+ iRt^RIt^RIt^RIt^RIt^RIHtHt^RIH t H t H t H t ^RI HtRtRtRtR^R ^R ^rz<[^>]+>)rehtmlunescapesubstrip)r8r;s& r _strip_htmlr@9sC == D 66&$ %D 66*b$ 'D ::<rc vV^8dQhR\R\R\R\R\\\3,/#)r topic from_dateto_datedepthr)rrr)rs"rrrBsB-- ---  -  #s(^ -rc r\PV\R,4p\V4p\V4R,p\RV RV RV R24RVRR R R V R V 2R \ V4/p^RIHp\ RV!V4 2p \P!RV ^R7p T PR.4p \R\T 4 R24T # \Pd(p \RT 24R.R\ T 4/uRp ? #Rp ? i\d(p \RT 24R.R\ T 4/uRp ? #Rp ? ii;i)zSearch Hacker News via Algolia API. Args: topic: Search topic from_date: Start date (YYYY-MM-DD) to_date: End date (YYYY-MM-DD) depth: 'quick', 'default', or 'deep' Returns: Dict with Algolia response (contains 'hits' list). r iQzSearching for 'z ' (since z, count=)querytagsstorynumericFiltersz created_at_i>z,created_at_i< hitsPerPage) urlencode?GETtimeoutzSearch failed: hitserrorNzFound z stories) DEPTH_CONFIGgetr/rr urllib.parserMALGOLIA_SEARCH_URLrrequest HTTPError Exceptionlen) rBrCrDrEcountfrom_tsto_tsparamsrMurlresponseerRs &&&& rsearch_hackernewsrcBsA"   UL$; >- qc "#GSV,, - qc "#GSV,,-s6C D6D;D6 D6D6D1+D61D6cV^8dQhR\\\3,R\\\\3,,/#)r rar)rrrr)rs"rrrrs/,,S#X,4S#X;O,rcVPR.4p.p\V4EFawr4VPRR4pVPR4;'g^pVPR4;'g^pVPR4pRp V'd \V4p VPR4;'gRp R V 2p \R R VR ,, 4p \ R \ P !V4^(, 4p \ R V R,V ,R,4pVPRVRVPRR4RV RV RVPRR4RV RRVRV/R\V^4RRVPRR4R, 2/ 4EKd V#)zmParse Algolia response into normalized item dicts. Returns: List of item dicts ready for normalization. rRobjectIDr:points num_comments created_at_iNr`z%https://news.ycombinator.com/item?id=g333333?g?g{Gz?g?gffffff?g? object_idtitlehn_urlauthordate engagement relevance why_relevantzHN story about rB:N<N) rU enumerater6maxminmathlog1pappendround)rarRitemsihitrjrgrhrir article_urlrl rank_scoreengagement_boostrps& rparse_hackernews_responserrs << #D ED/GGJ+ "''aww~.33! ww~.  $\2Hggen** 8 DcQX./ sDJJv$6$;<Z#-0@@3FG   SWWWb) ; f cggh+ H &  y!, ocgggw.G.L-MN  )"F Lrc^V^8dQhR\R\R\\\3,/#)r rj max_commentsr)rr rr)rs"rrrs.*@*@C*@s*@4S>*@rc L\ RV 2p\P!RV^R7pTP R .4pTUu.uF7pTP R 4'gKTP R 4'gK5TNK9 ppTP R R R7.p.p TRTFp\TP R R44p \T 4R8dT R,R,MT p TPR TP R R4R T RTP R4;'g^/4T PR4^,PR4^,R,p T 'gKT PT 4K RTRT /# \d"p\ RT RT 24R.R./uRp?#Rp?ii;iuupi)zFetch top-level comments for a story from Algolia items endpoint. Args: object_id: HN story ID max_comments: Max comments to return Returns: Dict with 'comments' list and 'comment_insights' list. /rOrPzFailed to fetch comments for z: commentscomment_insightsNchildrenr8rmc8VPR4;'g^#)rgrU)cs&r&_fetch_item_comments..sQUU8_%9%9%9rTkeyreverser:i,:Ni,Nz...rgz. r:NN) ALGOLIA_ITEM_URLrrXrZrrUsortr@r[rxr$) rjrr`datarbrr real_commentsrinsightsr8excerptfirst_sentences && r_fetch_item_commentsrs a { +C8||E33 xx B'Ha 55= UU8_ 894HHH =L )155,-(+D C$t*u$T aeeHb) G aeeHo**  D)!,2248;DA > OON +* "4h ??9 8 ,YKr! =>B 2B778s.E2F!F!3F!2 F=FFFc V^8dQhR\\\\3,,R\R\\\\3,,/#)r rzrEr)rrrr)rs"rrrs@// S#X / / $sCx./rc aS'gS#\PV\R,4p\\\ S44V3RlRR7pVRVp\ R\ V4 R24\ ^R7;_uu_4pVUu/uF(pVP\SV,R ,4VbK* pp\V4FDpWx,pVP^R 7p V R ,SV,R &V R ,SV,R &KF RRR4S#uupi \d.ST,R &.ST,R &K}i;i +'giS#;i)zFetch comments for top N stories by points. Args: items: Parsed HN items depth: Research depth (controls how many to enrich) Returns: Items with top_comments and comment_insights added. r cV<SV,PR/4PR^4#)rorgr)r{rzs&rr$enrich_top_stories..s!eAhll<4881ErTrNzEnriching top z stories with comments) max_workersrjrPr top_commentsr) ENRICH_LIMITSrUsortedranger[rrsubmitrrresultrZ) rzrElimit by_points to_enrichexecutoridxfuturesfuturers f& renrich_top_storiesrs`    e]9%= >E c%j EI &5!I>#i.))? @A  * *h !  ! OO$c ;'  !  #7+F/C 4r2-3J-?c >*178J1Kc -. , +& L%  4-/c >*13c -. 4 + *& LsBE.D5E8DEE#E <E?E E E )r ))__doc__r<rvrtimeconcurrent.futuresrrtypingrrrrr:rrWALGOLIA_SEARCH_BY_DATE_URLrrTrrr/r6r@rcrrrrrrs  ?,,;K8 R r B  Q q B #-`,^*@Z//r