Saravanan666/pypi-org huggingface dataset:
Package: ogura
oguraPoemsGeneratorQuote generator written completely in python that displays a random poem from the Ogura Hyakunin Isshu (Collection of 100 japanese poems by the Ogura poets).Pre-requisitespython&pip.InstallationCreate avenvand use pip to install the package.pip install -i https://test.pypi.org/simple/ oguraFeaturesDisplays poem in japanese, romaji (romanized spelling in english) and the english translation.Displays the text gradually letter by letter.
Package: oguzun-hesap-makinasi
Bu paket ÅŸu iÅŸe yarar ÅŸunlarÄ± yapar vs vs gibi birÅŸeyler yazmasÄ± gerekiyor.paketi sÄ±fÄ±rdan kurup pypi.org a atmak iÃ§in lattaki komutlar kullanÄ±nÄ±zpython3setup.pysdistbdist_wheel# paketimiz hazÄ±r ÅŸimdi paketimizi doÄŸrulayalÄ±mtwinecheckdist/*# upload iÃ§in doÄŸrulama. pypi.org domaini deÄŸl test.pypi.org sitesine ayrÄ±ca Ã¼ye olmak gerekiyor.twineupload-rtestpypidist/*# eÄŸer buraya publish yapabildiyseniz artÄ±k gerÃ§ek yere publish yapÄ±labilirtwineuploaddist/*Kurumu yaptÄ±ktan sonra kullanÄ±mfrommuratin_hesap_makinasiimportHesapMakinasihm=HesapMakinasi()hm.topla(3,2)# sonuc 5
Package: ogzoengine
This game engine is based on pygame. Our goal is to make it easy for people, even those who don't know python or coding, to create games.If you want to get started with this game engine by creating a sample game,How to DownloadFirst, you need to download Python. You can do this by going to thePython official websiteand downloading it according to your operating system.After downloading, to check, you can write this code in the terminal or CMD:python --versionIf the result isPython 3.11.5or higher, you are ready to download the game engine. You can do this by typing the following code in the terminal or CMD:pip install ogzoengineDownload a code editor of your choice. Recommended code editors are:Visual Studio: It has powerful debugging and code completion features but can be challenging for beginners and takes up a lot of space.Visual Studio Code Download PagePyCharm: Specifically made for the Python language, it provides a fast and efficient coding experience but the full version is not free.PyCharm Download PageSublime Text: It's fast and lightweight, offering quick performance, but the full version is paid and updates are not frequent.Sublime Text Download PageAtom: It has good auto-completion and provides GitHub assistance with integrated Git support, but it may cause high memory usage for some users.Atom Download PageNotepad++: It's simple and takes up less storage space, but it has a poor interface and lacks features like code completion.Notepad++ Download PageCodingimport BS.engine as bs

screen1 = bs.Screen()

# Variables
width, height = 1200, 600

# Drawwing
circle1 = bs.Circle(200,200,25,[255,255,255])
line1 = bs.Line(200,300,100,150,[255,255,255],3)
squ1 = bs.Square(500,500,45,45,[255,255,255])
text1 = bs.Text(350,350,"Hello",None,20,(255,255,255))

saved = None
# listener function
def listener():
    if bs.inputs(screen1.return_keys(),'a').return_key():
        print("a clicked")

# drawwing function
def draw():
    circle1.draw(screen1)
    line1.draw(screen1)
    squ1.draw(screen1)
    text1.draw(screen1)

# While function 
def whiles():
    pass

# Using function
screen1.use_drawing(draw)
screen1.use_while(whiles)
screen1.use_listener(listener)


screen1.set_screen(width,height,"Engine test")
screen1.run()
Package: ohcg
ohcg - OpenAPI3 HTTP client generatorThis package was developed for private use withFastAPIand it doesn't cover all OpenAPI specifications.InstallationpipinstallohcgorpoetryaddohcgUsageUsage:ohcggenerate[OPTIONS]URLGenerateclientfromspecifiedurl

Arguments:URL[required]Options:-o,--output-dirDIRECTORYdirectoryforgeneratedmodelsandclientinstance[required]-a,--auth,--authorization-headerTEXT--helpShowthismessageandexit.Exampleohcggenerate-omy_output_dirhttps://raw.githubusercontent.com/OAI/OpenAPI-Specification/main/examples/v3.0/petstore.jsonmy_output_dir/models.pyfrom__future__importannotationsimporttypingfrom.base_modelimport(_BaseListModel,_BaseModel,)classPet(_BaseModel):id:intname:strtag:typing.Optional[str]classPets(_BaseListModel):passclassError(_BaseModel):code:intmessage:strmy_output_dir/client.pyfromjsonimportJSONDecodeErrorfromtypingimportTypeimporthttpxfrom.modelsimport*classClient:"""Swagger Petstore @ 1.0.0"""def__init__(self,base_url:str=None,**kwargs):self.httpx_client=httpx.AsyncClient(base_url=base_url,**kwargs)asyncdefmake_request(self,method:str,path:str,*,response_model:Type=None,errors_models:dict[int,Type[BaseModel]]=None,**kwargs):asyncwithself.httpx_clientasclient:response=awaitclient.request(method,path,**kwargs)ifresponse.is_error:iferrors_modelsisNone:errors_models={}error_model=errors_models.get(response.status_code)ifbool(error_model):try:raiseparse_obj_as(error_model,response.json())except(JSONDecodeError,pydantic.ValidationError):response.raise_for_status()else:# Raise error if request is not succeeded before trying to parse responseresponse.raise_for_status()response_json=response.json()ifbool(response_model):returnpydantic.parse_obj_as(response_model,response_json)returnresponse_jsonasyncdefget_pets(self,*,limit:int=None,)->Pets:"""List all pets"""returnawaitself.make_request("get","/pets",response_model=Pets,params={"limit":limit,},)asyncdefpost_pets(self,):"""Create a pet"""returnawaitself.make_request("post","/pets",)asyncdefget_pets_pet_id(self,pet_id:str,)->Pet:"""Info for a specific pet"""returnawaitself.make_request("get","/pets/{petId}".format(petId=pet_id),response_model=Pet,)my_output_dir/base_model.pyfromtypingimport(Generic,TypeVar,)importpydanticclass_BaseModel(pydantic.BaseModel):classConfig:allow_population_by_field_name=Trueclass_Error(_BaseModel,Exception):passListItemType=TypeVar('ListItemType',bound=_BaseModel)class_BaseListModel(pydantic.BaseModel,Generic[ListItemType]):__root__:list[ListItemType]def__iter__(self):returniter(self.__root__)def__getitem__(self,item):returnself.__root__[item]RoadmapBasic models and client generatorAny OpenAPI types support for generated models (including allOf, anyOf, etc.)Cookie and headers parameters supportAuth and security schemas supportSync version with httpxSync version with requestsAsync version with aiohttpLICENSEThis project is licensed under the terms of the MIT license.
Package: ohdear-sdk
Oh Dear PythonAn SDK to easily work with theOh Dear APIInstallVia Pippipinstallohdear-sdkUsagefromohdearimportOhDearohdear=OhDear(api_token="your-token")sites=ohdear.sites.all()Available MethodsDescriptionohdear.me()Retrieve aUserInfodict with details about the currently authenticated user.ohdear.authenticated()Retrieve abooleanresponse indicating whether the current user is authenticated.ohdear.broken_links.show(123)Retrieve aBrokenLinksCollectiondict with details about broken links for a specific site.ohdear.certificates.enable(123)Retrieve aCertificateHealthdict containing details about the certificate and it's health.ohdear.checks.enable(123)Retrieve abooleanindicating whether a check was enabled successfully.ohdear.checks.disable(123)Retrieve abooleanindicating whether a check was disabled successfully.ohdear.cron_checks.show(123)Retrieve aCronChecksCollectiondict with details about the cron checks for a specific site.ohdear.domain_monitoring.domain(123)Retrieve aDomaindict with details about the domain for a specific site.ohdear.mixed_contents.show(123)Retrieve aMixedContentsCollectiondict with details about the mixed content for a specific site.ohdear.sites.all()Retrieve aSitesCollectiondict with details about all sites.ohdear.sites.show(123)Retrieve aSitedict with details about a specific site.Change logPlease seeCHANGELOGfor more information on what has changed recently.Testinghatchshell

hatchruntestSecurityIf you discover any security related issues, please emailsecurity@voke.devinstead of using the issue tracker.CreditsOwen VokeAll ContributorsLicenseThe MIT License (MIT). Please seeLicense Filefor more information.TreewareYou're free to use this package, but if it makes it to your production environment you are required to buy the world a tree.It’s now common knowledge that one of the best tools to tackle the climate crisis and keep our temperatures from rising above 1.5C is to plant trees. If you support this package and contribute to the Treeware forest you’ll be creating employment for local families and restoring wildlife habitats.You can buy treeshere.Read more about Treeware attreeware.earth.
Package: ohdsi-circe
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-cohort-diagnostics
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-cohort-generator
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-common
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-database-connector
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-feature-extraction
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohdsi-sqlrender
python-ohdsiPython wrappers for (some) OHDSI tools. This project has been initiated for
supporting OMOP data sources invantage6.Make sure you have a working R environment with the OHDSI packages installed.InstallationPython bindingInteract with the OMOP database using a python interface.Install Java JDK.Install R:sudo apt-get install r-base(setR_HOME)Install R packagespipinstallpython-ohdsiAPI serviceSpin up a small webserver next to the OMOP database to allow HTTP requests to
the OMOP database. You can use the prebuild image from dockerhub:dockerpull...
dockerrun...Or you can build the image yourself:dockerbuild-tohdsi-api.
dockerrun-p5000:5000ohdsi-apiOr you can run the API service directly from the source code:pipinstall-rrequirements.txt
pythonapi.pyBuilding documentationcddocsexportIGNORE_R_IMPORTS=True
makehtmlcddocsSet-Item-PathEnv:IGNORE_R_IMPORTS-ValueTruemakehtmlor you can usemake livehtmlto automatically rebuild the documentation
when a file is changed.You can set theIGNORE_R_IMPORTSenvironment variable to ignore the R imports
in the documentation. This is useful when you don't have the R packages
installed but want to build the documentation anyway.User DocumentationThe user documentation can be found atreadthedocs.
Package: ohHtmlToMarkdown
ohHTML2Markdown当爬取一些如新闻、简书、知乎之类的面向文档的网站时，通常需要将文章保存下来，最合适的介质莫过于Markdown文档（有些网站本来就是用Markdown渲染出来的）。ohHTML2Markdown可以将一部分或整个网页转化为Markdown文档，ohHTML2Markdown会尽量处理一些不规范的HTML文档，但是不保证输出文档的质量。When crawling doc-oriented websites contains news, knowledge market like quora, or even Github, sometimes, you might like to save the article. The best media for storage would be .md file, some articles are even generated from .md files.ohHTML2Markdownis able to convert HTML fragment or a complete html file to a human-friendly .md file. Although there would be some irresponsible use in HTML tags,ohHTML2Markdownwill do its best to ensure the output stays in its best quality.目前支持的HTML标签有：h1~h6,p,a,img,del,b,strong,i,em,hr,br,ul,ol,table,blockquote,code,pre,span,title,time,iframe,section,div,html,body,head。Currently, supported HTML tags include:h1~h6,p,a,img,del,b,strong,i,em,hr,br,ul,ol,table,blockquote,code,pre,span,title,time,iframe,section,div,html,body,head。处理主要靠的是BeautifulSoup库的html.parser解析器和.descendants对象。前者可以把html文档解析成一个树状模型，访问.contents可以访问到当前层级的所有子树的根节点；后者可以返回一个生成器，它包含了当前子树的所有节点（包含本身）。ohHTML2Markdownis mainly built onBeautifulSoupLibrary, to be more specific, itshtml.parserparser and the.descendantsobject. The parser is able to convert a html file to a tree structure, the using.contentwe can access all sub-trees on the same level;.descendantsreturns an generator which contains all nodes in the current (sub)tree (including itself).通过判断descendants的长度可以知道该子树有没有子节点，然后 根据当前tag的类型，可以选择继续进行深度遍历还是将它转换为Markdown的语义。By checking the length ofdescendantsgenerator, we can know whether this tree has descendants or not(not that this tree could also be one of descendants of another tree on its topper level). Then based the type of tags included, we make the decision to go further, or convert it to markdown semantics.其他关于本库的一些细节：发布自己的Python包 - ohHTML2Markdown。More about this library,发布自己的Python包 - ohHTML2Markdown. This post is Chinese.安装 Installationpip install ohHTML2Markdown使用 Usageimport ohHtml2Markdown as h2m

# 从字符串读取 Read from string
result = h2m.Parser("<h1>h1</h1>", h2m.Parser.STRING).convert()

# 或从文件读取 Read from file
result = h2m.Parser("test/test.html", h2m.Parser.FILE).convert()

with open("test/out.md", 'w', encoding='utf-8') as file:
        file.write(result)
Package: ohk
ohk, an interactive replacement to tools like grep and awkFeatures:Normal / fuzzy / regex search for linesCase sensitive / insensitive searchKeyboard shortcutsInstallation→pipinstallgit+https://github.com/kbairak/ohkor→gitclonehttps://github.com/kbairak/ohk
→cdohk
→pipinstall.Addsudoor--userto yourpip installcommand depending on your setupUsage→[previouscommand|]ohk[-f/-r/-i][|nextcommand]Theprevious command's output will be piped into ohk which will start an
interactive session to help you filter its lines and columns. Once you press
enter inside the interactive session, the filtered output will piped into thenext command.If theprevious commandis missing (ie ifohk's standard input is the
keyboard), you will be asked to provide a command before the interactive
session starts:➜ohk|xargsdockerstop
Entercommand:If thenext commandis missing (ie ifohk's standard output is the terminal
screen), you will be asked to provide one after you make your selection.You can even use pipes in the output command and even re-invokeohk:➜dockerps-a|ohk
Tips:-use'cat'(orleaveempty)toprinttoterminal-use'xargs'topassoutputasargument-use'{}'placeholdertopassoutputasargument-use'ohk'tore-runohkontheresults-append' | ohk'torunohkonthecommand'soutput
Pipeoutputto:sort|uniq|ohkNote: You should not useohktwice in the chain of processes because they
will launch in parallel and both try to take over the screen and keyboardKeyboard shortcutsEscQuit ohkEnterFinalize selectionAlt-EChange search modeAlt-IChange case sensitivity←↓↑→ / Alt-hjkl / (shift) tabFocus rows/columnsSpaceSelect row/columnAlt-123456789Select numbered columnLeft clickSelect columnAlt-A/CSelect all/none rows/columnsAlt-RRerun ohk with currently selected outputCommand line optionsusage: ohk [-h] [-f] [-r] [-i]

optional arguments:
  -h, --help            show this help message and exit
  -f, --fuzzy
  -r, --regex
  -i, --case-insensitiveTODOsUse Ctrl- shortcutsSet output as environment variable on the outer shell (will probably need
the user to set an alias)ScrollSearch for column titleDecorateOrganize code better
Package: ohlcobject
为 OHLC 处理去 pandas 化，从而避免大量的 pandas 内存拷贝，达到性能优化的效果（大概 8000%）。内部存储为 { "low": [], "high": [] }可将 ohlc_object[num]['key'] 的调用转化为 ohlc_object['key'][num] 的调用。initobj = OHLCObject()
obj['open'] = [1, 2, ...]
obj['high'] = [100, 200, ...]
obj['low'] = [1, 2, ...]
obj['close'] = [100, 200, ...]
obj['timestamp'] = [1498924800000, 1498939200000, ...]
return objmerge (concat OHLC)Merge obj2 into obj1, automatically sort using 'timestamp' keyobj1.merge(obj2)readobj['low'][1]  # best performance
obj[1]['low']
obj[3:][1]['low']
Package: ohlcvish
ohlcvishohlcvishtakesOHLCVdata, generate multiple technical indicators on it and then gives you all existingBuy-Hold-Sellcombinations in the dataset. Mean, median, min and max are the clustered results of the respective signal combination.How to useTo useohlcvishyou need your OHLCV data to be in apandas.DataFramelike this:importpandasaspdeth=pd.read_csv("data/ETH.csv",index_col="datetime",parse_dates=True)eth.head()close  high     low    open   volume
datetime                                        
2015-08-07   3.00   3.0  0.6747  0.6747   123.93
2015-08-08   1.20   3.0  0.1500  3.0000  2119.43
2015-08-09   1.20   1.2  1.2000  1.2000     0.00
2015-08-10   1.20   1.2  1.2000  1.2000     0.00
2015-08-11   0.99   1.2  0.6504  1.2000  9486.09Useohlcvish()function to get all signals:fromohlcvishimportohlcvishsignals=ohlcvish(eth)signals.head()macd  rsi  stoch  adx  aroon  bbands  sar  ma  amount  forecast_mean  forecast_median  forecast_min  forecast_max
0    -1   -1      0    0      0       0   -1   0       1      59.947906        59.947906     59.947906     59.947906
1    -1    0      0   -1     -1       0    0   0       1      -2.904930        -2.904930     -2.904930     -2.904930
2    -1    0      0   -1      0       0   -1   0       3      -7.415414        -6.642701    -11.645688     -3.957853
3    -1    0      0   -1      0       0    0   0       1     298.919554       298.919554    298.919554    298.919554
4    -1    0      0    0     -1       1   -1  -1       1     -54.082750       -54.082750    -54.082750    -54.082750Defineforecast_periodto change forecast for mean, median, min and max.signals=ohlcvish(eth,forecast_period=10)