Saravanan666/pypi-org huggingface dataset:
Package: simple-nn-cooper
ABOUTThis is a mini deep learning framework created by coopercooper@ShanghaiFeaturesDefine Dynamic Computing-GraphDefine Neural Network OperatorDefine Linear,Sigmoid, L2_lossAuto-Diff ComputingAuto-Feedforward and BackwordRemainClassificationCross-EntropyCNN,RNNConnectionwechat: 497464497Mail :497464497@qq.com
Package: simple-NOAA
simple_NOAA
Welcome to simple_NOAA, a Python package for accessing weather data from the National Oceanic and Atmospheric Administration (NOAA) through their API. The package includes a dataframe of station metadata, which can be used to request weather data based on location and time.Dependenciespandas
request
from shapely.geometry import Point, PolygonUsageThe package includes the following functionalities:stations_frame: A dataframe of station data from NOAA
stations_in_region(lat, lon, num_closest, radius): Returns a list of the num_closest stations within radius kilometers of the point created by lat and lon
yearly_request(search_type, station_list, year1, year2): Returns a dataframe of global-summary-of-the-year datasets for the requested stations
monthly_request(search_type, station_list, year1, year2): Returns a dataframe of global-summary-of-the-month datasets for the requested stations
daily_request(search_type, station_list, year1, year2): Returns a dataframe of daily-summaries datasets for the requested stations
Examples and testing of the package's functionality can be found in the testing.ipynb file.ContributionIf you're interested in contributing to the development of the library, please reach out to me atdevinrshaw@gmail.com. We welcome bug reports and feature requests.LicenseThis package is released under a open-source license. Please refer to the license file for any restrictions on its use.ContactCreator:devinrshaw@gmail.comReferencesMetadata on NOAA stations:https://www.ncei.noaa.gov/access/homr/reports/mshrNOAA dataset API user documentation:https://www.ncei.noaa.gov/support/access-data-service-api-user-documentationNOAA datasets explained:https://www.ncdc.noaa.gov/cdo-web/datasetsExplanation of dataset labels:https://www.ncei.noaa.gov/pub/data/metadata/documents/FAQsWhat is the package's main purpose?
simple_NOAA is a Python package that provides an easy-to-use interface for accessing weather data from the National Oceanic and Atmospheric Administration (NOAA) through their API.
What kind of weather data can I request?
You can request global-summary-of-the-year, global-summary-of-the-month, and daily-summaries datasets for specific stations.
How do I find the stations I want to request data for?
You can use the stations_in_region function to find stations within a certain radius of a given latitude and longitude.
Is there a limit on how much data I can request?
The NOAA API has usage limits, please refer to their API documentation for more information.
Please let me know if you have any other question.
Package: simpleNomo
Project DescriptionsimpleNomo is a python package for generating nomograms of logistic regression models with only model coefficients and variables ranges.BackgroudNomogram, a graphical calculator, has adequately solved the problem of inconvenient calculation. Nomogram is a chart consisting of several arranged lines for visualization of logistic regression model. With the development of the electronic calculators and computers, nomograms become less popular these days. However, they are still very prevalent in the condition without the computation sources. There are several tools for generating nomograms. They are available in SAS, Stata, as well asrmsandhdnompackages in R language.However, these tools either lack an integrated toolbox such as SAS or take input only from model trained within the programming language like hdnom and rms. In this case, it is difficult for converting existing works that established logistic regression models but not published the training data or developed nomograms. Therefore, plenty of works will stagnate into logistic regression models with good performance rather than meaningful clinical applications.simpleNomo is a straightforward framework for creating nomograms for logistic regression models. PyNG can accepts only the coefficients
and range of predictors in a logistic regression model as inputs.Requirementspandas==1.2.4
numpy==1.21.5
matplotlib==3.5.1To installpip install simpleNomoOr more specifically athttps://github.com/Hhy096/nomogram.Function Introductionnomogram(path,result_title="Positive Risk",fig_width=10,single_height=0.45,dpi=300,ax_para={"c":"black","linewidth":1.3,"linestyle":"-"},tick_para={"direction":'in',"length":3,"width":1.5,},xtick_para={"fontsize":10,"fontfamily":"Songti Sc","fontweight":"bold"},ylabel_para={"fontsize":12,"fontname":"Songti Sc","labelpad":100,"loc":"center","color":"black","rotation":"horizontal"},total_point=100)path:Path of the excel that reserves the model coefficients and variabels range. The template of excel can be downloade athttps://github.com/Hhy096/nomogram/blob/main/template.xlsx.result_title:Title for the predictive name. Default "Positive Risk".fig_width:Width for the figure. Default 10.single_height:Hight for each axis of the nomogram. Default 0.45.dpi:The resolution in dots per inch. Default 300.ax_para:The parameters for axises in the nomogram. You can find more fromOther Parameterspart inhttps://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.axhline.html.tick_para:The parameters for probability matching axis. You can find more inhttps://matplotlib.org/stable/api/_as_gen/matplotlib.axes.Axes.tick_params.html.xtick_para:The parameters for x-ticklables of axises. You can find more paramters inhttps://matplotlib.org/stable/api/text_api.html#matplotlib.text.Text.ytick_para:The parameters for y-ticklabels of axises. You can find more paramters inhttps://matplotlib.org/stable/api/text_api.html#matplotlib.text.Text.total_point:The maximum point for aixes. Default 100.ExampleCheckhttps://github.com/Hhy096/nomogramfor more examples.
Package: simple-nose-selenium
simple-nose-selenium*************A simple Selenium WebDriver plugin for nose.This plugin is a python3 only stripped down version of `nose-selenium <https://github.com/klrmn/nose-selenium>`_.nosetests command line options==============================.. code-block:: bash$ nosetests --with-simple-nose-selenium --helpUsage: nosetests [options]Options:...--with-simple-nose-selenium   Enable plugin Simple Nose Selenium--browser=BROWSER             Run this type of browser (default ['FIREFOX'], options:[FIREFOX,  CHROME, SAUCELABS]Example Commands----------------.. code-block:: bash$ nosetests --with-simple-nose-selenium --browser=FIREFOXTo run your tests on Saucelabs you need to set the required environment variables first... code-block:: bash$ export SAUCELABS_USERNAME=foo$ export SAUCELABS_ACCESSKEY=123key$ export SAUCELABS_PLATFORM=windows$ export SAUCELABS_BROWSER_NAME=chrome$ export SAUCELABS_BROWSER_VERSION=4.1$ nosetests --with-simple-nose-selenium --browser=SAUCELABSInheriting from SeleniumTestCase--------------------------------SeleniumTestCase creates the webdriver and stores it in self.wd in its setUp()and closes it in tearDown()... code-block:: pythonfrom nose_selenium import SeleniumTestCaseclass MyTestCase(SeleniumTestCase):def test_that_google_opens(self):self.wd.get("http://google.com")self.assertEqual(self.wd.title, "Google")
Package: simplenote-jekyll
This is an integration script between Jekyll blog format andSimpleNotenotes tagged withblog.InstallInstallpipsiRunpipsi install simplenote_jekyllSetupSet the following environment variables:SIMPLENOTE_USER:Username (email) for yourSimpleNoteaccountSIMPLENOTE_PASSWD:Password for yourSimpleNoteaccountUseChange directory to the base of your Jekyll blog, then runsn-export. Runninggit statusshould show you what posts are newly imported fromSimpleNote.
Package: simple-note-taker
A simple CLI note taker, written in Python.Home:https://github.com/GitToby/simple_note_takerPypi:https://pypi.org/project/simple-note-taker/FeaturesTake notes via CLI and save to a flat json file.Configure tasks and reminders in notes with magic commands such as!taskand!reminder.Search your notes with fuzzy matching or exact term matching.Coming SoonOptionally, share notes with other users via rest of the s3 protocol. Server app coming soon.Summary commands will let you consolidate competed tasks, general notes and other items and share in a verity of methods.InstallViapippip install simple_note_takerUsage.Usage: snt [OPTIONS] COMMAND [ARGS]...

Options:
  --version
  --install-completion [bash|zsh|fish|powershell|pwsh]
                                  Install completion for the specified shell.
  --show-completion [bash|zsh|fish|powershell|pwsh]
                                  Show completion for the specified shell, to
                                  copy it or customize the installation.

  --help                          Show this message and exit.

Commands:
  config     For interacting with configuration tooling
  delete     Delete a note you've taken.
  edit       Edit a note you've taken.
  ls         Fetch the latest notes you've taken.
  mark-done  Mark a task type note as done.
  match      Search your notes you've saved previously which match a search...
  search
  size       Returns details on the size of you notes.
  take       Take a note and save it.
  tasks      Lists notes marked as Tasks.Dev SetupDev withPoetry. Run tests from root withpytest
Package: simple-notifications
simple-notificationsInstallationInstall from pypi:pip install simple-notificationsHow to useSend email with file attachmentsmain.pyfrom simplenotifications import mail

if __name__ == '__main__':
    try:
        mailer = mail.mail("myserver", "myuser", "mypassword", 25, "sender@example.com")

        mailer.send('receiver@example.com',
                    'My message',
                    'My subject',
                    ['c:\\test.txt',
                     'c:\\test.png'])

    except mail.mail_error as e:
        print(e)Send email from template filemain.pyfrom simplenotifications import mail

if __name__ == '__main__':
    try:
        mailer = mail.mail("myserver", "myuser", "mypassword", 25, "sender@example.com")
        mailer.send_template("receiver@example.com",
                             "./template.txt'"
                             { "name": "John"},
                             'Testsubject')
    except mail.mail_error as e:
        print(e)template.txtHello, $name!Send webhook message (http post request)main.pyfrom simplenotifications import webhook

if __name__ == '__main__':
    hook = webhook.webhook_post("http://example.com/webhook")
    try:
        hook.post("Hello, world!")
    except webhook.webhook_error as e:
        print(e)
Package: simple-notifs
IntroductionThis library was built for making simple, shortened human readable versions of time deltas.
This was specifically made for notifications on applications where a user wants to see how long it has been
since the notification was made. For example, instead of a time delta such as "1 hour ago" or "20 minutes ago", the resulting time delta would be
"1h" and "20mi", respectivelyAccessFrom simple_notifs.simple_notifs import utc_to_humanArgumentsMandatory, a datetime object must be passed as input to the function.By default, is_utc is set to True. If false, the built in method converts the datetime object to utc, then performs its operation.By default, days_and_above is set to False. If True, the built in method will only display time deltas starting at "1d". This means any deltas
in seconds, minutes, or hours that are less than a full day, will be truncated to "1d".
Package: simple-novel-reader
CLI light novel reader written in Python for Linux.Dependencies:BeautifulSoup4lxmllangcodesPyHyphenSetup/Usage:To install:pip3installsimple-novel-readerTo run program:snr\path\to\epub\fileOn the first run you need to specify a file, next time the file will be opened as default.Features:save reading progress and quickmarks of a book upon exit,starting program without argument will open last read book,quickmarks,bookmarks,colored dialogs,dual page view.Screenshots:
Package: simple-oauth2
Oauth2 library for python flask and restplusWith this simple library, you can authenticate clients coming from a browser (Implicit Flow) or using Bearer token (Credential flow).
You can manage authorization using rbac function as described here after.RequirementsInstall these requirementscryptography
PyJWT==1.7.1
flask-restplus
simple-oauth2Usage exampleimportosfromflaskimportFlaskfromflask_restplusimportApi,Resourcefromsimple_oauth2importOAuthapi=Api()app=Flask(__name__)app.secret_key=os.urandom(32)api.init_app(app)oauth_config={'well_known_url':'{well_known_url}','client_id':'{client_id}','redirect_uri':'{host:port}/signin-oidc','audience':'{audience}','scopes':'{coma separated scopes}','whitelist':['/openbar?']}defrbac(client,operation):print('client ',client,' is asking for operation ',operation)returnTrueoauth=OAuth(app,oauth_config,rbac=rbac)# flask@app.route('/')defslah():return'Hello'@app.route('/hello')@oauth.authorize('hello')defhello():return'hi'@app.route('/openbar')defopenbar():return'Chimay'# restplus@api.route('/toto')classToto(Resource):@oauth.authorize('toto')defget(self):return{'hello':'world'}if__name__=="__main__":app.run(host='0.0.0.0',debug=True)ContributorsRegisterhereInstall required packagespython-mpipinstall--user--upgradesetuptoolswheel
python-mpipinstall--user--upgradetwinePackage like this:pythonsetup.pysdistbdist_wheel
python-mtwineupload--repository-urlhttps://test.pypi.org/legacy/dist/*Test installpipinstall-ihttps://test.pypi.org/simple/simple-oauth2
Package: simpleobfuscate
Quick-and-dirty obfuscation for strings, designed to
hide URL parameters from the casual experimenter without
adding too much length. A little randomness is baked
in to make it look like the parameters are constantly
changing, even if they’re not.Obviously this is NOT SECURE; don’t rely on it for strong secrecy.
A chosen-plaintext attack will recover the key, just like xor.Only works for ASCII strings.  Not Unicode-safe.
Package: simpleobject
simpleobjectSimple json serializable objectCan be used as atypes.SimpleNamespace, but it is json serializable like a python dictionary.Installpython -m pip install simpleobjectUsagefromsimpleobjectimportsimpleobjectfromjsonimportdumpso=simpleobject()o.foo=1o.bar=2print(o)#simpleobject(foo=1, bar=2)print(dumps(o))#{"foo": 1, "bar": 2}You can also set the nameo.name='FooBarObject'print(o)#FooBarObject(foo=1, bar=2)
Package: simple-observable
simple-observableA simple observer pattern implementation.Usage examplefromsimple_observableimportObservableobservable=Observable()defmy_callback(event):print(f"Called with{event}")observable.add_listener("mytopic",my_callback)observable.notify("mytopic",{"event_details":"hello"})Topic lifecycle eventsThe special topicObservable.LIFECYCLE_EVENTScan be used to perform an actions when new topics are added and existing ones are removed.fromsimple_observableimportObservableobservable=Observable()defon_lifecycle_event(event):ifevent["event_type"]==observable.TOPIC_ADDED_EVENT:topic=event["topic"]print(f"topic lifecycle: added '{topic}'")ifevent["event_type"]==observable.TOPIC_REMOVED_EVENT:topic=event["topic"]print(f"topic lifecycle: removed '{topic}'")observable.add_listener(observable.LIFECYCLE_EVENTS,on_lifecycle_event)defmy_callback(event):print(f"Called with{event}")# the next line triggers a lifecycle event {"event_type": observable.TOPIC_ADDED_EVENT, "topic": "mytopic"}listener_id=observable.add_listener("mytopic",my_callback)observable.notify("mytopic",{"key":"value"})# and the last line triggers a lifecycle event {"event_type": observable.TOPIC_REMOVED_EVENT, "topic": "mytopic"}observable.remove_listener(listener_id)
Package: simpleobserver
A simple implementation of the observer pattern.importsimpleobserver# Create a subject and list the events it might firefoo=simpleobserver.Subject('bar','baz')# Add a listenerdeffoo_bar_listener(*args):print("heard 'bar'",args)foo('bar',foo_bar_listener)# fire eventsfoo.fire('bar',1,2,3)# -> heard 'bar' (1, 2, 3)# Trying to listen to an unregistered event throws an errorfoo('snorble',lambda:None)# -> AssertionError: snorble is not a valid event for this subject# Same with trying to fire an unregistered eventfoo.fire('snorble')# -> AssertionError: snorble is not a valid event for this subject
Package: simpleobsws
simpleobswsA simple obs-websocket library in Python for people who just want JSON output.Please Notesimpleobsws >= v1.0.0 isonlyfor versions of obs-websocket that are 5.0.0 or higher. If you are using obs-websocket pre-5.0.0, use a pre v1.0.0 version of simpleobsws.Clickhereto go to the pre-5.0.0 branch.Installing:pip install simpleobswsPyPi LinkDocs:Library docs:the sort-of docsobs-websocket docs:https://github.com/obsproject/obs-websocket/blob/master/docs/generated/protocol.mdSamples:Samples are located in the samples folderhere.IRLTookit LinksPlease go to theobs-websocket Discordfor support.https://twitter.com/IRLToolkithttps://irltoolkit.com
Package: simpleocr
Simpleocr librarySimpleocr is a traditional chinese OCR python package that based on deep learning method.The library consists of text localization and text recognition.Text localizationThe model is a reimplementation of CRAFT(Character-Region Awareness For Text detection) by tensorflow.paper|githubText recognitionThe reimplementation is based on CRNN model that RNN layer is replaced with self-attention layer.CRNNpaperSelf attentionpaperInstallation$ pip install simpleocror$ git clone https://github.com/xianyuntang/simpleocr
$ cd simpleocr
$ python setup.py installUsagefrom simpleocr import ocr
ocr.get_text(['image.jpg'])TODOEnglish supportGPU support
Package: simple-openai
simple-openaiThis is a simple wrapper around the OpenAI API.  It's not meant to be a full-featured library, but rather a simple way to get started with the API.The library provides both synchronous and asynchronous methods for interacting with the API.InstallationInstall using pip:pipinstallsimple-openaiUsageCalling the APIFor the synchronous version, you can use the following code:from simple_openai import SimpleOpenai

def main():
    # Initialise a storage location
    storage_location = Path("/path/to/storage")

    # Create a system message
    system_message = "You are a helpful chatbot. You are very friendly and helpful. You are a good friend to have."

    # Create the client
    client = SimpleOpenai(api_key, system_message, storage_location)

    # Create tasks for the chat response and the image response
    result = client.get_chat_response("Hello, how are you?", name="Bob", chat_id="Group 1")

    # Print the result
    if result.success:
        # Print the message
        print(f'Success: {result.message}')
    else:
        # Print the error
        print(f'Error: {result.message}')

    result = client.get_image_url("A cat")

    # Print the result
    if result.success:
        # Print the message
        print(f'Success: {result.message}')
    else:
        # Print the error
        print(f'Error: {result.message}')

if __name__ == "__main__":
    # Run the main function
    main()For the asynchronous version, you can use the following code:from simple_openai import AsyncSimpleOpenai
import asyncio

async def main():
    # Initialise a storage location
    storage_location = Path("/path/to/storage")

    # Create a system message
    system_message = "You are a helpful chatbot. You are very friendly and helpful. You are a good friend to have."

    # Create the client
    client = AsyncSimpleOpenai(api_key, system_message, storage_location)

    # Create tasks for the chat response and the image response
    tasks = [
        client.get_chat_response("Hello, how are you?", name="Bob", chat_id="Group 1"),
        client.get_image_url("A cat"),
    ]

    # Wait for the tasks to complete
    for task in asyncio.as_completed(tasks):
        # Get the result
        result = await task

        # Print the result
        if result.success:
            # Print the message
            print(f'Success: {result.message}')
        else:
            # Print the error
            print(f'Error: {result.message}')

if __name__ == "__main__":
    # Run the main function
    asyncio.run(main())OutputThe output of the functions is aSimpleOpenaiResponseobject, which contains the following properties:success- A boolean indicating whether the request was successful or not.message- The message returned by the API.FunctionsFunctions can be added to the client using theadd_functionmethod. This method takes a function name and a function as arguments. The function should take anOpenAIFunctionobject as its first argument, and the Python function itself as the second argument.The Python function should return a string, which will be passed to the API using thefunctionroleDocumentationThe documentation is available onGitHub
Package: simple-openapi-client
Simple Open API Client generatorThis project was made to generate a simple client (async or not) from an openapi
specifications (unlike other client generators, which typically produce
code that is difficult for python beginners to use). It aims to produce a
single file that contains the Client class.NotesThis project is in alpha and has probably bugs.
Issues/bugfixes/additions are welcome.Installation$pipinstallsimple-openapi-clientUsageThis package is usage from a Python script.
Simply load the openapi file (from local file or url) and make the client.For instance:fromsimple_openapi_clientimportparse_openapi,make_client,Configconfig=Config(client_name='Orthanc',package_name='client')document=parse_openapi(url_or_path='https://api.orthanc-server.com/orthanc-openapi.json')client_str=make_client(document,config,use_black=True)withopen(f'./{config.package_name}.py','w')asfile:file.write(client_str)Or, for an async client:fromsimple_openapi_clientimportparse_openapi,make_client,Configconfig=Config(client_name='AsyncOrthanc',package_name='async_client')document=parse_openapi(url_or_path='https://api.orthanc-server.com/orthanc-openapi.json')client_str=make_client(document,config,async_mode=True,use_black=True)withopen(f'./{config.package_name}.py','w')asfile:file.write(client_str)