| | |
|---|
| | | return __time * 3600, (__time + 1) * 3600 |
|---|
| | | |
|---|
| | | |
|---|
| | | # 获取买入时间范围 |
|---|
| | | def get_buy_time_range(cancel_data): |
|---|
| | | # 计算时间区间 |
|---|
| | | min_space, max_space = compute_time_space_as_second(cancel_data["val"]["cancelTime"], |
|---|
| | | cancel_data["val"]["cancelTimeUnit"]) |
|---|
| | | max_time = __sub_time(cancel_data["val"]["time"], min_space) |
|---|
| | | min_time = __sub_time(cancel_data["val"]["time"], max_space) |
|---|
| | | return min_time, max_time |
|---|
| | | |
|---|
| | | |
|---|
| | | # 根据买撤数据(与今日总的数据)计算买入数据 |
|---|
| | | def get_buy_data_with_cancel_data(cancel_data, local_today_num_operate_map): |
|---|
| | | # 计算时间区间 |
|---|
| | | min_space, max_space = compute_time_space_as_second(cancel_data["val"]["cancelTime"], |
|---|
| | | cancel_data["val"]["cancelTimeUnit"]) |
|---|
| | | max_time = __sub_time(cancel_data["val"]["time"], min_space) |
|---|
