Hopsworks

https://docs.hopsworks.ai/latest/
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Hopsworks is a modular MLOps platform with a Python-centric feature store, model registry, model...
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### Example: Create and run an application

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/app_api

Demonstrates the workflow for logging into a project, creating an app, and starting it.

```python
import hopsworks

project = hopsworks.login()
apps = project.get_app_api()

app = apps.create_app(
    "my_dashboard",
    app_path="Resources/app.py",
)

app.run()
print(app.app_url)
```

--------------------------------

### Deploying and Iterating an Agent

Source: https://docs.hopsworks.ai/latest/python-api/hsml/model_serving

Example showing how to initialize, start, and update an agent deployment.

```python
ms = project.get_model_serving()

agent = ms.deploy_agent(entry="my_agent.py")
agent.start() # or agent.restart()

# iterate: edit code locally, push, then roll the running agent onto it
agent = ms.deploy_agent(entry="my_agent.py")
agent.restart()
```

--------------------------------

### start(await_running: int | None = 600)

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment

Starts the deployment. The method optionally waits for the deployment to reach a running state.

```APIDOC
## start(await_running: int | None = 600)

### Description
Starts the deployment. If the deployment has not started within the specified timespan, the call returns while the deployment continues in the background.

### Parameters
- **await_running** (int | None) - Optional - Awaiting time (seconds) for the deployment to start. Default is 600.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - Raised if the backend encounters an issue.
```

--------------------------------

### Install requirements from file

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/environment

Installs libraries defined in a requirements.txt file uploaded to Hopsworks.

```python
install_requirements(
    path: str, await_installation: bool | None = True
)
```

```python
import hopsworks

project = hopsworks.login()

# Upload to Hopsworks
ds_api = project.get_dataset_api()
requirements_path = ds_api.upload("requirements.txt", "Resources")

# Install
env_api = project.get_environment_api()
env = env_api.get_environment("my_custom_environment")

env.install_requirements(requirements_path)
```

--------------------------------

### Install Hopsworks Python Client

Source: https://docs.hopsworks.ai/latest/user_guides/client_installation

Standard installation command for the base Hopsworks Python library.

```bash
pip install hopsworks[python]
```

--------------------------------

### Register Model with Input Example

Source: https://docs.hopsworks.ai/latest/user_guides/mlops/registry/input_example

Attaches the input example to the model during creation and saves the model to the registry.

```python
model = mr.tensorflow.create_model(name="mnist", input_example=input_example)
model.save("./model")
```

--------------------------------

### Run an App

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/app

Starts the application and waits for it to be serving if await_serving is True.

```python
run(await_serving: bool = True) -> App
```

```python
apps = project.get_app_api()
app = apps.get_app("my_dashboard")
app.run()
print(app.app_url)
```

--------------------------------

### Start a deployment

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment

Initiates the deployment process with an optional timeout for waiting until it is running.

```python
start(await_running: int | None = 600)
```

--------------------------------

### Install a Python wheel

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/environment

Installs a Python library from a wheel file uploaded to Hopsworks.

```python
install_wheel(
    path: str, await_installation: bool | None = True
)
```

```python
import hopsworks

project = hopsworks.login()

# Upload to Hopsworks
ds_api = project.get_dataset_api()
whl_path = ds_api.upload("matplotlib-3.1.3-cp38-cp38-manylinux1_x86_64.whl", "Resources")

# Install
env_api = project.get_environment_api()
env = env_api.get_environment("my_custom_environment")

env.install_wheel(whl_path)
```

--------------------------------

### Install Hopsworks Python Client with Profiles

Source: https://docs.hopsworks.ai/latest/user_guides/client_installation

Install the library with additional dependencies for Great Expectations and Polars support.

```bash
pip install hopsworks[python,great-expectations,polars]
```

--------------------------------

### Install AWS Load Balancer Controller

Source: https://docs.hopsworks.ai/latest/setup_installation/aws/getting_started

Helm commands to add the EKS chart repository and install the load balancer controller.

```bash
helm repo add eks https://aws.github.io/eks-charts
helm repo update eks
helm install aws-load-balancer-controller eks/aws-load-balancer-controller -n kube-system --set clusterName=CLUSTER_NAME
```

--------------------------------

### Example usage of secondary_indexes

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/online_config

Demonstrates how to initialize OnlineConfig with specific secondary indexes.

```python
OnlineConfig(secondary_indexes=[["user_id"], ["country", "city"]])
```

--------------------------------

### install_wheel(path, await_installation)

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/environment

Installs a Python library packaged in a wheel file.

```APIDOC
## install_wheel(path: str, await_installation: bool | None = True)

### Description
Install a python library packaged in a wheel file.

### Parameters
- **path** (str) - The path in Hopsworks where the wheel file is located.
- **await_installation** (bool | None) - If `True` the method returns only when the installation finishes. Default is `True`.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Install Hopsworks Python Library

Source: https://docs.hopsworks.ai/latest/user_guides/integrations/mlstudio_notebooks

Install the library using pip with the python profile to ensure all dependencies are included.

```bash
pip install hopsworks[python]~=[HOPSWORKS_VERSION]

```

--------------------------------

### Deploy Trained Model

Source: https://docs.hopsworks.ai/latest/user_guides/mlops/serving/deployment

Creates a deployment for the model and starts the service.

```python
my_deployment = my_model.deploy()

# optionally, start your model deployment
my_deployment.start()
```

--------------------------------

### install_requirements(path, await_installation)

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/environment

Installs libraries specified in a requirements.txt file located in Hopsworks.

```APIDOC
## install_requirements(path: str, await_installation: bool | None = True)

### Description
Install libraries specified in a `requirements.txt` file.

### Parameters
- **path** (str) - The path in Hopsworks where the `requirements.txt` file is located.
- **await_installation** (bool | None) - If `True` the method returns only when the installation is finished. Default is `True`.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Init Container Database Wait

Source: https://docs.hopsworks.ai/latest/setup_installation/common/helm_chart_values

Waits for the database to be available before starting the container.

```bash
/bin/sh","-c","dockerize -wait \"tcp://$DB_HOST:$DB_PORT\" -timeout 120s
```

--------------------------------

### Install Hopsworks Feature Store connector via script action

Source: https://docs.hopsworks.ai/latest/user_guides/integrations/hdinsight

This bash script installs the necessary Python library and client dependencies on HDInsight nodes. Ensure placeholders for instance, project, version, API key, and conda environment are replaced before execution.

```bash
set -e

HOST="MY_INSTANCE.cloud.hopsworks.ai" # DNS of your Feature Store instance
PROJECT="MY_PROJECT"                  # Port to reach your Hopsworks instance, defaults to 443
HOPSWORKS_VERSION="MY_VERSION"        # The major version of Hopsworks library needs to match the major version of Hopsworks
API_KEY="MY_API_KEY"                  # The API key to authenticate with Hopsworks
CONDA_ENV="MY_CONDA_ENV"              # py35 is the default for HDI 3.6

apt-get --assume-yes install python3-dev
apt-get --assume-yes install jq

/usr/bin/anaconda/envs/$CONDA_ENV/bin/pip install hopsworks==$HOPSWORKS_VERSION

PROJECT_ID=$(curl -H "Authorization: ApiKey ${API_KEY}" https://$HOST/hopsworks-api/api/project/getProjectInfo/$PROJECT | jq -r .projectId)

mkdir -p /usr/lib/hopsworks
chown root:hadoop /usr/lib/hopsworks
cd /usr/lib/hopsworks

curl -o client.tar.gz -H "Authorization: ApiKey ${API_KEY}" https://$HOST/hopsworks-api/api/project/$PROJECT_ID/client

tar -xvf client.tar.gz
tar -xzf client/apache-hive-*-bin.tar.gz
mv apache-hive-*-bin apache-hive-bin
rm client.tar.gz
rm client/apache-hive-*-bin.tar.gz

curl -H "Authorization: ApiKey ${API_KEY}" https://$HOST/hopsworks-api/api/project/$PROJECT_ID/credentials | jq -r .kStore | base64 -d > keyStore.jks

curl -H "Authorization: ApiKey ${API_KEY}" https://$HOST/hopsworks-api/api/project/$PROJECT_ID/credentials | jq -r .tStore | base64 -d > trustStore.jks

echo -n $(curl -H "Authorization: ApiKey ${API_KEY}" https://$HOST/hopsworks-api/api/project/$PROJECT_ID/credentials | jq -r .password) > material_passwd

chown -R root:hadoop /usr/lib/hopsworks
```

--------------------------------

### Trigger an Alert Example

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/alerts_api

Demonstrates how to initialize the alerts API and trigger a new alert.

```python
import hopsworks

project = hopsworks.login()

alerts_api = project.get_alerts_api()

alerts_api.trigger_alert(receiver_name="email", title="Title", summary="Alert summary", description="Alert description", severity="info", status="script_finished", name="my_alert")
```

--------------------------------

### Create and Deploy an Endpoint

Source: https://docs.hopsworks.ai/latest/python-api/hsml/model_serving

Example of initializing a model serving handle, creating an entrypoint, and deploying it.

```python
# login into Hopsworks using hopsworks.login()

# get Hopsworks Model Registry handle
ms = project.get_model_serving()

my_endpoint = ms.create_entrypoint(name="feature_server", entrypoint_file="feature_server.py")

my_deployment = my_endpoint.deploy()
```

--------------------------------

### Create a Training Dataset

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Example showing how to initialize a feature view and trigger the creation of a training dataset.

```python
# get feature store instance
fs = ...

# get feature view instance
feature_view = fs.get_feature_view(...)

# create a training dataset
version, job = feature_view.create_training_data(
    description='Description of a dataset',
    data_format='csv',
    # async creation in order not to wait till finish of the job
    write_options={"wait_for_job": False}
)
```

--------------------------------

### Create a deployment using Model Serving handle

Source: https://docs.hopsworks.ai/latest/python-api/hsml/model_serving

Example showing the creation of a predictor and deployment using the Model Serving handle.

```python
# login into Hopsworks using hopsworks.login()

# get Hopsworks Model Registry handle
mr = project.get_model_registry()

# retrieve the trained model you want to deploy
my_model = mr.get_model("my_model", version=1)

# get Hopsworks Model Serving handle
ms = project.get_model_serving()

my_predictor = ms.create_predictor(my_model)

my_deployment = ms.create_deployment(my_predictor)
my_deployment.save()
```

--------------------------------

### Install Hopsworks Python Library

Source: https://docs.hopsworks.ai/latest/user_guides/integrations/python

Install the library via pip, ensuring the version matches your Hopsworks deployment.

```bash
pip install hopsworks[python]~=[HOPSWORKS_VERSION]
```

--------------------------------

### run(await_serving: bool = True) -> App

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/app

Starts the application and optionally waits for it to be in a serving state.

```APIDOC
## run(await_serving: bool = True) -> App

### Description
Start the app.

### Parameters
- **await_serving** (bool) - Optional - If True, wait until the app is serving before returning. Default: True

### Returns
- **App** - Self, with updated state.

### Raises
- **hopsworks.client.exceptions.JobExecutionException** - If the app fails to start or the serving timeout is exceeded.
```

--------------------------------

### Initialize Multiple Clients and Fetch Vectors

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_view/feature-vectors

Initializes both SQL and REST clients simultaneously and demonstrates switching between them using force flags.

```python
# initialize both clients and set the default to REST
my_feature_view.init_serving(
    init_rest_client=True,
    init_sql_client=True,
    config_rest_client={
        "api_key": "your_api_key",
    },
    default_client="rest",
)

# this will fetch a feature vector via REST
try:
    my_feature_view.get_feature_vector(
        entry={"pk1": 1, "pk2": 2},
    )
except TimeoutException:
    # if the REST client times out, the SQL client will be used
    my_feature_view.get_feature_vector(
        entry={"pk1": 1, "pk2": 2}, force_sql=True
    )
```

--------------------------------

### Apply Lookback with Only Start Bound

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_view/batch-data

Defines a lookback window using only a start bound, which emits a single lower-bound predicate.

```python
import datetime

df = feature_view.get_batch_data(
    lookback={
        "key": "PARTITION_KEY",
        "start": datetime.date(2026, 5, 10),
    },
)
```

--------------------------------

### Usage Example for get_or_create_feature_group

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_store

Demonstrates how to initialize a feature group with specific configurations like primary keys, online storage settings, and TTL.

```python
# connect to the Feature Store
fs = ...

fg = fs.get_or_create_feature_group(
    name="electricity_prices",
    version=1,
    description="Electricity prices from NORD POOL",
    primary_key=["day", "area"],
    online_enabled=True,
    event_time="timestamp",
    transformation_functions=transformation_functions,
    online_config={'online_comments': ['NDB_TABLE=READ_BACKUP=1']},
    online_disk=True, # Online data will be stored on disk instead of in memory
    ttl=timedelta(days=30),
)
```

--------------------------------

### Initialize a feature view for serving

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Example showing how to retrieve a feature view instance and initialize it for feature vector retrieval.

```python
# get feature store instance
fs = ...

# get feature view instance
feature_view = fs.get_feature_view(...)

# initialise feature view to retrieve a feature vector
feature_view.init_serving(training_dataset_version=1)
```

--------------------------------

### Example: Searching for Features

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/search_api

Demonstrates how to initialize the search API and retrieve feature metadata matching a specific search term.

```python
import hopsworks

project = hopsworks.login()
search_api = project.get_search_api()

# Search for features
features = search_api.features("age")

for feature in features:
    print(f"Feature: {feature.name}")
```

--------------------------------

### Create and run an app using the Python SDK

Source: https://docs.hopsworks.ai/latest/user_guides/projects/apps

Initializes a project connection and deploys a Streamlit application from a local path.

```python
import hopsworks


project = hopsworks.login()
apps = project.get_app_api()

app = apps.create_app(
    "customer_dashboard",
    app_path="Resources/app.py",
)

app.run()
print(app.app_url)
```

--------------------------------

### get_subjects()

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/kafka_api

Get all subjects.

```APIDOC
## get_subjects

### Description
Get all subjects.

### Returns
- **list[str]** - List of registered subjects.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### get

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/secret_api

Retrieves the value of a secret.

```APIDOC
## get(name: str, owner: str | None = None) -> str

### Description
Get the secret's value. If the secret does not exist, it prompts the user to create the secret if the application is running interactively.

### Parameters
- **name** (str) - Required - Name of the secret.
- **owner** (str | None) - Optional - Email of the owner for a secret shared with the current project. Default: None

### Returns
- **str** - The secret value.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### get_topics()

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/kafka_api

Get all Kafka topics.

```APIDOC
## get_topics

### Description
Get all kafka topics.

### Returns
- **list[kafka_topic.KafkaTopic]** - List of KafkaTopic objects.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Create a project

Source: https://docs.hopsworks.ai/latest/user_guides/projects/project/create_project

Creates a new project instance with the specified name.

```python
project = hopsworks.create_project("my_project")
```

--------------------------------

### get_alerts

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Get all alerts for this feature view.

```APIDOC
## get_alerts()

### Description
Get all alerts for this feature view.

### Returns
- **list[FeatureViewAlert] | Alert** - A list of FeatureViewAlert objects or a single Alert object if there is only one alert.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### get_tag

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/training_dataset

Get the tags of a training dataset.

```APIDOC
## get_tag(name)

### Description
Get the tags of a training dataset.

### Parameters
- **name** (str) - Required - Name of the tag to get.

### Returns
- **Any** - tag value

### Errors
- **hopsworks.client.exceptions.RestAPIError** - in case the backend fails to retrieve the tag.
```

--------------------------------

### get_endpoint_url()

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment

Get the base endpoint URL for this deployment.

```APIDOC
## get_endpoint_url()

### Description
Get the base endpoint URL for this deployment. Returns the base URL for external HTTP clients.

### Returns
- **str | None** - Base endpoint URL, or None if the Istio client is unavailable.
```

--------------------------------

### Example: Searching for Feature Views

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/search_api

Demonstrates how to initialize the search API and retrieve feature view metadata matching a specific search term.

```python
import hopsworks

project = hopsworks.login()
search_api = project.get_search_api()

# Search for feature views
fv_metas = search_api.feature_views("customer")

for fv_meta in fv_metas:
    print(f"Feature View: {fv_meta.name} v{fv_meta.version}")

    # Get the same FeatureView object as returned by featurestore.get_feature_view
    fv = fv_meta.get()
```

--------------------------------

### get

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/env_var_api

Convenience method to retrieve the value of an environment variable.

```APIDOC
## get(name)

### Description
Returns the value of an environment variable as a string, or `None` if it does not exist.

### Parameters
- **name** (str) - Required - Variable name.

### Returns
- **str | None** - The value of the variable or `None`.
```

--------------------------------

### get_topic(name: str)

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/kafka_api

Get Kafka topic by name.

```APIDOC
## get_topic

### Description
Get kafka topic by name.

### Parameters
- **name** (str) - Required - Name of the topic.

### Returns
- **kafka_topic.KafkaTopic | None** - The KafkaTopic object or None if not found.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Create and Deploy a Predictor

Source: https://docs.hopsworks.ai/latest/python-api/hsml/model_serving

Example workflow for retrieving a model from the registry and creating a deployment via the model serving handle.

```python
# login into Hopsworks using hopsworks.login()

# get Hopsworks Model Registry handle
mr = project.get_model_registry()

# retrieve the trained model you want to deploy
my_model = mr.get_model("my_model", version=1)

# get Hopsworks Model Serving handle
ms = project.get_model_serving()

my_predictor = ms.create_predictor(my_model)

my_deployment = my_predictor.deploy()
```

--------------------------------

### get_schemas(subject: str)

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/kafka_api

Get all schema versions for the subject.

```APIDOC
## get_schemas

### Description
Get all schema versions for the subject.

### Parameters
- **subject** (str) - Required - Subject name.

### Returns
- **list[kafka_schema.KafkaSchema]** - List of KafkaSchema objects.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Search for training datasets example

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/search_api

Demonstrates how to initialize the search API and retrieve training dataset metadata based on a search term.

```python
import hopsworks

project = hopsworks.login()
search_api = project.get_search_api()

# Search for training datasets
td_metas = search_api.training_datasets("model")

for td_meta in td_metas:
    print(f"Training Dataset: {td_meta.name} v{td_meta.version}")

    # Get the same TrainingDataset object as returned by featurestore.get_training_dataset
    td = td_meta.get()
```

--------------------------------

### Get all jobs

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/job_api

Retrieves a list of all jobs available in the project.

```python
get_jobs() -> list[job.Job]
```

--------------------------------

### Initialize SQL or REST Client

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_view/feature-vectors

Initializes the serving client for a Feature View. The SQL client is default, while the REST client requires an API key.

```python
# initialize the SQL client to fetch feature vectors from the Online Store
my_feature_view.init_serving()

# or use the REST client
my_feature_view.init_serving(
    init_rest_client=True,
    config_rest_client={
        "api_key": "your_api_key",
    },
)
```

--------------------------------

### Connector Options and Client Initialization

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/storage_connector

Retrieves arguments for a pymongo client and demonstrates initialization.

```python
connector_options() -> dict[str, Any]
```

```python
from pymongo import MongoClient

sc = fs.get_storage_connector("mongo_conn")
client = MongoClient(**sc.connector_options())
```

--------------------------------

### Create a Kafka Topic

Source: https://docs.hopsworks.ai/latest/user_guides/projects/kafka/create_topic

Define the topic and schema names, then create the topic with specified partitions and replicas.

```python
TOPIC_NAME = "topic_example"
SCHEMA_NAME = "schema_example"

my_topic = kafka_api.create_topic(
    TOPIC_NAME, SCHEMA_NAME, 1, replicas=1, partitions=1
)
```

--------------------------------

### get_parent_feature_groups()

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Get the parents of this feature view, based on explicit provenance.

```APIDOC
## get_parent_feature_groups()

### Description
Get the parents of this feature view, based on explicit provenance. Parents are feature groups or external feature groups.

### Returns
- **explicit_provenance.Links | None** - Object containing the section of provenance graph requested or None if it does not exist.
```

--------------------------------

### get_parent_feature_groups

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Get the parents of this feature group, based on explicit provenance.

```APIDOC
## get_parent_feature_groups()

### Description
Get the parents of this feature group, based on explicit provenance. Parents are feature groups or external feature groups.

### Returns
- **explicit_provenance.Links | None** - Object containing the section of provenance graph requested or None if it does not exist.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Initialize Kafka API

Source: https://docs.hopsworks.ai/latest/user_guides/projects/kafka/create_schema

Connect to the Hopsworks project and retrieve the Kafka API instance.

```python
import hopsworks


project = hopsworks.login()

kafka_api = project.get_kafka_api()
```

--------------------------------

### Initialize Hopsworks Git API

Source: https://docs.hopsworks.ai/latest/user_guides/projects/git/clone_repo

Establishes a connection to the project and retrieves the Git API instance.

```python
import hopsworks


project = hopsworks.login()

git_api = project.get_git_api()
```

--------------------------------

### get_data_source_provenance

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Get the parents of this feature group, based on explicit provenance.

```APIDOC
## get_data_source_provenance()

### Description
Get the parents of this feature group, based on explicit provenance. Parents are storage connectors.

### Returns
- **explicit_provenance.Links | None** - The data source used to generate this feature group or None if it does not exist.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Example MySQL JDBC Connection URL

Source: https://docs.hopsworks.ai/latest/user_guides/fs/data_source/creation/jdbc

A sample JDBC connection string for a MySQL database.

```text
jdbc:mysql://10.0.2.15:3306/[databaseName]?useSSL=false&allowPublicKeyRetrieval=true
```

--------------------------------

### Get specific embedding feature

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/embedding

Retrieve an EmbeddingFeature object by its name.

```python
get_embedding(name: str) -> EmbeddingFeature
```

--------------------------------

### Create a Feature Group with Transformations

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_store

Example demonstrating how to define transformation functions and create a feature group with specific configurations like TTL and online storage settings.

```python
# connect to the Feature Store
fs = ...

# define the on-demand transformation functions
@udf(int)
def plus_one(value):
    return value + 1

@udf(int)
def plus_two(value):
    return value + 2

# construct list of "transformation functions" on features
transformation_functions = [plus_one("feature1"), plus_two("feature2")]

fg = fs.create_feature_group(
    name='air_quality',
    description='Air Quality characteristics of each day',
    version=1,
    primary_key=['city','date'],
    online_enabled=True,
    event_time='date',
    transformation_functions=transformation_functions,
    online_config={'online_comments': ['NDB_TABLE=READ_BACKUP=1']},
    online_disk=True,  # Online data will be stored on disk instead of in memory
    ttl=timedelta(days=7)  # features will be deleted after 7 days
)
```

--------------------------------

### Get an expectation from the suite

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/expectation_suite

Fetches a specific expectation by its ID from the backend.

```python
# connect to the Feature Store
fs = ...

# get the Feature Group instance
fg = fs.get_or_create_feature_group(...)

expectation_suite = fg.get_expectation_suite()
selected_expectation = expectation_suite.get_expectation(expectation_id=123)
```

--------------------------------

### Access Format Property

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/core/data_source

Get or set the format of the data source.

```python
format: str | None

```

--------------------------------

### Get dataset metadata

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/dataset_api

Retrieves metadata for a dataset. This method is deprecated.

```python
get(path: str) -> dict
```

--------------------------------

### prepare_spark(path: str | None = None)

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/storage_connector

Prepares the Spark environment to interact with the storage connector.

```APIDOC
## prepare_spark(path: str | None = None)

### Description
Configures the Spark session to use this storage connector for data access.

### Parameters
- **path** (str | None) - Optional - The specific path to prepare for reading from cloud storage. Defaults to None.
```

--------------------------------

### get(name: str)

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/tag_schemas_api

Fetches a single tag schema by name.

```APIDOC
## get(name: str)

### Description
Fetch a single tag schema by name.

### Parameters
- **name** (str) - Schema name.

### Returns
- **dict[str, Any]** - The raw schema payload.

### Raises
- **RestAPIError** - If the schema does not exist.
```

--------------------------------

### Superset Initialization Command

Source: https://docs.hopsworks.ai/latest/setup_installation/common/helm_chart_values

Bootstrap script for initializing Superset, including role creation.

```bash
/bin/sh","-c",". {{ .Values.configMountPath }}/superset_bootstrap.sh; . {{ .Values.configMountPath }}/superset_init.sh;\n{{- if .Values.extraRoles }}\n{{- range $role := .Values.extraRoles }}\npython /scripts/create_role.py --role-name {{ $role.name }} --permissions '{{ $role.permissions | toJson | b64enc }}';\n{{- end }}\n{{- end }}\n{{- if and .Values.publicRolePermissions (eq .Values.publicRoleLike .Values._publicRoleDefaultName) }}\npython /scripts/create_role.py --role-name {{ .Values._publicRoleDefaultName }} --permissions '{{ .Values.publicRolePermissions | toJson | b64enc }}';\n{{- end }}\n
```

--------------------------------

### Get All Environment Variables

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/env_var_api

Retrieve a list of all account-level environment variables.

```python
get_env_vars(
    include_value: bool = True,
) -> list[env_var.EnvVar]
```

--------------------------------

### Initialize serving with transformations

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_view/feature-vectors

Initializes serving for a feature view with transformation functions, requiring a training dataset version for statistics.

```python
feature_view.init_serving(training_dataset_version=1)
```

--------------------------------

### init_serving(training_dataset_version, external, options, init_sql_client, init_rest_client, reset_rest_client, config_rest_client, default_client, feature_logger, n_processes, **kwargs)

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Initializes the feature view to retrieve feature vectors from the online and offline feature store.

```APIDOC
## init_serving

### Description
Initialise feature view to retrieve feature vector from online and offline feature store.

### Parameters
- **training_dataset_version** (int | None) - Optional - Transformation statistics are fetched from training dataset and applied to the feature vector. Defaults to 1 for online feature store.
- **external** (bool | None) - Optional - If set to True, the connection to the online feature store is established using the same host as for the host parameter in the hopsworks.login method.
- **options** (dict[str, Any] | None) - Optional - Additional options as key/value pairs for configuring online serving engine.
- **init_sql_client** (bool | None) - Optional - If set to True, this ensure the online store sql client is initialised.
- **init_rest_client** (bool) - Optional - If set to True, this ensure the online store rest client is initialised. Defaults to False.
- **reset_rest_client** (bool) - Optional - If set to True, the rest client will be reset and reinitialised with provided configuration. Defaults to False.
- **config_rest_client** (dict[str, Any] | None) - Optional - Additional configuration options for the rest client.
- **default_client** (Literal['sql', 'rest'] | None) - Optional - Which client to default to if both are initialised.
- **feature_logger** (FeatureLogger | None) - Optional - Custom feature logger which FeatureView.log uses to log feature vectors.
- **n_processes** (int | None) - Optional - Number of worker processes used to apply transformation functions in parallel during serving.
```

--------------------------------

### DeploymentTracingConfig.describe()

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment_tracing_config

Prints a JSON representation of the current tracing configuration settings.

```APIDOC
## describe()

### Description
Prints a JSON description of the tracing configuration to the console.

### Signature
`describe()`
```

--------------------------------

### get_newest_model(training_dataset_version)

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Get the latest generated model using this feature view.

```APIDOC
## get_newest_model(training_dataset_version)

### Description
Get the latest generated model using this feature view, based on explicit provenance. Searches only through accessible models.

### Parameters
- **training_dataset_version** (int | None) - Optional - Filter generated models based on the used training dataset version.

### Returns
- **Model | None** - Newest Generated Model or None if it does not exist.
```

--------------------------------

### Initialize Feature Monitoring for Comparison

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_group/feature_monitoring

Sets up a monitoring configuration where statistics comparison is enabled for later definition.

```python
fg_monitoring_config = trans_fg.create_feature_monitoring(
    name="trans_fg_amount_monitoring",
    description="Compute and compare descriptive statistics on the Feature Group on a daily basis",
)
```

--------------------------------

### Get Log Timeline

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Retrieves the commit metadata timeline for the feature view.

```python
get_log_timeline(
    wallclock_time: str
    | int
    | datetime
    | datetime.date
    | None = None,
    limit: int | None = None,
    transformed: bool | None = False,
) -> dict[str, dict[str, str]]
```

```python
# get log timeline
log_timeline = feature_view.get_log_timeline(limit=10)
```

--------------------------------

### List files and directories

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/dataset_api

Retrieve a list of files and directories from a specified path in the Hopsworks Filesystem.

```python
list(
    path: str, offset: int = 0, limit: int = 1000
) -> list[str]
```

```python
import hopsworks

project = hopsworks.login()

dataset_api = project.get_dataset_api()

# list all files in the Resources dataset
files = dataset_api.list("/Resources")

# list all datasets in the project
files = dataset_api.list("/")
```

--------------------------------

### Manage Notification Topic

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Gets or sets the Kafka topic used for notifications.

```python
notification_topic_name: str | None

```

--------------------------------

### Manage Expectation Suite

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Gets or sets the configuration object for data validation.

```python
expectation_suite: (
    hsfs.expectation_suite.ExpectationSuite | None
)

```

--------------------------------

### Transformer Initialization with Parameters

Source: https://docs.hopsworks.ai/latest/user_guides/mlops/serving/transformer

Demonstrates injecting optional runtime parameters like project and model handles into the Transformer class.

```python
class Transformer:
    def __init__(self, project, model):
        # Access the project and model directly
        self.project = project
        self.model_metadata = model
```

--------------------------------

### Manage Event Time

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Gets or sets the event time feature column.

```python
event_time: str | None

```

--------------------------------

### describe()

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment

Print a JSON description of the deployment.

```APIDOC
## describe()

### Description
Print a JSON description of the deployment to the console.
```

--------------------------------

### create_training_data(start_time, end_time, storage_connector, location, description, extra_filter, data_format, coalesce, seed, statistics_config, write_options, spine, transformation_context, data_source, tags, lookback, **kwargs)

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_view

Creates the metadata for a training dataset and saves the training data. Returns a tuple containing the training dataset version and the associated Hopsworks Job.

```APIDOC
## create_training_data

### Description
Create the metadata for a training dataset and save the corresponding training data into a specified location. The training data can be retrieved later by calling `feature_view.get_training_data`.

### Parameters
- **start_time** (str | int | datetime | date | None) - Optional - Start time for the training data.
- **end_time** (str | int | datetime | date | None) - Optional - End time for the training data.
- **storage_connector** (storage_connector.StorageConnector | None) - Optional - Storage connector for the data location.
- **location** (str | None) - Optional - Path to save the training data.
- **description** (str | None) - Optional - Description of the training dataset.
- **extra_filter** (filter.Filter | filter.Logic | None) - Optional - Filter to apply to the data.
- **data_format** (str | None) - Optional - Format of the training data (default: 'parquet').
- **coalesce** (bool | None) - Optional - Whether to coalesce the data.
- **seed** (int | None) - Optional - Random seed for reproducibility.
- **statistics_config** (StatisticsConfig | bool | dict | None) - Optional - Configuration for statistics computation.
- **write_options** (dict[Any, Any] | None) - Optional - Additional options for the execution engine.
- **spine** (SplineDataFrameTypes | None) - Optional - Spine dataframe for point-in-time joins.
- **transformation_context** (dict[str, Any]) - Optional - Contextual information for transformation functions.
- **data_source** (ds.DataSource | dict[str, Any] | None) - Optional - Data source location.
- **tags** (tag.Tag | dict[str, Any] | list[tag.Tag | dict[str, Any]] | None) - Optional - Tags for discoverability.
- **lookback** (FeatureGroupLookback | Lookback | dict[str, Any] | None) - Optional - Lookback window configuration.

### Returns
- **td_version** (int) - The training dataset version.
- **job** (job.Job) - The Hopsworks Job launched to create the training dataset (when using python engine).

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error.

### Example
```python
# create a training dataset
version, job = feature_view.create_training_data(
    description='Description of a dataset',
    data_format='csv',
    # async creation in order not to wait till finish of the job
    write_options={"wait_for_job": False}
)
```
```

--------------------------------

### Manage Deprecation Status

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/feature_group

Gets or sets the deprecation status of the feature group.

```python
deprecated: bool

```

--------------------------------

### Get all embedding features

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/embedding

Retrieve a list of all EmbeddingFeature objects associated with the index.

```python
get_embeddings() -> list[EmbeddingFeature]
```

--------------------------------

### Access Table Property

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/core/data_source

Get or set the table name for the data source.

```python
table: str | None

```

--------------------------------

### Importing models from HuggingFace

Source: https://docs.hopsworks.ai/latest/python-api/hsml/model_registry

Examples showing how to import public models, private models using a token, and models with specific variants.

```python
import hopsworks

project = hopsworks.login()
mr = project.get_model_registry()

# Public model — minimal call.
m = mr.hf_download("Qwen/Qwen2.5-0.5B")

# Gated / private — supply an HF access token.
m = mr.hf_download("meta-llama/Llama-3.2-1B", hf_token="hf_xxx")

# Multi-quant repo — pick exactly one variant.
m = mr.hf_download(
    "unsloth/Kimi-K2.6-GGUF", selected_variants=["UD-Q4_K_XL"]
)
```

--------------------------------

### Access Group Property

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/core/data_source

Get or set the group/schema name for the data source.

```python
group: str | None

```

--------------------------------

### Access Database Property

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/core/data_source

Get or set the database name for the data source.

```python
database: str | None

```

--------------------------------

### Create a Training Dataset with Time-Based Filtering

Source: https://docs.hopsworks.ai/latest/user_guides/fs/feature_group/create

Demonstrates creating a feature view and generating a training dataset using start and end time filters.

```python
query = fg.select_all()

# create a simple feature view
fv = fs.create_feature_view(name="transactions_view", query=query)

# set up dates
start_time = "2022-01-01"
end_time = "2022-06-30"

# create a training dataset
version, job = fv.create_training_data(
    start_time=start_time,
    end_time=end_time,
    description="Description of a dataset",
)
```

--------------------------------

### create_model_monitoring(name: str, description: str | None = None, start_date_time: int | str | None = None, end_date_time: int | str | None = None, cron_expression: str | None = '0 0 12 ? * * *')

Source: https://docs.hopsworks.ai/latest/python-api/hsml/deployment

Create a model monitoring configuration bound to the deployment's model.

```APIDOC
## create_model_monitoring(name: str, description: str | None = None, start_date_time: int | str | None = None, end_date_time: int | str | None = None, cron_expression: str | None = '0 0 12 ? * * *')

### Description
Create a model monitoring config bound to this deployment's model. This method resolves the model's parent feature view and returns a FeatureMonitoringConfig builder.

### Parameters
- **name** (str) - Required - Name of the feature monitoring configuration.
- **description** (str | None) - Optional - Description of the configuration. Default: None.
- **start_date_time** (int | str | None) - Optional - Start date and time for computing statistics. Default: None.
- **end_date_time** (int | str | None) - Optional - End date and time for computing statistics. Default: None.
- **cron_expression** (str | None) - Optional - Cron expression scheduling the FM job. Default: '0 0 12 ? * * *'.

### Returns
- **FeatureMonitoringConfig** - A builder object to further configure and save the monitoring job.

### Raises
- **hopsworks.client.exceptions.ModelServingException** - If the deployment's model has no parent feature view recorded.
```

--------------------------------

### Get current project reference

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks

Retrieves a reference to the currently logged-in project.

```python
get_current_project() -> project.Project
```

```python
import hopsworks

hopsworks.login()

project = hopsworks.get_current_project()
```

--------------------------------

### Create S3 Bucket for Project Data

Source: https://docs.hopsworks.ai/latest/setup_installation/aws/getting_started

Initializes an S3 bucket for storing project data. Replace BUCKET_NAME, REGION, and PROFILE with your specific values.

```bash
aws s3 mb s3://BUCKET_NAME --region REGION --profile PROFILE
```

--------------------------------

### Get Trino API

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/project

Retrieves the handle for the project's Trino API.

```python
get_trino_api() -> trino_api.TrinoApi
```

--------------------------------

### Create Artifact Registry repository

Source: https://docs.hopsworks.ai/latest/setup_installation/gcp/getting_started

Initializes a Docker repository in Artifact Registry for storing project images.

```bash
gcloud artifacts repositories create <repo-name> \
  --repository-format=docker \
  --location=<region>
```

--------------------------------

### Get Superset API

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/project

Retrieves the handle for the project's Superset API.

```python
get_superset_api() -> superset_api.SupersetApi
```

--------------------------------

### Get Search API

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/project

Retrieves the handle for the project's Search API.

```python
get_search_api() -> search_api.SearchApi
```

--------------------------------

### mkdir(path: str) -> str

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/core/dataset_api

Create a directory in the Hopsworks Filesystem.

```APIDOC
## mkdir(path: str) -> str

### Description
Create a directory in the Hopsworks Filesystem.

### Parameters
- **path** (str) - Required - Path to directory.

### Returns
- **str** - Path to the created directory.

### Raises
- **hopsworks.client.exceptions.RestAPIError** - If the backend encounters an error when handling the request.
```

--------------------------------

### Get OpenSearch API

Source: https://docs.hopsworks.ai/latest/python-api/hopsworks/project

Retrieves the handle for the project's OpenSearch API.

```python
get_opensearch_api() -> opensearch_api.OpenSearchApi
```

--------------------------------

### Configure Equal Width Binner Bins

Source: https://docs.hopsworks.ai/latest/python-api/hsfs/builtin_transformations

Example of setting a custom number of bins for the equal width binner using the transformation context.

```python
tf = equal_width_binner("feature")
tf.transformation_context = {"n_bins": 20}
```
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