{"library":"numpy-rms","title":"NumPy RMS","description":"numpy-rms is a fast Python library designed for calculating the Root Mean Square (RMS) of NumPy arrays. It leverages C implementations with SIMD acceleration (AVX on x86-64, NEON on ARM) to provide significant performance benefits, especially for 1-dimensional and 2-dimensional C-contiguous float32 arrays. The current version is 0.6.0, with a fairly active release cadence.","language":"python","status":"active","last_verified":"Fri May 15","install":{"commands":["pip install numpy-rms"],"cli":null},"imports":["import numpy_rms\nrms_value = numpy_rms.rms(arr, window_size=10)"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import numpy_rms\nimport numpy as np\n\narr = np.arange(40, dtype=np.float32)\nrms_series = numpy_rms.rms(arr, window_size=10)\nprint(f\"Original array shape: {arr.shape}\")\nprint(f\"RMS series shape: {rms_series.shape}\")\nprint(f\"First few RMS values: {rms_series[:5]}\")","lang":"python","description":"This quickstart demonstrates how to import `numpy_rms` and calculate a series of RMS values for a 1D NumPy array with a specified window size. Ensure your input array is `float32` for optimal performance.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-15","installed_version":"0.6.0","pypi_latest":"0.6.0","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":3.9,"avg_import_s":0.24,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.23,"mem_mb":6.7,"disk_size":"90.9M"},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":3.8,"import_time_s":0.19,"mem_mb":6.7,"disk_size":"87M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.26,"mem_mb":7.2,"disk_size":"98.7M"},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":3.7,"import_time_s":0.3,"mem_mb":7.2,"disk_size":"94M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.24,"mem_mb":7,"disk_size":"87.0M"},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":3.6,"import_time_s":0.32,"mem_mb":7,"disk_size":"83M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.24,"mem_mb":7.6,"disk_size":"86.6M"},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":3.7,"import_time_s":0.32,"mem_mb":7.6,"disk_size":"82M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.15,"mem_mb":6.5,"disk_size":"99.4M"},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"numpy-rms","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":4.5,"import_time_s":0.19,"mem_mb":6.5,"disk_size":"98M"}]}}