{"id":18283600,"url":"https://github.com/thesmartmonkey/chess-analysis","last_synced_at":"2025-04-09T05:42:58.741Z","repository":{"id":140586616,"uuid":"458492885","full_name":"TheSmartMonkey/chess-analysis","owner":"TheSmartMonkey","description":"Analyse your own games get some good insights that helps you to improve at chess","archived":false,"fork":false,"pushed_at":"2023-09-10T22:21:31.000Z","size":67,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-15T00:19:12.406Z","etag":null,"topics":["chess","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/TheSmartMonkey.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-02-12T10:46:33.000Z","updated_at":"2022-08-06T22:32:17.000Z","dependencies_parsed_at":null,"dependency_job_id":"a8356659-e240-4a99-af72-40b77e6fb989","html_url":"https://github.com/TheSmartMonkey/chess-analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TheSmartMonkey%2Fchess-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TheSmartMonkey%2Fchess-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TheSmartMonkey%2Fchess-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/TheSmartMonkey%2Fchess-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/TheSmartMonkey","download_url":"https://codeload.github.com/TheSmartMonkey/chess-analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247987108,"owners_count":21028891,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["chess","python"],"created_at":"2024-11-05T13:10:04.604Z","updated_at":"2025-04-09T05:42:58.722Z","avatar_url":"https://github.com/TheSmartMonkey.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# chess-analysis\n\nAnalyse your own games get some good insights that helps you to improve at chess\n\n## Getting started\n\n### Lichess\n\n1. Go to https://lichess.org/@/{your_name}/download\n\n1. Download you opening file with this include settings\n\n![APP IMAGE](https://github.com/TheSmartMonkey/chess-analysis/blob/main/.github/lichess-import.PNG)\n\n1. Add the file at the root of the project\n\n### Chess.com\n\n1. Go to https://chessinsights.xyz/\n\n1. Enter the players name and export file in json\n\n1. Add the file at the root of the project\n\n1. Rename the file and put `chesscom_` on front\n\n### Next steps\n\n1. Install pipx : https://pypa.github.io/pipx/\n\n1. Avalable commands with `npm run` (`npm run start` runes your code)\n\n```\nstart\n    py main.py\ntest\n    python -m pipenv run pytest\nlint\n    python -m pipenv run mypy .\nformat\n    python -m black . \u0026\u0026 python -m isort -y\nformat:check\n    python -m black --check . \u0026\u0026 python -m isort --check-only\ncoverage\n    python -m pipenv run pytest --cov --cov-fail-under=90\n```\n\nResult exemple :\n\n```\nPlayed result:\nwin: 105\nlose: 58\nequal: 5\n\nwin: 62.5%\nlose: 34.52%\nequal: 2.98%\n\nMost played openings:\n75 games: Queen's Pawn Game: Mason Variation\n32 games: Indian Defense\n15 games: Horwitz Defense\n7 games: Queen's Pawn Game\n5 games: Englund Gambit\n5 games: Modern Defense\n4 games: Mikenas Defense\n3 games: French Defense: Franco-Hiva Gambit \n\nMost common lines:\n8 games: 1. d4 d5 2. Bf4 Nf6 3. e3 e6 4. Bd3 \n6 games: 1. d4 d5 2. Bf4 Nc6 3. e3 Bf5 4. c4 \n6 games: 1. d4 d5 2. Bf4 Bf5 3. e3 e6 4. c4 \n6 games: 1. d4 Nf6 2. Bf4 g6 3. Nc3 Bg7 4. e4 \n4 games: 1. d4 d5 2. Bf4 e6 3. e3 Nf6 4. Bd3 \n4 games: 1. d4 d5 2. Bf4 Nc6 3. e3 f6 4. Nf3 \n4 games: 1. d4 d5 2. Bf4 Nf6 3. e3 Bf5 4. c4 \n4 games: 1. d4 d5 2. Bf4 e6 3. e3 Bd6 4. Bg3 \n4 games: 1. d4 Nf6 2. Bf4 d6 3. Nc3 g6 4. e4 \n4 games: 1. d4 d5 2. Bf4 Nf6 3. e3 c5 4. c3 \n4 games: 1. d4 d5 2. Bf4 Nc6 3. e3 Bf5 4. c4 e6         \n4 games: 1. d4 d5 2. Bf4 Nf6 3. e3 e6 4. Bd3 c5         \n4 games: 1. d4 Nf6 2. Bf4 g6 3. Nc3 Bg7 4. e4 d6        \n4 games: 1. d4 d5 2. Bf4 Nf6 3. e3 e6 4. Bd3 c5 5. c3   \n4 games: 1. d4 Nf6 2. Bf4 g6 3. Nc3 Bg7 4. e4 d6 5. Qd2 \n3 games: 1. d4 d5 2. Bf4 Nc6 3. e3 Nf6 4. Nf3 \n3 games: 1. d4 d5 2. Bf4 e6 3. e3 c5 4. c3 \n3 games: 1. d4 d5 2. Bf4 e6 3. e3 Bd6 4. Bg3 Bxg3       \n3 games: 1. d4 d5 2. Bf4 Nf6 3. e3 Bf5 4. c4 c6         \n3 games: 1. d4 d5 2. Bf4 Bf5 3. e3 e6 4. c4 c6 \n```\n\n## Current Functionalities\n\n1. Give the most played lines (then you know were to train)\n\n## Upcoming Functionalities\n\n1. Analyse the most common mistakes in the opening\n\n1. Give alternative moves to improve your games\n\n1. Machine leaning (https://github.com/mptedesco/python-chess-analysis)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthesmartmonkey%2Fchess-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthesmartmonkey%2Fchess-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthesmartmonkey%2Fchess-analysis/lists"}