Saravanan666/pypi-org huggingface dataset:
Package: keeprofi
KEEPROFIFast rofi drun menu for keepass databaseInstallationaur:keeprofipip:keeprofiSystem dependencies:rofixclip- copy password in clipboardsystem keyring(optional)UsageBind and press shortcut forkeeprofiFind keepass database fileType the master password for your keepass databaseSelect passwordPressEnterfor default action(copy password in clipboard)Ctrl+Enter- for additional action(type password in active window)Shift+Enter- for open password attributes menu where you can select any attr withEnterorCtrl+EnterFeaturesSaves last opened*.kdbpathSaves last*.kdbmaster password in system keyring(disabled by default)Desktop notifications with log and error messagesCtrl+h- switch hidden filesConfigurationXDG_CONFIG_HOME/keeprofi/config.json:default_action:copy# ['copy'|'type'] - default action that will done by 'Enter' pressingsave_masterpass:false# [false|true|'1W2D3H4M5S'] - this flag controlles using keyring for `*.kdb` file password savingkeybinds:hidden:Control+h# switch hidden filescustom_action:Control+Return# custom action(typing by default)pass_attrs:Shift+Return# password attributes menu opennotify_icons:success:keepassxc-darkfail:keepassxc-lockeddir_format:/{name}# format of directories and keepass groups outputsave_masterpassCan take 3 value:false(default) -*.kdbfile password never saves in keyringtrue-*.kdbfile password always saves in keyring1W2D3H4M5S- time interval format that specify how long password can be stored in keyring. Where:W - weeksD - daysH - hoursM - minutesS - secondsany unit can be missed, but existing units should observe the specified order
Package: keep-sabbath
Keep-SabbathKeep Sabbath is a Django app to automatically redirect website visitors when it is the Sabbath day, with support for overriding on other Biblical Holy days.IntroductionKeep-Sabbath is for webmasters with e-commerce shops, blogs, etc. who would like to keep the Biblical 7th-day Sabbath and other Holy days of the Bible Holy.The django app allows you to easily setup a system for a Django-powered website that will automatically redirect visitors to a single page (explaining about the Sabbath, redirect, etc.) if it is the Sabbath day or another Holy day.The app uses internal, offline calculations (via the SolarTime module) and the current date/time of the server to figure out if it is the Sabbath day (thus, if the user should be redirected), so you do not have to do it manually. It is optimized for performance and speed.There is also an option to manually override it as well, which is useful for other Biblical Holy days.The timing is based on the understanding that the 7th-day Sabbath day starts on 6th day ("Friday") evening and ends on 7th day ("Saturday") evening, according to the Bible.FeaturesSimple setup2 ways to use itAutomatically redirects when it is the 7th day SabbathSupport for manual overridingSupports Django 3.2+Installationpip install keep_sabbathpip install pytzDocumentationThe documentation can be found in the demo:example/examplewebsite.ContributingAll contributions are welcome!Feel free to open a PR or ask questions. :)Releasing on PyPINavigate to the root directoryRunpy -m buildThen runtwine upload dist/*and follow the prompts.LicenseKeep-Sabbath is licensed under the BSD 3-Clause License. Feel free to use as needed in your own projects. See the LICENSE for full copyright and license information.
Package: keepsake-ui
Keepsake UIOut of the box web UI to visualize machine learning experiments versioned
bykeepsake. Supports listing experiments,
experiment deletion and comparison.InstallationYou can install the tool via pippip install keepsake_uiUsageIf you havekeepsake.yamlin your current directory you can runkeepsake-uiand openhttp://localhost:8080in your web browser to see the
experiments and checkpoints.Alternatively, you can manually specify the repository via-roptionkeepsake-ui -r "<repository>"
Package: keep-screen-alive
SummaryA simple command line wrapper forcaffeinateon macOS that provides a forward looking relative datetime interface.Install$pipinstallkeep-screen-aliveExamples$date
WedJun108:00:00CDT2023$keep-alive2h
Keepingaliveuntil10:00AMCDT,Jun01,2023$keep-alive12pm
Keepingaliveuntil12:00PMCDT,Jun01,2023$keep-alive7am
Keepingaliveuntil07:00AMCDT,Jun02,2023
Package: keepstart
Monitor keepalived status, run start.sh if server get MASTER role, and run stop.sh if server get SLAVE role.Installpip install keepstartExample Configapplication:
    daemon: false
    pidfile: jenkins-keep.pid

keepstart:
    nic: eth0
    vip: 172.18.1.44
    start: /opt/app/start.sh
    stop: /opt/app/stop.sh
    is-running: /opt/app/status.sh

logging:
    version: 1
    disable_existing_loggers: false
    formatters:
        simple:
        format: "%(asctime)-15s\t%(levelname)s\t%(message)s"
    handlers:
        console:
            class: logging.StreamHandler
            level: DEBUG
            formatter: simple
    loggers:
        keepstart:
            level: DEBUG
            handlers:
                - console
            propagate: no
    root:
        level: DEBUG
        handlers:
            - consoleServer commandkeepserver -c config.yaml start
keepserver -c config.yaml stop
keepserver -c config.yaml reloadCommand helpzencoreDeMacPro:keepstart zencore$ keepserver --help
Usage: keepserver [OPTIONS] COMMAND [ARGS]...

Options:
-c, --config FILENAME  Config file path, use yaml format. Default to
                        config.yaml.
--help                 Show this message and exit.

Commands:
reload  Reload application server.
start   Start application server.
stop    Stop application server.
zencoreDeMacPro:keepstart zencore$
Package: keepthis
KeepThisAbout projectScientific toolkit which will inspire you and your team to work with more collaboration than ever before.It works almost like LRU Cache but allows you:Use same cache in different processes;Use same cache at the different moments of time;Easily share your local runtime's results with your teammates!Usingmemcachedas a backend allows you to cache really large things.Try it!How to installInstall the package.Clone this repoOpen repo's root path in terminalInstall package usingpip install -e .Please ensure that you have memcached instance.
I recommend you to use docker image for your first-time interactions with library:dockerrun-d--rm-p11211:11211memcachedMore information about docker imageMore examplesYou can find out usages of KeepThis inexamples/andnotebooks/
Package: keepup
keepup is a command line process manager, similar toForemanandHoncho, except it usesnpyscreento provide a curses interface for monitoring stdout, stderr, and for sending input to stdin.keepup uses anUpfilesimilar to aProcfile. An example is shown below# Upfiles support comments by prefixing a line with the # charactermytask:pythonmyscript.py# The following line will set the working directory for the specified task@mytask:/home/user/directorySupport for advanced features is limited.
Package: keepvariable
keepvariableA Python package keeping the values of variables between separate runs in a seamless and effortless way.InstallationUse the package managerpipto install keepvariable.pipinstallkeepvariableUsage with Redisimportkeepvariable_coreaskvimportpandasaspdkv_redis=kv.KeepVariableRedisServer(host="127.0.0.1",port=6379)kv_redis.set("test","abc123")result=kv_redis.get("test")print(result)#abc123#even pandas dataframes, and numpy arrays can be storeddf=pd.DataFrame([[1,2,3,4],[4,5,6,7]],columns=["a","b","c","d"])array=df.valueskv_redis.set("test_df",df)result=kv_redis.get("test_df")print(result)#   a  b  c  d#0  1  2  3  4#1  4  5  6  7kv_redis.set("test_array",array)result=kv_redis.get("test_array")print(result)# #[[1 2 3 4]# # [4 5 6 7]]Usage (locally)fromkeepvariable_coreimportVar,kept_variables,save_variables,load_variablea=Var("b")b=Var("c")c=a+bprint(c)dict1=Var({1,2,3,4,5})list1=Var(a)print(kept_variables)save_variables(kept_variables)list1=load_variable()b=load_variable()c=Var(c)print(list1)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseMIT
Package: keewee
KeeWee 🥝Global applicationstate managementandrecording.The Keewee library implements an auxiliary class that can be used to manage class and instance attributes at runtime.One major usecase is to decouple your state-management from your business-logic
and keep your code nice and concise.You can also use it to record statistics about an attribute during runtime.The library works with regularPython classesordataclassesbut needs little different configuration.InstallingInstall and update usingpip$pipinstall-UkeeweeA Simple Exampleimportrandomfromdataclassesimportdataclass,fieldfromkeeweeimportKeeWee@dataclassclassPokemonTrainer:name:strskill_level:int|KeeWee=field(default=KeeWee(),repr=False)if__name__=="__main__":ash=PokemonTrainer(name="Ash Ketchum",skill_level=0)for_inrange(10):ash.skill_level=random.randint(1,10)print(KeeWee.dumpd()){'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":[0,5,9,6,3,6,10,8,4,2,9]}}}Collection Record ModesWhen assigning a KeeWee instance to an attribute,
the user can customize its internal recording-behavior by providing themode-option.
Currently, there are four different modes, whereas thelist-mode is the default setting.Direct modeWhen only the current or resp. the last value is of interest, one can choose thedirectmode,
where the attribute isdirectelymapped
to its value.{'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":3}}}List modeThelist-mode keeps all occurring values in an ordered list from the first to the last value this attribute was assigned.Since this use-case is probably themostcommon it is also chosen to be thedefaultrecord-behavior.{'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":[0,5,9,6,3,6,10,8,4,2,9]}}}Set modeTheset-modes only difference to the list-mode is that duplicates are not tracked.{'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":{0,2,3,5,7,9}}}}Datetime to valueIf one wants to know exactly at what timestamp the modification took place thedtv(datetime-value)-mode is the best to choose.Here a new dictionary is created for every attribute and the current time is mapped onto the state change.{'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":{'15:11:44.976976':0,'15:11:44.976985':8,'15:11:44.976987':6,'15:11:44.976990':2,'15:11:44.976992':6,'15:11:44.976994':9,'15:11:44.976996':8,'15:11:44.976998':7,'15:11:44.977000':3,'15:11:44.977002':9,'15:11:44.977004':7}}}}Numerical Record ModesThe following record modes only work for numerical values, e.g.intorfloatetc.The result will look similar to thedirect-mode.Currently there are three numerical record modessumthe sum of all occurring valuesminthe minimal value that has occurredmaxthe maximum value that has occurredAn example usage for taking thesumover all values could look like the following.@dataclassclassPokemonTrainer:name:strskill_level:int|KeeWee=field(default=KeeWee(mode='sum'),repr=False){'PokemonTrainer':{'skill_level':{"PokemonTrainer(name='Ash Ketchum')":49}}}LinksPyPI Releases:https://pypi.org/project/keewee/
Package: kegbot-pyutils
kegbot-pyutilsThis is a small collection of common Python library code used in the Kegbot
project.Homepage:https://github.com/Kegbot/kegbot-pyutilsFor documentation and more information, seehttps://kegbot.org/docsLicense and CopyrightAll code is offered under theMITlicense, unless otherwise noted.  Please
seeLICENSE.txtfor the full license.
Package: keggm
Keggm - a small suite of tools I use to analyses microbial genomesThis is currently a very barebones package. Only two functions are fully operational.enrichm looks for metabolic blocks which are enriched in your genomes compared to some background.
This is good to try and get a quick idea on how your genomes are different to the background set in terms of certain metabolic functions.
You can specify you own blocks and use custom protein names which make it quite extensible.completm is a small tool to aid exploring what functions your genome can perform.
It creates a “completeness” matrix which gives you an idea if your genome shows the potential to perform that metabolic block.
It also create a matrix with the protein names which contributed to that completeness which can help you check if your metabolic block was
complete due to proteins which are normally poorly annotated and, if there are complementary proteins, which ones were present.
This will be expanded to provide a list of “complete” modules for each organism based on some user threshold.In the worksplots aims to create some small visualisations to better parse the completeness results. It consists of heatmaps, to quickly scan across genomes,
and will later included arrows diagrams of each metabolic block where each arrow represents a protein.
The arrows will be coloured based on the organisms which had the relevant proteins.overlap tries to identify is organisms have the potential to supplement each other.
It does this by looking for metabolic blocks which are complete in one organisms but the rests of the metabolic block can be found in another organism.TODO:Make a better test suiteMake it usable on the command line (for convenience)Implement auxilliary non-enrichment features into main softwarePlots with options to compare completenessVisualisation of overlap within module across multiple genomes similar to Symbiodinium+coral paperSome kind of colourisation of KEGG pathways to give you a broad idea of what’s present within a pathway.Eventually, if I can, make the network stuff robust enough for the potential automated discovery of novel metabolismAdd more customisability - Make it that any user can essentially create there own extra kegg data for use in this softwarerequires a few auxilliary tools to augment permanent databasesUnify Database scraping and production to be a single commandOther todo:Make it multithreaded/multiprocessor at the comparison stage (current scale of comparisons poses no speed issue)Implement in terms of producure consumer model of multithreadingInvestigate optimised Booschloo’s test and if it has reasonable runtime (unlikely)Implement a logging system for better debugging - will make my life easier.
Package: kegg-pull
DescriptionThekegg_pullpackage provides a number of useful CLI and API features for interacting with the KEGG REST API. This includes wrapper methods/commands for all the REST API operations, pulling lists of KEGG entry IDs, and pulling an arbitrary number of KEGG entries, in a single call, that are automatically separated and saved in individual files.DocumentationThe complete documentation for our API and CLI including tutorials can be foundhere.InstallationRequires python 3.10 and above.Install on Linux, Mac OS Xpython3 -m pip install kegg-pullInstall on Windowspy -3 -m pip install kegg-pullNote:Many KEGG entry IDs contain colons andkegg_pullsaves KEGG entry files with their ID in the file name. When running on Windows, all file names with colons will have their colons replaced with underscores.Note:Ifpyis not installed on Windows (e.g. Python was installed via the Windows store rather than from the official Python website), the installation command is the same as Linux and Mac OS X.Note:If thekegg_pullconsole script is not found on Windows, the CLI can be used viapython3-mkegg_pullorpy-3-mkegg_pullorpath\to\console\script\kegg_pull.exe. Alternatively, the directory where the console script is located can be added to the Path environment variable. For example, the console script may be installed at:c:\users\<username>\appdata\local\programs\python\python310\Scripts\PyPiSee our PyPi pagehere.Questions, Feature Requests, and Bug ReportsPlease submit any questions or feature requests you may have and report any potential bugs/errors you observe onour GitHub issues page.DependenciesNote, thepipcommand will install dependencies automatically.docopt
requests
tqdm
jsonschemaGet the source codeCode is available on GitHub:https://github.com/MoseleyBioinformaticsLab/kegg_pull.You can clone the repository via:git clonehttps://github.com/MoseleyBioinformaticsLab/kegg_pull.gitOnce you have a copy of the source, you can embed it in your own Python package, or install it into your system site-packages easily:Linux, Mac OS Xpython3 setup.py installWindowspy -3 setup.py install
Package: keggrest
keggrest========implementation of the rest API to access the kegg databaseImplemented functions--------RESTrequest(*args, **kwargs) -> response stringcreate a request to the KEGG url, is the basis for all the other call.Take as argument the pieces of the rest call.KEGGlink(db1, db2, **kwargs) -> (dict, dict)evaluate the connection between two databases, return two dictionariesof list that gives how each element of the database is related to theelements of the otherKEGGconv(db1, db2, **kwargs) -> (dict, dict)convert between one kegg database and an external one. currently supportedare the uniprot, ncbi-gi and ncbi-geneid for genes and pubchem, chebifor chemical compounds. Return the two lookup table (dicts) two convertfrom one dictionary to the otherKEGGlist(db, organism='', **kwargs) -> dictreturn all the element of a specific database for a certain organism,in the form of a dictionary element: descriptionKEGGget(element, option='', **kwargs) -> dictreturn the dictionary of description of the required object.possible options are: aaseq | ntseq | mol | kcf | image | kgmlKEGGbrite(britename, option='', **kwargs) -> dict of dictsanalize a brite ontology and return a dictionary of dictionaries.still in beta version, works up to three level of hierarchy.
Package: keggstand
keggstandKEGG API client and parsers for pathway protein-protein interactionsFree software: MIT licenseUsageTo use the API client, instantiate a new instance:client = Kegg(cache=True)To list organism codes in KEGG:client.organisms()To list available pathway accessions and names for a given organism:accessions = client.list_pathways(organism='hsa')To parse a particular pathway into a dataframe of protein-protein interactions, pass a KEGG pathway
accession to the method below:pathway = client.get_pathway(pathway='path:hsa01521')

# Inspect individual protein/genes parsed from XML file
pathway.entries

# Inspect relations between entries parsed from XML file
pathway.relations

# Pandas DataFrame of interactions with annotated post-translational modifications
pathway.interactionsTo make a call to the accession mapping service you can convert a source database to a destination
database:client.convert(source='hsa', destination='uniprot')This will create a mapping from KEGG hsa identifiers to uniprot swissprot identifiers.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.0.7 (2020-07-19)First release on PyPI.
Package: keggtools
keggtoolsLibrary for KEGG pathway enrichment analysis.Documentation:https://keggtools.org/PyPi:https://pypi.org/project/keggtools/Installationkeggtoolsonly supportspythonversion greater than or equal3.8.DependenciesgraphvizpythondependenciesrequestspydotscipyInstallationkeggtoolspackage usingpip:python3-mpipinstallkeggtoolsTo get a more detailed list of install options, please read theINSTALL.mdAPIDownload and ParsingfromkeggtoolsimportResolver,IMMUNE_SYSTEM_PATHWAYSORGANISM_ID="hsa"resolver=Resolver()# Select first immune system pathway as examplepathway_id=list(IMMUNE_SYSTEM_PATHWAYS.keys())[1]# Resolve pathwaypathway=resolver.get_pathway(organism=ORGANISM_ID,code=pathway_id)print(pathway)Enrichment and TestingfromkeggtoolsimportEnrichment# Add pathway object to listpathway_list=[]# Init analysis with organism codeanalysis=Enrichment(pathways=pathway_list)# Study genes as list of entrez gene id'sstudy_genes=[]analysis.run_analysis(gene_list=study_genes)# to_dataframe method requires pandas installationresult=analysis.to_dataframe()print(result.head())Renderingfromkeggtools.renderimportRenderer# Load and parse pathwayrenderer=Renderer(kegg_pathway=pathway)# Render to dot graphrenderer.render()# Export to pngrenderer.to_file("output.png",extension="png")DevelopmentDev installationFast install withvirtualenvfor development.python3-mvirtualenvvenvsource./venv/bin/activate
pipinstall--upgradepip# Install from requirementspipinstall-rrequirements.txt# Or use makefilemakeinstallLintingRun linting withpylintforkeggtoolspackage.# Run linting for packagemakepylintStatic code analysisStatic code analysis usingmypy. Run static code analysis withmypy.# Run static code analysismakemypyTestingRun unittest forkeggtoolspackage.# Run unittest for packagemakepytestInstall package from repoThe package is using theflitbackend with apyproject.tomlandtwine. To install from repo use# Install package from repomaketwine
Package: kegg-viewer
Generate Highlighted SVG/PNG for KEGG PathwayInstallationpipinstallkegg_viewerExampleskegg_viewer-h
kegg_viewer-pko00196
kegg_viewer-pko00196,ko00197
kegg_viewer-ppath.list
kegg_viewer-ppath.list-ggene.list-c./cache-Ooutput
kegg_viewer-ppath.list-ggene.list-monline
kegg_viewer-ppath.list-ggene.list-tpng
kegg_viewer-ppath.list-ggene.list-tbothgenelist examplesK08913	red
K08912	blue
LAMA2	blue
K02289	red
K20713	blue
K08910	#FF1188example resultspng modesvg modeSVG Mode:local# use local image as backgroundonline# use online image as backgroundbase64# convert background to base64,default and recommend!TODOsadd list, link method for KEGGRestprepare cache data(png/conf) for input organism
Package: kegs
Easy enums for Python.>>>RGB=StringEnum(['Red','Green','Blue'])>>>RGB.Red'Red'Contents1Installation2Features3Use4Contributing4.1Installing for development4.2Running the tests4.3Adding documentation5Credits1InstallationInstallezenumwith:pipinstallezenum2FeaturesPure Python.Compatible with Python 3.5+.Easy creation of usefull enum objects.String enums with unified value and name attributes.3UseStringEnumEasilly get a string enum from a string list.4ContributingPackage author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help.4.1Installing for developmentClone:gitclonegit@github.com:shaypal5/ezenum.gitInstall in development mode with test dependencies:cdezenumpipinstall-e".[test]"4.2Running the testsTo run the tests, use:python-mpytest--cov=ezenum4.3Adding documentationThis project is documented using thenumpy docstring conventions, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings (in my personal opinion, of course). When documenting code you add to this project, please followthese conventions.5CreditsCreated by Shay Palachy (shay.palachy@gmail.com).
Package: kegtron-ble
Kegtron BLEkegtron BLE supportInstallationInstall this via pip (or your favourite package manager):pip install kegtron-bleContributors ✨Thanks goes to these wonderful people (emoji key):This project follows theall-contributorsspecification. Contributions of any kind welcome!CreditsThis package was created withCookiecutterand thebrowniebroke/cookiecutter-pypackageproject template.