Saravanan666/pypi-org huggingface dataset:
Package: chord-lib
CHORD Library (for Python CHORD microservices)Common utilities and helpers for CHORD services.Running Testspython3-mtoxReleasing1. Release ChecklistAll tests pass and test coverage has not been reducedPackage version has been updated (following semver) inchord_lib/package.cfgThe latest changes have been merged from thedevelopbranch into themasterbranchA release has been created, tagged in the format ofv#.#.#and named
in the format ofVersion #.#.#, listing any changes made, in the GitHub
releases pagetagged from the master branch!2. Releasing from the Command Line# IF NECESSARY: Install twine OUTSIDE of the virtual environmentpython3-mpipinstalltwine# Switch to the correct branch and make sure it's up to dategitcheckoutmaster
gitpull# If needed, enter the project virtual environmentsourceenv/bin/activate# Remove existing build filesrm-rfbuild/dist/chord_lib.egg-info/# Build the new packagepython3setup.pysdistbdist_wheel# In between these steps - test out the package... make sure everyhting works# before uploading it to production PyPI.# Upload it to PyPItwineuploaddist/*Modulesauthauthprovides Python service decorators and Django / DRF backends for dealing
with the CHORD container authentication headers (derived fromlua-resty-openidc, set by the internal container NGINX instance.)eventseventsfacilitates JSON-serialized message-passing between CHORD
microservices. Serialized objects can be at most 512 MB.Events should have a lower-case type which is type-insensitively unique and
adequately describes the associated data.All CHORD channels are prefixed withchord..ingestioningestioncontains common code used for handling ingestion routines in
different CHORD data services.schemasschemascontains common JSON schemas which may be useful to a variety of
different CHORD services.schemas.chordcontains CHORD-specific schemas, andschemas.ga4ghcontains
GA4GH-standardized schemas (possibly not exactly to spec.)searchsearchcontains definitions, validators, and transformations for the query
syntax for CHORD, as well as a transpiler to thepsycopg2PostgreSQL IR.The query syntax for CHORD takes advantage of JSON schemas augmented with
additional properties about the field's accessibility and, in the case of
Postgres, how the field maps to a table column (or JSON column sub-field.)search.data_structurecontains code for evaluating a CHORD query against a
Python data structure.search.operationscontains constants representing valid search operations one
can allow against particular fields from within an augmented JSON schema.search.postgrescontains a "transpiler" from the CHORD query syntax to thepsycopg2-providedintermediate representation (IR)for
PostgreSQL, allowing safe queries against a Postgres database.search.queriesprovides definitions for the CHORD query AST and some helper
methods for creating and processing ASTs.utilsutilscontains miscellaneous utilities commonly required by CHORD services.workflowsworkflowscontains common code used for handling workflow metadata processing
and response generation.
Package: chordparser
chordparser is a Python 3 package that provides a musical framework to analyse chords. Chord notation can be parsed into Chords, which can then be analysed against other chords or the key of the song. This allows for harmonic analysis in chord sheets and helps musicians understand why and how chord progressions work.Quick demo:>>>importchordparser>>>cp=chordparser.Parser()>>>new_chord=cp.create_chord("C7add4/E")>>>new_chord.notes(Enote,Cnote,Fnote,Gnote,B♭note)>>>new_chord.transpose_simple(6)F♯7add4/A♯chord>>>new_chord.notes(A♯note,F♯note,Bnote,C♯note,Enote)>>>e_scale=cp.create_scale("E","major")>>>cp.to_roman(new_chord,e_scale)II65romanchord>>>e_fifth=cp.create_diatonic(e_scale,5)>>>e_fifthBchord>>>cp.analyse_secondary(new_chord,e_fifth,e_scale)"V65/V"FeaturesCreate and manipulate notes, keys, scales and chords easilyParse complex chord notationsTranspose musical classes easily and accuratelyAutomatically generate notes for scales and chords from notationGenerate roman numeral notation from chordsAnalyse chord-scale relationshipsInstallationTo install chordparser, run this command in your terminal:$pipinstallchordparserUsageCheck out theColab notebook, which runs through a working example to showcase chordparser’s functions and help you get started on using it.The full documentation can be foundhere.ContributeIssue Tracker:github.com/titus-ong/chordparser/issuesSource Code:github.com/titus-ong/chordparserSupportIf you are having issues, please let me know at:titusongyl@gmail.comAuthorsDevelopment LeadTitus Ong <titusongyl@gmail.com>LicenseThe project is licensed under the MIT license.
Package: chords2midi
![chords2midi](https://i.imgur.com/rvXoXOf.png)# chords2midiGiven it a chord progression, get a MIDI file!Take your MIDI file, drop it into your favorite DAW and [make a beat!](https://clyp.it/drltahki) Or [two](https://clyp.it/f0g1ko5b).## Installation$ pip install chords2midi## Usage$ c2m I V vi IV --key C$ lsC-I-V-vi-IV.midMore usage:$ c2m I V vi iii IV I IV V --key D --bpm 128 --octave 5 --duration .25 # Pachabel's Canon in D, Staccato EDM Version$ lsD-I-V-vi-iii-IV-I-IV-V-128.midYou can also use named chords directly:$ c2m Am Em F G --bpm 80$ lsAm-Em-F-G-80.midYou can place rests with `X`:$ c2m I X V X vi X IVFurther options:```usage: c2m.py [-h] [-b BPM] [-t OCTAVE] [-i INPUT] [-k KEY] [-n NOTES][-d DURATION] [-H HUMANIZE] [-o OUTPUT] [-v][U [U ...]]chords2midi - Create MIDI files from written chord progressions.positional arguments:U                     Please supply chord progression!. See --help for moreoptions.optional arguments:-h, --help            show this help message and exit-b BPM, --bpm BPM     Set the BPM (default 160)-t OCTAVE, --octave OCTAVESet the octave (default 4)-i INPUT, --input INPUTRead from an input file.-k KEY, --key KEY     Set the key (default C)-n NOTES, --notes NOTESNotes in each chord (default all)-d DURATION, --duration DURATIONSet the chord duraction (default 1)-H HUMANIZE, --humanize HUMANIZESet the amount to "humanize" (strum) a chord, in ticks- try .11 (default 0.0)-o OUTPUT, --output OUTPUTSet the output file path. Default is the current keyand progression in the current location.-v, --version         Display the current version of chords2midi```## Common ProgressionsThe classic:$ c2m I V vi IV50's progression:$ c2m I vi IV V12 bar blues:$ c2m I I I I IV IV I I V V I Ior:$ c2m I I I I IV IV I I V VI I VSmoke on the water:$ c2m ii IV VWild thing:$ c2m I IV  V IVFlamenco:$ c2m vi V VI VGently weeps:$  c2m ii I V6 VIIb VISad:$ c2m vi IV I VAnd [lots more](https://www.hooktheory.com/theorytab/common-chord-progressions)!## PlaybackIf you're on OSX:$ brew install timidity$ timidity your-midi.mid## Related* [UltimateTemplate](https://github.com/Miserlou/UltimateTemplate) - Production-ready Ableton Live project templates.* [ADGMaker](https://github.com/Miserlou/ADGMaker) - Make Ableton ADG instruments from Free Philharmonia Orchestra samplesRich Jones, 2018. MIT.
Package: chordstransposer
# transposer**transposer** helps musicians by transposing the chords of a song.## Basic usage example```bashpython transposer.py mySong.txt G Bb  # transposes the song mySong for G to B-flat```For instance, let's take the file `lost-in-the-stars.txt` :```Before Lord God made the sea and the land,G         G°           A-7sus      D  D+He held all the stars in the palm of his handG6/B         E7b9         A-7         A-7b5```You can use transposer to transpose this song in any tone you like, for instance :```bashpython transposer.py lost-in-the-stars.txt G F# # transposes lost-in-the-stars from G to F sharp```You can then find in the newly created file (lost-in-the-stars.transposed.txt) :```Before Lord God made the sea and the land,F#         F#°           G#-7sus      C#  C#+He held all the stars in the palm of his handF#6/A#         D#7b9         G#-7         G#-7b5```_These are the first bars of Kurt Weill's [Lost in the Stars](https://www.youtube.com/watch?v=6xJ1u920c2o)_## File formatSince chord lines are auto-detected, you can structure your file as you wish, though each line must be only text or only chords (not a mix of both).## About the harmony**transposer** tries to follow as much as possible harmonic rules (eg. Cb instead of B when necessary). These are defined in the destination scale : for instance, if you want to transpose a song to Db, then the 3rd note of the minor scale is Fb and not E. You don't need your original file to follow these rules for this to work.However, in [traditional notation of the chords in popular music](<https://en.wikipedia.org/wiki/Chord_names_and_symbols_(popular_music)>), we avoid writing double-flat (bb) and double-sharp (x) for the sake of readability. Here, when they should appear to be perfectly correct in terms of harmony, the double-flat and double-sharp are transposed to their most simple equivalent.
Package: chore
DescriptionThe Chore dispatcher is a multi-job scheduler module for sending jobs to different
systems. It was developed to help manage bioinformatics jobs in a django website
environment. But should equally work well outside of django.How to Use the ModuleA simple example:from chore.shell import JobManager

manager = JobManager()
manager.submit('job_1', 'wait 10')Basic options example:manager = JobManager(pipedir='/specific/stash_dir', batch=True)
manager.submit('job_1', cmd='wait 10')A slurm example:from chore.slurm import JobManager

manager = JobManager('/tmp/stash_dir', batch=True)
manager.submit('job_1', 'wait 10', provide='job_2')
manager.submit('job_2', 'wait 20', depend='job_1')
Package: ch-orm
A fork ofinfi.clikchouse_ormaimed at more frequent maintenance and bugfixes.This repository is expected to use more type hints and only supports Python 3.7+.Supports both synchronous and asynchronous ways to interact with the clickhouse server. Means you can use asyncio to perform asynchronous queries.BuildPackageDocsIntroductionThis project is simple ORM for working with theClickHouse database.It allows you to define model classes whose instances can be written to the database and read from it.This and other examples can be found in theexamplesfolder.To learn more please visit thedocumentation.
Package: chorny
chornyChorny (russian: чёрный) is a loader ofBlackthat patches code on the fly to change the formatting to satisfy Athenian's conventions.So far, the only difference with the original rules is how magic trailing commas work. Chorny
prevents new line expansion by the magic trailing comma for parentheses unless the code is
a function signature. Example:asyncdeffoo(self,arg,other,):passbecomesasyncdeffoo(self,arg,other,):passHowever,foo(1,"one,)stays intact.Installationpip install chornyUsagechornypatches and launchesblackand should be used the same way.LicenseMIT, seeLICENSE.
Package: chorogrid
# chorogrid
A python script to produce choropleths and colored square- and hex-grid mapsExamples:![Examples](https://raw.githubusercontent.com/Prooffreader/chorogrid/master/examples.png“Examples”)There are two classes, Chorobin to assign colors to quantities, and Chorogrid to make the maps.Maps are made in SVG format; if you need to convert them to PNG you can do so in an external application like Inkscape or Adobe Illustrator, or in python with CairoSVG among other solutions.Pro tip, because I made this mistake for a long time: it’s “choropleth”, not “chloropleth”; there’s no L. The word comes from ancient Greek χώρα (khṓra, “location”) and πλῆθος (plêthos, “a great number”, same root asplethora), not χλωρός (khlōrós, “pale green”) as inchlorineandchlorophyll. Luckily Google knows enough to suggest the right one.
Package: chorus-api
CHORUS-API / PISTE.GOUV.FRchorus-apiChorus API Packagehttps://piste.gouv.frHow to install chorus-apiInstallpipinstallchorus-api1.0.5CHANGESFixbase_64_encode_filemethod in utilsAllow pass encoding1.0.4CHANGESIntegration de l'état courantLe service ConsulterCR permet de consulter les informations liées au dépôt d'un flux et de récupérer au format PDF le
compte rendu de traitement du flux déposé via le portail ou le service exposé DeposerFluxFacture.KeycodedescriptionIN_RECUIN_RECULe flux a été reçu par Chorus ProIN_TRAITE_SE_CPPIN_TRAITE_SE_CPPLe fichier arrivé dans le système d’échange Chorus ProIN_EN_ATTENTE_TRAITEMENT_CPPIN_EN_ATTENTE_TRAITEMENT_CPPLe flux est en liste d’attenteIN_EN_COURS_TRAITEMENT_CPPIN_EN_COURS_TRAITEMENT_CPPLe flux est en cours de traitementIN_INCIDENTEIN_INCIDENTEFlux non traité par le système d’échange, il sera nécessaire de reprendre le flux intégralement.IN_REJETEIN_REJETELe flux a été traité mais rejeté car il comporte des anomaliesIN_EN_ATTENTE_RETRAITEMENT_CPPIN_EN_ATTENTE_RETRAITEMENT_CPPLe flux a été bloqué, il attend une reprise manuelleIN_INTEGREIN_INTEGRELe flux a été traité et tout a été intégré dans Chorus Pro.IN_INTEGRE_PARTIELIN_INTEGRE_PARTIELCela concerne des flux qui sont en rejet partiel, seules les factures correctes sont intégrées.UsageGET TOKENfromchorusapi.clientimportChorusAPIfromexemples.envimportCLIENT_ID,CLIENT_SECRETchorus_api=ChorusAPI(client_id=CLIENT_ID,client_secret=CLIENT_SECRET)token=chorus_api.auth().get_token()print(token)Consulter les informations liées au dépôt d'un fluxfromchorusapi.clientimportChorusAPIfromexemples.envimportCLIENT_ID,CLIENT_SECRET,TECH_USERNAME,TECH_PASSWORDchorus_api=ChorusAPI(client_id=CLIENT_ID,client_secret=CLIENT_SECRET,tech_username=TECH_USERNAME,tech_password=TECH_PASSWORD)status_depot=chorus_api.auth().consulter_cr("CPP0XXXXXXXXXXXXX")print(status_depot.__dict__)More details inexamplesfolders
Package: chosco
chosco 🏷️Package on top ofipywidgetsto label media resources onNotebookpages.Table of ContentsInstallation :computer:Development :construction_worker:Testing :white_check_mark:Contact :mailbox_with_mail:Installation :computer:>> pip install choscoDevelopment :construction_worker:Uselume :fire:to install dependencies:Example:>> python3 -m venv venv>> source venv/bin/activate(venv)>> pip install lume(venv)>> lume -installTesting :white_check_mark:Unit, Integration and Acceptance(venv)>> lume -testNotebooksRun jupyter server:(venv)>> jupyter notebookGo to dummy examplehereContact :mailbox_with_mail:support@alicebiometrics.com
Package: choto
Term Article SummaryInstallationpip install chotoInstallation (from source)Clone the repositorygit clone https://github.com/ayushsubedi/chotoCD into the cloned directory and create a virtualenvpython -m venv envEnable virtualenv.\env\Scripts\activateInstall dependency packages from requirements.txtpip install -r requirements.txtRun the apppython choto.py --url=https://abc.xyz --ratio=0.5 --algorithm=bertUsage: choto.py [OPTIONS]Options:
--url TEXT                      Enter a valid URL
--ratio FLOAT                   Ratio to summarize to.
--algorithm [gensim|spacy|bert] Algorithm to use
--help                          Show this message and exit.
Package: choubun
Choubun 超文(this is not recommended as a real way of generating HTML!)—@contextlib.contextmanagerChoubun is an alternative approach to templating engines.
Where a traditional template system has you writing your templates as separate files,
Choubun allows you to mix Python control flow and HTML markup, all within Python's syntax.To prevent injection vulnerabilities, Choubun usesMarkupSafeto escape unsafe text.markupsafe.Markupis also reexported asMarkupandM.How do I install it?Choubun isavailable on PyPI.
Usepoetry add choubunor your favorite dependency wrangler to start using Choubun in your project.What does code using Choubun look like?fromchoubunimportNodedoc=Node()doc.raw('<!DOCTYPE html>')withdoc.node('html',lang='en'):withdoc.node('head'):doc.leaf('meta',charset='utf-8')fork,vindict(viewport="width=device-width, initial-scale=1",referrer='no-referrer',).items():doc.leaf('meta',name=k,content=v)withdoc.node('body'):doc.text("Page body")
Package: chouette-iot-client
Chouette-IoT-ClientPython client library forChouette-IoTmetrics collection agent.This library can be used in applications to send Datadog-ish like messages to a Chouette-IoT metrics aggregator.It uses Redis as a broker. Metrics are being stored in Redis and then they are collected, processed and dispatched by Chouette-IoT.This library is able to send follow metric types:count,gauge,histogram,rateandset.distributionmetric isNOTsupported.ExamplesUsage example:from time import time
from chouette_iot_client import ChouetteClient

# These metrics takes a float as their value:
ChouetteClient.count(metric="my.count.metric", value=1, timestamp=time(), tags={"importance": "high"})
ChouetteClient.gauge("my.gauge.metric", 1)
ChouetteClient.histogram("my.histogram.metric", 1.5)
ChouetteClient.rate("my.rate.metric", 1)

# Set metric takes a list or a set as its value:
ChouetteClient.set("my.set.metric.set", {1, 2, 3})
ChouetteClient.set("my.set.metric.list", [1, 2, 3])Metric namemetricandvalueare mandatory parameters.timestampandtagsare optional.When notimestampis specified, actual time is automatically taken. When notagsare specified, empty dict is being sent.Also ChouetteClient supportstimedboth as a context manager and a decorator:from time import sleep
from chouette_iot_client import timed

# ContextManager:
with timed(metric="my.timed.context_manager", tags={"units": "seconds"}, use_ms=False):
    sleep(1)

# Decorator:
@timed(metric="my.timed.decorator", tags={"units": "milliseconds"}, use_ms=True)
def rest():
    sleep(1)

rest()Both these options will send the same data. But in one case it's going to be a value in seconds (~1.0) and in another case it will be a value in milliseconds (~1000).LicenseChouette-IoT-Client is licensed under theApache License, Version 2.0.
Package: chouf
# choufLogging handler how do custom action## DescriptionI was looking for a light framework able to act when something wrong arrive on execution.I didn't need a big solution.For my project, when I was loosing USB connection I want to act quickly.If a log record CRITICAL arrive 2 times in less than 2 seconds, It's easy to act with the lib.Let me show you.```pythonfrom chouf.chouffer import ChoufHandlerfrom chouf.triggers.base import FilterMatchfrom chouf.triggers.repeat import RepeatedRecordTriggerdef action():print('Action fired')f = FilterMatch(min_level=logging.CRITICAL, name='^.*$', msg='^.*$')rrt = RepeatedRecordTrigger(times=10, period_s=5, filters=[f], action=lambda: action())ch = ChoufHandler(triggers=[rrt])logging.root.addHandler(ch)```With this piece of code If a log record arrive 10 times in 5 second action will be run
Package: choujiang
A tool to generate user cards and pickup a winner for prize randomly.一个抽奖工具，支持输入内容，然后随机抽取一个幸运个体。Support scheduling prize picker and for multiple prizes, it can be achieved by click on right button to random winner picking支持定时随机抽奖，多个奖项可以点击多次。Support the adaptive UI rendering per resizing .支持窗口自适应，动态根据抽奖人数自动调节组件大小。Support multiple inputs like (line-by-line, lines[id:comment] string etc)支持多种格式生成抽奖个体卡片, 比如按行号，id:comment行格式提取id生成个体卡片。Package hosted on [pypi] and powered by [pypi-seed]Installation / 安装pip install prizeMore InfoAuthor levin （雷学委）
Package: chouseisan-py
chouseisan_pychouseisan_py automates the operations of調整さん(Chouseisan).
Currently, it only supports creating events.Installation$pipinstallchouseisan-pyUsage>>>fromdatetimeimportdatetime>>>fromchouseisan_py.chouseisanimportAuth,Chouseisan>>>auth=Auth(email="test@example.com",password="<secret>")>>>chouseisan=Chouseisan(auth)>>>chouseisan.create_event(...title="test event",...candidate_days=[datetime(2021,10,17,19,0),datetime(2021,10,18,19,0)]...)'https://chouseisan.com/s?h=f7b7fc11995b441782844bc3fddaf456'
Package: chowda
ChowdaCLAMS processing appDocumentationVisit thedocumentationfor install and usage instructions.Basic Pipeline with 2 CLAMS AppsActors:UserChowdaWebappPulbicly available on internetDBPostgresqlVPCSperate Cluster?RunnerPipeline RunnerIn CLAMS clusterCLAMSIndividual CLAMS appsIn CLAMS clusterDeployed as either:WebserviceKubernetes JobCall Sequence DiagramUserstarts jobChowdaenters it in theDBRunnersees new job and startsCLAM1with initial MMIFCLAM1Processes data and returns MMIF toRunnerRunnerUpdatesDBand startsCLAM2CLAM2Processes data and returns MMIF toRunnerRunnerUpdatesDBUsergets data fromChowdasequenceDiagram
    actor User
    participant Chowda
    participant DB
    participant Runner
    participant CLAM1
    participant CLAM2


    %% User starts job
    activate User
    note left of User: Hey, Chowda! Start batch 123 on pipeline 456
    User ->> + Chowda: Start batch 123 with files [] through pipeline 456
    Chowda ->> + DB: INSERT (batch, pipeline, Initial mmif) to TABLE pipeline_runs
    DB ->> - Chowda: {pipeline_run_id, status: waiting}
    Chowda ->> - User: Pipeline run {id} is {status}
    deactivate User
    loop backgroud process
        Runner ->> DB: Check for new jobs
    end

    %% Runner
    activate Runner
    note left of Runner: Found new job!
    Runner ->> + CLAM1: Start app 1, with initial MMIF
    deactivate Runner

    %% CLAM1
    note right of CLAM1: Processing!
    loop Status check
        Runner ->> CLAM1: Status report!
        CLAM1 ->> Runner: XX %
        Runner ->> DB: UPDATE pipeline_run_id SET status CLAM1 XX %
    end
    note right of CLAM1: Done!
    CLAM1 ->> - Runner: intermediate MMIF
    activate Runner
    Runner ->> DB: UPDATE pipeline_run_id SET status 'done' + MMIF

    %% CLAM 2
    Runner ->> + CLAM2: Start app 2 with intermediate MMIF
    deactivate Runner
    note right of CLAM2: Processing!
    loop Status check
        Runner ->> CLAM2: Status report!
        CLAM2 ->> Runner: XX %
        Runner ->> DB: UPDATE pipeline_run_id SET status CLAM2 XX %
    end

    %% User update
    activate User
    note left of User: Is it done yet?
    User ->> + Chowda: Pipeline update?
    Chowda ->> + DB: WATCH pipeline_runs WHERE status=running
    DB ->> Chowda: ACTIVE_PIPELINE_RUNS
    Chowda -->> User: Websocket: Batch 123 status [CLAM1: done, CLAM2: XX %]
    note left of User: Not quite, but it should be done soon.

    %% CLAMS finished
    note right of CLAM2: Done!
    CLAM2 -->> - Runner: finished MMIF
    activate Runner
    Runner ->> - DB: UPDATE pipeline_run_id SET status MMIF
    DB ->> Chowda: Batch 123 update
    Chowda -->> User: WS: batch 123 Finished!
    deactivate Chowda
    deactivate DB

    note left of User: Yay! My metadata is perfect!
    deactivate Userdeveloppre-commit secret scanningInstallggshieldpipinstallggshield# orbrewinstallgitguardian/tap/ggshieldLogin to gitguardianggshieldauthloginInstall the pre-commit hookspre-commitinstall
Package: chowtest
Chow TestThis project provides an implementation of the Chow break test.The Chow test was initially developed by Gregory Chow in 1960 to test whether one regression or two or more regressions best characterise the data. As such, the Chow test is capable of detecting "structural breaks" within time-series. Additional information can be obtained from:Chow, Gregory C. "Tests of equality between sets of coefficients in two linear regressions." Econometrica: Journal of the Econometric Society (1960): 591-605.Toyoda, Toshihisa. "Use of the Chow test under heteroscedasticity." Econometrica: Journal of the Econometric Society (1974): 601-608.This implementation supports simple linear models, and finding breaks where k = 2.InstallationThis module requires Python 3.0+ to run. The module can can be imported by:pipinstallchowtestfromchow_testimportchowtestInput ArgumentsThe required input arguments are listed below:ArgumentDescriptionydependent variable (Pandas DataFrame Column)Xindependent variable(s) (Pandas Dataframe Column(s))last_index_in_model_1index of final point prior to assumed structural break (str)first_index_in_model_2index of first point following structural break (str)significance_levelthe significance level for hypothesis testing (float)