if not os.path.exists(LOG_PATH):
时间: 2024-04-23 12:28:08 浏览: 10
如果你想检查 `LOG_PATH` 路径是否存在并执行相应的操作,你可以使用以下代码:
```python
import os
if not os.path.exists(LOG_PATH):
# 执行你想要的操作,例如创建文件夹或者进行其他处理
os.makedirs(LOG_PATH)
```
在这个例子中,`os.path.exists(LOG_PATH)` 用于检查路径是否存在。如果路径不存在,`os.makedirs(LOG_PATH)` 可以用来创建该路径。你可以在这个条件下执行你想要的操作。
相关问题
优化代码 def fault_classification_wrapper(vin, main_path, data_path, log_path, done_path): start_time = time.time() isc_path = os.path.join(done_path, vin, 'isc_cal_result', f'{vin}_report.xlsx') if not os.path.exists(isc_path): print('No isc detection input!') else: isc_input = isc_produce_alarm(isc_path, vin) ica_path = os.path.join(done_path, vin, 'ica_cal_result', f'ica_detection_alarm_{vin}.csv') if not os.path.exists(ica_path): print('No ica detection input!') else: ica_input = ica_produce_alarm(ica_path) soh_path = os.path.join(done_path, vin, 'SOH_cal_result', f'{vin}_sohAno.csv') if not os.path.exists(soh_path): print('No soh detection input!') else: soh_input = soh_produce_alarm(soh_path, vin) alarm_df = pd.concat([isc_input, ica_input, soh_input]) alarm_df.reset_index(drop=True, inplace=True) alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(lambda _: str(_)) print(vin) module = AutoAnalysisMain(alarm_df, main_path, data_path, done_path) module.analysis_process() flags = os.O_WRONLY | os.O_CREAT modes = stat.S_IWUSR | stat.S_IRUSR with os.fdopen(os.open(os.path.join(log_path, 'log.txt'), flags, modes), 'w') as txt_file: for k, v in module.output.items(): txt_file.write(k + ':' + str(v)) txt_file.write('\n') for x, y in module.output_sub.items(): txt_file.write(x + ':' + str(y)) txt_file.write('\n\n') fc_result_path = os.path.join(done_path, vin, 'fc_result') if not os.path.exists(fc_result_path): os.makedirs(fc_result_path) pd.DataFrame(module.output).to_csv( os.path.join(fc_result_path, 'main_structure.csv')) df2 = pd.DataFrame() for subs in module.output_sub.keys(): sub_s = pd.Series(module.output_sub[subs]) df2 = df2.append(sub_s, ignore_index=True) df2.to_csv(os.path.join(fc_result_path, 'sub_structure.csv')) end_time = time.time() print("time cost of fault classification:", float(end_time - start_time) * 1000.0, "ms") return
Here are some suggestions to optimize the code:
1. Use list comprehension to simplify the code:
```
alarm_df = pd.concat([isc_input, ica_input, soh_input]).reset_index(drop=True)
alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(str)
```
2. Use context manager to simplify file operation:
```
with open(os.path.join(log_path, 'log.txt'), 'w') as txt_file:
for k, v in module.output.items():
txt_file.write(f"{k}:{v}\n")
for x, y in module.output_sub.items():
txt_file.write(f"{x}:{y}\n\n")
```
3. Use `Pathlib` to simplify path operation:
```
fc_result_path = Path(done_path) / vin / 'fc_result'
fc_result_path.mkdir(parents=True, exist_ok=True)
pd.DataFrame(module.output).to_csv(fc_result_path / 'main_structure.csv')
pd.DataFrame(module.output_sub).to_csv(fc_result_path / 'sub_structure.csv')
```
4. Use f-string to simplify string formatting:
```
print(f"time cost of fault classification: {(end_time - start_time) * 1000.0} ms")
```
Here's the optimized code:
```
def fault_classification_wrapper(vin, main_path, data_path, log_path, done_path):
start_time = time.time()
isc_path = Path(done_path) / vin / 'isc_cal_result' / f'{vin}_report.xlsx'
if not isc_path.exists():
print('No isc detection input!')
isc_input = pd.DataFrame()
else:
isc_input = isc_produce_alarm(isc_path, vin)
ica_path = Path(done_path) / vin / 'ica_cal_result' / f'ica_detection_alarm_{vin}.csv'
if not ica_path.exists():
print('No ica detection input!')
ica_input = pd.DataFrame()
else:
ica_input = ica_produce_alarm(ica_path)
soh_path = Path(done_path) / vin / 'SOH_cal_result' / f'{vin}_sohAno.csv'
if not soh_path.exists():
print('No soh detection input!')
soh_input = pd.DataFrame()
else:
soh_input = soh_produce_alarm(soh_path, vin)
alarm_df = pd.concat([isc_input, ica_input, soh_input]).reset_index(drop=True)
alarm_df['alarm_cell'] = alarm_df['alarm_cell'].apply(str)
print(vin)
module = AutoAnalysisMain(alarm_df, main_path, data_path, done_path)
module.analysis_process()
with open(Path(log_path) / 'log.txt', 'w') as txt_file:
for k, v in module.output.items():
txt_file.write(f"{k}:{v}\n")
for x, y in module.output_sub.items():
txt_file.write(f"{x}:{y}\n\n")
fc_result_path = Path(done_path) / vin / 'fc_result'
fc_result_path.mkdir(parents=True, exist_ok=True)
pd.DataFrame(module.output).to_csv(fc_result_path / 'main_structure.csv')
pd.DataFrame(module.output_sub).to_csv(fc_result_path / 'sub_structure.csv')
end_time = time.time()
print(f"time cost of fault classification: {(end_time - start_time) * 1000.0} ms")
return
```
优化代码:def save_file(data, out_path): if not os.path.exists(out_path): os.mkdir(out_path) with open(out_path, 'w') as f: json.dump(data, f)
可以尝试使用os.makedirs()代替os.mkdir(),因为前者能够递归创建路径中的所有文件夹。
同时,建议添加异常处理,以确保在发生错误时代码不会崩溃。例如,可以使用try-except语句来捕获文件打开或写入错误,并进行相应处理。最好将错误信息记录到日志文件中,以便后续查看和调试。
修改后的代码如下:
```python
import os
import json
def save_file(data, out_path):
try:
os.makedirs(out_path, exist_ok=True)
with open(out_path, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False)
except Exception as e:
# 记录错误信息到日志文件中
with open('error.log', 'a', encoding='utf-8') as f:
f.write(f'Error in save_file: {str(e)}\n')
```
其中,`exist_ok=True`表示如果目录已经存在则不会报错,`ensure_ascii=False`表示以utf-8编码写入json文件,避免中文出现乱码。同时,异常处理语句可以根据具体情况进行修改和优化。