03aa368776
* add the comparison between latest test and last one to html * resolve some comments * modify some code logics
59 lines
No EOL
2.2 KiB
Python
59 lines
No EOL
2.2 KiB
Python
#
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# Copyright 2016 The BigDL Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# Python program to convert CSV to HTML Table
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import os
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import sys
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import argparse
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import pandas as pd
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def main():
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parser = argparse.ArgumentParser(description="convert .csv file to .html file")
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parser.add_argument("-f", "--folder_path", type=str, dest="folder_path",
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help="The directory which stores the .csv file", default="/mnt/disk1/nightly_perf/")
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args = parser.parse_args()
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csv_files = []
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for file_name in os.listdir(args.folder_path):
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file_path = os.path.join(args.folder_path, file_name)
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if os.path.isfile(file_path) and file_name.endswith(".csv"):
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csv_files.append(file_path)
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csv_files.sort(reverse=True)
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data1 = pd.read_csv(csv_files[0], index_col=0)
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if len(csv_files)>1:
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data2 = pd.read_csv(csv_files[1], index_col=0)
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origin_column_1='1st token avg latency (ms)'
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origin_column_2='2+ avg latency (ms/token)'
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added_column_1='last1'
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added_column_2='diff1(%)'
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added_column_3='last2'
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added_column_4='diff2(%)'
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data1.insert(loc=3,column=added_column_1,value=data2[origin_column_1])
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data1.insert(loc=4,column=added_column_2,value=round((data2[origin_column_1]-data1[origin_column_1])*100/data2[origin_column_1],2))
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data1.insert(loc=5,column=added_column_3,value=data2[origin_column_2])
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data1.insert(loc=6,column=added_column_4,value=round((data2[origin_column_2]-data1[origin_column_2])*100/data2[origin_column_2],2))
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daily_html=csv_files[0].split(".")[0]+".html"
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data1.to_html(daily_html)
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if __name__ == "__main__":
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sys.exit(main()) |