Feature Store

# Get the latest lib from Rapidcanvas
# !pip install --extra-index-url=https://us-central1-python.pkg.dev/rapidcanvas-361003/pypi/simple utils==0.12dev0

from utils.rc.client.requests import Requests
from utils.rc.client.auth import AuthClient

from utils.rc.dtos.project import Project
from utils.rc.dtos.dataset import Dataset
from utils.rc.dtos.recipe import Recipe
from utils.rc.dtos.transform import Transform
from utils.rc.dtos.template import Template
from utils.rc.dtos.template import TemplateTransform
from utils.rc.dtos.template import TemplateInput
from utils.rc.dtos.artifact import Artifact
from utils.rc.dtos.dataSource import DataSource
from utils.rc.dtos.dataSource import DataSourceType
from utils.rc.dtos.dataSource import RedisStorageConfig

from utils.rc.dtos.template_v2 import TemplateV2, TemplateTransformV2

import pandas as pd
import logging
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)

online_data_store = DataSource.createDataSource(
    "online-redis",
    DataSourceType.REDIS_STORAGE,
    {RedisStorageConfig.HOST: "127.0.0.1", RedisStorageConfig.PORT: "6379"}
)

project = Project.create(
    name="Example Feature Store",
    description="Testing feature store",
    createEmpty=True
)

project.id

titanic = project.addDataset(
    dataset_name="titanic",
    dataset_description="titanic golden",
    dataset_file_path="data/titanic.csv"
)

titanic.getData(5)

recipe = project.addRecipe([titanic], name="feature_store_sync")

template = TemplateV2(
    name="FeatureStoreSync", description="FeatureStoreSync", project_id=project.id, source="CUSTOM", status="ACTIVE", tags=["Number", "datatype-long"]
)
template_transform = TemplateTransformV2(type = "python", params=dict(notebookName="FeatureStoreSync.ipynb"))
template.base_transforms = [template_transform]
template.publish("transforms/FeatureStoreSync.ipynb")

transform = Transform()
transform.templateId = template.id
transform.name = "transform_1"
transform.variables = {
    "datasetName": titanic.name,
    "columns": "Name,Sex,Age",
    "featureEntityName": "Passenger",
    "featureEntityColumn": "PassengerId",
    "dataSourceName": online_data_store.name
}

recipe.prepareForLocal(transform, "feature_store")

recipe.addTransform(transform)

recipe.run()