René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Support Data Labeling and LabelViews","articleBody":"**Is your feature request related to a problem? Please describe.**\nHistorically, Feast has played a key role in feature development. Particularly around dataset preparation for model development and feature serving for online inference. \n\nPictorially, you can think of it like this:\n\n![Image](https://github.com/user-attachments/assets/a1d2a6e7-c661-4e5c-9f0e-ccad9ff22e4f)\n\nYet labels are the core piece of a training dataset that makes model training successful. Without labels, features are a waste of time (excluding semi/self-supervised learning). \n\nGiven the work with compute engine, my proposal is to expand Feast to include the entire Training Dataset preparation life cycle which would include labels and their correction.\n\nA proof of concept was developed in the UI to highlight educate users about this here: https://github.com/feast-dev/feast/pull/5410\n\nWe should expand this properly so that users can define a `LabelView` in the online store that can be used to store labels explicitly.\n\n**Describe the solution you'd like**\nA `LabelView` that can be used to write data to the online and offline store. \n\n**Describe alternatives you've considered**\nA clear and concise description of any alternative solutions or features you've considered. It could look something like:\n\n```python\ncustomer = Entity(name=\"customer_id\", dtype=Int64)\n\n# 2) Point to your label data in e.g. Parquet\nlabel_source = FileSource(\n    path=\"gs://my-bucket/churn_labels/*.parquet\",\n    event_timestamp_column=\"label_timestamp\",\n    created_timestamp_column=\"created_ts\",\n)\n\n# 3) Declare the LabelView\ncustomer_churn = LabelView(\n    name=\"customer_churn\",\n    entities=[customer],\n    schema=[\n        Field(name=\"churned\", dtype=ValueType.BOOL),\n        Field(name=\"risk_score\", dtype=ValueType.FLOAT),\n    ],\n    batch_source=label_source,\n    ttl=timedelta(days=90),\n    description=\"Customer churn flag and risk score for training/monitoring.\",\n)\n\n```\n\n**Additional context**\nAdd any other context or screenshots about the feature request here.\n","author":{"url":"https://github.com/franciscojavierarceo","@type":"Person","name":"franciscojavierarceo"},"datePublished":"2025-06-16T13:24:35.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":3},"url":"https://github.com/5456/feast/issues/5456"}