Saravanan666/pypi-org huggingface dataset:
Package: anyhedge
anyhedgeBasic components for AnyHedge contracts.Currently, this only deals with contract execution and focuses on sats-accurate values in relation
to the reference typescriptAnyHedge Library.Installpip install anyhedge(use venv, miniconda, etc. - don't install things on your system python)Requirementspython >= 3.10(use venv, miniconda, etc. - don't install things on your system python)requirements.txt(pip install -r requirements.txtusing your virtual python)Demopython demo.pyYou should see something like this:ContractProposal(start_timestamp=1668818394 (2022-11-19T00:39:54+00:00),
                 maturity_timestamp=1668829194 (2022-11-19T03:39:54+00:00),
                 nominal_oracleUnits_x_satsPerBch=10000000000000,
                 start_price_oracleUnits_per_bch=10000,
                 low_liquidation_price_oracleUnits_per_bch=7143,
                 oracle_public_key='02d3c1de9d4bc77d6c3608cbe44d10138c7488e592dc2b1e10a6cf0e92c2ecb047',
                 maker_side=Hedge)
That is a $1000.0 Long Taker contract.

ContractFunding(base_proposal=...,
                fee_agreements=(FeeAgreement (maker fee): Taker --> 1000 Sats (1e-05 BCH) --> Maker,
                                FeeAgreement (settlement service fee): Taker --> 2000 Sats (2e-05 BCH) --> Settlement Service))
That is a contract funding with a total of 1e-05 BCH in fees to Maker.

ContractRedemption(base_funding=...,
                   end_price_timestamp=1668829194 (2022-11-19T03:39:54+00:00),
                   naive_end_price_oracleUnits_per_bch=11000,
                   redemption_type=Maturation)
That is a redemption paying 4.90881092 BCH to Taker versus their original 3.99972001 BCH for a gain of 22.728113661135996%.
Package: anyHR
anyHRA collection ofhit-and-run Markov Chain Monte Carloalgorithms for sampling of n-dimensional sets defined by arbitrary inequality constraints.IntroductionThis tool implements some variants of thehit and runormixingalgorithms.LetSbe an open bounded set in n dimensions defined by inequality constraints of the formf(x1,..., xn) < g(x1,..., xn), where f and g are arbitrary functions.Let all parameters also have parameter ranges defined as intervals, soSis a subset of a hyperrectangle.(As an example, one could imposex + y < 1in the two dimensional plane, with x in (0,1) and y in (0,1)).Hit-and-run algorithms can be used to get a sample uniformly at random inside of this setS.anyHRparses the parameters and their respective constraints and returns a number of samples that satisfy this spec,while being distributed uniformly on the set of allowed values.For more information on mixing algorithms seeInstallationIt is necessary to have a working installation of Python 3,pipandgitfor the following installation process.Open the target installation directory in a terminal and typepipinstallanyHRUseA minimal running example for the above specification can be sampled with the following code:# Import modulesimportnumpyasnpimportmatplotlib.pyplotaspltfromanyHR.constraint.ConstraintimportConstraintsfromanyHR.hit_and_run.hit_and_runimportHitAndRun# Define variables to usevar_names=['x','y']# Define the set of constraintc=Constraints(var_names)c.add_constraint('x+y < 1')# Define the bounding hyperrectanglex_bound=[0,1]y_bound=[0,1]bounds=[x_bound,y_bound]# build hr objecthr=HitAndRun(constraint=c,bounding_box=bounds)# generate samplessamples=[]total_rejections=0nb_samples=100mixing=10foriinrange(nb_samples*mixing):sample,rejections=hr.next_sample()# do some mixing in between samplesifi%mixing==0:samples.append(sample)xs=[sample[0]forsampleinsamples]ys=[sample[1]forsampleinsamples]plt.scatter(xs,ys)plt.show()ReferencesFor more information about mixing algorithms, see:Smith, R. L. (1984). Efficient Monte Carlo procedures for generating points uniformly distributed over bounded regions. Operations Research, 32(6), 1296-1308.Kiatsupaibul, S., Smith, R. L., & Zabinsky, Z. B. (2011). An analysis of a variation of hit-and-run for uniform sampling from general regions. ACM Transactions on Modeling and Computer Simulation (TOMACS), 21(3), 1-11.Neal, R. M. (2003). Slice sampling. The annals of statistics, 31(3), 705-767.We also thank Abraham Lee for his implementation of the PSO algorithms which is used here.Seehttps://github.com/tisimst/pyswarmfor more information.
Package: anyhttp
anyhttp provides a generic layer to use existing http clients.The primary purpose is to be used by packages which need http,
do not need or want to depend on one of the existing clients,
and/or want to re-used by applications which already have a
dependency on a http clients.anyhttp supports:requestshttplib2urllib3pycurlfidohttqasync_httpweboburlfetchsimplefetchhttputilstornadoihttpbasic_httpuniresthttpstreamhttp1reqrestinydavultraliteurlgrabberdogbutlerpylhttphyperasynchttpgeventhttpclientstreaming_httplib2bolachadresthttxlibdugongaiohttpyieldfrom.http.clientNormal useNormal usage of anyhttp involves simply using either:anyhttp.get_text(url)
anyhttp.get_binary(url)anyhttp will look for a capable http clients in sys.modules.
The sequence will look like:app:import httplib2  # must be firstimport your_packageyour_package:import anyhttpanyhttp:http = Wrapper(httplib2)Testinganyhttp includes tests that verify the supported clients can perform
certain http operations, and that test suite allows basic HTTP conformance
testing of HTTP features.It is easy to add a new client to the test suite.
The list of supported clients is in the main anyhttp module, and the test
suite automatically applies the tests to new clients added.The automatic support of additional clients is achieved using
python package testscenarios with an unmerged patch.  This can be installed
fromhttps://code.launchpad.net/~jayvdb/testscenarios/0.4-with_scenarios
Package: anyio
AnyIO is an asynchronous networking and concurrency library that works on top of eitherasyncioortrio. It implements trio-likestructured concurrency(SC) on top of asyncio and works in harmony
with the native SC of trio itself.Applications and libraries written against AnyIO’s API will run unmodified on eitherasyncioortrio. AnyIO can also be adopted into a library or application incrementally – bit by bit, no full
refactoring necessary. It will blend in with the native libraries of your chosen backend.DocumentationView full documentation at:https://anyio.readthedocs.io/FeaturesAnyIO offers the following functionality:Task groups (nurseriesin trio terminology)High-level networking (TCP, UDP and UNIX sockets)Happy eyeballsalgorithm for TCP connections (more robust than that of asyncio on Python
3.8)async/await style UDP sockets (unlike asyncio where you still have to use Transports and
Protocols)A versatile API for byte streams and object streamsInter-task synchronization and communication (locks, conditions, events, semaphores, object
streams)Worker threadsSubprocessesAsynchronous file I/O (using worker threads)Signal handlingAnyIO also comes with its ownpytestplugin which also supports asynchronous fixtures.
It even works with the popularHypothesislibrary.
Package: anyioc
anyiocAnother simple ioc framework for python.UsagefromanyiocimportServiceProviderprovider=ServiceProvider()provider.register_singleton('the key',lambdaioc:102)# ioc will be a `IServiceProvider`value=provider.get('the key')assertvalue==102Register and resolveBy default, you can use following methods to register services:ServiceProvider.register_singleton(key, factory)ServiceProvider.register_scoped(key, factory)ServiceProvider.register_transient(key, factory)ServiceProvider.register(key, factory, lifetime)ServiceProvider.register_value(key, value)ServiceProvider.register_group(key, keys)ServiceProvider.register_bind(new_key, target_key)And use following methods to resolve services:ServiceProvider.__getitem__(key)ServiceProvider.get(key)ServiceProvider.get_many(key)getreturnNoneif the service was not found, but__getitem__will raise aServiceNotFoundError.Read fulldocumentation.
Package: anyio-serial
A small Python wrapper that combinesanyioandpySerial.Implementation detail: This library is using too many short-lived threads.
Yes this should be improved.Quick startA simple serial port readeranyio_serial is a reasonably intuitive mash-up ofpySerialand anyio’sStream:import anyio
from anyio_serial import Serial

async def main():
   async with Serial(port='COM1') as port:
      while True:
         print((await port.receive()).decode(errors='ignore'), end='', flush=True)

anyio.run(main)APIanyio_serial’s interface is really simple:from anyio_serial import Serial

async with Serial(...) as port:  # same options as serial.Serial
   ...
   # use "port" like any other anyio ByteStreamAttributesThe states of the serial status linescd,cts,dsrandriare supported.
Package: any-iter-to-html-table
Converts any nested iterable (json, dict, list ...) to an HTML table#pip install any-iter-to-html-tablefromany_iter_to_html_tableimportcreate_html_table_from_iterabledata={"glossary":{"title":"example glossary","GlossDiv":{"title":"S","GlossList":{"GlossEntry":{"ID":"SGML","SortAs":"SGML","GlossTerm":"Standard Generalized Markup Language","Acronym":"SGML","Abbrev":"ISO 8879:1986","GlossDef":{"para":"A meta-markup language, used to create markup languages such as DocBook.","GlossSeeAlso":["GML","XML"],},"GlossSee":"markup",}},},}}"""https://json.org/example.html"""fromjsonorg_result=create_html_table_from_iterable(data,filename="fromjsonorg.html",title="Pandas - DataFrame",sparsify=True)jsonfile=r"F:\jsonstackoverflow.json"#'https://api.stackexchange.com/2.2/answers?order=desc&sort=activity&site=stackoverflow'json_from_file=create_html_table_from_iterable(jsonfile,filename="json_from_file.html",title="Pandas - DataFrame",sparsify=False,)sparsify=TrueWithout CSSDesign is separated from data. You can use the preset, but if you want,you can easily create your own CSS style#'https://stackoverflow.com/questions/64359762/constructing-a-pandas-dataframe-with-columns-and-sub-columns-from-nested-dictionnesteddict={"level1":{"t1":{"s1":{"col1":5,"col2":4,"col3":4,"col4":9},"s2":{"col1":1,"col2":5,"col3":4,"col4":8},"s3":{"col1":11,"col2":8,"col3":2,"col4":9},"s4":{"col1":5,"col2":4,"col3":4,"col4":9},},"t2":{"s1":{"col1":5,"col2":4,"col3":4,"col4":9},"s2":{"col1":1,"col2":5,"col3":4,"col4":8},"s3":{"col1":11,"col2":8,"col3":2,"col4":9},"s4":{"col1":5,"col2":4,"col3":4,"col4":9},},"t3":{"s1":{"col1":1,"col2":2,"col3":3,"col4":4},"s2":{"col1":5,"col2":6,"col3":7,"col4":8},"s3":{"col1":9,"col2":10,"col3":11,"col4":12},"s4":{"col1":13,"col2":14,"col3":15,"col4":16},},},"level2":{"t1":{"s1":{"col1":5,"col2":4,"col3":9,"col4":9},"s2":{"col1":1,"col2":5,"col3":4,"col4":5},"s3":{"col1":11,"col2":8,"col3":2,"col4":13},"s4":{"col1":5,"col2":4,"col3":4,"col4":20},},"t2":{"s1":{"col1":5,"col2":4,"col3":4,"col4":9},"s2":{"col1":1,"col2":5,"col3":4,"col4":8},"s3":{"col1":11,"col2":8,"col3":2,"col4":9},"s4":{"col1":5,"col2":4,"col3":4,"col4":9},},"t3":{"s1":{"col1":1,"col2":2,"col3":3,"col4":4},"s2":{"col1":5,"col2":6,"col3":7,"col4":8},"s3":{"col1":9,"col2":10,"col3":11,"col4":12},"s4":{"col1":13,"col2":14,"col3":15,"col4":16},},},}nested_dict=create_html_table_from_iterable(nesteddict,filename="from_nested_dict.html",title="Pandas - DataFrame",sparsify=False,)ConvertanynestediterabletoanHTMLtable.Designisseparatedfromdata.Youcanusethepreset,butifyouwant,youcaneasilycreateyourownCSSstyle.Parameters:data:AnyYoucanpassanyiterable(list,dict,tuple…),jsonfilepath(str)orjsonURL(str)filename:Union[None,str]Filepathforoutput,willbesavedinyourcurrentworkingdirectoryIfNone,nofileswillbewritten.title:strTitleforHTML(default='Pandas DataFrame')sparsify:boolRepeatkeysineveryline(default=False)Returns:tuple[str,str]
Package: anyjson
OverviewAnyjson loads whichever is the fastest JSON module installed and provides
a uniform API regardless of which JSON implementation is used.Originally part of carrot (http://github.com/ask/carrot/)ExamplesTo serialize a python object to a JSON string, call theserializefunction:>>> import anyjson
>>> anyjson.serialize(["test", 1, {"foo": 3.141592}, "bar"])
'["test", 1, {"foo": 3.141592}, "bar"]'Conversion the other way is done with thedeserializecall.>>> anyjson.deserialize("""["test", 1, {"foo": 3.141592}, "bar"]""")
['test', 1, {'foo': 3.1415920000000002}, 'bar']Regardless of the JSON implementation used, the exceptions will be the same.
This means that trying to serialize something not compatible with JSON
raises a TypeError:>>> anyjson.serialize([object()])
Traceback (most recent call last):
  <snipped traceback>
TypeError: object is not JSON encodableAnd deserializing a JSON string with invalid JSON raises a ValueError:>>> anyjson.deserialize("""['missing square brace!""")
Traceback (most recent call last):
  <snipped traceback>
ValueError: cannot parse JSON descriptionContactThe module is maintaned by Rune F. Halvorsen <runefh@gmail.com>.
The project resides athttp://bitbucket.org/runeh/anyjson. Bugs and feature
requests can be submitted there. Patches are also very welcome.ChangelogSee CHANGELOG fileLicensesee the LICENSE file
Package: anyjson2csv
See the source for this project here:https://github.com/mehdiabidi/json2csv"(Example)from anyjson2csv.json_to_csv import convert_json_to_csv
import jsonwith open("listing_data_sampled.json", "r") as f:
json_data = json.load(f)convert_json_to_csv(json_data, "test.csv")
Package: anykeystore
A generic interface wrapping multiple different backends to provide a
consistent key-value storage API. This library is intended to be used by other
libraries that require some form of generic storage.Usagefrom anykeystore import create_store

store = create_store('sqla', url='postgres+psycopg2://bob@localhost/mydb')

settings = {
    'mystore.store': 'sqla',
    'mystore.url': 'mysql://bob@localhost/mydb',
}
store = create_store_from_settings(settings, prefix='mystore.')Supported Backendsmemorysqlalchemyrequires: sqlalchemymongodbrequires: pymongoredisrequires: redis-pymemcachedrequires: python-memcached, or python3-memcached
Package: anylabeling
🌟 AnyLabeling 🌟Effortless data labeling with AI support fromYOLOandSegment Anything!AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labelingAuto Labeling with Segment AnythingYoutube Demo:https://www.youtube.com/watch?v=5qVJiYNX5KkDocumentation:https://anylabeling.nrl.aiFeatures:Image annotation for polygon, rectangle, circle, line and point.Auto-labeling with YOLOv5 and Segment Anything.Text detection, recognition and KIE (Key Information Extraction) labeling.Multiple languages availables: English, Vietnamese, Chinese.I. Install and run1. Download and run executableDownload and run newest version fromReleases.For MacOS:After installing, go to Applications folderRight click on the app and select OpenFrom the second time, you can open the app normally using Launchpad2. Install from PypiRequirements: Python >= 3.8, <= 3.10.Recommended:Miniconda/Anaconda.Create environment:condacreate-nanylabelingpython=3.8
condaactivateanylabeling(For macOS only)Install PyQt5 using Conda:condainstall-cconda-forgepyqt==5.15.7Install anylabeling:pipinstallanylabeling# or pip install anylabeling-gpu for GPU supportStart labeling:anylabelingII. DevelopmentGenerate resources:pyrcc5-oanylabeling/resources/resources.pyanylabeling/resources/resources.qrcRun app:pythonanylabeling/app.pyIII. Build executableInstall PyInstaller:pipinstall-rrequirements-dev.txtBuild:bashbuild_executable.shCheck the outputs in:dist/.IV. ContributionIf you want to contribute toAnyLabeling, please readContribution Guidelines.V. Star historyVI. ReferencesLabeling UI built with ideas and components fromLabelImg,LabelMe.Auto-labeling withSegment Anything Models,MobileSAM.Auto-labeling withYOLOv5,YOLOv8.
Package: anylabeling-gpu
🌟 AnyLabeling 🌟Effortless data labeling with AI support fromYOLOandSegment Anything!AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labelingAuto Labeling with Segment AnythingYoutube Demo:https://www.youtube.com/watch?v=5qVJiYNX5KkDocumentation:https://anylabeling.nrl.aiFeatures:Image annotation for polygon, rectangle, circle, line and point.Auto-labeling with YOLOv5 and Segment Anything.Text detection, recognition and KIE (Key Information Extraction) labeling.Multiple languages availables: English, Vietnamese, Chinese.I. Install and run1. Download and run executableDownload and run newest version fromReleases.For MacOS:After installing, go to Applications folderRight click on the app and select OpenFrom the second time, you can open the app normally using Launchpad2. Install from PypiRequirements: Python >= 3.8, <= 3.10.Recommended:Miniconda/Anaconda.Create environment:condacreate-nanylabelingpython=3.8
condaactivateanylabeling(For macOS only)Install PyQt5 using Conda:condainstall-cconda-forgepyqt==5.15.7Install anylabeling:pipinstallanylabeling# or pip install anylabeling-gpu for GPU supportStart labeling:anylabelingII. DevelopmentGenerate resources:pyrcc5-oanylabeling/resources/resources.pyanylabeling/resources/resources.qrcRun app:pythonanylabeling/app.pyIII. Build executableInstall PyInstaller:pipinstall-rrequirements-dev.txtBuild:bashbuild_executable.shCheck the outputs in:dist/.IV. ContributionIf you want to contribute toAnyLabeling, please readContribution Guidelines.V. Star historyVI. ReferencesLabeling UI built with ideas and components fromLabelImg,LabelMe.Auto-labeling withSegment Anything Models,MobileSAM.Auto-labeling withYOLOv5,YOLOv8.
Package: anyleaf
AnyleafFor use with the AnyLeaf pH and RTD sensors in PythonHomepageQuickstartTo get started as quickly as possible on Raspberry Pi:Activate I2C (pH and ORP module): Runsudo raspi-config. SelectInterfacing Optionsâ†’I2Câ†’Yes.Activate SPI (RTD temp module): Same as above, but selectSPIinstead ofI2C.RebootThen run these commands from a terminal:sudo apt install python3-scipypip3 install anyleafgit clone https://github.com/anyleaf/anyleaf-python.gitcd anyleaf-python/examplespython3 ph_orp.pypH readings will display in your terminal.To install theanyleafPython package, runpip3 install anyleaf, orpip install anyleaf, depending on howpipis set up on your operating system.Example use, for Raspberry Pi, and CircuitPython boards:importtimeimportboardimportbusiofromanyleafimportPhSensor,CalPt,CalSlot,OnBoard,OffBoarddefmain():i2c=busio.I2C(board.SCL,board.SDA)delay=1# Time between measurements, in secondsph_sensor=PhSensor(i2c,delay)# 2 or 3 pt calibration both give acceptable results.# Calibrate with known values. (voltage, pH, temp in Â°C).# You can find voltage and temperature with `ph_sensor.read_voltage()` and# `ph_sensor.read_temp()` respectively.# For 3 pt calibration, pass a third argument to `calibrate_all`.ph_sensor.calibrate_all(CalPt(0.,7.,25.),CalPt(0.17,4.,25.))# Or, call these with the sensor in the appropriate buffer solution.# This will automatically use voltage and temperature.# Voltage and Temp are returned, but calibration occurs# without using the return values.# V, T = ph_sensor.calibrate(CalSlot.ONE, 7., Offboard(40.))# ph_sensor.calibrate(CalSlot.TWO, 4., OnBoard())# Store the calibration parameters somewhere, so they persist# between program runs.whileTrue:pH=ph_sensor.read(OnBoard())# To use an offboard temperature measurement: `ph_sensor.read(OffBoard(30.))`print(f"pH:{pH}")time.sleep(delay)if__name__=="__main__":main()
Package: anylearn
anylearn-sdk为AnyLearn深度学习系统设计的SDK，用于支持基于python的代码调用方式，并在上层扩展复杂应用。在线用户手册稳定版 (master)|开发版 (dev)DevVirtual envpython3-mvenvvenvsourcevenv/bin/activateDependenciespython-mpipinstall-rrequirements_dev.txt
pythonsetup.pyinstallTestpytestBuildpythonsetup.pysdist
pythonsetup.pybdist_wheel
Package: anylinux
ANYLINUX[+] Description :Ultimate tool for installing Any LINUX in termux.[+] InstallationInstall primary dependencies (git and python)pkg install python -yInstall this toolpip install anylinuxRun the toolanylinuxOr, directly runpip install anylinux && anylinuxFeatures:Many platform Options Available(Supports most linux)14 different LINUX options available.Easy to useRequirementsActive Internet ConnectionPython(3)If not found, all of the required packages will be installed on first run.Tested onTermux (version 0.118)UsageRun the ToolChoose a LINUXWait sometimes for setting up allStart LINUX AND ENJOY[+] LINUX OPTIONS AVAILABLEUBUNTUDEBUANKALIKALI NETHUNTERPARROT SECURITY OSBACKBOXFEDORAXCENT OSOPEN SUSE LEAPOPEN SUSE TUMBLEWEEDARCH LINUXBLACK ARCHALPINEVOID LINUXThis repository is open source to help others. So if you wish to copy, consider giving credit !!!If this tool helped you, consider staring repository. Your stars encourage me a lot !!!https://github.com/Nishant2009/anylinux
Package: anyllm
🔥 PⒶutoBot 🔥Private AutoGPT Robot- Your private task assistant with GPT!🔥Chatto your offlineLLMs on CPU Only.100% private, no data leaves your execution environment at any point.🔥Ask questionsto your documents without an internet connection. Engine developed based onPrivateGPT.🔥Automate taskseasily withPAutoBot plugins. Easy for everyone.🔥Easy coding structurewithNext.jsandPython. Easy to understand and modify.🔥Built withLangChain,GPT4All,Chroma,SentenceTransformers,PrivateGPT.The supported extensions are:.csv: CSV,.docx: Word Document,.doc: Word Document,.enex: EverNote,.eml: Email,.epub: EPub,.html: HTML File,.md: Markdown,.msg: Outlook Message,.odt: Open Document Text,.pdf: Portable Document Format (PDF),.pptx: PowerPoint Document,.ppt: PowerPoint Document,.txt: Text file (UTF-8),I. Installation and Usage1. InstallationPython 3.8 or higher.InstallPAutoBot:pipinstallpautobot2. UsageRun the app:python-mpautobot.appor just:pautobotGo tohttp://localhost:5678/to see the user interface. You can choose one of the two modes:Chat OnlyDocuments Q&AUpload some documents to the app (see the supported extensions above). You can trydocs/python3.11.3_lite.zipfor a quick start. This zip file contains 45 files from thePython 3.11.3 documentation.Force ingesting documents withIngest Databutton.You can also run PAutoBot publicly to your network or change the port with parameters. Example:pautobot--host0.0.0.0--port8080II. Development1. Clone the source codegitclonehttps://github.com/nrl-ai/pautobotcdpautobot2. Run your backendPython 3.8 or higher.To install Pautobot from source, frompautobotsource code directory, run:pipinstall-e.Run the app:python-mpautobot.appGo tohttp://localhost:5678/to see the user interface.2. Run your frontendInstall the dependencies:cdfrontend
npminstallRun the app:npmrundevGo tohttp://localhost:3000/to see the user interface. Use this address to develop the frontend.