{"payload":{"feedbackUrl":"https://github.com/orgs/community/discussions/53140","repo":{"id":698580010,"defaultBranch":"master","name":"books","ownerLogin":"robertnurnberg","currentUserCanPush":false,"isFork":true,"isEmpty":false,"createdAt":"2023-09-30T10:39:48.000Z","ownerAvatar":"https://avatars.githubusercontent.com/u/28635489?v=4","public":true,"private":false,"isOrgOwned":false},"refInfo":{"name":"","listCacheKey":"v0:1715675706.0","currentOid":""},"activityList":{"items":[{"before":"510870d3f11ce58992b8051c69b3866270e798d8","after":null,"ref":"refs/heads/v2","pushedAt":"2024-05-14T08:35:06.000Z","pushType":"branch_deletion","commitsCount":0,"pusher":{"login":"robertnurnberg","name":"Robert Nürnberg","path":"/robertnurnberg","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/28635489?s=80&v=4"}},{"before":null,"after":"510870d3f11ce58992b8051c69b3866270e798d8","ref":"refs/heads/v2","pushedAt":"2024-03-15T20:17:36.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"robertnurnberg","name":"Robert Nürnberg","path":"/robertnurnberg","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/28635489?s=80&v=4"},"commit":{"message":"refinement of UHO Lichess book","shortMessageHtmlLink":"refinement of UHO Lichess book"}},{"before":"abb48fd6133fed423c19f16481f195221ccf8e6f","after":"426eca422c202ef381a1380ada1873a7f185c4b9","ref":"refs/heads/master","pushedAt":"2023-10-23T06:59:52.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"robertnurnberg","name":"Robert Nürnberg","path":"/robertnurnberg","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/28635489?s=80&v=4"},"commit":{"message":"Another book with unbalanced human openings (#39)\n\nA new book derived from Lichess games, with a model draw rate between 48% and 52%\r\n\r\nIt attempts to address the following points, relative to the currently used book:\r\n\r\n* about 10x larger (2.6M pos), i.e. more variety while testing on fishtest, no repeated openings for any single test played.\r\n* both white and black advantage around +- 1.0\r\n* positions at all game plies between 1 and 16\r\n\r\nThe construction process involved\r\n\r\n1) Parsing all 15B lichess games in the database https://database.lichess.org/ for the period Jan - Sept 2023.\r\n   Extract from these the popular positions, i.e. seen at least twice, within the first 16 plies played, exploring newly added games to at most 8 previously unseen plies.\r\n```\r\n$ ./fastpopular --dir /mnt/md0/chess/lichessgames/2023/ --minCount 2 --stopEarly --countStopEarly 8 --maxPlies 16 --concurrency 9 -o popular_Lichess_JanSept_maxPlies16_stopEarly8.epd\r\nLooking for pgn files in /mnt/md0/chess/lichessgames/2023/\r\nFound 9 .pgn(.gz) files, creating 9 chunks for processing.\r\nProcessed 9 files\r\nRetained 296993424 positions from 1127228493 unique visited in 15251265926 games.\r\nTotal time for processing: 7374.5 s\r\n```\r\n   fastpopular as available at https://github.com/vondele/fastpopular\r\n\r\n2) Score all these 296M games with a modified stockfish, based on master, that analyses positions up to a depth 24, for as long as the draw rate is predicted (UCI_ShowWDL) near 50%.\r\n   Positions will be analysed to low depth if the draw rate is very different from 50% at low depth.\r\n   From these scored positions, extract those with a draw rate in the range 48 - 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