Saravanan666/pypi-org huggingface dataset:
Package: cybertnetica
# <h1> cybertnetica<sub><sub><sup>is a auotomata to package,publish and validate my simple project(s) .</sup></sub></sub></h1><br>## Prefaceimage that you are facing a scenario:frequently build docker image(s) ,more than 2 times a day.20 vm(s) to deploy.Note:* Same procedure will be executed in each one of the vm .*## cybertneticacybertnetica is an AUTOMATA.  cybertnetica will…Greatly reduce the time for packaging and publishingRetrieve a certain result to validate the deploymentcybertnetica will _not_…Take the place of routine monitoringAware of hardware malfunction### InstallationFirst of all we have to install it:`Shell pip install cybertnetica `I recommend using the parameter-ihttps://pypi.douban.com/simplevia the the installation above in person.
Package: cyberuskey
How to installpipinstallcyberuskeyor you can clone repository and use CyberusKey class directly in your project
#Usage Examplefromcyberuskey.cyberuskeyimportCyberusKeyfromcyberuskey.exceptionsimportAuthenticateExceptionclassAuthenticationHandler:defget(self):cyberus=CyberusKey('CLIENT_ID','CLIENT_SECRET','REDIRECT_URI')arguments=self.request.argumentstry:id_token_data,access_token=cyberus.authorize(arguments)exceptAuthenticateExceptionasexc:self.write(exc.error_description)self.set_status(401)raiseexc...LinksCyberusKey docs:http://loginwithoutpasswords.com/docs/CyberusKey widget:https://github.com/CyberusLabs/cyberuskey-widgetLicenseMIT© Cyberus Labs sp. z o.o.
Package: cyberutils
cyberutilsPyPI Package·GitHub Repositoryusageexecute bash queryget bash query result and errorfromcyberutils.bashimportexecute_bashexecute_bash(bash_command='cyber status --node https://rpc.bostrom.cybernode.ai:443')get json from bash query resultfromcyberutils.bashimportget_json_from_bash_queryget_json_from_bash_query(bash_command='cyber status --node https://rpc.bostrom.cybernode.ai:443')execute a cosmwasm contractimportrequestsfromcyber_sdk.client.lcdimportLCDClientfromcyber_sdk.key.mnemonicimportMnemonicKeyfromcyberutils.contractimportexecute_contractWALLET_SEED='rack canyon puzzle grow afford faint heavy kick furnace economy change loop debate tip acquire render rib truth bachelor monster page range wine measure'CONTRACT_ADDRESS='bostrom1nwm9pjmfgmxgc4euyfps05p9pfde8vd4sm8pavy93eu9xquz27dsgyxtml'# initiate lcd client and walletmk=MnemonicKey(mnemonic=WALLET_SEED)lcd_client=LCDClient(url='https://lcd.bostrom.cybernode.ai/',chain_id='bostrom',prefix='bostrom')wallet=lcd_client.wallet(mk)# an execution message in a contract must match its schemaexecute_msg={"transfer":{"recipient":"bostrom1xszmhkfjs3s00z2nvtn7evqxw3dtus6yr8e4pw","amount":"1000000"}}# load a contract schema for an execute message validationcontract_schema_json=\requests.get(url='https://raw.githubusercontent.com/Snedashkovsky/cw-plus/main/contracts/cw20-base/schema/cw20-base.json').json()# execution of a contractexecute_contract(execute_msgs=[execute_msg],wallet=wallet,contract_address=CONTRACT_ADDRESS,lcd_client=lcd_client,gas=500_000,fee_amount=0,fee_denom='boot',contract_execute_schema=contract_schema_json['execute'],memo='the first transfer')execute a graphql queryimportpandasaspdfromcyberutils.graphqlimportexecute_graphqlres=awaitexecute_graphql(request="""query AllContracts {contracts(order_by: {tx: desc_nulls_last}) {addressadmincode_idcreation_timecreatorfeesgasheightlabeltx}}""",graphql_url='https://index.bostrom.cybernode.ai/v1/graphql')pd.DataFrame(res['contracts'])a query with variable valuesimportpandasaspdfromcyberutils.graphqlimportexecute_graphqlres=awaitexecute_graphql(request="""query ContractsCodeID($code_id: bigint) {contracts(order_by: {tx: desc_nulls_last}, where: {code_id: {_eq: $code_id}}) {addressadmincreation_timecreatorfeesgasheightlabeltxcode_id}}""",variable_values={"code_id":"3"},graphql_url='https://index.bostrom.cybernode.ai/v1/graphql')pd.DataFrame(res['contracts'])get messages with a given address and typeimportpandasaspdfromcyberutils.graphqlimportget_messages_by_address_and_typeres=awaitget_messages_by_address_and_type(address='bostrom1xszmhkfjs3s00z2nvtn7evqxw3dtus6yr8e4pw',msg_type='cosmos.bank.v1beta1.MsgSend',graphql_url='https://index.bostrom.cybernode.ai/v1/graphql')pd.DataFrame(res)
Package: cybervec
cyber-vector-notationThis is a"NOTATION"for those who use computers.Commentary by author:📖電脳記数法 (Cyber Number Notation)Two prior knowledge📖dictionary-ordinal-number-notation📖beads-vector-notationInstall# pip install dicordnum# pip install beadsvecpipinstallcybervecMethodstrail_zero() operationWith trailing zero👇 Append,0cn = CyberVec.trail_zero((1, 2))
print(f"{cn.elements}")                # (1, 2, 0)

cn = CyberVec.trail_zero(3)
print(f"{cn.elements}")                # (3, 0)👇 Samecn = CyberVec((1, 2, 0))
print(f"{cn.elements}")                # (1, 2, 0)

cn = CyberVec((3, 0))
print(f"{cn.elements}")                # (3, 0)Let's give an exampleConsIt's eccentric👇 Pre-zero cannot be used# Normal
0001

# Cyber
O1o0👇 Hexadecimal cannot be used# Normal
0xFF

# Cyber
O255o0            # Use decimalProsIt is considered to be used for variable names, class names, method names, file names, folder names, URLs, etc.Use as dictionary ordinal number👇 For Version number# Normal
Version1.0.1

# Cyber
VersionO1o0o1o0   # Default
VersionO1o0o1o0   # PascalCase
versionO1o0o1o0   # lowerCamelCase
version_o1o0o1o0  # snake_case
version-o1o0o1o0  # kebab-case
VERSION_O1O0O1O0  # UPPER_SNAKE_CASE👇 For IPv4# Normal
128.0.0.1

# Cyber
OAA128o0o0o1o0  # Default
Oaa128o0o0o1o0  # PascalCase
oaa128o0o0o1o0  # lowerCamelCase
oaa128o0o0o1o0  # snake_case
oaa128o0o0o1o0  # kebab-case
OAA128O0O0O1O0  # UPPER_SNAKE_CASE👇 Negative number included# Normal
20, 18, -1, -14, 5

# Cyber
OA20oA18o_9o__86o5  # Default
Oa20oa18o_9o__86o5  # PascalCase (Bad)
oa20oa18o_9o__86o5  # lowerCamelCase (Bad)
oa20oa18o_9o__86o5  # snake_case
oa20oa18o_9o__86o5  # kebab-case (Bad)
OA20OA18O_9O__86O5  # UPPER_SNAKE_CASE👇 Folder# Normal
📂 00
└── 📂 01
  └── 📂 99

# Normal Flat by "/"
00/01/99

# Cyber
📂 O0o0          # Not O00o0
└── 📂 O1o0
  └── 📂 OA99o0

// # **TODO** Cyber Flat by "x1x"
// O0o0x1xO1o0x1xOA99o0👇 Chapter# Normal
1. Food
1.1. Fruits
1.1.1. Apple
1.1.2. Banana
1.1.11. Kiwi

# Cyber
O1o0. Food
O1o1o0. Fruits
O1o1o1o0. Apple
O1o1o2o0. Banana
O1o1oA11o0. KiwiNow you have mastered cyber vector notation
Package: cyber-wiz-email-client
cyber-wiz-email-clientcyber-wiz-email-client is a Python library to interact with email.cyber-wiz.com.InstallationUse the package managerpipto install cyber-wiz-email-client.pipinstallcyber-wiz-email-clientUsagefromcyber_wiz_apiimportEmailClient# create a client objectclient=EmailClient()# returns search results that matches search term with domainnameclient.get_domain_search_results(search_term="cyber-wiz.com",limit=10)# returns search results that matched search term with usernameclient.get_user_name_search_results(search_term='cyber',limit=10)# returns search results that matches search term with emailclient.get_generic_search_results(search_term='cyber',limit=10)ContributingPull requests are welcome. For major changes, please contact us:info@cyber-wiz.com.
Package: cybex
CybexAutonomously generate high-quality unit tests for entire repositories, just plug in and play the repo link and enjoy high quality tests to elevate your projectInstallationpip install cybexUsagefromcybeximportTestGenerator# Example usage:test_generator=TestGenerator(repo_url="https://github.com/kyegomez/exa",api_key="")test_generator.download()test_generator.generate_tests()LicenseMIT
Package: cyborg-tempest-plugin
This is a cyborg tempest plugin package. Tests can be run as a tempest plugin
against any cyborg-enabled OpenStack cloud.Please fill here a long description which must be at least 3 lines wrapped on
80 cols, so that distribution package maintainers can use it in their packages.
Note that this is a hard requirement.Free software: Apache licenseDocumentation:https://docs.openstack.org/cyborg-tempest-plugin/latestSource:https://opendev.org/openstack/cyborg-tempest-plugin/Bugs:https://storyboard.openstack.org/#!/project/968FeaturesTODO
Package: cybotrade
CybotradeThis is the Client SDK for building automated trading strategies onCybotrade. This library provides the core runtime, integration with Exchanges API, historical and live market data collector and wrap them into a simple, easy-to-use and easy-to-learn Python SDK as a foundation users' strategies.DocumentationThe documentation for the Cybotrade SDK can be foundhere.InstallationpipinstallcybotradeUsageThe following example shows how to create a simple strategy that buys 0.01 BTC when the price goes up and sells 0.01 BTC when the price goes down.For a more advanced usage, please refer to thedocumentation.fromcybotrade.strategyimportStrategyasBaseStrategyfromcybotrade.modelsimport(OrderParams,OrderSide,RuntimeMode,RuntimeConfig,Exchange,)fromdatetimeimportdatetime,timedelta,timezoneimportasyncioclassStrategy(BaseStrategy):asyncdefon_candle_closed(self,strategy,topic,symbol,data_map):# Get the currently closed candlescandles=data_map[topic]ifcandles[-1].close>candles[-2].close:# Buy 0.01 BTCawaitstrategy.open(side=OrderSide.Buy,take_profit=None,stop_loss=None,quantity=0.01,limit=None)else:# Sell 0.01 BTCawaitstrategy.open(side=OrderSide.Sell,take_profit=None,stop_loss=None,quantity=0.01,limit=None)asyncdefmain():runtime=awaitRuntime.connect(RuntimeConfig(mode=RuntimeMode.Backtest,exchange=Exchange.BybitLinear,datasource_topics=[],candle_topics=["candles-1h-BTC/USDT-bybit"],hedge_mode=False,start_time=datetime.now(timezone.utc)-timedelta(minutes=10000),end_time=datetime.now(timezone.utc),api_key="YOUR_CYBOTRADE_API_KEY",api_secret="YOUR_CYBOTRAD_API_SECRET",data_count=100),Strategy(),)awaitruntime.start()asyncio.run(main())
Package: cybotrade-indicators
Cybotrade IndicatorsThis library provides a wide variety of technical analysis indicators, it was orignally forked fromtulipindicatorsand we added additional indicators on top of the original ones.InstallationInstalling this library is simple, just dopipinstallcybotrade-indicatorsExamplefromcybotrade_indicatorsimportabs,rsi_divergenceimportnumpyasnpprint(rsi_divergence(high=np.array([23509.68,23459.89,23647.68,23223.32,23472.86,23354.36,23402,24245,23933.25,24226]),low=np.array([22850,22654.37,22681.22,22400,22586.95,22909.52,22844.62,23154.25,22865,22664.69]),close=np.array([23268.01,22987.79,22818.37,22622.98,23312.42,22954.21,23174.39,23810,23149.95,23954.05]),left_bar=4,right_bar=2,rsi_length=6))The original documentation fortulipindicatorscan be found athttps://tulipindicators.org.Below shows the list of additional indicators we have added:chaikin_vol"Chaikin Volatility"stoch_rsi"Stoch Rsi"supertrend"Supertrend"wavetrend"Wavetrend"andean_osc"Andean Osc"braid_filter"Braid Filter"boom_pro"Boom Pro"chandelier_exit"Chandelier Exit"cm_ema_trendbars"CM EMA TRENDBARS"di_dx"DI-DX"half_trend"Half Trend"heatmap_vol"Heatmap Volume"hull_suite"Hull Suite"macd_fastline_divergence"MACD Fastline Divergence"macd_hist_divergence"MACD Hist Divergence"mobo_band"Mobo Band"qqe_mod"QQE Mod"rsi_divergence"Relative Strength Index Divergence"rvi"Relative Volatility Index"rvi_divergence"Relative Volatility Index Divergence"ssl"SSL"stc"STC"stoch_divergence"Stochastic Divergence"sup_and_res"Support and Resistance"ut_bot"UT Bot Alert"volatility_oscillator"Volatility Oscillator"vu_man_chu_swing"VU Man Chu Swing"waddah"Waddah"psar"PSAR"dx"Directional Movement Index"adx"Average Directional Movement Index"dema"Double Exponential Moving Average"ema"Exponential Moving Average"hma"Hull Moving Average"sma"Simple Moving Average"tema"Triple Exponential Moving Average"trima"Triangular Moving Average"vwma"Volume Weighted Moving Average"wma"Weighted Moving Average"linreg"Linear Regression"bbands"Bollinger Bands"cci"Commodity Channel Index"stoch"Stochastic Oscillator"mfi"Money Flow Index"macd"Moving Average Convergence/Divergence"rsi"Relative Strength Index"natr"Normalized Average True Range"atr"Average True Range"insidebar"Inside Bar"price"Compare Price"
Package: cybox
A Python library for parsing, manipulating, and generatingCyber Observable eXpression (CybOX™)v2.1.0 content.Source:https://github.com/CybOXProject/python-cyboxDocumentation:https://cybox.readthedocs.io/Information:https://cyboxproject.github.io/Download:https://pypi.python.org/pypi/cybox/OverviewA primary goal of the python-cybox library is to remain faithful to both the
CybOX standard and to customary Python practices. There are places where these
will conflict, and the goal is to make the library intuitive both to those
familiar with the XML schemas (but less familiar with Python) and also to
experienced Python developers who want to add CybOX support to their programs.There are currently two levels of APIs for dealing with CybOX content:A low-level API is provided by auto-generated XML Schema - Python class
bindings. These bindings were generated usinggenerate_ds. With these, any CybOX
content can be parsed from or written to XML, but requires a bit more
knowledge of the actual CybOX schemas. These “binding classes” are all
located in thecybox.bindingspackage.A higher-level API consisting of manually designed Python classes. These
“native classes” are intended to behave more like Python programmers would
expect. As they are designed manually, they currently do not support the
entire CybOX standard, but rather those object types we expect are used most
frequently. These “native classes” also support exporting their content as
Python dictionaries and lists, which can easily be converted to JSON.
Importing from JSON is also supported.VersioningReleases of the python-cybox library will be given version numbers of the formmajor.minor.update.revision, wheremajor,minor, andupdatecorrespond to the CybOX version being supported. Therevisionnumber is
used to indicate new versions of the python-cybox library itself.InstallationThecyboxpackage depends on the following Python libraries:lxmlpython-dateutilsetuptools(only if installing using setup.py)For Windows installers of the above libraries, we recommend looking here:http://www.lfd.uci.edu/~gohlke/pythonlibs/.To buildlxmlon Ubuntu, you will need the following packages from the
Ubuntu package repository:python-devlibxml2-devlibxslt1-devzlib1g-devFor more information about installing lxml, seehttp://lxml.de/installation.html.LayoutThe structure of the python-cybox repository is as follows:cybox/: the root packageexamples/: example scripts that leverage the python-cybox librarycybox/utils/: utility modules that are leveraged internally by the python-cybox librarycybox/test/: unit testscybox/bindings/: generateDS created xml-to-python bindings (leveraged in parsing and output of CybOX XML content)cybox/core/: APIs for core CybOX constructs (e.g., Observables)cybox/common/: APIs for common CybOX constructs (e.g., Measure Source)cybox/object/: APIs for CybOX objects (e.g., File Object, Address Object)Please refer to the example scripts for examples of how to use the python-cybox library.FeedbackBug reports and feature requests are welcome and encouraged. Pull requests are
especially appreciated. Feel free to use the issue tracker on GitHub or send an
email directly tocybox@mitre.org.
Package: cybox211
A Python library for parsing, manipulating, and generating CybOX content.Source:https://github.com/CybOXProject/python-cyboxDocumentation:http://cybox.readthedocs.orgInformation:https://cyboxproject.github.io/Download:https://pypi.python.org/pypi/cybox/OverviewA primary goal of the python-cybox library is to remain faithful to both the
CybOX standard and to customary Python practices. There are places where these
will conflict, and the goal is to make the library intuitive both to those
familiar with the XML schemas (but less familiar with Python) and also to
experienced Python developers who want to add CybOX support to their programs.There are currently two levels of APIs for dealing with CybOX content:A low-level API is provided by auto-generated XML Schema - Python class
bindings. These bindings were generated usinggenerate_ds. With these, any CybOX
content can be parsed from or written to XML, but requires a bit more
knowledge of the actual CybOX schemas. These “binding classes” are all
located in thecybox.bindingspackage.A higher-level API consisting of manually designed Python classes. These
“native classes” are intended to behave more like Python programmers would
expect. As they are designed manually, they currently do not support the
entire CybOX standard, but rather those object types we expect are used most
frequently. These “native classes” also support exporting their content as
Python dictionaries and lists, which can easily be converted to JSON.
Importing from JSON is also supported.VersioningReleases of the python-cybox library will be given version numbers of the formmajor.minor.update.revision, wheremajor,minor, andupdatecorrespond to the CybOX version being supported. Therevisionnumber is
used to indicate new versions of the python-cybox library itself.InstallationThecyboxpackage depends on the following Python libraries:lxmlpython-dateutilsetuptools(only if installing using setup.py)For Windows installers of the above libraries, we recommend looking here:http://www.lfd.uci.edu/~gohlke/pythonlibs/.To buildlxmlon Ubuntu, you will need the following packages from the
Ubuntu package repository:python-devlibxml2-devlibxslt1-devzlib1g-devFor more information about installing lxml, seehttp://lxml.de/installation.html.LayoutThe structure of the python-cybox repository is as follows:cybox/: the root packageexamples/: example scripts that leverage the python-cybox librarycybox/utils/: utility modules that are leveraged internally by the python-cybox librarycybox/test/: unit testscybox/bindings/: generateDS created xml-to-python bindings (leveraged in parsing and output of CybOX XML content)cybox/core/: APIs for core CybOX constructs (e.g., Observables)cybox/common/: APIs for common CybOX constructs (e.g., Measure Source)cybox/object/: APIs for CybOX objects (e.g., File Object, Address Object)Please refer to the example scripts for examples of how to use the python-cybox library.FeedbackBug reports and feature requests are welcome and encouraged. Pull requests are
especially appreciated. Feel free to use the issue tracker on GitHub or send an
email directly tocybox@mitre.org.
Package: cybro.usergroup.shift
An addon which can change multiple user’s to one groupFeaturesFrom settings, multiple user’s user group can be changed.InstallationInstall cybro.usergroup.shift by adding it to your buildout:[buildout]

...

eggs =
    cybro.usergroup.shiftand then runningbin/buildoutAuthorsMidhlaj.nkLicenseThe project is licensed under the GPLv2.Contributorsmidhlaj-nk,midhlaj.nk@gmail.comChangelog1.0.0Initial release.
[midhlaj-nk]
Package: cybr-pypsm
pyPSMCyberArk Privileged Session Manager RDPFile Generator for Python 3UsageSupported Parametersbase_uri(required)username(required)password(required)address(required)authtype(cyberark, ldap, windows, radius)otpmode(required ifauthtype='radius'- push,challenge, append - default: push)otp(required ifauthtype='radius'andotpmode=challengeorotpmode=append)platformid(default: PSMSecureConnect)verify(default:True)Generate RDPFile for PSM-RDP ConnectionsfrompypsmimportRDP# Configure the connection detailspsmconnect=RDP(base_uri='https://cyberark.joegarcia.dev/',username='user',password='password123',address='10.0.4.48',authtype='radius',otpmode='push')# Retrieve RDPFile data from CyberArk and create `connect.rdp` locallypsmconnect.connect()Secure Handling of Username + PasswordIt is recommended to use environment variables within the script that can be populated at runtime.  These should not be placed into script variables and should be used just-in-time (JiT).LicenseMIT
Package: cybsi-sdk
Cybsi SDKБиблиотека для взаимодействия с API Threat Analyzer. Позволяет:Настраивать продуктРасширять возможности продукта пользовательскими источниками данныхВыгружать и загружать Threat Intelligence в различных форматахБиблиотека имеет как синхронный, так и асинхронный интерфейс.
Package: cybuffer
cybufferA Python 2/3 compatible buffer in CythonFree software: BSD licenseDocumentation:https://cybuffer.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thedask-image/dask-image-cookiecutterproject template.History0.1.0 (2018-11-13)First release on PyPI.
Package: cycahvore
# CycahvoreCython wrapper for CAHVORE camera modules from VICAR.### IntroductionCycahvore (sigh-cah-vor) is a cython wrapper for the C ‘cahvor’ camera models from JPL’s VICAR software.It currently wraps a subset of the functions available in the C library for CAHV, CAHVOR, CAHVORE camera models,
assuming contiguous numpy arrays as inputs. Some functions are also provided with vectorized wrappers to efficiently loop over many coordinates in N-D numpy arrays.
Package: cycarla-backend
cycarla-backendis a Python Flask server that serves as the backend toCYCARLAThe three components of Cycarla are:CARLA- An open-source simulator for autonomous driving research.cycarla_backend- This Python Flask server which links the frontend to CARLA.cycarla_frontend- A Javascript (Next.js) front-end which presents a web-based interface from your browser.InstallationSupported platforms: Windows 10, Ubuntu 22.04. Other versions can work if you install Python 3.10 and pipx.Windows 10-specific PrerequisitesIf you are on Ubuntu 22.04, skip ahead to the next section. Windows needs a couple of things to be set up beforehand.1. Install Python 3.10Scroll to the bottom and download the 'Windows Installer (64-bit)'.At the installer, make sure to enable the bottom option "Add python.exe to PATH"2. Install ScoopInstall usingpipxcycarla-backendis a CLI package that is developed withpoetryand published onpypi.We'll usepipxto run it in an isolated python environment.InstallpipxFollow relevant instructions for your platformInstall cycarla-backendusingpipxpipx install cycarla-backendNote the dash (minus) sign.Run AppIn your terminal (Ubuntu) or Powershell (Windows):cycarla_backendNote the underscore.On Windows, Allow firewall permissions when prompted.r Cycoutput including:* Running on http://127.0.0.1:9000This app will receive web requests from the CYCARLA Frontend which should run at localhost port 3000, and communicate with the Python API of a local CARLA simulator whose default port is 2000.You should start the CARLA and frontend applications next, if they haven't been started already.SeeCYCARLA top-level project READMEfor more informationCompatibilityCurrently, Windows 10 and Ubuntu 22.04 are the officially supported OSes for the CYCARLA project. Mac is not supported because CARLA can't run on it.It is possible to run CARLA and this backend on two different computers, but it is very slow (~5 FPS).
Package: cyc-gbm
cyc-gbmA package for the Cyclical Gradient Boosting Machine algorithm. For the (pre-print) paper describing the algorithm, seehere.InstallationYou can install the package using pip:pipinstallcyc-gbmAlternatively, you can install the package from source.
This will also include a pipeline for reproducing the results in the paper. Follow these steps:Clone this repository to your local machine:gitclonehttps://github.com/henningzakrisson/cyc-gbm.gitCreate a virtual environment in the root directory of the repository:python3-mvenvvenvActivate the virtual environment:sourcevenv/bin/activateInstall the required dependencies:pipinstall-rrequirements.txtUsage exampleFitting the mean and (log) sigma parameters of a normal distribution to a simulated dataset:importnumpyasnpfromcyc_gbmimportCyclicalGradientBoosterfromsklearn.model_selectionimporttrain_test_split# Simulate dataX=np.random.normal(size=(1000,2))mu=X[:,0]+10*(X[:,1]>0)sigma=np.exp(3-2*(X[:,0]>0))y=np.random.normal(mu,sigma)# Split dataX_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2)# Fit modelmodel=CyclicalGradientBooster(distribution='normal',learning_rate=0.1,n_estimators=[26,34],min_samples_split=2,min_samples_leaf=20,max_depth=2,)model.fit(X_train,y_train)# Evaluateloss=model.dist.loss(y=y_test,z=model.predict(X_test)).sum()print(f'negative log likelihood:{loss}')ContactIf you have any questions, feel free to contact mehere.