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"value": 128.87263056104638, "unit": "ms/iter", "extra": "iterations: 9\ncpu: 128.75597947734045 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 26.428079633176615, "unit": "ms/iter", "extra": "iterations: 45\ncpu: 26.40944781213226 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.005001354377346366, "unit": "ms/iter", "extra": "iterations: 236017\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "6501e9e23e7c6c01b27dfccba23e73a243c1020c", "message": "jmp for byteCode is ok", "timestamp": "2022-03-14T10:49:14+08:00", "tree_id": "b55aae1f6011997a2a7e750bdd65549d43946ba3", "url": "https://github.com/pikasTech/pikascript/commit/6501e9e23e7c6c01b27dfccba23e73a243c1020c" }, "date": 1647226427293, "tool": "googlecpp", "benches": [ { "name": "Performance 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ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "f72fb9d84a1dbedf8d7690351cc09cb8564e440b", "message": "use __gotoXXXLine instead", "timestamp": "2022-03-14T11:02:54+08:00", "tree_id": "bce63130913458abd4918c55e8cacae0fd487c01", "url": "https://github.com/pikasTech/pikascript/commit/f72fb9d84a1dbedf8d7690351cc09cb8564e440b" }, "date": 1647227250016, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 1854.4348395100285, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 1854.4348395100285 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 150.649762550659, "unit": "ms/iter", "extra": "iterations: 8\ncpu: 150.52570429655069 ms\nthreads: 1" }, { "name": "while_loop_10000", "value": 136.2891875848696, "unit": "ms/iter", "extra": "iterations: 9\ncpu: 136.27978117487365 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 26.964277240354992, "unit": "ms/iter", "extra": "iterations: 44\ncpu: 26.962392495392724 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.0050002811391339965, "unit": "ms/iter", "extra": "iterations: 235905\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "dddcc30b44ca123af45d6f88c77eceae12c8ee14", "message": "test for continue and break is ok", "timestamp": "2022-03-14T12:12:04+08:00", "tree_id": "359289f2275c3f4a4bbef63832d1e06042affacf", "url": "https://github.com/pikasTech/pikascript/commit/dddcc30b44ca123af45d6f88c77eceae12c8ee14" }, "date": 1647231458974, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 1870.3363586721425, "unit": "Point/iter", "extra": 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"committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "c21a1cfc3b198f8ab4490e2a63f10c434aed86b3", "message": "use ARG_TYPE to run method", "timestamp": "2022-03-14T13:54:10+08:00", "tree_id": "0674d18e6c964e53afce6d7a14830978141d2a3e", "url": "https://github.com/pikasTech/pikascript/commit/c21a1cfc3b198f8ab4490e2a63f10c434aed86b3" }, "date": 1647237516397, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 1985.4970490163614, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 1985.4970490163614 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 140.32632901931092, "unit": "ms/iter", "extra": "iterations: 8\ncpu: 140.24274323776945 ms\nthreads: 1" }, { "name": "while_loop_10000", "value": 121.65143698203882, "unit": "ms/iter", "extra": "iterations: 10\ncpu: 121.64737754174348 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 25.192576797814613, "unit": "ms/iter", "extra": "iterations: 47\ncpu: 25.182611087118254 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.005000171096237339, "unit": "ms/iter", "extra": "iterations: 235872\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "7f0413a458364154d30a545076f5fa6004aac452", "message": "run frame_buff in local is not ok", "timestamp": "2022-03-14T14:04:21+08:00", "tree_id": "2f730d979b30abcea6c2d7eaa6a1d614320b9ef6", "url": "https://github.com/pikasTech/pikascript/commit/7f0413a458364154d30a545076f5fa6004aac452" }, "date": 1647238145214, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 1988.9385474023725, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 1988.9385474023725 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 140.7318703061749, "unit": 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"ms/iter", "extra": "iterations: 143\ncpu: 12.347482428372539 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 3.0888754575581485, "unit": "ms/iter", "extra": "iterations: 569\ncpu: 3.0886857892479895 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.0050004252715791855, "unit": "ms/iter", "extra": "iterations: 352482\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "89487381+b4yuan@users.noreply.github.com", "name": "Brian", "username": "b4yuan" }, "committer": { "email": "noreply@github.com", "name": "GitHub", "username": "web-flow" }, "distinct": true, "id": "fba5e0b8ae2e65eb22acbc9f1109ac8d808d6f7c", "message": "Add CodeQL Workflow for Code Security Analysis (#331)\n\n* Add CodeQL Workflow for Code Security Analysis\r\n\r\nAdd CodeQL Workflow for Code Security Analysis\r\n\r\nThis pull request introduces a CodeQL workflow to enhance the security analysis of our repository. CodeQL is a powerful static analysis tool that helps identify and mitigate security vulnerabilities in our codebase. By integrating this workflow into our GitHub Actions, we can proactively identify and address potential issues before they become security threats.\r\n\r\nWe added a new CodeQL workflow file (.github/workflows/codeql.yml) that\r\n- Runs on every push and pull request to the main branch.\r\n- Excludes queries with a high false positive rate or low-severity findings.\r\n- Does not display results for third-party code, focusing only on our own codebase.\r\n\r\nTesting:\r\nTo validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.\r\n\r\nDeployment:\r\nOnce this pull request is merged, the CodeQL workflow will be active and automatically run on every push and pull request to the main branch. To view the results of these code scans, please follow these steps:\r\n1. Under the repository name, click on the Security tab.\r\n2. In the left sidebar, click Code scanning alerts.\r\n\r\nAdditional Information:\r\n- You can further customize the workflow to adapt to your specific needs by modifying the workflow file.\r\n- For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation.\r\n\r\nSigned-off-by: Brian \r\n\r\n* Add CodeQL Workflow for Code Security Analysis\r\n\r\nAdd CodeQL Workflow for Code Security Analysis\r\n\r\nThis pull request introduces a CodeQL workflow to enhance the security analysis of our repository. CodeQL is a powerful static analysis tool that helps identify and mitigate security vulnerabilities in our codebase. By integrating this workflow into our GitHub Actions, we can proactively identify and address potential issues before they become security threats.\r\n\r\nWe added a new CodeQL workflow file (.github/workflows/codeql.yml) that\r\n- Runs on every pull request (functionality to run on every push to main branches is included as a comment for convenience).\r\n- Runs daily.\r\n- Excludes queries with a high false positive rate or low-severity findings.\r\n- Does not display results for git submodules, focusing only on our own codebase.\r\n\r\nTesting:\r\nTo validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.\r\n\r\nDeployment:\r\nOnce this pull request is merged, the CodeQL workflow will be active and automatically run on every push and pull request to the main branch. To view the results of these code scans, please follow these steps:\r\n1. Under the repository name, click on the Security tab.\r\n2. In the left sidebar, click Code scanning alerts.\r\n\r\nAdditional Information:\r\n- You can further customize the workflow to adapt to your specific needs by modifying the workflow file.\r\n- For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation (https://codeql.github.com/ and https://codeql.github.com/docs/).\r\n\r\nSigned-off-by: Brian \r\n\r\n* Add CodeQL Workflow for Code Security Analysis\r\n\r\nAdd CodeQL Workflow for Code Security Analysis\r\n\r\nThis pull request introduces a CodeQL workflow to enhance the security analysis of our repository. CodeQL is a powerful static analysis tool that helps identify and mitigate security vulnerabilities in our codebase. By integrating this workflow into our GitHub Actions, we can proactively identify and address potential issues before they become security threats.\r\n\r\nWe added a new CodeQL workflow file (.github/workflows/codeql.yml) that\r\n- Runs on every pull request (functionality to run on every push to main branches is included as a comment for convenience).\r\n- Runs daily.\r\n- Excludes queries with a high false positive rate or low-severity findings.\r\n- Does not display results for git submodules, focusing only on our own codebase.\r\n\r\nTesting:\r\nTo validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.\r\n\r\nDeployment:\r\nOnce this pull request is merged, the CodeQL workflow will be active and automatically run on every push and pull request to the main branch. To view the results of these code scans, please follow these steps:\r\n1. Under the repository name, click on the Security tab.\r\n2. In the left sidebar, click Code scanning alerts.\r\n\r\nAdditional Information:\r\n- You can further customize the workflow to adapt to your specific needs by modifying the workflow file.\r\n- For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation (https://codeql.github.com/ and https://codeql.github.com/docs/).\r\n\r\nSigned-off-by: Brian \r\n\r\n* Add CodeQL Workflow for Code Security Analysis\r\n\r\nAdd CodeQL Workflow for Code Security Analysis\r\n\r\nThis pull request introduces a CodeQL workflow to enhance the security analysis of our repository. CodeQL is a powerful static analysis tool that helps identify and mitigate security vulnerabilities in our codebase. By integrating this workflow into our GitHub Actions, we can proactively identify and address potential issues before they become security threats.\r\n\r\nWe added a new CodeQL workflow file (.github/workflows/codeql.yml) that\r\n- Runs on every pull request (functionality to run on every push to main branches is included as a comment for convenience).\r\n- Runs daily.\r\n- Excludes queries with a high false positive rate or low-severity findings.\r\n- Does not display results for git submodules, focusing only on our own codebase.\r\n\r\nTesting:\r\nTo validate the functionality of this workflow, we have run several test scans on the codebase and reviewed the results. The workflow successfully compiles the project, identifies issues, and provides actionable insights while reducing noise by excluding certain queries and third-party code.\r\n\r\nDeployment:\r\nOnce this pull request is merged, the CodeQL workflow will be active and automatically run on every push and pull request to the main branch. To view the results of these code scans, please follow these steps:\r\n1. Under the repository name, click on the Security tab.\r\n2. In the left sidebar, click Code scanning alerts.\r\n\r\nAdditional Information:\r\n- You can further customize the workflow to adapt to your specific needs by modifying the workflow file.\r\n- For more information on CodeQL and how to interpret its results, refer to the GitHub documentation and the CodeQL documentation (https://codeql.github.com/ and https://codeql.github.com/docs/).\r\n\r\nSigned-off-by: Brian \r\n\r\n* Remove failing on error and clean up codeql.yml\r\n\r\n---------\r\n\r\nSigned-off-by: Brian ", "timestamp": "2023-12-03T01:51:52+08:00", "tree_id": "487a560a33455e2deef8cf7e971c3ae3f65f2d60", "url": "https://github.com/pikasTech/PikaPython/commit/fba5e0b8ae2e65eb22acbc9f1109ac8d808d6f7c" }, "date": 1701541281377, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 16199.494313773574, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 16199.494313773574 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 24.202168079045606, "unit": 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"prime_number_100_c", "value": 0.005000109196306005, "unit": "ms/iter", "extra": "iterations: 351946\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "eea7dbd0fc22e24f019c51d89fd8f8ef550b5db1", "message": "fix mem lack, get_blob for default_kvs not work", "timestamp": "2023-12-06T23:57:48+08:00", "tree_id": "c918382d0990ec42b80bc69ab6fbd528d151ef68", "url": "https://github.com/pikasTech/PikaPython/commit/eea7dbd0fc22e24f019c51d89fd8f8ef550b5db1" }, "date": 1701880838162, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 16533.645723402657, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 16533.645723402657 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 24.473581199994758, "unit": "ms/iter", "extra": "iterations: 72\ncpu: 24.47125358515377 ms\nthreads: 1" }, { "name": "while_loop_10000", "value": 12.992415208498109, "unit": "ms/iter", "extra": "iterations: 137\ncpu: 12.992512060499118 ms\nthreads: 1" }, { "name": "for_print_1000", "value": 12.515355289782935, "unit": "ms/iter", "extra": "iterations: 142\ncpu: 12.51450310913815 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 3.024172695529679, "unit": "ms/iter", "extra": "iterations: 587\ncpu: 3.024136408658326 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.005000281656387929, "unit": "ms/iter", "extra": "iterations: 354577\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "3efc4488592517ee60247649b762f1c424cda1ef", "message": "rename FDB to KVDB", "timestamp": "2023-12-07T22:22:42+08:00", "tree_id": "70ccc91afee81493f530e79b6fcc5772ccaf6158", "url": "https://github.com/pikasTech/PikaPython/commit/3efc4488592517ee60247649b762f1c424cda1ef" }, "date": 1701962887585, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 15802.307038024293, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 15802.307038024293 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 24.473400801344038, "unit": "ms/iter", "extra": "iterations: 72\ncpu: 24.472824568739007 ms\nthreads: 1" }, { "name": "while_loop_10000", "value": 13.502488888098142, "unit": "ms/iter", "extra": "iterations: 131\ncpu: 13.502433588954803 ms\nthreads: 1" }, { "name": "for_print_1000", "value": 12.037028891853469, "unit": "ms/iter", "extra": "iterations: 147\ncpu: 12.036864366007585 ms\nthreads: 1" }, { "name": "prime_number_100", "value": 3.164198761178796, "unit": "ms/iter", "extra": "iterations: 557\ncpu: 3.16409495649512 ms\nthreads: 1" }, { "name": "prime_number_100_c", "value": 0.005000197083199238, "unit": "ms/iter", "extra": "iterations: 354752\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "be098b033cf2a9e2ed7c49e9d6adf4905b5d9c93", "message": "fix flashdb test assert", "timestamp": "2023-12-07T23:03:01+08:00", "tree_id": "9f7de965a01fd7ac92c78991a14edc1be831b9c2", "url": "https://github.com/pikasTech/PikaPython/commit/be098b033cf2a9e2ed7c49e9d6adf4905b5d9c93" }, "date": 1701963474539, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 15850.557938952586, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 15850.557938952586 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 24.220372609550253, "unit": "ms/iter", "extra": "iterations: 73\ncpu: 24.22076413645691 ms\nthreads: 1" }, { "name": "while_loop_10000", 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354977\ncpu: 0.005 ms\nthreads: 1" } ] }, { "commit": { "author": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "committer": { "email": "liang6516@outlook.com", "name": "lyon1998", "username": "pikasTech" }, "distinct": true, "id": "0a02e54ae0c9de11ac2fc8bc151950630d3425ad", "message": "update pdsc for v1.13.0", "timestamp": "2023-12-16T21:24:05+08:00", "tree_id": "f35486cd87ffcbe7e2f38559f5ba54f7fa322604", "url": "https://github.com/pikasTech/PikaPython/commit/0a02e54ae0c9de11ac2fc8bc151950630d3425ad" }, "date": 1702734947705, "tool": "googlecpp", "benches": [ { "name": "Performance Points", "value": 15653.162055353027, "unit": "Point/iter", "extra": "iterations: 1\ncpu: 15653.162055353027 Point\nthreads: 1" }, { "name": "for_loop_10000", "value": 24.784412657330954, "unit": "ms/iter", "extra": "iterations: 71\ncpu: 24.78366153957803 ms\nthreads: 1" }, { "name": "while_loop_10000", "value": 13.76779775577368, "unit": "ms/iter", "extra": 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