feast-dev · franciscojavierarceo · Mar 30, 2025 · Mar 30, 2025
@@ -62,6 +62,8 @@ The list below contains the functionality that contributors are planning to deve
   * [x] [Python feature server](https://docs.feast.dev/reference/feature-servers/python-feature-server)
   * [x] [Java feature server (alpha)](https://github.com/feast-dev/feast/blob/master/infra/charts/feast/README.md)
   * [x] [Go feature server (alpha)](https://docs.feast.dev/reference/feature-servers/go-feature-server)
+  * [x] [Offline Feature Server (alpha)](https://docs.feast.dev/reference/feature-servers/offline-feature-server)
+  * [x] [Registry server (alpha)](https://github.com/feast-dev/feast/blob/master/docs/reference/feature-servers/registry-server.md)
 * **Data Quality Management (See [RFC](https://docs.google.com/document/d/110F72d4NTv80p35wDSONxhhPBqWRwbZXG4f9mNEMd98/edit))**
   * [x] Data profiling and validation (Great Expectations)
 * **Feature Discovery and Governance**

@@ -152,6 +152,7 @@ pprint(feature_vector)
 Please refer to the official documentation at [Documentation](https://docs.feast.dev/)
  * [Quickstart](https://docs.feast.dev/getting-started/quickstart)
  * [Tutorials](https://docs.feast.dev/tutorials/tutorials-overview)
+ * [Examples](https://github.com/feast-dev/feast/tree/master/examples)
  * [Running Feast with Snowflake/GCP/AWS](https://docs.feast.dev/how-to-guides/feast-snowflake-gcp-aws)
  * [Change Log](https://github.com/feast-dev/feast/blob/master/CHANGELOG.md)
 

@@ -19,6 +19,7 @@
 from typing import Any, List, Optional
 
 import click
+import pandas as pd
 import yaml
 from bigtree import Node
 from colorama import Fore, Style
@@ -537,6 +538,175 @@ def feature_view_list(ctx: click.Context, tags: list[str]):
     print(tabulate(table, headers=["NAME", "ENTITIES", "TYPE"], tablefmt="plain"))
 
 
+@cli.group(name="features")
+def features_cmd():
+    """
+    Access features
+    """
+    pass
+
+
+@features_cmd.command(name="list")
+@click.option(
+    "--output",
+    type=click.Choice(["table", "json"], case_sensitive=False),
+    default="table",
+    show_default=True,
+    help="Output format",
+)
+@click.pass_context
+def features_list(ctx: click.Context, output: str):
+    """
+    List all features
+    """
+    store = create_feature_store(ctx)
+    feature_views = [
+        *store.list_batch_feature_views(),
+        *store.list_on_demand_feature_views(),
+        *store.list_stream_feature_views(),
+    ]
+    feature_list = []
+    for fv in feature_views:
+        for feature in fv.features:
+            feature_list.append([feature.name, fv.name, str(feature.dtype)])
+
+    if output == "json":
+        json_output = [
+            {"feature_name": fn, "feature_view": fv, "dtype": dt}
+            for fv, fn, dt in feature_list
+        ]
+        click.echo(json.dumps(json_output, indent=4))
+    else:
+        from tabulate import tabulate
+
+        click.echo(
+            tabulate(
+                feature_list,
+                headers=["Feature", "Feature View", "Data Type"],
+                tablefmt="plain",
+            )
+        )
+
+
+@features_cmd.command("describe")
+@click.argument("feature_name", type=str)
+@click.pass_context
+def describe_feature(ctx: click.Context, feature_name: str):
+    """
+    Describe a specific feature by name
+    """
+    store = create_feature_store(ctx)
+    feature_views = [
+        *store.list_batch_feature_views(),
+        *store.list_on_demand_feature_views(),
+        *store.list_stream_feature_views(),
+    ]
+
+    feature_details = []
+    for fv in feature_views:
+        for feature in fv.features:
+            if feature.name == feature_name:
+                feature_details.append(
+                    {
+                        "Feature Name": feature.name,
+                        "Feature View": fv.name,
+                        "Data Type": str(feature.dtype),
+                        "Description": getattr(feature, "description", "N/A"),
+                        "Online Store": getattr(fv, "online", "N/A"),
+                        "Source": json.loads(str(getattr(fv, "batch_source", "N/A"))),
+                    }
+                )
+    if not feature_details:
+        click.echo(f"Feature '{feature_name}' not found in any feature view.")
+        return
+
+    click.echo(json.dumps(feature_details, indent=4))
+
+
+@cli.command("get-online-features")
+@click.option(
+    "--entities",
+    "-e",
+    type=str,
+    multiple=True,
+    required=True,
+    help="Entity key-value pairs (e.g., driver_id=1001)",
+)
+@click.option(
+    "--features",
+    "-f",
+    multiple=True,
+    required=True,
+    help="Features to retrieve. (e.g.,feature-view:feature-name) ex: driver_hourly_stats:conv_rate",
+)
+@click.pass_context
+def get_online_features(ctx: click.Context, entities: List[str], features: List[str]):
+    """
+    Fetch online feature values for a given entity ID
+    """
+    store = create_feature_store(ctx)
+    entity_dict: dict[str, List[str]] = {}
+    for entity in entities:
+        try:
+            key, value = entity.split("=")
+            if key not in entity_dict:
+                entity_dict[key] = []
+            entity_dict[key].append(value)
+        except ValueError:
+            click.echo(f"Invalid entity format: {entity}. Use key=value format.")
+            return
+    entity_rows = [
+        dict(zip(entity_dict.keys(), values)) for values in zip(*entity_dict.values())
+    ]
+    feature_vector = store.get_online_features(
+        features=list(features),
+        entity_rows=entity_rows,
+    ).to_dict()
+
+    click.echo(json.dumps(feature_vector, indent=4))
+
+
+@cli.command(name="get-historical-features")
+@click.option(
+    "--dataframe",
+    "-d",
+    type=str,
+    required=True,
+    help='JSON string containing entities and timestamps. Example: \'[{"event_timestamp": "2025-03-29T12:00:00", "driver_id": 1001}]\'',
+)
+@click.option(
+    "--features",
+    "-f",
+    multiple=True,
+    required=True,
+    help="Features to retrieve. feature-view:feature-name ex: driver_hourly_stats:conv_rate",
+)
+@click.pass_context
+def get_historical_features(ctx: click.Context, dataframe: str, features: List[str]):
+    """
+    Fetch historical feature values for a given entity ID
+    """
+    store = create_feature_store(ctx)
+    try:
+        entity_list = json.loads(dataframe)
+        if not isinstance(entity_list, list):
+            raise ValueError("Entities must be a list of dictionaries.")
+
+        entity_df = pd.DataFrame(entity_list)
+        entity_df["event_timestamp"] = pd.to_datetime(entity_df["event_timestamp"])
+
+    except Exception as e:
+        click.echo(f"Error parsing entities JSON: {e}", err=True)
+        return
+
+    feature_vector = store.get_historical_features(
+        entity_df=entity_df,
+        features=list(features),
+    ).to_df()
+
+    click.echo(feature_vector.to_json(orient="records", indent=4))
+
+
 @cli.group(name="on-demand-feature-views")
 def on_demand_feature_views_cmd():
     """