./setup.py build_sphinx `### Running the testsAfter installation, you can launch the test suite with pytest :`bash pytest `## LicenseThis project is licensed under the GLP-2.0 License - see the [LICENSE.md](LICENSE.md) file for details.