FrePPle embeds an interpreter for the Python programming language. The full capabilities of this scripting language and its rich library are accessible from frePPLe, and Python also has access to the frePPLe objects in memory.
Python is thus a very powerful way to interact with the planning engine. For complex data integration tasks and for customization of the algorithms Python is your big friend.
Here’s a simple annotated example of a Python script that is executed by the planning engine:
# Loads the planning engine as a Python module. import frepple # Use the standard Python module to read a CSV-formatted text file import csv with open('products.csv', newline='') as csvfile: csvreader = csv.reader(csvfile, delimiter=' ', quotechar='|') for row in csvreader: # The next line creates an item object in the frePPle core # planning engine. frepple.item(name=row, description=row) # Call the planning engine solver to create a fully constrained plan frepple.solver_mrp(plantype=1, constraints=15, loglevel=2).solve() # Echo the plan resultsto the screen: load of all resources for i in frepple.resources(): for j in i.loadplans: print(j.operationplan.id, j.resource.name, j.quantity, j.startdate, j.enddate) # Echo the plan resultsto the screen: inventory profile of all buffers for i in frepple.buffers(): for j in i.flowplans: print(j.operationplan.id, j.buffer.name, j.quantity, j.date, j.onhand)
You can execute a Python script either from the planning engine’s executable frepple(.exe), or you can run it from the standard Python executable and load the planning engine as an extension module.
There are plenty of sample Python scripts available:
- A very nice example is the code where the planning engine reads from the PostgreSQL database: https://github.com/frePPLe/frePPLe/blob/master/freppledb/input/commands.pyAn SQL statement is executed, and in the loop over the resulting records we create the objects in the planning engine’s memory.
- Another example is the code to write the plan results from the planning engine’s memory back to the database: https://github.com/frePPLe/frePPLe/blob/master/freppledb/execute/export_database_plan.pyWe loop over the relevant objects in memory, and send it to a PostgreSQL copy/insert/update command.