Saravanan666/pypi-org huggingface dataset:
Package: arcana
Abstraction of Repository-Centric ANAlysis (Arcana) is Python framework
for “repository-centric” analyses of data tree (e.g. NeuroImaging
studies) built on thePydradataflow engine.Arcanamanages all interactions with “store” the data tree is stored in via adapter layers
designed for specific repository software or data structures (e.g. XNAT or BIDS).
Intermediate outputs are stored, along with the parameters used to derive them,
back into the store for reuse by subsequent analysis steps.Analysis workflows are constructed and executed using thePydradataflow
API, and can either be run locally or submitted to cloud or HPC clusters
usingPydra’s various execution plugins. For a requested output, Arcana determines the
required processing steps by querying the store to check for missing intermediate
outputs and parameter changes before constructing the required workflow graph.DocumentationDetailed documentation on Arcana can be found athttps://arcana.readthedocs.ioQuick InstallationArcana-core can be installed for Python 3 usingpip:$ python3 -m pip install arcanaLicenseThis work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International LicenseNote: For the legacy version of Arcana as described in
Close TG, et. al. Neuroinformatics. 2020 18(1):109-129. doi:10.1007/s12021-019-09430-1please seehttps://github.com/MonashBI/arcana-legacy.Conceptually, the legacy version and the versions in this repository are similar.
However, instead of Nipype, later versions use the Pydra dataflow engine (Nipype’s successor)
and the syntax has been rewritten from scratch to make it more streamlined and intuitive.AcknowledgementsThe authors acknowledge the facilities and scientific and technical assistance of the National Imaging Facility, a National Collaborative Research Infrastructure Strategy (NCRIS) capability.
Package: arcana-bids
An extension of the Arcana framework to work with Brain Imaging Data Structure (BIDS)
datasets and appsQuick InstallationThis extension can be installed for Python 3 usingpip:$ pip3 install arcana-bidsThis will also install the coreArcanapackage and any required dependencies.LicenseThis work is licensed under aCreative Commons Attribution 4.0 International License
Package: arcana-testing
This is the “testing” extension to theArcanaframework, which adds basic classes
used in test routines of the core package.Quick InstallationThis extension can be installed for Python 3 usingpip:$ pip3 install arcana-testingThis will also install the coreArcanapackage and any required dependencies.LicenseThis work is licensed under aCreative Commons Attribution 4.0 International License
Package: arcana-xnat
An extension for theArcanaframework that adds the following classes to allow integrated
deployment of workflows and analysis classes withXNATimaging data repositories:Xnatdata store for accessing data via REST API (only)XnatViaCSdata store for accessing data in the XNAT archive directly when running within the XNAT Container ServiceXnatAppcontainer image class, for building Docker images that can be installed, ready-to-go, in the XNAT Container ServiceQuick InstallationThis extension can be installed for Python 3 usingpip:$ pip3 install arcana-xnatThis will also install the coreArcanapackage and any required dependencies.LicenseThis work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Package: arcane-bigquery
Arcane bigqueryThis package is based ongoogle-cloud-bigquery.Get Startedpipinstallarcane-bigqueryExample Usagefromarcaneimportbigqueryclient=bigquery.Client()dataset_ref=client.dataset('name')dataset=bigquery.Dataset(dataset_ref)dataset.location='US'dataset=client.create_dataset(dataset)Create clients with credentials:fromarcaneimportbigquery# Import your configsfromconfigureimportConfigclient=bigquery.Client.from_service_account_json(Config.KEY,project=Config.GCP_PROJECT)
Package: arcane-bing
Arcane bingThis package is based onbingads.Get Startedpipinstallarcane-bingExample UsageReportingbing_client=Client(credentials=Config.BING_ADS_CREDENTIALS,secrets_bucket=Config.SECRETS_BUCKET,refresh_token_location=Config.BING_ADS_REFRESH_TOKEN,storage_client=storage_client)reporting_service_manager,reporting_service=bing_client.get_bing_ads_api_client()report_request=build_campaigns_report(reporting_service,bing_account_id)result_file_path=bing_client.submit_and_download(report_request,reporting_service_manager)Campaign Service:warning: For some API methods, you must provide the client's account id and the manager's customer idfromarcane.bingimportClientfromarcane.bing.helpersimportparse_webfault_errors,parse_bing_responsebing_client=Client(credentials=Config.BING_ADS_CREDENTIALS,secrets_bucket=Config.SECRETS_BUCKET,refresh_token_location=Config.BING_ADS_REFRESH_TOKEN,storage_client=storage_client,customer_id=CUSTOMER_ID,account_id=ACCOUNT_ID)campaign_service=bing_client.get_service_client(service_name='CampaignManagement')try:response=campaign_service.GetCampaignsByAccountId(AccountId=ACCOUNT_ID)all_campaigns=parse_bing_response(response)['Campaign']# do stuff with all_campaignsexceptWebFaultase:bing_error=parse_webfault_errors(e)# do stuff with bing_error
Package: arcane-datastore
Arcane DatastoreThis package is based ongoogle-cloud-datastore.Get Startedpipinstallarcane-datastoreExample Usagefromarcaneimportdatastoreclient=datastore.Client()entity=client.get_entity('kind-id-here',1)orfromarcaneimportdatastore# Import your configsfromconfigureimportConfigclient=datastore.Client.from_service_account_json(Config.KEY,project=Config.GCP_PROJECT)entity=client.get_entity('kind-id-here',1)
Package: arcane-ga4
Arcane ga4 READMEThis package helps us to interact with Google Analytics V4 API:+ [Analytics Data API](https://developers.google.com/analytics/devguides/reporting/data/v1)
+ [Google Analytics Admin API](https://developers.google.com/analytics/devguides/config/admin/v1)Release historyTo see changes, please see CHANGELOG.md
Package: arcane-notification
Arcane notificationDescriptionCe package nous permet de créer des objetsNotification, des les créer et de les valider pour ne plus les recevoir (acknowledge).
Vous pouvez trouver leschéma d'architecturedans le drive produit.
Une notification correspond concrètement à un mail envoyé par les cloud functions denotification_services.
Vous pouvez trouver dans la définition du typeNotificationles différents paramètres et leurs usages mais on peut distinguer plusieurs configurations classiques:Je souhaite envoyer un mail dès la création de la notification et un rappel le lendemain matin.Il suffit de mettre le paramètresend_on_activationàTruepour qu'automatiquement un mail soit envoyé lors de la création de la notification (c'est à dire dans la cloud functionpost_notification).
Pour activer les rappels le matin, il faut mettreseverityàMEDIUM.
Pour que les rappels cessent d'être envoyés, on peut définir uneend_dateau lendemain. Une fois la date de fin passée, une notification ne génère plus de mail.
Attention, si lenotification_nameexiste déjà, aucun mail ne sera envoyé lors du post. Par contre, laend_datesera décalée.Je souhaite envoyer un mail tous les 3 heures jusqu'à ce que l'utilisateur choisisse de ne plus recevoir la notification.Pour recevoir des mails toutes les 3h, il suffit de mettreseverityàHIGH.
Sur chaque email envoyé, l'utilisateur peut acknowledge une notification via l'icône de l'horloge.FAQJ'ai créé un nouveau mail. Comment faire en sorte de le recevoir?S'assurer que la cloud functionpost_notificationexiste sur le projet en question, la créer sinon.Créer uneNotificationà partir du type avecsend_on_activationàTrue,recipientsdoit contenir uniquement votre email etnotification_namene doit pas déjà exister (vous pouvez regarder dans Datastore).Une fois le message pubsub envoyé avec la fonctionpost_notificationvous devriez recevoir un mail.Si vous n'avez rien reçu, vous pouvez vérifier les logs de la cloud functionpost_notification. Si il n'y a pas le logSending alert to, il y a un problème dans l'objet notification que vous avez envoyé. Si le log est présent mais que vous ne recevez rien, il est possible que le problème vienne demailjet.
Package: arcane-pubsub
Arcane PubSubThis package is base ongoogle-cloud-pubsub.Get Startedpipinstallarcane-pubsubExample Usagefromarcaneimportpubsub# Import your configsfromconfigureimportConfigclient=pubsub.Client(Config.KEY)client.push_to_topic('project','topic',{"parameter":"value"})Publish with a new schemaresult=pubsub_client.publish_with_schema(project='my-project',topic_name='my-topic-with-schema',message=message,await_response=True,)
Package: arcane-secret
Arcane secretThis package allows to encode and decode secrets.Get Startedpipinstallarcane-secretExample Usagefromarcane.secretimportdecodedecoded_secret=decode('secret','path_to_secret_key_file')orfromarcane.secretimportencode# Import your configsfromconfigureimportConfigencoded_secret=encode(secret,Config.SECRET_KEY_FILE)
Package: arcane-snapchat
Arcane snapchat READMECredentialsThe access token for production environnement has been generated with:snapchat@arcane.runThe access token for staging environnement has been generated with:billel@arcane.runThe access token can be be expired, we receive a 401 if it is the case. We need to use the refresh token located in the credentials, this token is generated through a one time life 'code'. For more information :https://marketingapi.snapchat.com/docs/#receive-the-redirected-userRelease historyTo see changes, please see CHANGELOG.md
Package: arcane-stackdriver
Arcane StackdriverThis package is based ongoogle-cloud-error-reporting.Get Startedpipinstallarcane-stackdriverExample Usagefromarcaneimportstackdriverclient=stackdriver.Client()orfromarcaneimportstackdriver# Import your configsfromconfigureimportConfigclient=stackdriver.Client.from_service_account_json(Config.KEY,project=Config.GCP_PROJECT)
Package: arcane-storage
Arcane StorageThis package is base ongoogle-cloud-storage.Get Startedpipinstallarcane-storageExample Usagefromarcaneimportstorageclient=storage.Client()blobs=client.list_blobs('bucket-id-here')orfromarcaneimportstorage# Import your configsfromconfigureimportConfigclient=storage.Client.from_service_account_json(Config.KEY,project=Config.GCP_PROJECT)blobs=client.list_blobs('bucket-id-here')
Package: arcane-tasks
Arcane CloudTaskThis package is base ongoogle-cloud-cloudtasks.Get Startedpipinstallarcane-tasks## Example Usage```python
fromarcaneimporttasks# Import your configsfromconfigureimportConfigtasks_client=tasks.Client(adscale_key=Config.KEY,project=Config.GCP_PROJECT)body={'attribute':value}task_name="My task"tasks_client.publish_task(queue=<your-queue>,url=<url-to-triger>,body=body,task_name=task_name)
Package: arcaverborum
Arca VerborumArca Verborum is a project to interface with the data from the GLED package.The main available function is currently the one for performing weighted sampling of
languages based on their phylogenetic distance, on their geographic distance
accounting for areal effects
(currently computed as a simple Haversine distance between the coordinates),
and on the frequency among previous random samples.When obtaining random samples for multiple iterations, it is strongly
recommended to obtain all the samples in a single pass, so that the
library can account for the potential oversampling of languages
belonging to outgroups.Note that the loading of the distance matrices, particularly of the
geographic one, can take up to a minute on slower machines.See code for more documentation, as below.>>>importarcaverborum>>>sampler=arcaverborum.GLED_Sampler()WARNING:root:LoadingthephylogeneticmatrixfromGLED...WARNING:root:LoadingthegeographicmatrixfromGLED...WARNING:root:Rescalingthephylogeneticmatrix...WARNING:root:Rescalingthegeographicmatrix...>>>foridx,langsetinenumerate(sampler.sample(4,10)):...print(idx,langset)...0('TlamacazapaNahuatl_tlam1239','GaviaoDoJiparana_gavi1246','Tubar_tuba1279','Pei_peii1238')1('IslandCarib_isla1278','Samburu_samb1315','Dahalo_daha1245','Potawatomi_pota1247')2('VlaxRomani_vlax1238','Gwahatike_gwah1244','NezPerce_nezp1238','Kwakwala_kwak1269')3('AnaTingaDogon_anat1248','Zulgo-Gemzek_zulg1242','SkoltSaami_skol1241','Xokleng_xokl1240')4('Mangarrayi_mang1381','Narak_nara1264','Matses_mats1244','Ionic-AtticAncientGreek_anci1242')5('Jeli_jeri1242','Burum-Mindik_buru1306','Kistane_kist1241','Bongo_bong1285')6('Patwin_patw1250','WesternTamang_west2415','Kapori_kapo1250','Sakha_yaku1245')7('Kuy_kuyy1240','Kistane_kist1241','Kuruaya_kuru1309','Bolivar-NorthChimborazoHighlandQuichua_chim1302')8('Betaf_beta1253','Bargam_barg1252','Pengo_peng1244','Wuding-LuquanYi_wudi1238')9('NuclearWintu_nucl1651','Munit_muni1257','Nyawaygi_nyaw1247','MadaCameroon_mada1293')
Package: arcbound
ArcboundCollection of tools to arrange bound methods into a graph.Arcbound contains a series of decorators to aid data-driven programming, where
the methods and properties of a class are abstracted as nodes on a graph,
inter-connected by arcs (directed edges).InstallationpipinstallarcboundUsage exampleimportmathfromtypingimportTuple,Unionimportarcboundasabimportattr@ab.graph@attr.s(auto_attribs=True)classQuadraticSolver(object):""" Calculates the solutions to a given quadratic equation.Input parameters:a: Quadratic coefficient.b: Linear coefficient.c: Constant."""a:float=0.b:float=0.c:float=0.# Here we explicitly define the coefficient arcs.@property@ab.arcs(a="a",b="b",c="c")defdiscriminant(self,a:float,b:float,c:float)->float:""" Discriminant of the quadratic equation; used to determine thenumber of roots and if they are rational."""returnb*b-4*a*c# Here we use the auto_arcs decorator to automatically link to the# property of the same name.@property@ab.auto_arcs()defroots(self,a:float,b:float,discriminant:float)->Tuple[Union[float,complex],...]:""" Returns the root(s) of the equation."""ifdiscriminant==0:roots=(-b/(2*a),)elifdiscriminant>0:roots=((-b+math.sqrt(discriminant))/(2*a),(-b-math.sqrt(discriminant))/(2*a),)else:real=-b/(2*a)imag=math.sqrt(-discriminant)/(2*a)roots=(complex(real,imag),complex(real,-imag))returnroots# Since this property is not decorated with an arcbound decorator, a node# is not generated on the arcbound_graph.@propertydefnumber_of_roots(self)->int:""" Returns the number of roots."""discriminant=self.discriminantreturn(1ifdiscriminant==0.else2)quad_solver=QuadraticSolver(a=1,b=4,c=3)quad_solver.roots# (-1,0, -3.0)# Create a function that solves for the discriminant of a quadratic equation.# Retains the defaults of a=1, b=4, and c=3 from the quad_solver object.discriminant_solver=quad_solver.get_arcbound_node("discriminant")discriminant_solver(a=2,b=4)# -8quad_solver.visualize_arcbound_graph()
Package: arc_cache
Adaptive Replacement Cache - a Python3 decoratorMostly for self-study purposes. Use at your own risk.Usagefromarc_cacheimportarc_cache@arc_cache()defmy_heavy_function(arg1):do_stuff()DevelopingSetup a virtualenv using$pip3installtox$tox-edevelop$..venv/bin/activateTestingRun all tests using$toxReleasing$pythonsetup.pybdistsdistbdist_wheel$gpg-u...--detach-sign-adist/...$twineuploaddist/*ReferencesPython 3.5 (I believe) uses a C-implementation oflru_cache.ARC- A Self-Tuning, Low Overhead Replacement Cache (2003)Adaptive Replacement Cacheon Wikipedialru_cachein cpython 3.4
Package: arc-cli
ARCA tool for building declarative, and highly extendable CLI systems for Python 3.10+ARC FeaturesCommand line arguments based on python type hintsArbitrary command nestingAutomatic--helpdocumentationFully Extensible with custom middlewares,  types, validators, parameter configurations, etc...LinksDocsPlaygroundPyPiQuick Startimportarc@arc.commanddefhello(name:str):"""My first arc program!"""arc.print(f"Hello{name}!")hello()$ python hello.py Sean
Hello, Sean!$ python hello.py --help
USAGE
    hello.py [-h] [--] name

DESCRIPTION
    My first arc program!

ARGUMENTS
    name

OPTIONS
    --help (-h)  Displays this help messageInstallation$ pip install arc-cliClone for development$ git clone https://github.com/seanrcollings/arc
$ poetry installTestsTests are written withpytest$ pytest
Package: arcdico
ArC Digital Control ModuleThis is a Python wrapper for the ArC Digital Control (ArC DiCo) serial protocol.UsageUsage of the library is fairly straightforward. You only to know the serial
port where the DiCo is connected to.fromarcdicoimportDiCodico=DiCo('/dev/ttyUSB0')# The DiCo will disable all outputs when initially# powered on but you can do that programmatically by# using the `reset` function.dico.reset()# connect specified pins to the DAC outputdico.set_state(pins=[1,8,22])# set output voltage at 3.50 Vdico.set_state(voltage=3.50)# or do bothdico.set_state(pins=[1,8],voltage=2.25)
Package: arcee
ArceeIt is a Python parser generator, use EBNF-like syntax.Install$pipinstallArceeExampleIt's really readable.grammar:KEYWORDS        : let, if, zero, -
NUMBER          : \d+(\.\d*)?
ASSIGN          : =
SUBTRACTION     : -
RIGHT_BRACKET   : (
COLON           : ,
LETF_BRACKET    : )
ID              : [A-Za-z]+
SKIP            : [ \\t]+

program : expression ;
expression : zeroexp
    | diffexp
    | ifexp
    | varexp
    | letexp
    | constexp
    ;
constexp : $NUMBER ;
diffexp : '-' '(' expression ',' expression ')' ;
zeroexp : 'zero' '(' expression ')' ;
ifexp : 'if' expression 'then' expression 'else' expression ;
varexp : $ID ;
letexp : 'let' $ID '=' expression 'in' expression ;$ arcee grammar > result.pyresult.pyhas three parts:TokenfromcollectionsimportnamedtupleToken=namedtuple('Token',['type','value','line','column'])Program=namedtuple('Program',['expression'])# ...Lexerimportredeftokenize(code):pass# ...ParserclassParser:def__init__(self,token_list):pass# ...defparse_expression(self):ifxxx:self.parse_constexp()elifyyy:self.parse_diffexp()#...defparse_constexp(self):passdefparse_diffexp(self):passdefparse_zeroexp(self):passdefparse_ifexp(self):passdefparse_varexp(self):passdefparse_letexp(self):passYou can parse input such as:input='''let a = 0 in if zero(a) then -(a, 1) else -(a, 2)'''tokens=list(tokenize(input))parser=Parser(tokens)parser.parse_program()result is:result=Program(expression=Expression(nonterminal=Letexp(ID=Token(type='ID',value='a',line=2,column=4),expression1=Expression(nonterminal=Constexp(NUMBER=Token(type='NUMBER',value='0',line=2,column=8))),expression2=Expression(nonterminal=Ifexp(expression1=Expression(nonterminal=Zeroexp(expression=Expression(nonterminal=Varexp(ID=Token(type='ID',value='a',line=2,column=21))))),expression2=Expression(nonterminal=Diffexp(expression1=Expression(nonterminal=Varexp(ID=Token(type='ID',value='a',line=2,column=31))),expression2=Expression(nonterminal=Constexp(NUMBER=Token(type='NUMBER',value='1',line=2,column=34))))),expression3=Expression(nonterminal=Diffexp(expression1=Expression(nonterminal=Varexp(ID=Token(type='ID',value='a',line=2,column=44))),expression2=Expression(nonterminal=Constexp(NUMBER=Token(type='NUMBER',value='2',line=2,column=47))))))))))Now, you can use this ast to do what you like.You can also use api in your Python file.fromarceeimportgenerategrammar='''KEYWORDS        : let, if, zero, -NUMBER          : \d+(\.\d*)?ASSIGN          : =SUBTRACTION     : -RIGHT_BRACKET   : (COLON           : ,LETF_BRACKET    : )ID              : [A-Za-z]+SKIP            : [\\t]+program : expression ;expression : zeroexp| diffexp| ifexp| varexp| letexp| constexp;constexp : $NUMBER ;diffexp : '-' '(' expression ',' expression ')' ;zeroexp : 'zero' '(' expression ')' ;ifexp : 'if' expression 'then' expression 'else' expression ;varexp : $ID ;letexp : 'let' $ID '=' expression 'in' expression ;'''print(generate(grammar))
Package: arcee-align
Arcee:tulip:	The open source toolkit for finetuning and deploying LLMs :tulip:Finetune LLMSfrom arcee.models import LM
from arcee.data import Instuctions

lm = LM("falcon30b")
instructions = Instructions("./datasets/stripe-api.json")
lm.train(instructions)

lm.predict("Place an order for the LLM-9000 product for 100 USD to the card 3007200039992000")Deploy LLMSAuthenticateimport arcee
arcee.login()Deploy to the Arcee cloudproject = arcee.create_project("stripe-api-operator")
#project = arcee.load_project(...)

#regulated under 7b params for free
#only PEFT uploadable for free

hosted_lm = project.deploy(llm)
hosted_lm.url
hosted_lm.predict("Place an order for the LLM-9000 product for 100 USD to the card 3007200039992000")

#view a streaming web app of the llm
project.demo()LangChain Integrationfrom langchain import Arcee
#goes in llms/arcee.py

prompt_template = "Write a stripe API request for the following: {order}."

llm = Arcee(temperature=0)
llm_chain = LLMChain(
    llm=llm,
    prompt=PromptTemplate.from_template(prompt_template)
)
llm_chain("Place an order for the LLM-9000 product for 100 USD to the card 3007200039992000")
Package: arcesetc
Exposure time calculator for APO/ARCESCalculate S/N and exposure times for
stellar spectroscopy with theARC Echelle Spectrograph (ARCES)on theARC 3.5 m TelescopeatApache Point Observatory.The ARC Echelle Spectroscopic (ARCES) Exposure Time Calculator, orarcesetc,
is a simple exposure time calculator for the ARCES instrument on the
Astrophysical Research Consortium (ARC) 3.5 m Telescope at Apache Point
Observatory for stellar spectroscopy. Users can supplyarcesetcfunctions
with the spectral type of their target star, the V band magnitude, and either:
the desired exposure time in order to determine the counts and signal-to-noise
ratio as a function of wavelength; or the desired signal-to-noise ratio at a
given wavelength to determine the required exposure time.We estimate the count rates for stars as a function of wavelength by fitting
15th-order polynomials to each spectral order of real observations of a star of
each spectral type. These polynomial coefficients and some wavelength metadata
are stored in an HDF5 archive for compactness and easy of reconstruction. Then
upon callingarcesetc, the archive is opened and the spectral order closest
to the wavelength of interest is reconstructed from the polynomial
coefficients, for a star of the closest available spectral type to the one
requested.InstallationYou can installarcesetcwith pip:pip install arcesetcYou can installarcesetcfrom the source code by doing the following:git clone https://github.com/bmorris3/arcesetc.git
cd arcesetc
pip install .arcesetcrequires python >=3.5, numpy, astropy, h5py, and matplotlib.For more information,read the docs.LicenseThis project is Copyright (c) Brett Morris & Trevor Dorn-Wallenstein and licensed under
the terms of the MIT license. This package is based upon
theAstropy package templatewhich is licensed under the BSD 3-clause licence. See the licenses folder for
more information.
Package: arceus
ArceusThe best (probably) free Minecraft name sniper.IMPORTANT - LICENSE TERMSThe arceus project is licensed under GNU GPLv3 or later. This means you CANNOT redistribute modifications to the project except under GNU GLPv3. In other words, any modifications you make must also be open source.FeaturesTransfer and blocking sniperBenchmark to test settingsLow latency by opening the TCP connections before sending requestsHigh requests/second by bypassing HTTP overheadDiscussion and SupportJoin theDiscord Serverfor support, feature suggestions, usage help, and general discussion.InstallationYou can read the installation instructionshere.UsageFirst, you'll need to create aconfig.json:IMPORTANT: If you don't know JSON syntax, please readthis tutorialand make sure your JSON is validbeforeasking for help.{
  "accounts": [
    {
      "email": <ACCOUNT_EMAIL>,
      "password": <ACCOUNT_PASSWD>
    }
    ...
  ]
  "offset": <REQUEST_OFFSET>,
  "attempts": <REQUEST_ATTEMPTS>
}CLI Options:NameShortDescription--target-tName to snipe--config-cConfig file to use--attempts-aRequest attempts--later-lDays later to snipeTransfer Snipe:arceustransferBlock Snipe:arceusblockBenchmarkingCLI Options:NameShortDescription--host-hBenchmark API to use--offset-oRequest timing offset--attempts-aRequest attempts--delay-dSeconds before the benchmarkBenchmarking doesn't readconfig.json, if you want to specify an offset, use the--offsetoptionarceusbenchmarkContributingFeel free to fork the project and make a pull request on GitHub.