Informe JSON sin procesar legible por máquina
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"body": "Platform packages (csvql-query-{platform}-{arch}):\n darwin-arm64, darwin-x64, linux-x64, linux-arm64, win32-x64\n Each has os/cpu fields so npm installs only the matching one.\n Binary (csvql.node) is dropped in by CI at publish time.\n\nMain package (csvql-query):\n Lists all platform packages as op\n[…]\n ubuntu-24.04-arm.\n Each runner builds csvql.node natively, publishes its platform package.\n Main package published after all platform packages succeed.\n Requires NPM_TOKEN secret in repo settings.",
"is_bot": false,
"headline": "feat: npm publish infrastructure for csvql-query",
"author_name": "Melih Birim",
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"body": "find(file, opts) translates simple options to SQL internally,\nso users who don't know SQL can still use the engine.\n\n csvql.find('employees.csv', {\n columns: ['name', 'city', 'salary'],\n where: 'salary>100000 AND department=Engineering',\n orderBy: 'salary:desc',\n limit: 10,\n\n[…]\nesc' / 'col:asc'\n limit — max rows\n + delimiter, comment, skipEmptyLines from QueryOptions\n\nFor GROUP BY / aggregates / JOIN, use query() instead.\n18/18 tests pass. README and index.d.ts updated.",
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"body": "Explains the csv-parse vs csvql difference for the most common\nreal-world pattern: CSV → filter → database insert.\n\nCovers:\n- Why csv-parse must load all rows before filtering (parser only)\n- The cast:true boolean string footgun (silent 0 results)\n- How csvql pushes WHERE into the engine (heap scales with result, not file)\n- Comparison table: 100k rows, csv-parse 200ms +31MB vs csvql 22ms +3MB\n- On a 10GB file: csv-parse OOM, csvql same cost",
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"body": "node --experimental-sqlite example_etl.js\n\nShows csv-parse vs csvql for the most common real-world pattern:\nread CSV, filter rows, insert into database.\n\ncsv-parse: must load all 100k rows into memory as JS objects first,\nthen .filter() in JS (200ms, +31 MB heap).\n\ncsvql: WHERE clause runs inside th\n[…]\n+3 MB heap).\n\nAlso documents a csv-parse footgun: cast:true converts numbers\nbut leaves boolean strings as-is, so r.active === true silently\nreturns 0 rows. Must compare against 'true' string instead.",
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"body": "node nodejs/example.js\n\nCovers:\n 1. SELECT * LIMIT\n 2. WHERE filter + ORDER BY\n 3. GROUP BY + COUNT + AVG\n 4. Top-N (ORDER BY LIMIT)\n 5. JOIN two CSV files\n 6. TSV file ({ delimiter: '\\t' })\n 7. Skip comment/blank lines ({ comment: '#', skipEmptyLines: true })\n 8. queryCsv — return CSV string\n 9. queryCsv — write result to file",
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"body": "README: new Language Libraries section with Node.js + Python.\n - query() / queryCsv() examples\n - options table (delimiter, comment, skipEmptyLines)\n - memory comparison note\n - bench.js / compare.js pointers\n\nindex.js: full JSDoc with @typedef QueryOptions, @param, @returns,\n @throws, and @example blocks for every function.\n\nindex.d.ts: QueryOptions interface + typed signatures for both exports.",
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"body": "query(sql, { delimiter: '\\t' }) — TSV / pipe / any separator\nquery(sql, { comment: '#' }) — skip comment rows\nquery(sql, { skipEmptyLines: true }) — skip blank lines\n\nWorks for JOIN queries too — all file paths in the SQL get preprocessed.\nDelimiter conversion is quote-aware (handles quoted fields containing the delimiter).\n13/13 tests pass.",
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"body": "Covers 10 real tasks: basic parse, type casting, custom delimiters,\nskip blank/comment rows, filter, aggregate, sort, JOIN, CSV writing,\nstreaming. Each shows code + actual output for all three libraries.",
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"body": "Results on 42 MB / 1M row file:\n GROUP BY: csvql 10ms +0 MB vs csv-parse 1386ms +277 MB (143x faster)\n ORDER BY: csvql 23ms +0 MB vs csv-parse 1872ms +290 MB (80x faster)\n WHERE: csvql 103ms +58 MB vs csv-parse 1357ms +289 MB (13x faster)\n LIMIT 5: csvql 3ms +0 MB vs papaparse 389ms +309 MB (papaparse reads whole file)\n\nFeature table updated: csvql sync API stays ~5 MB;\ncsv-parse/papaparse sync APIs materialize all rows as JS objects.",
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"body": "node bench.js — 200k rows, 4 queries, timing + feature matrix\n\nResults (8.3 MB file):\n LIMIT 5 csvql 1.9ms vs csv-parse 3.1ms (1.6x faster)\n GROUP BY csvql 9ms vs csv-parse 357ms (39x faster)\n WHERE csvql 38ms vs csv-parse 344ms (9x faster)\n ORDER BY csvql 52ms vs csv-parse 376ms (7x faster)\n\nFeature diff: csvql has SQL; csv-parse/papaparse have streaming,\ncustom delimiters, browser support.",
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"body": "Build: zig build node -Doptimize=ReleaseFast\nOutput: zig-out/lib/csvql.node\n\nAPI (mirrors Python package):\n const { query, queryCsv } = require('csvql-query')\n const rows = query(\"SELECT * FROM 'data.csv' WHERE salary > 100000\")\n const csv = queryCsv(\"SELECT city, COUNT(*) FROM 'data.csv' GROUP \n[…]\n at build time\n\nFiles:\n nodejs/index.js - JS entry point + loader\n nodejs/index.d.ts - TypeScript types\n nodejs/package.json - npm package (csvql-query)\n nodejs/test.js - 8/8 tests pass",
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"headline": "cleanup: remove generated CSVs, stale benchmarks, unused examples",
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"body": "Co-authored-by: Copilot <copilot@github.com>",
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"headline": "enhance help text and schema options",
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{
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}
],
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{
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{
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"notes": [],
"value": 70,
"inputs": {
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"has_license": true,
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{
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}
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{
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{
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"points": 0,
"status": "missed",
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}
]
},
{
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}
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{
"key": "pr_acceptance",
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{
"key": "openssf_scorecard_code_review",
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]
},
{
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"notes": [
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"code": "excluded_no_data",
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"components": [
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{
"code": "weights_renormalized",
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"inputs": {
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"components": [
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"status": "partial",
"details": [
{
"code": "owner_personal",
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}
],
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{
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{
"key": "owner_reach",
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{
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{
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},
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{
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],
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{
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{
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]
},
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"notes": [],
"value": 100,
"inputs": {
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{
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]
}
],
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{
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"weight": 0.16,
"metrics": [
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"notes": [],
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{
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{
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{
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{
"key": "contributors",
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"points": 0,
"status": "missed",
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{
"key": "dangerous_workflow",
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"points": 10,
"status": "met",
"details": [],
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{
"key": "dependency_update_tool",
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"points": 0,
"status": "missed",
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{
"key": "fuzzing",
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"status": "missed",
"details": [],
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{
"key": "license",
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"points": 2.5,
"status": "met",
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{
"key": "maintained",
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"points": 7.5,
"status": "met",
"details": [],
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{
"key": "packaging",
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"points": 5,
"status": "met",
"details": [],
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{
"key": "pinned_dependencies",
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"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
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{
"key": "sast",
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"points": 0,
"status": "missed",
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{
"key": "security_policy",
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"points": 5,
"status": "met",
"details": [],
"max_points": 5
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{
"key": "signed_releases",
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"points": 0,
"status": "missed",
"details": [],
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{
"key": "token_permissions",
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"points": 0,
"status": "missed",
"details": [],
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{
"key": "vulnerabilities",
"name": "Vulnerabilities",
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]
},
{
"key": "high_risk_jurisdiction_exposure",
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"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
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],
"value": 100,
"inputs": {
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"review_only_matches": 0,
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"components": [
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"key": "policy_exposure_multiplier",
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"status": "met",
"details": [
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"code": "jurisdiction_no_match",
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],
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]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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{
"key": "ai_readiness",
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"name": "AI Readiness",
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"weight": 0,
"metrics": [
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"key": "ai_agent_context",
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"notes": [],
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"inputs": {
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"components": [
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"status": "missed",
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],
"max_points": 45
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{
"key": "machine_readable_docs_llms_txt",
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"points": 0,
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{
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"code": "legible_history",
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]
},
{
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"notes": [],
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"inputs": {
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"components": [
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{
"key": "automated_tests",
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