{"adoption": {"forks": 361, "observed_at": "2026-08-28T04:08:38.831771+00:00", "stars": 4193}, "canonical_url": "https://ross.abutalabs.com/products/finance", "card": {"archived": false, "artifact_type": "learning-resource", "description": "150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data", "domain": ["fintech", "data-science", "machine-learning", "analytics"], "enriched": true, "function": ["data-science", "machine-learning", "web-scraping", "data-visualization", "trading"], "health_score": 64, "homepage": null, "language": "Python", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["shashankvemuri/Finance"], "name": "shashankvemuri/Finance", "platform": ["python", "cross-platform"], "pushed_at": "2026-03-26T06:24:50+00:00", "repo": "shashankvemuri/Finance", "stars": 4193, "tags": ["quantitative-finance", "stock-market", "algorithmic-trading", "technical-indicators", "educational", "script-collection"], "topics": ["stocks", "stock-market", "finance", "python", "machine-learning", "data-science", "technical-indicators", "quantitative-finance", "pandas", "algorithmic-trading", "stock", "trading-strategies"], "urls": [], "use_cases": ["screen stocks based on technical and fundamental analysis", "predict stock prices with machine learning", "backtest trading strategies and portfolio simulations", "visualize technical indicators like RSI, MACD, and Bollinger Bands", "scrape and collect stock price and company data", "learn quantitative finance programming in Python"], "what_it_is": "A collection of 150+ standalone Python programs for gathering, manipulating, and analyzing stock market data. It covers stock screening, machine learning for prediction, portfolio strategies, technical indicators, and data collection via APIs and web scraping.", "when_to_avoid": ["you need a production trading system or a maintained library with an API", "you require professional investment advice or guaranteed returns", "you need a single cohesive package rather than independent scripts"], "when_to_choose": ["you want ready-made example scripts for quantitative finance tasks", "you are learning Python for stock market analysis", "you need standalone programs for stock screening, indicators, or data collection"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/finance", "repo": "shashankvemuri/Finance", "role": "main", "score": 66}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:08:38.831771+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T18:22:35.730292+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0a6445be7a5cf1f5a377c3e4367e017b8fa97f80016d5e5e4e678c37b7837137", "fetched_at": "2026-08-28T04:08:38.831771+00:00", "kind": "readme", "missing": false, "url": "https://github.com/shashankvemuri/Finance"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 74, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2397, "days_push": 160, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 66, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}