69 lines
2.8 KiB
Python
69 lines
2.8 KiB
Python
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#!/usr/bin/python3
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# -*- coding: utf-8 -*-
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# Copyright (c) 2019 Huawei Technologies Co., Ltd.
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# A-Tune is licensed under the Mulan PSL v1.
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# You can use this software according to the terms and conditions of the Mulan PSL v1.
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# You may obtain a copy of Mulan PSL v1 at:
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# http://license.coscl.org.cn/MulanPSL
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# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR
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# PURPOSE.
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# See the Mulan PSL v1 for more details.
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# Create: 2019-10-29
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"""
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The parser to parse the output of perf-cpu.sh and perf-mem.sh.
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"""
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from __future__ import division
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from __future__ import print_function
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from . import base
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class PerfParser(base.Parser):
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"""The parser to parse the output of perf-cpu.sh and perf-mem.sh"""
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def __init__(self, raw_data_file, data_to_collect, interval=1, **kwargs):
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"""Initialize a perf parser.
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@param raw_data_file: the path of raw data
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@param data_to_collect: list of str which represents the metrics to parse
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@param interval: the interval time of data. It is only for perf-mem.sh.
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If you want to parse the output of perf-cpu.sh, please
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set interval to 1.
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@param alias: alias name of output fields (default: "perf")
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"""
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base.Parser.__init__(self, raw_data_file, data_to_collect, **kwargs)
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self._interval = interval
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def _check_data_to_collect(self):
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"""Read the first batch output of perf-cpu.sh or perf-mem.sh and check
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whether or not all metrics in data_to_collect are in the output. If
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not, it will raise ValueError.
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"""
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with open(self._raw_data_file, 'r') as raw_data_fd:
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raw_data_fd.readline()
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datas = raw_data_fd.readline().split()
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diff_set = set(self._data_to_collect) - set(datas)
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if diff_set:
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raise ValueError("`{}`: Unknown data name `{}`".format(self._raw_data_file, ','.join(diff_set)))
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def _get_iter(self):
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"""Get the iteration of the perf parser.
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@return: the iteration of the perf parser
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"""
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with open(self._raw_data_file, 'r') as raw_data_fd:
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raw_data_fd.readline()
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attrs = raw_data_fd.readline().split()
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for row_num, line in enumerate(raw_data_fd, 3):
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line_part = line.split()
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line_data = [float(d[:-1] if d.endswith('%') else d) / self._interval for d in line_part]
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if len(attrs) != len(line_data):
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print("WARNING: {}: Line {}: The number of columns may be wrong."
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.format(self._raw_data_file, row_num))
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return
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data = dict(zip(attrs, line_data))
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yield [data[attr] for attr in self._data_to_collect]
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