compound_growth_projection

Inputs

Outputs

from spl import SPLClient

result = SPLClient.embedded().call(
    "splime://@ky/public-examples/compound_growth_projection@1",
    kwargs={'annual_rate': 0.0, 'principal': 0.0, 'years': 0},
    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

• Compound growth projection
• Whole year calculation
• Annual rate
• Principal amount
• Floating point
• Integer values
• Growth rate
• Virtual environment

• v124 Aug 202615 downloads

• summarize_topicsMeasure observed topic counts, shares, scores and comments separately from topic assignment; compare equal-duration windows under one fixed model and report overlapping feed coverage.
• 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.
• analyze_titlesApply explicit topic rules and compare document shares in adjacent equal-duration windows. Counts describe the supplied snapshot, not all Hacker News activity.
• 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.
• render_digestRender observed HN topics, tags, attention summaries, collection coverage and real story links as an escaped notebook-safe HTML fragment with scoped CSS; optional standalone document.