Python分析，导入（尤其是__init__）似乎是花费最多的时间

我有一个脚本，运行似乎很慢，并且使用cProfile（和可视化工具KCacheGrind）进行了概要分析

似乎占用了几乎90％的运行时间的是导入顺序，尤其是_ _ init _ _.py文件的运行...

这是KCacheGrind输出的屏幕截图（很抱歉，附加图片...）

我对导入序列在python中的工作方式不是很熟悉，所以也许我感到有些困惑...我也将_ _ init _ _.py文件放置在我的所有自定义软件包中，不确定是否应该这样做。

无论如何，如果有人有任何暗示，不胜感激！

EDIT: additional picture when function are sorted by self:

EDIT2:

here the code attached, for more clarity for the answerers:

from strategy.strategies.gradient_stop_and_target import make_one_trade

from datetime import timedelta, datetime
import pandas as pd
from data.db import get_df, mongo_read_only, save_one, mongo_read_write, save_many
from data.get import get_symbols

from strategy.trades import make_trade, make_mae, get_prices, get_signals, \
    get_prices_subset
#from profilehooks import profile


mongo = mongo_read_only()


dollar_stop = 200
dollar_target = 400
period_change = 3


signal = get_df(mongo.signals.signals, strategy = {'$regex' : '^indicators_group'}).iloc[0]


symbol = get_symbols(mongo, description = signal['symbol'])[0]


prices = get_prices(
    signal['datetime'], 
    signal['datetime'].replace(hour = 23, minute = 59),
    symbol,
    mongo)


make_one_trade(
    signal, 
    prices, 
    symbol,             
    dollar_stop,
    dollar_target,
    period_change)

The function get_prices simply get data from a mongo db database, and make_one_trade does simple calculation with pandas. This never poses problem anywhere else in my project.

EDIT3:

Here the Kcache grind screen when i select 'detect cycle' option in View tab:

Could that actually mean that there are indeed circular imports in my self created packages that takes all that time to resolve?