Saravanan666/pypi-org huggingface dataset:
Package: iapws
iapwsPython implementation of standard from IAPWS (http://www.iapws.org/release.html). The module implements the full set of standards, including:IAPWS-IF97
IAPWS-95
IAPWS-06 for Ice
IAPWS-08 for seawater
IAPWS-17 for Heavy water
...dependencesSupport for both python branch:* python 2.7
* python 3.4 or laterNumpy-scipy: library with mathematic and scientific toolsinstallIn debian you can find in official repositories in jessie, testing and sid. In ubuntu it’s in official repositories from ubuntu saucy (13.10). In other system you can install using pip:pip install iapwsor directly from the github repository:pip install git+https://github.com/jjgomera/iapws.gitThis is the recommended option to have the latest version.documentationTo see the full documentation of package, seereadthedocsFor a rapid usage demostration, see this examplesIAPWS-IF97 (see full documentation)fromiapwsimportIAPWS97sat_steam=IAPWS97(P=1,x=1)#saturated steam with known Psat_liquid=IAPWS97(T=370,x=0)#saturated liquid with known Tsteam=IAPWS97(P=2.5,T=500)#steam with known P and Tprint(sat_steam.h,sat_liquid.h,steam.h)#calculated enthalpiesIAPWS-95 (see full documentation)fromiapwsimportIAPWS95sat_steam=IAPWS95(P=1,x=1)#saturated steam with known Psat_liquid=IAPWS95(T=370,x=0)#saturated liquid with known Tsteam=IAPWS95(P=2.5,T=500)#steam with known P and Tprint(sat_steam.h,sat_liquid.h,steam.h)#calculated enthalpiesIAPWS-17 for Heavy water (see full documentation)fromiapwsimportD2Osat_liquid=D2O(T=370,x=0)#saturated liquid with known Tprint(sat_liquid.h)#calculated enthalpyIAPWS-06 for Ice Ih (see full documentation)fromiapwsimport_Iceice=_Ice(273.15,0.101325)#Ice at normal melting pointprint(ice["rho"])#Calculated densityIAPWS-08 for seawater (see full documentation)fromiapwsimportSeaWaterstate=SeaWater(T=300,P=0.101325,S=0.001)#Seawater with 0.1% Salinityprint(state.cp)# Get cpTODOFIXME: Electrolytic conductiviyTODO: Improve convergence in two phase region for IAPWS95 and D2O classTODO: Implement SBTL method for fast calculationTODO: Implement TTSE method for fast calculationAmmonia-water mixture:TODO: Add equilibrium routineI’ve tried to test all code and use all values for computer verification the standards give, but anyway the code can have hidden problem.
For any suggestions, comments, bugs … you can usage thegithub issue section, or contact directly with me atemail.
Package: iaqualink
Asynchronous library for Jandy iAqualinkUsage (using apython):>>>asyncwithAqualinkClient('xxx@example.com','password')asc:...s=awaitc.get_systems()...print(s)...d=awaitlist(s.values())[0].get_devices()...print(d)...{'XXX':AqualinkPoolSystem(name='Pool'serial='XXX'data={'id':1234,'serial_number':'XXX','created_at':'2017-09-23T01:00:08.000Z','updated_at':'2017-09-23T01:00:08.000Z','name':'Pool','device_type':'iaqua','owner_id':None,'updating':False,'firmware_version':None,'target_firmware_version':None,'update_firmware_start_at':None,'last_activity_at':None})}{'spa_temp':AqualinkSensor(name='spa_temp'data={'name':'spa_temp','state':'100'}),'pool_temp':AqualinkSensor(name='pool_temp'data={'name':'pool_temp','state':''}),'air_temp':AqualinkSensor(name='air_temp'data={'name':'air_temp','state':'76'}),'spa_set_point':AqualinkThermostat(name='spa_set_point'data={'name':'spa_set_point','state':'102'}),'pool_set_point':AqualinkThermostat(name='pool_set_point'data={'name':'pool_set_point','state':'84'}),'cover_pool':AqualinkSensor(name='cover_pool'data={'name':'cover_pool','state':''}),'freeze_protection':AqualinkBinarySensor(name='freeze_protection'data={'name':'freeze_protection','state':'0'}),'spa_pump':AqualinkPump(name='spa_pump'data={'name':'spa_pump','state':'1'}),'pool_pump':AqualinkPump(name='pool_pump'data={'name':'pool_pump','state':'1'}),'spa_heater':AqualinkHeater(name='spa_heater'data={'name':'spa_heater','state':'0'}),'pool_heater':AqualinkHeater(name='pool_heater'data={'name':'pool_heater','state':'0'}),'solar_heater':AqualinkHeater(name='solar_heater'data={'name':'solar_heater','state':'1'}),'spa_salinity':AqualinkSensor(name='spa_salinity'data={'name':'spa_salinity','state':''}),'pool_salinity':AqualinkSensor(name='pool_salinity'data={'name':'pool_salinity','state':''}),'orp':AqualinkSensor(name='orp'data={'name':'orp','state':''}),'ph':AqualinkSensor(name='ph'data={'name':'ph','state':''}),'aux_1':AqualinkAuxToggle(name='aux_1'data={'aux':'1','name':'aux_1','state':'0','label':'CLEANER','icon':'aux_1_0.png','type':'0','subtype':'0'}),'aux_2':AqualinkLightToggle(name='aux_2'data={'aux':'2','name':'aux_2','state':'0','label':'SPA LIGHT','icon':'aux_1_0.png','type':'0','subtype':'0'}),'aux_3':AqualinkLightToggle(name='aux_3'data={'aux':'3','name':'aux_3','state':'0','label':'POOL LIGHT','icon':'aux_1_0.png','type':'0','subtype':'0'}),'aux_4':AqualinkAuxToggle(name='aux_4'data={'aux':'4','name':'aux_4','state':'0','label':'AIR BLOWER','icon':'aux_1_0.png','type':'0','subtype':'0'}),'aux_5':AqualinkAuxToggle(name='aux_5'data={'aux':'5','name':'aux_5','state':'0','label':'SHEER DSCNT','icon':'aux_1_0.png','type':'0','subtype':'0'})}
Package: iar
iAR packageDescriptionData sets, functions and scripts with examples to implement
autoregressive models for irregularly observed time series. The models
available in this package are the irregular autoregressive model(Eyheramendy et al.(2018)), the complex irregular autoregressive model(Elorrieta et al.(2019))and the bivariate irregular autoregressive model(Elorrieta et al.(2021)).ContentsIrregular Autoregressive (IAR) Model[1]Complex Irregular Autoregressive (CIAR) Model[2]Bivariate Irregular Autoregressive (BIAR) Model[3]InstalationDependencies:numpy
pandas
scipy
matplotlib
sklearn
statsmodelsInstall from PyPI using:pip install iaror clone this github and do:python setup.py install --userExamplesIAR Model demohereCIAR Model demohereBIAR Model demohereAuthorsFelipe Elorrieta (felipe.elorrieta@usach.cl) (Millennium Institute of Astrophysics and Universidad de Santiago de Chile)Cesar Ojeda (Universidad del Valle - Colombia)Susana Eyheramendy (Millennium Institute of Astrophysics and Universidad Adolfo Ibañez)Wilfredo Palma (Millennium Institute of Astrophysics)AcknowledgmentsThe authors acknowledge support from the ANID – Millennium Science Initiative Program – ICN12_009 awarded to the Millennium Institute of Astrophysics MAS (www.astrofisicamas.cl)References[1]Eyheramendy S, Elorrieta F, Palma W (2018). “An irregular discrete time series model to identify residuals with autocorrelation in astronomical light curves.” Monthly Notices of the Royal Astronomical Society, 481(4), 4311–4322. ISSN 0035-8711, doi: 10.1093/mnras/sty2487,https://academic.oup.com/mnras/article-pdf/481/4/4311/25906473/sty2487.pdf.[2]Elorrieta, F, Eyheramendy, S, Palma, W (2019). “Discrete-time autoregressive model for unequally spaced time-series observations.” A& A, 627, A120. doi: 10.1051/00046361/201935560,https://doi.org/10.1051/0004-6361/201935560.[3]Elorrieta, F, Eyheramendy, S, Palma, W, Ojeda, C (2021).A novel bivariate autoregressive model for predicting and forecasting irregularly observed time series, Monthly Notices of the Royal Astronomical Society, 505 (1),1105–1116,https://doi.org/10.1093/mnras/stab1216[4]Jordán A, Espinoza N, Rabus M, Eyheramendy S, Sing DK, Désert J, Bakos GÁ, Fortney JJ, LópezMorales M, Maxted PFL, Triaud AHMJ, Szentgyorgyi A (2013). “A Ground-based Optical Transmission Spectrum of WASP-6b.” The Astrophysical Journal, 778, 184. doi: 10.1088/0004637X/
778/2/184, 1310.6048,https://doi.org/10.1088/0004-637X/778/2/184.[5]Lira P, Arévalo P, Uttley P, McHardy IMM, Videla L (2015). “Long-term monitoring of the archetype Seyfert galaxy MCG-6-30-15: X-ray, optical and near-IR variability of the corona, disc and torus.” Monthly Notices of the Royal Astronomical Society, 454(1), 368–379. ISSN 0035-8711, doi: 10.1093/mnras/stv1945,https://doi.org/10.1093/mnras/stv1945.
Package: iar-inflector
IAR InflectorThe IAR (Iván Arias Rodríguez) Inflector is an inflector for Spanish lemmas. It is able to create all the forms that derive from a given lemma. It also assigns its EAGLES tag to each form.The creation of this software was supported by the Spanish Ministry of Education, Culture and Sport via a doctoral grant to Iván Arias Rodríguez (FPU16/04039). It has also been funded by research projects TIN2014-52010-R (RedR+Human) and TIN2017-88092 R (CetrO+Spec).You can install this software with pip :pip install iar-inflectorIf you change or adapt a function, change its name (for example add your initial after the name)This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/This code is given as is without warranty of any kind.
In no event shall the authors or copyright holder be liable for any claim damages or other liability.El IAR (Iván Arias Rodríguez) Inflector es un flexionador de lemas de la lengua española. Puede crear todas las formas que derivan de un cierto lema dado. También les asigna su etiqueta EAGLES correspondiente.La creación de este software fue apoyada por el Ministerio de Educación, Cultura y Deporte de España, a través de una beca doctoral otorgada a Iván Arias Rodríguez (FPU16/04039). También ha sido financiado por los proyectos de investigación TIN2014-52010-R (RedR+Human) y TIN2017-88092 R (CetrO+Spec).Puedes instalar este software con pip :pip install iar-inflectorSi cambias o adaptas una función, cambia su nombre (por ejemplo añade tus iniciales tras el nombre)Este trabajo se ofrece bajo la licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/Este código se ofrece como es sin ninguna garantía de ningún tipo.
En ningún caso los autores o el titular de los derechos de autor serán responsables de cualquier reclamación por daños y perjuicios u otra responsabilidad.
Package: iarm
IArm is an ARM interpreter for the ARMv6 THUMB instruction set (More
specifically for the ARM Cortex M0+ CPU). It supports almost 100% of the
instructions, and some assembler directives. There is also itsJupyterkernel counterpart so it can be used
with Jupyter notebooks. Check out the/docsfolder to see a
technical overview and some example notebooks.InstallInstall with pippip install iarmOr clone the repo and install with setuptoolspython setup.py installTo install the Jupyer kernel counterpart, after installation, runpython -m iarm_kernel.installUsagePythonImport thearmmodule and instantiate an interpreter from theArmclassimport iarm.arm
interp = iarm.arm.Arm()To run code, pass the code into theevaluatemethod. Multiple lines
can be sent in as well as one line at a time.interp.evaluate(" MOVS R0, #5")
interp.evaluate("""
    MOVS R1, #3
    ADDS R2, R0, R1
""")By default, code is not run. Therunmethod must be called.interp.run()
print(interp.register)  # Print out the status of all the registersJupyterSimply activate the iarm_kernel module and make a new notebook as anIArmnotebook. Most of the magics have a 1 to 1 to the module. Refer
to the notebooks in the/docs/examplesfolder and the%helpmagic.
Package: iAROnline
Data sets, functions and scripts with examples to implement online estimation methods for the irregularly observed autoregressive (iAR) model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>). The online learning algorithms implemented are: gradient descent (IAR_OGD), Newton-step (IAR-ONS) and Kalman filter recursions (IAR-OBR).
Package: iarray-community
ironArray Community EditionWhat it isironArray Community is the open source version ofironArray.  It has been developed to mimic the same API than h5py or Zarr.  It implements the support for simple and double floating-point data using a metalayer. With the community edition of ironArray you can extract slices from floating-point datasets in a simple way!For more info, see the docs at:https://ironarray.io/docs/iarray-community/InstallingironArray Community is a pure Python package, so it can easily be installed for any platform.
You can install binary packages from PyPi usingpip:python -m pip install iarray-communityHave fun!The ironArray Team
Package: iar-tokenizer
IAR TokenizerThe IAR (Iván Arias Rodríguez) Tokenizer is a tokenizer developed mainly for Spanish. It is able to divide a text in paragraphs, those in sentences, and each sentence in a list of tokens.The creation of this software was supported by the Spanish Ministry of Education, Culture and Sport via a doctoral grant to Iván Arias Rodríguez (FPU16/04039). It has also been funded by research projects TIN2014-52010-R (RedR+Human) and TIN2017-88092 R (CetrO+Spec).You can install this software with pip :pip install iar-tokenizerIf you change or adapt a function, change its name (for example add your initial after the name)This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/This code is given as is without warranty of any kind.
In no event shall the authors or copyright holder be liable for any claim damages or other liability.El IAR (Iván Arias Rodríguez) Tokenizer es un tokenizador desarrollado principalmente para la lengua española. Es capaz de dividir un texto en párrafo, estos en frases, y cada frase en una lista de tokens.La creación de este software fue apoyada por el Ministerio de Educación, Cultura y Deporte de España, a través de una beca doctoral otorgada a Iván Arias Rodríguez (FPU16/04039). También ha sido financiado por los proyectos de investigación TIN2014-52010-R (RedR+Human) y TIN2017-88092 R (CetrO+Spec).Puedes instalar este software con pip :pip install iar-tokenizerSi cambias o adaptas una función, cambia su nombre (por ejemplo añade tus iniciales tras el nombre)Este trabajo se ofrece bajo la licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/Este código se ofrece como es sin ninguna garantía de ningún tipo.
En ningún caso los autores o el titular de los derechos de autor serán responsables de cualquier reclamación por daños y perjuicios u otra responsabilidad.
Package: iar-transcriber
IAR TranscriberThe IAR (Iván Arias Rodríguez) Transcriber is a phonetic transcriber developed for Spanish. It is able to get the phonological and phonetic transcription of a Spanish text.The creation of this software was supported by the Spanish Ministry of Education, Culture and Sport via a doctoral grant to Iván Arias Rodríguez (FPU16/04039). It has also been funded by research projects TIN2014-52010-R (RedR+Human) and TIN2017-88092 R (CetrO+Spec).You can install this software with pip :pip install iar-transcriberIf you change or adapt a function, change its name (for example add your initial after the name)This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/This code is given as is without warranty of any kind.
In no event shall the authors or copyright holder be liable for any claim damages or other liability.El IAR (Iván Arias Rodríguez) Transcriber es un transcriptor fonético desarrollado para la lengua española. Es capaz de realizar una transcripción fonológica y fonética (ancha y estrecha) de un texto en español.La creación de este software fue apoyada por el Ministerio de Educación, Cultura y Deporte de España, a través de una beca doctoral otorgada a Iván Arias Rodríguez (FPU16/04039). También ha sido financiado por los proyectos de investigación TIN2014-52010-R (RedR+Human) y TIN2017-88092 R (CetrO+Spec).Puedes instalar este software con pip :pip install iar-transcriberSi cambias o adaptas una función, cambia su nombre (por ejemplo añade tus iniciales tras el nombre)Este trabajo se ofrece bajo la licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/Este código se ofrece como es sin ninguna garantía de ningún tipo.
En ningún caso los autores o el titular de los derechos de autor serán responsables de cualquier reclamación por daños y perjuicios u otra responsabilidad.
Package: iar-wiki-parser
IAR Wikipedia parserThe IAR (Iván Arias Rodríguez) Wikipedia parser is a parser that downloads the Spanish Wikipedia, divides it in smaller chunks, deletes non-content articles and cleans all kind of tags or any other element that is not pure plain text, so it creates a corpus out of the content of the Wikipedia.The creation of this software was supported by the Spanish Ministry of Education, Culture and Sport via a doctoral grant to Iván Arias Rodríguez (FPU16/04039). It has also been funded by research projects TIN2014-52010-R (RedR+Human) and TIN2017-88092 R (CetrO+Spec).You can install this software with pip :pip install iar-wiki-parserIf you change or adapt a function, change its name (for example add your initial after the name)This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/This code is given as is without warranty of any kind.
In no event shall the authors or copyright holder be liable for any claim damages or other liability.El IAR (Iván Arias Rodríguez) Wikipedia parser is un analizador que se descarga el contenido de la Wikipedia en español, la divide en trozos más pequeños, borra los artículos sin contenido enciclopédico y limpia todo tipo de etiquetas y cualquier otro elemento que no es puramente texto sin formato, de manera que crea un corpus a partir del contenido de la Wikipedia.La creación de este software fue apoyada por el Ministerio de Educación, Cultura y Deporte de España, a través de una beca doctoral otorgada a Iván Arias Rodríguez (FPU16/04039). También ha sido financiado por los proyectos de investigación TIN2014-52010-R (RedR+Human) y TIN2017-88092 R (CetrO+Spec).Puedes instalar este software con pip :pip install iar-wiki-parserSi cambias o adaptas una función, cambia su nombre (por ejemplo añade tus iniciales tras el nombre)Este trabajo se ofrece bajo la licencia Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.http://creativecommons.org/licenses/by-nc-sa/4.0/Este código se ofrece como es sin ninguna garantía de ningún tipo.
En ningún caso los autores o el titular de los derechos de autor serán responsables de cualquier reclamación por daños y perjuicios u otra responsabilidad.
Package: i-asana
i-AsanaThis is a standardized and customized connector to Asana.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes.PrerequisitesThis package supports the following version of Python. It probably supports older versions, but they have not been tested.Python 3.10 or laterInstallingInstall the latest package using pip.$ pip install i-asanaEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this system$ python -m pytestUsageTODOAuthorsJason Romano-AracnidSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: iasap
interactive as soon as possible (a.k.a iasap)——————————————–iasap は、key-value store 形式のテキスト検索を目的として開発しました。iasap は、incremental 検索機能を実現しています。iasap は、key-value store の key, value の保存先として、sqlite3 を使用しています。iasap は、tkinter, curses, command prompt のいずれかで、対話的に検索できます。iasap は、検索単語に空白を入力せずに検索すると、一致検索を実行します。iasap は、検索単語の前に空白を入力すると前方一致検索、 検索単語の後に空白を入力すると後方一致検索、を実行します。開発者の私は、手元の PC で英辞郎を使いたくて、iasap を開発しました。英辞郎を PC で辞書として使う方法について詳しくは、同梱の README.txt をご覧下さい。このバージョンの iasap は、Python3.x で使用してください。
Package: iascan
iascaniascanest un outil de balayage d'adresses IP conÃ§u pour Ãªtre simple et efficace. Il permet aux utilisateurs de scanner rapidement des adresses IP uniques ou des plages d'adresses IP pour collecter des informations de base sur les hÃ´tes connectÃ©s.InstallationPour installeriascan, exÃ©cutez simplement la commande suivante :pip install iascanAssurez-vous d'avoirpipinstallÃ© et de l'utiliser avec une version de Python supÃ©rieure Ã  3.6.UtilisationPour scanner une adresse IP spÃ©cifique, utilisez la commande suivante :iascan -ip 192.168.1.1Pour scanner une liste d'adresses IP Ã  partir d'un fichier, utilisez :iascan -list ip_list.txtLe fichierip_list.txtdoit contenir une adresse IP par ligne.FonctionnalitÃ©sRecherche d'adresses IP uniques.Balayage d'une liste d'adresses IP.Affichage des informations de base telles que les hostnames, les ports ouverts, les tags associÃ©s, et potentiellement les vulnÃ©rabilitÃ©s connues.Utilisation simple en ligne de commande.ContributionLes contributions Ãiascansont les bienvenues ! Si vous avez des suggestions ou des amÃ©liorations, n'hÃ©sitez pas Ã  ouvrir une issue ou une pull request sur notre dÃ©pÃ´t GitHub Ã  l'adresse suivante :GitHub - iascan.Licenceiascanest distribuÃ© sous la licence MIT. Voir le fichierLICENSEpour plus d'informations.
Package: ia-sdk
GAIuS™ Python SDKA Python SDK for Intelligent Artifacts' GAIuS™ agents.What is GAIuS™?GAIuS™ is an Artificial General Intelligence framework for rapidly building machine intelligence solutions for any problem domain.What is IA's Python SDK?This package, ia-sdk-python, is a software development kit for interacting with IA's GAIuS agents from Python.  It provides useful tools and services.Installpip install ia-sdkProvides:- GenomeInfo
- AgentClient
- PerformanceValidationTest
- Higher Level Agent Operations
- Utilities for interacting with the GAIuS FrameworkDocumentationDetailed documentation for the Python SDK can be found atthis site
Package: iAST
# iAST #(Supports Python 3.3 and 3.4)This library provides a way of defining and transforming abstract syntax
trees (ASTs) for custom languages. It can be used to help build a compiler
or other program transformation system.iAST reads your language’s abstract syntax from an ASDL grammar, and
automatically generates node classes. A standard visitor-style framework
is provided for traversing, transforming, and pattern matching over trees.
Nodes are hashable, have structural equality, and support optional type
checking. (Parsing is not supported and should be handled by an external
parser generator.)Node definitions for the ASTs of Python 3.3 and Python 3.4 are provided
out-of-the-box, along with tools for writing code templates and macros
targeting Python code. However, the main framework works on ASTs for
arbitrary languages.## Examples ##See [arith.py](examples/arith.py) for basic usage and visitors/transformers.
See [toy.py](examples/toy.py) for a comparison with Python’s own ast module
and the use of type checking. Both examples use abstract grammars from the
corresponding ASDL files.## Installation ##To install from pip/PyPI:` python-mpip install iast `To use a development version:` python-mpip installhttps://github.com/brandjon/iast/tree/tarball/develop`Python 3.3 and 3.4 are supported. The only dependency is
[simplestruct](https://github.com/brandjon/simplestruct), which is used to
define the node classes.## Developers ##Tests can be run withpython setup.py test, or by installing
[Tox](http://testrun.org/tox/latest/) and runningpython -m toxin the project root. Tox tests both Python 3.3 and 3.4 configurations.
Building a source distribution (python setup.py sdist) requires the
setuptools extension package
[setuptools-git](https://github.com/wichert/setuptools-git).## References ##[1]:https://github.com/eliben/asdl_parser[[1]]: Eli Bendersky’s rewrite of the Python ASDL parser, which powers
iAST’s generation of nodes from ASDL.