gitea
04bd1238d2
此版本改动较大，公共部分做了规整，放置到新建文件夹 commons 当中，并所有自定义模块引入 logging 模块，记录重要信息 1. [t_change_ui: clibs.py] - 调整代码组织结构，新增模块，将公共函数以及类合并入此 - 将一些常量放入该模块 - 引入logging/concurrent_log_handler模块，并作初始化操作，供其他模块使用，按50M切割，最多保留10份 - prj_to_xcore函数设置工程名部分重写，修复了多个prj工程可能不能执行的问题 2. [t_change_ui: openapi.py] - 完全重写了 get_from_id 函数，使更精准 - 在 msg_storage 函数中，增加 logger，保留所有响应消息 - 删除 heartbeat 函数中的日志保存功能部分 - 心跳再次修改为 2s... 3. [t_change_ui: aio.py] - 增加了日志初始化部分 - detect_network 函数中修改重新实例化HR间隔为 4s，对应心跳 4. [t_change_ui: do_brake.py] - 使用一直打开曲线的方法规避解决了 OOM 的问题，同时修改数据处理方式，只取最后 12s 5. [t_change_ui: do_current.py] - 保持电流，只取最后 15s 6. [t_change_ui: all the part]: 引入 commons 包，并定制了 logging 输出，后续持续优化
184 lines
8.5 KiB
Python
184 lines
8.5 KiB
Python
# _*_ encoding：utf-8 _*_
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import pdfplumber
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from openpyxl import load_workbook
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from os import remove
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from sys import argv
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from logging import getLogger
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from commons import clibs
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logger = getLogger(__file__)
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def p_iso(file, p_files, ws, tmpfile):
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p_files.append(file)
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pdf = pdfplumber.open(file)
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with open(tmpfile, mode='w', encoding='utf-8') as fb:
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for page in pdf.pages:
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fb.write(page.extract_text())
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with open(tmpfile, mode='r', encoding='utf-8') as fb:
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lines = fb.readlines()
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lines = [line for line in lines if not line.startswith('Page ')]
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for line in lines:
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if line.strip() == "Pose Accuracy and Repeatability":
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index = lines.index(line)
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ws.cell(row=3, column=7).value = float(lines[index+4].split()[1])
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ws.cell(row=4, column=7).value = float(lines[index+5].split()[1])
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ws.cell(row=5, column=7).value = float(lines[index+6].split()[1])
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ws.cell(row=6, column=7).value = float(lines[index+7].split()[1])
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ws.cell(row=7, column=7).value = float(lines[index+8].split()[1])
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ws.cell(row=8, column=7).value = float(lines[index+4].split()[2])
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ws.cell(row=9, column=7).value = float(lines[index+5].split()[2])
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ws.cell(row=10, column=7).value = float(lines[index+6].split()[2])
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ws.cell(row=11, column=7).value = float(lines[index+7].split()[2])
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ws.cell(row=12, column=7).value = float(lines[index+8].split()[2])
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elif line.strip() == 'Pose Accuracy Variation':
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index = lines.index(line)
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ws.cell(row=13, column=7).value = float(lines[index+4].split()[1])
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ws.cell(row=14, column=7).value = float(lines[index+5].split()[1])
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ws.cell(row=15, column=7).value = float(lines[index+6].split()[1])
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elif line.strip() == 'Distance Accuracy':
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index = lines.index(line)
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ws.cell(row=16, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=17, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Stabilisation Time and Overshoot':
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index = lines.index(line)
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ws.cell(row=18, column=7).value = float(lines[index + 7].split()[3])
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ws.cell(row=19, column=7).value = float(lines[index + 7].split()[2])
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elif line.strip() == 'Velocity Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=20, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=21, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=22, column=7).value = float(lines[index + 4].split()[3])
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elif line.strip()[:31] == 'Path Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=29, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=30, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Corner Overshoot and Roundoff':
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index = lines.index(line)
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ws.cell(row=35, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=36, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Robot Weaving':
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index = lines.index(line)
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ws.cell(row=41, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=42, column=7).value = float(lines[index + 4].split()[3])
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ws.cell(row=43, column=7).value = float(lines[index + 4].split()[4])
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else:
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pass
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def p_iso_100(file, p_files, ws, tmpfile):
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p_files.append(file)
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pdf = pdfplumber.open(file)
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with open(tmpfile, mode='w', encoding='utf-8') as fb:
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for page in pdf.pages:
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fb.write(page.extract_text())
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with open(tmpfile, mode='r', encoding='utf-8') as fb:
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lines = fb.readlines()
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lines = [line for line in lines if not line.startswith('Page ')]
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for line in lines:
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if line.strip() == 'Velocity Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=26, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=27, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=28, column=7).value = float(lines[index + 4].split()[3])
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elif line.strip()[:31] == 'Path Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=33, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=34, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Corner Overshoot and Roundoff':
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index = lines.index(line)
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ws.cell(row=39, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=40, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Robot Weaving':
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index = lines.index(line)
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ws.cell(row=47, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=48, column=7).value = float(lines[index + 4].split()[3])
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ws.cell(row=49, column=7).value = float(lines[index + 4].split()[4])
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else:
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pass
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def p_iso_1000(file, p_files, ws, tmpfile):
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p_files.append(file)
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pdf = pdfplumber.open(file)
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with open(tmpfile, mode='w', encoding='utf-8') as fb:
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for page in pdf.pages:
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fb.write(page.extract_text())
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with open(tmpfile, mode='r', encoding='utf-8') as fb:
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lines = fb.readlines()
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lines = [line for line in lines if not line.startswith('Page ')]
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for line in lines:
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if line.strip() == 'Velocity Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=23, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=24, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=25, column=7).value = float(lines[index + 4].split()[3])
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elif line.strip()[:31] == 'Path Accuracy and Repeatability':
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index = lines.index(line)
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ws.cell(row=31, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=32, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Corner Overshoot and Roundoff':
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index = lines.index(line)
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ws.cell(row=37, column=7).value = float(lines[index + 4].split()[1])
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ws.cell(row=38, column=7).value = float(lines[index + 4].split()[2])
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elif line.strip() == 'Robot Weaving':
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index = lines.index(line)
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ws.cell(row=44, column=7).value = float(lines[index + 4].split()[2])
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ws.cell(row=45, column=7).value = float(lines[index + 4].split()[3])
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ws.cell(row=46, column=7).value = float(lines[index + 4].split()[4])
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else:
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pass
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def main(path, w2t):
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dirs, files = clibs.traversal_files(path, 1)
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try:
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wb = load_workbook(path + "/iso-results.xlsx")
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ws = wb.active
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for i in range(3, 50):
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ws.cell(row=i, column=7).value = None
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tmpfile = f"{path}\\data.txt"
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except Exception as Err:
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w2t(f"发生错误：{Err}", 0, 2, 'red')
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p_files = []
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for file in files:
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if file.endswith('.pdf') and file.split('\\')[-1] == 'ISO.pdf':
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w2t(f"正在处理{file}......")
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p_iso(file, p_files, ws, tmpfile)
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w2t(f"文件{file}已处理完毕。\n")
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elif file.endswith('.pdf') and file.split('\\')[-1] == 'ISO-V100.pdf':
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w2t(f"正在处理{file}......")
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p_iso_100(file, p_files, ws, tmpfile)
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w2t(f"文件{file}已处理完毕。\n")
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elif file.endswith('.pdf') and file.split('\\')[-1] == 'ISO-V1000.pdf':
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w2t(f"正在处理{file}......")
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p_iso_1000(file, p_files, ws, tmpfile)
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w2t(f"文件{file}已处理完毕。\n")
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else:
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pass
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wb.save(path + '/iso-results.xlsx')
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wb.close()
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if len(p_files) == 0:
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w2t(f"目录 {path} 下没有需要处理的文件，需要确认......", 0, 3, 'red')
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else:
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remove(tmpfile)
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w2t("------------------------------------------")
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w2t("所有文件均已处理完毕！")
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if __name__ == '__main__':
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main(path=argv[1], w2t=argv[2])
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