Saravanan666/pypi-org huggingface dataset:
Package: hebspacy
HebSpaCyA custom spaCy pipeline for Hebrew text including a transformer-based multitask NER model that recognizes 16 entity types in Hebrew, includingGPE,PER,LOCandORG.InstallationTo run the package you will need to install the package as well as the model, preferably in a virtual environment:# Create conda env (optional)condacreate--namehebspacypython=3.8
condaactivatehebsafeharbor# Install hebspacypipinstallhebspacy# Download and install the model (see below availbable models)pipinstall</path/to/download>Available ModelsModelDescriptionInstall URLhe_ner_news_trfA full spaCy pipeline for Hebrew text including a multitask NER model trained against the BMC and NEMO corpora. Read morehere.DownloadGetting startedimportspacynlp=spacy.load("he_ner_news_trf")text="""מרגלית דהןמספר זהות 11278904-52/12/2001ביקור חוזר מ18.11.2001במסגרת בירור פלפיטציות ואי סבילות למאמצים,מנורגיות קשות ע"ר שרירנים- ביצעה מעבדה שהדגימה:המוגלובין 9, מיקרוציטי היפוכרומטי עם RDW 19,פריטין 10, סטורציית טרנספרין 8%.מבחינת עומס נגיפי HIV- undetectable ומקפידה על HAART"""doc=nlp(text)forentityindoc.ents:print(f"{entity.text}\t{entity.label_}:{entity._.confidence_score:.4f}({entity.start_char},{entity.end_char})")>>>מרגליתדהןPERS:0.9999(0,10)>>>2/12/2001DATE:0.9897(33,42)>>>מ18.11.2001DATE:0.8282(54,65)>>>8%PERCENT:0.9932(230,232)he_ner_news_trf'he_ner_news_trf' is a multitask model constructed fromAlephBertand two NER focused heads, each trained against a different NER-annotated Hebrew corpus:NEMO corpus- annotations of the Hebrew Treebank (Haaretz newspaper) for the widely-used OntoNotes entity category:GPE(geo-political entity),PER(person),LOC(location),ORG(organization),FAC(facility),EVE(event),WOA(work-of-art),ANG(language),DUC(product).BMC corpus- annotations of articles from Israeli newspapers and websites (Haaretz newspaper, Maariv newspaper, Channel 7) for the common entity categories:PERS(person),LOC(location),ORG(organization),DATE(date),TIME(time),MONEY(money),PERCENT(percent),MISC__AFF(misc affiliation),MISC__ENT(misc entity),MISC_EVENT(misc event).The model was developed and trained using the Hugging Face and PyTorch libraries, and was later integrated into a spaCy pipeline.Model integrationThe output model was split into three weight files:the transformer embeddings, the BMC head, and the NEMO head.
The components were each packaged in a separate pipe and integrated into the custom pipeline.
Furthermore, a custom NER head consolidation pipe was added last to address signal conflicts/overlaps, and sets theDoc.entsproperty.To access the entities recognized by each NER head, use theDoc._.<ner_head>property (e.g.,doc._.nemo_entsanddoc._.bmc_ents).ContributionYou are welcome to contribute tohebspacyproject and introduce new feature/ models.
Kindly follow thepipeline codebase instructionsand themodel training and packaging guidelines.HebSpaCy is an open-source project developed by8400 The Health Network.
Package: hecate
Hecate is a Python 3 library for testing command line interfaces that make
interesting use of the terminal, e.g. through ncurses. Unlike tools like
expect or pexpect it runs a full blown terminal emulator (specifically, tmux)
behind the scenes, so you can take accurate snapshots of what your application
would look like when run by a real user.UsageHecate is currently shall we say lightly documented (this is a euphemism for
undocumented). Howeverthe testsshould work tolerably well as usage examples and there are reasonable docstrings
onthe implementation.Frequently Anticipated QuestionsAre you serious?Not very, no. As a concept it works and works well, and I’m fully prepared to
maintain this if it proves popular, but this should be considered a semi
experimental hack which just happens to be orders of magnitude better than
all of the for serious mature projects you could be using instead.On the other hand the last time I wrote a semi-experimental testing hack that
just happened to be the best around (in Python), we gotHypothesis, so…Will you support Python 2.7?No.Why not?Because you shouldn’t need it and I don’t want to. Hecate scripts are stand
alone applications that interact with your program through its terminal
interface. You can easily test things written in any language you like,
including other versions of Python.What versions of tmux does it support?My CI tests it on versions 1.6 through 2.0, so that’s the officially supported
set. It probably works on earlier ones but I haven’t tested and am not very
interested in doing so.Why is it called Hecate?It seemed appropriate to name a Selenium style tool for curses based
applications aftera goddess whose domain includes the moon and magic.How does it work?Behind the scenes Hecate is spawning a tmux instance and running your command
with it along with a monitoring process so that we can report back the exit
code (after all, who would make a testing framework that didn’t report the
standard mechanism for indicating errors back to you?). Hecate interacts with
the tmux server using its command line tools.I might update it to use the control protocol at some point, but it so far
doesn’t seem that useful to do so and that would limit the range of supported
tmux versions or require a lot of version specific code.
Package: hecatomb
Ahecatombis a great sacrifice or an extensive loss.
Heactomb the software empowers an analyst to make data driven decisions to'sacrifice'false-positive viral reads from
metagenomes to enrich for true-positive viral reads.
This process frequently results in a great loss of suspected viral sequences / contigs.ContentsDocumentationCitationQuick Start GuideInputsDependenciesLinksDocumentationComplete documentation is hosted at Read the DocsCitationHecatomb is currently on BioRxiv!Quick start guideInstall Hecatomboption 1: PIP# Optional: create a virtual with conda or venvcondacreate-nhecatombpython=3.10# activatecondaactivtehecatomb# Installpipinstallhecatomboption 2: Conda# Create the conda env and install hecatomb in one stepcondacreate-nhecatomb-cconda-forge-cbiocondahecatomb# activatecondaactivatehecatombCheck installationhecatomb--helpInstall databases and envsDownload the databases# 8 threads = 8 downloads at a timehecatombinstall--threads8Optional: prebuild envsThese are automatically built when running hecatomb, but manually pre-building is useful if your cluster nodes are isolated from the internet.hecatombtestbuild_envsRun test dataset# locally: using 32 threads and 64 GB RAM by defaulthecatombtest--threads32# HPC: using a profile named 'slurm'hecatombtest--profileslurmSnakemake profiles (for running on HPCs)Hecatomb is powered bySnakemakeand greatly benefits from the use of
Snakemake profiles for HPC Clusters.More information and example for setting up Snakemake profiles for Hecatomb in the documentation.NOTE: Hecatomb currently uses Snakemake version 7.
The recent version 8 for Snakemake has some breaking changes, including some changes to the command line interface for cluster execution.
Any new Snakemake v8 profiles might not work with Hecatomb.
Please open an issue if you need help setting up a profile.InputsParsing samples with--readsYou can pass either a directory of reads or a TSV file to--reads.
Note that Hecatomb expects paired read file names to include common R1/R2 tags.Directory:Hecatomb will infer sample names and various R1/2 tag combinations from the filenames.TSV file:Hecatomb expects 2 or 3 columns, with column 1 being the sample name and columns 2 and 3 the reads files.More information and examples are available hereLibrary preprocessing with--trimHecatomb usesTrimnamifor read trimming which supports many different
trimming methods. Current options arefastp(default),prinseq,roundAB,filtlong(longreads),cutadapt(FASTA input), andnotrim(skip trimming). See Trimnami's documentation for more information.ConfigurationYou can configure advanced parameters for Hecatomb.
Copy the default config:hecatomb config.
Edit the config file in your favourite text editor:nano hecatomb.out/hecatomb.config.yaml.DependenciesThe only dependency you need to get up and running with Hecatomb iscondaor
the python package managerpip.
Hecatomb relies oncondato ensure portability and ease of installation of its dependencies.
All of Hecatomb's dependencies are installed during installation or runtime, so you don't have to worry about a thing!LinksHecatomb @ PyPIHecatomb @ biocondaHecatomb @ bio.toolsHecatomb @ WorkflowHub
Package: heccer
Heccer is a fast compartmental solver, that is based on hsolve of the GENESIS simulator.Heccer can be instantiated from C, or from Perl (or other scripting languages). It is also possible to link Heccer directly to Matlab. Heccer comes with Swig interface definitions, such that linking Heccer to any other technologies should be easy.
Adding new channel types to Heccer can be done using callouts. The callout mechanism allows for general user extensions that contribute a current or conductance at a particular time in a simulation. Heccer automatically integrates this contribution into the membrane potential.Heccer is currently capable of simulating Purkinje cells (see the Purkinje Cell Model), and, at first evaluation, runs slightly faster than hsolve (It is difficult to assess why exactly: while the hsolve implementation is much more optimized than Heccer’s, the Heccer design is slightly better optimized than hsolve’s.).Heccer can operate in a “passive-only” mode, i.e. all channels in a model are ignored with exception of the synaptic channels.
Tables to speed up computations, are dynamically generated and optimized.
All parts of a model with the same kinetics automatically share tables.
Computes the contribution of one channel type to the overall dendritic current, e.g. the contribution of all calcium channels or the contribution of all persistent calcium channels.
.
Heccer has been validated with a Purkinje cell model and produces an exact match with hsolve (see the purkinje cell model and the Purkinje cell tutorial in the GENESIS simulator distribution). Heccer is constantly undergoing regression tests.
Package: hecho
hechohecho is a fast and simple HTTP echo server.An example is running on “http://hecho.bigode.net/”.It usesFalconHTTP library andBjoernWSGI server to serve thousands
requests per second using just one CPU Core and approximately 15MB of RAM.The response is a “prettified” json containing the request.Simple request/response example:$ curl --header "Content-Type: application/json" \
    --request POST --data '{"user": "john", "pass": "1234"}' \
    http://localhost:8000?p=param

{
    "headers": {
        "ACCEPT": "*/*",
        "CONTENT-LENGTH": "32",
        "CONTENT-TYPE": "application/json",
        "HOST": "localhost:8000",
        "USER-AGENT": "curl/7.19.7 (x86_64-redhat-linux-gnu) libcurl/7.19.7 NSS/3.27.1 zlib/1.2.3 libidn/1.18 libssh2/1.4.2"
    },
    "json": {
        "pass": "1234",
        "user": "john"
    },
    "method": "POST",
    "origin": "127.0.0.1",
    "params": {
        "p": "param"
    },
    "url": "http://localhost:8000/?p=param"
}It supports get, post, put, patch and delete methods.The request data must be JSON or x-www-form-urlencoded (standard simple post).NotesWorks on Python 2.7 and Python3.4+InstallInstall using pip:pip install hechoUsageUsage: hecho [options] start|stop|restart

simple and fast http echo server

Options:
--version           show program's version number and exit
-h, --help          show this help message and exit
-l ADDRESS          address to listen (default: localhost)
-p PORT             application port (default: 8000)
--log-path=LOGPATH  logfile path (default: ~/.hecho/hecho.log)
--pid-path=PIDPATH  pidfile path (default: ~/.hecho/hecho.pid)
--foreground        run in foreground mode (default: disabled)
--disable-log       disable logging (default: disabled)RunningStarting the server:$ hecho startVerify log, process and tcp listen address:$ tail ~/.hecho/hecho.log
[28/Dec/2018 16:23:10] Starting server...

$  ps aux | grep hecho
myuser  23648  0.0  1.5 214444 15720 ?  S  15:54  0:00 python hecho.py start

$ netstat -nlp | grep python
tcp  0  0 127.0.0.1:8000  0.0.0.0:*  LISTEN  23648/pythonSimple test:$ curl localhost:8000

{
    "headers": {
        "ACCEPT": "*/*",
        "HOST": "localhost:8000",
        "USER-AGENT": "curl/7.19.7 (x86_64-redhat-linux-gnu) libcurl/7.19.7 NSS/3.27.1 zlib/1.2.3 libidn/1.18 libssh2/1.4.2"
    },
    "method": "GET",
    "origin": "127.0.0.1",
    "params": {},
    "url": "http://localhost:8000/"
}Verify log:$ tail ~/.hecho/hecho.log
[28/Dec/2018 16:23:10] Starting server...
[28/Dec/2018 16:24:55] 127.0.0.1 GET http://localhost:8000/ 200 313 curl/7.19.7 (x86_64-redhat-linux-gnu) libcurl/7.19.7 NSS/3.27.1 zlib/1.2.3 libidn/1.18 libssh2/1.4.2Stopping the server:$ hecho stop
Package: hecho-events
Hecho-eventsEvent Broker for Rasa Chatbot to send metrics toHecho Dashboard.StartmonitoringyourRasa Chatbotright now, accesshttps://hecho.ml!!Getting Startedpip install hecho-events aiohttpRegister athttps://hecho.mlto get an api key.After install add this entries toendpoints.yml:# endpoints.ymlevent_broker:type:hecho-events.main.RasaEventBrokerapi_key:"<your-api-key>"api_url:"https://localhost:6000"Get bridge-endpoint uri and change the api_url with him.Dependenciespip install aiohttpAbout HechoHecho Dashboardis a platform to store and show messaging, users, intents and much more from yourchatbot.
Package: heco
__  __________________          __  ________   ______                      _ __         
   / / / / ____/ ____/ __ \   _    / / / / ____/  / ____/___  ____ ___  ____  (_) /__  _____
  / /_/ / __/ / /   / / / /  (_)  / /_/ / __/    / /   / __ \/ __ `__ \/ __ \/ / / _ \/ ___/
 / __  / /___/ /___/ /_/ /  _    / __  / /___   / /___/ /_/ / / / / / / /_/ / / /  __/ /    
/_/ /_/_____/\____/\____/  (_)  /_/ /_/_____/   \____/\____/_/ /_/ /_/ .___/_/_/\___/_/     
                                                                    /_/HECO is an optimizing compiler for Fully Homomorphic Encryption (FHE).
FHE allows computation over encrypted data, but imposes a variety of cryptographic and engineering challenges.
This compiler translates high-level program descriptions (expressed in Python) into the circuit-based programming paradigm of FHE.
It does so while automating as many aspects of the development as possible,
including automatically identifying and exploiting opportunities to use the powerful SIMD parallelism ("batching") present in many schemes.HECO Python FrontendNoteHECO's Python Frontend is still undergoing a major revision.
The current version only prints a (almost MLIR) version of the code.
We are working on extending the frontend with more functionality and completing the toolchain, such that frontend programs can be executed again.Finalize InstallationThe HECO frontend relies on a development version ofxdsl. If you install HECO from PyPi, you need to install the xdsl dependency afterwards with:python3 -m pip install git+https://github.com/xdslproject/xdsl.git@frontendExamplesExamples of HECO can be found in theexamplesfolder.One of them, for computing the hamming distance of two encrypted vectors, is shown here:fromxdsl.frontendimport*fromxdsl.frontend.dialects.builtinimport*fromheco.frontend.dialects.fheimport*p=FrontendProgram()secret_f64=SecretType[f64]arg_type=BatchedSecretType[f64]withCodeContext(p):defencryptedHammingDistance(x:arg_type,y:arg_type)->secret_f64:sum:SecretType[f64]=SecretAttr(FloatAttr(0.0))foridxinrange(0,4):sum=sum+(x[idx]-y[idx])*(x[idx]-y[idx])returnsum# XXX: the part below was not yet ported to the new frontend# Compiling FHE codecontext=SEAL.BGV.new(poly_mod_degree=1024)f=p.compile(context=context)# Running FHF codex=[random.randrange(100)for_inrange(4)]y=[random.randrange(100)for_inrange(4)]x_enc=context.encrypt(x)y_enc=context.encrypt(y)s_enc=f(x_enc,y_enc)# Verifying Results=context.decrypt(s_enc)asserts==sum([(x[i]-y[i])**2foriinrange(4)])
Package: hecss
HECSSHigh Efficiency Configuration Space SamplerHECSS is a Markow chain Monte-Carlo, configuration space sampler using Metropolis-Hastings algorithm for probablity distribution sampling. It provides an alternative way to create representations of systems at thermal equilibrium without running a very expensive molecular dynamics simulation. The theoretical foundation of the code are presented inSciPost Phys. 10, 129 (2021)(short excerpt inBackgroundin theDocumentation). More detailed examples are included in theLAMMPSandVASPtutorials.If you use this software in published research please cite the above paper (BibTeX) in your publication.A very short exampleMinimal example using LAMMPS potential from the asap3 package and OpenKIM database. Here we will sample the thermodynamic distribution of 3C-SiC crystal at 300K. We start by importing required modules, define the crystal and energy/forces calculator, run the sampler and finally plot the energy distribution.#asapfromase.buildimportbulkimportasap3fromhecss.coreimportHECSS,select_asap_modelfromhecss.monitorimportplot_statsThen we define the crystal and interaction model used in the calculation. In this case we use 3x3x3 supercell of the SiC crystal in zincblende structure and describe the interaction using LAMMPS potential from the OpenKIM database and ASAP3 implementation of the calculator.#asap# model = 'Tersoff_LAMMPS_ErhartAlbe_2005_SiC__MO_903987585848_003'model=select_asap_model('SiC')cryst=bulk('SiC',crystalstructure='zincblende',a=4.38120844,cubic=True).repeat((3,3,3))cryst.set_calculator(asap3.OpenKIMcalculator(model))Then we define the sampler parameters (N -- number of samples, T -- temperature) and run it.#asapT=300N=1_000samples=HECSS(cryst,asap3.OpenKIMcalculator(model),T).generate(N)And finally we plot the histogram of the resulting energy distribution which corresponds to the thermal equilibrium distribution.#asapplot_stats(samples,T)InstallThe HECSS package is avaliable on pypi and conda-forge additionally the package is present also in my personal anaconda channel (jochym). Installation is simple, but requires a number of other packages to be installed as well. Package menagers handle these dependencies automatically.Install with pipIt is advisable to install in a dedicated virtual environment e.g.:python3 -m venv venv
. venv/bin/activatethen install withpip:pip install hecssInstall with condaAlso installation with conda should be performed for dedicated or some other non-base environment. To create dedicated environment you can invokeconda create:conda create -n hecss -c conda-forge hecssor you can install in some working environmentvenv:conda install -n venv -c conda-forge hecssExample data archiveThe example subdirectory from the source may be downloaded directly from the source repository:hecss-examples.zipThe source codeThe source is published at theGitlab hecss repository.
You can access it with git (recommended, particularly if you want to contribute to the development):gitclonehttps://gitlab.com/jochym/hecss.gitor you can download the whole distribution as a zip archive:hecss.zip
Package: hectare
HECTARE - Hamburg Elegant CreaTor from Accellera™ systemrdl™ to REgistersThis is a tool which generates AXI4-Lite slave from a description inSystemRDL.It usessystemrdl-compileras a front end and a custom backend to generate a VHDL module.The HECTARE tool is developed byMicroTCA Tech Labat DESY.Usage$ hectare.py --help
usage: hectare.py [-h] [--debug] [--axi-vhdl VHDL_NAME] filename

HECTARE - Hamburg Elegant CreaTor from Accelera systemrdl to REgisters

positional arguments:
  filename              .rdl file

optional arguments:
  -h, --help            show this help message and exit
  --debug               enable debugging information
  --axi-vhdl VHDL_NAME  generate AXI4-Lite slaveUseful argumentssw:r,rw,w,nahw:r,rw,w,naswmodsinglepulsewoclrencodeChangelog[0.2.4] - 2021-06-19Read decode error returns0xbadcofee[0.2.3] - 2021-06-07Add support forwoclr[0.2.2] - 2021-04-11Add support forsinglepulse[0.2.1] - 2021-02-19Add C header generatorAdd support for reset valuesAdd version argument (--version) to print version information[0.2.0] - 2020-06-08First public releaseProvides generation of AXI4-Lite module in VHDLSupports all possible combination forswandrwproperties as well asswmodandencodeattributeTestsSeveral tests are provided intestfolder00_unit_testThis is a simple unit test based on the Python [] framework.01_uvvm_simpleUVVM version: v2019.12.04Regenerating the output products (in shell, from folderhdl):$ ./gen_output.sh
Parsing finished.
generate_package
Generating mymodule.vhd ...
Generating mymodule_pkg.vhd ...
Done.Running the test (in ModelSim, from folderwork)do ../scripts/compile_uvvm.do
do ../scripts/sim.do02_hdlparseRequireshdlparsefrom a fork (the one from pip is missing some features)
available fromhttps://github.com/andresmanelli/hdlparseon branchentity.03_ordt_equivalenceCompares the output of HECTARE against Juniper®ordt.Alias toordtshould be created, as explainedhere.Accellera™ and SystemRDL™ are trademarks of Accellera Systems Initiative Inc.Juniper® is a registered trademark of Juniper Networks, Inc.
Package: heddex.cityportal
Introduction============Overview--------heddex.cityportal is free Plone theme from HedDex team (www.heddex.biz)Credits-------Authors:- Michael Krishtopa [theo at heddex.biz] - All theme development, CSS- Kristina Kudryavceva [kristinka.kartinka at gmail.com] - theme graphical designChangelog=========2.0 (2012-04-22)-------------------- Release for Plone 4.11.1 (2009-06-13)----------------* fixed bug with pathbar viewlet1.0 (2008-12-09)----------------* First theme release
Package: heddex.greenfield
Introduction============Overview--------heddex.greenfield is the first free Plone theme from HedDex team (www.heddex.biz)Credits-------Authors:- Michael Krishtopa [theo@heddex.biz] - All theme development, CSS- Kristina Kudryavceva [kristinka.kartinka@gmail.com] - theme graphical designChangelog=========2.0 (2012-04-21)--------------------- Release for Plone 41.0 (2008-08-21)-------------------- Final release for Plone3
Package: hedera-cli
hedera-cli-pyHederaCLI in PythonInstallpip install hedera-cliHow to UseJust run:hedera-cliSince hedera-cli depends onhedera-sdk-py, which requires Java >= 11, please make sure your JAVA_HOME environment is set up correctly.You can runsetupinside hedera-cli and enter your account ID and private key.  You can also put them in an .env file to be read automatically at hedera-cli startup.  To use a different env file, just use the filename as the argument for hedera-cli.  For example:hedera-cli mainnet.envA sample env filesample.envis provided.commandsType ? orhelpfor a list of commands.  Type?commandfor help on a specific command, for example?topic.setupSet up the client.accountaccount create  (create an account, account id and privatekey will be printed)

account info [accoun_id]  (get account info for current account if no accountId is provided,
                           or for a different account if accountId is provided)

account balance [account_id]  (get account balance for current account if no accountId,
                               or for a different account if accountId is provided)

account delete account_id  (delete the account identified by accountId.
                                you will be prompted for that account's private key)filefile create [file_path]
file info file_id
file contents file_id
file append file_id [file_path]
file delete file_idsendsend  (no argument, you will prompted for recipient account and amount)topictopic create [memo]  (create a topic with an optional memo)
topic info topic_id  (get info about a topic)
topic send topic_id message [[message]]  (send message to topic_id)
topic get topic_id [sequence_number]  (get topic message(s).  If you specify a sequence_number,
                                       you get one message, otherwise, you get all the messages on the topic)keygenCreate a key pair.networkSwitch networkexitExit the CLI