#Supplychainpy
Supplychainpy is a Python library for supply chain analysis, modeling and simulation. Use in conjunction with popular data analysis libraries and excel tools such as xlwings or openpyxl (for Excel spreadsheet applications).
The library is currently in early stages of development, so not ready for use in production. However some fun can be had
by passing a csv or text file in the correct format. For quick exploration, the analyse_orders_abcxyz_from_file
will output the following inventory analysis:
- economic order quantities
- safety stock
- abc xyz classification
- demand variability
- ...
##Quick Install
The easiest way to install supplychainpy is via pip: pip install supplychainpy
.
An alternative is to clone the repository and run python setup.py install
##Dependencies
- NumPy
##Optional Dependencies
- pandas
- matplotlib
- xlwings
- openpyxl
##Python Version
- python 3.5
##Quick Guide
-
Fire up the python interpreter or
ipython notebook
from the command line. -
Format the
.csv
or.txt
.e.gsku id
,order1
,order2
,...orders12
,unit cost
,lead time
,
At the moment the lead-time must match the orders time bucket i.e both should be in days, weeks or months. This will change promptly.
from xlwings import Workbook, Range
from supplychainpy.model_inventory import analyse_orders_abcxyz_from_file
wb = Workbook(r'~/Desktop/test.xlsx'), Range
abc = analyse_orders_abcxyz_from_file(file_path="data.csv", z_value= 1.28, reorder_cost=5000, file_type="csv")
for index ,sku in enumerate(abc.orders, 1):
Range('A'+ str(index)).value = sku.sku_id
Range('B' + str(index)).value = float(sku.economic_order_qty)
Range('C' + str(index)).value = float(sku.revenue)
Range('D' + str(index)).value = sku.abcxyz_classification
or get the whole analysis using:
from supplychainpy.model_inventory import analyse_orders_abcxyz_from_file
abc = analyse_orders_abcxyz_from_file(file_path="data.csv", z_value=Decimal(1.28),
reorder_cost=Decimal(5000), file_type="csv")
for sku in abc.orders:
print(sku.orders_summary())
Further examples and explanations will be available in the documentation. Please find below.
Documentation: supplychainpy.readthdocs
Website: supplychainpy.org
Forum: google groups