def prepare(filePath: str) -> Tuple[List[str], pd.DataFrame]:
files = os.listdir(filePath)
# 已处理文件
dataOld = readJson(saveM['Record']['Path'], funcClass)
filesNew = list(set(files).difference(set(dataOld)))
# 读取权重数据
weight = getData(readM['weight500'], DBN.PKL)
return filesNew, weight
def prepare(filePath: str) -> List[Tuple[str, str]]:
with open(filePath, 'rb') as f:
UpLimitStock = pickle.load(f)
data = (UpLimitStock['date'] + '_' + UpLimitStock['stock_id']).to_list()
# 已处理文件
dataOld = readJson(saveM['Record']['Path'], funcClass)
# 数据参数
UpLimitStock_ID = list(set(data).difference(set(dataOld)))
return UpLimitStock_ID
def prepare(filePath: str) -> List[str]:
folderFiles = os.listdir(filePath)
# 已处理文件
dataOld = readJson(saveM['Record']['Path'], funcClass)
# 过滤文件夹
folderFiles = [file_ for file_ in folderFiles if len(file_.split('.')) == 1]
# 生成文件夹
subFolderPath = []
for subFolder in folderFiles:
subFolders2 = os.listdir(os.path.join(filePath, subFolder))
# 过滤已处理文件
subFoldersE = list(set(subFolders2).difference(set(dataOld)))
subFolderPath += [os.path.join(os.path.join(filePath, subFolder), x) for x in subFoldersE]
return subFolderPath
def prepare(filePath: str) -> List[str]:
files = os.listdir(filePath)
# 已处理文件
dataOld = readJson(saveM['Record']['Path'], funcClass)
filesNew = list(set(files).difference(set(dataOld)))
return filesNew