akrishnamo / invsim

inventory simulation module for sd

invsim

This is the repository for inventory simulation module for Safe Decor. It includes simulation and order recommendation functionality

Install

pip install invsim

How to use

Clip_date returns first non zero date if there are at least 30 elements, if not just returns the first date

Case1: there are more than 30 elements

ndays=40
leading_zero_days=5
dates=pd.date_range(start='2022-01-01', periods=ndays, freq='D')
values=[0]*leading_zero_days+[10]*(ndays-leading_zero_days)

df=pd.DataFrame({'date':dates, 'qty': values})
df['date']=df.date.apply(lambda x: x.date())
display(df.T)

print("clip date =", clip_date(df))

<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; }

.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}

</style>

	0	1	2	3	4	5	6	7	8	9	...	30	31	32	33	34	35	36	37	38	39
date	2022-01-01	2022-01-02	2022-01-03	2022-01-04	2022-01-05	2022-01-06	2022-01-07	2022-01-08	2022-01-09	2022-01-10	...	2022-01-31	2022-02-01	2022-02-02	2022-02-03	2022-02-04	2022-02-05	2022-02-06	2022-02-07	2022-02-08	2022-02-09
qty	0	0	0	0	0	10	10	10	10	10	...	10	10	10	10	10	10	10	10	10	10

2 rows × 40 columns

clip date = 2022-01-06

Case2: There are less than 30 elements

ndays=29
leading_zero_days=5
dates=pd.date_range(start='2022-01-01', periods=ndays, freq='D')
values=[0]*leading_zero_days+[10]*(ndays-leading_zero_days)

df=pd.DataFrame({'date':dates, 'qty': values})
df['date']=df.date.apply(lambda x: x.date())
display(df.T)

print("clip date =", clip_date(df))

<style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; }

.dataframe tbody tr th {
    vertical-align: top;
}

.dataframe thead th {
    text-align: right;
}

</style>

	0	1	2	3	4	5	6	7	8	9	...	19	20	21	22	23	24	25	26	27	28
date	2022-01-01	2022-01-02	2022-01-03	2022-01-04	2022-01-05	2022-01-06	2022-01-07	2022-01-08	2022-01-09	2022-01-10	...	2022-01-20	2022-01-21	2022-01-22	2022-01-23	2022-01-24	2022-01-25	2022-01-26	2022-01-27	2022-01-28	2022-01-29
qty	0	0	0	0	0	10	10	10	10	10	...	10	10	10	10	10	10	10	10	10	10

2 rows × 29 columns

clip date = 2022-01-01