functionVerified releasev2
fetch_snapshot
Collect real HN stories from date-filtered Algolia search or current Firebase feeds. Explicit time range, overlapping feeds, request/item/time budgets and collection timestamp; no substitute data. Returns normalized rows and coverage diagnostics.
Interface
Verified contract
Inputs
| Name | Type |
|---|---|
| source | unspecified |
| start_utc | unspecified |
| end_utc | unspecified |
| feeds | unspecified |
| max_items | unspecified |
| page_size | unspecified |
| max_requests | unspecified |
| timeout | unspecified |
| attempts | unspecified |
| budget_seconds | unspecified |
| pause_seconds | unspecified |
| max_response_bytes | unspecified |
| proxy | unspecified |
| transport | unspecified |
Outputs
| Name | Type |
|---|---|
| default | unspecified |
Exact release
Pinned local call
from spl import SPLClient
result = SPLClient.embedded().call(
"splime://@splime.project/case4-hn/fetch_snapshot@2",
kwargs={'attempts': 'replace-with-value', 'budget_seconds': 'replace-with-value', 'end_utc': 'replace-with-value', 'feeds': 'replace-with-value', 'max_items': 'replace-with-value', 'max_requests': 'replace-with-value', 'max_response_bytes': 'replace-with-value', 'page_size': 'replace-with-value', 'pause_seconds': 'replace-with-value', 'proxy': 'replace-with-value', 'source': 'replace-with-value', 'start_utc': 'replace-with-value', 'timeout': 'replace-with-value', 'transport': 'replace-with-value'},
trust=True,
)Review before running. Public bundles contain executable code. Verify the publisher and exact content hash; a virtual environment isolates dependencies, not the operating system.
Evidence
Evidence-backed concepts
- Fetch snapshot
- Current firebase feeds
- Explicit time range
- Request time budgets
- Overlapping feeds
- Collection timestamp
- No substitute
- Normalized rows
History
Public versions
- v28 downloads
- v110 downloads
Discover
Similar Objects
- hn_topic_digestFetch real HN stories, normalize them, apply the required immutable embedded trained model, count observed attention and render notebook-safe HTML. Training is a separate operation. Published implementation executes locally in embedded mode.
- evaluate_topics_temporallySplit HN stories chronologically, fit vocabulary and topics only on earlier titles, then inspect later-title coverage and reconstruction. No supervised accuracy or future-popularity forecast is claimed.
- normalize_storiesNormalize HN records or a snapshot, preserve missing popularity values, merge overlapping feed membership and deduplicate story IDs. Returns acquisition provenance and quality counts.
- train_topic_modelFit a simple TF-IDF and nonnegative matrix factorization topic model on supplied training titles only. Returns portable JSON vocabulary, IDF weights, learned components, automatic top-term names and a content identity; no rule-generated labels.
- tag_titlesAssign HN titles to topics with the immutable trained model embedded as a required native graph dependency. Automatic names use learned top terms; no caller model file or retraining. Returns hn-topics-v1 predictions.