def handle(self, **options):
# Make sure the debug flag is not set!
# When it is set, the django database wrapper collects a list of all sql
# statements executed and their timings. This consumes plenty of memory
# and cpu time.
tmp_debug = settings.DEBUG
settings.DEBUG = False
# Pick up the options
if 'verbosity' in options:
verbosity = int(options['verbosity'])
else:
verbosity = 1
if 'cluster' in options:
cluster = int(options['cluster'])
else:
cluster = 100
if 'demand' in options:
demand = int(options['demand'])
else:
demand = 30
if 'forecast_per_item' in options:
forecast_per_item = int(options['forecast_per_item'])
else:
forecast_per_item = 50
if 'level' in options:
level = int(options['level'])
else:
level = 5
if 'resource' in options:
resource = int(options['resource'])
else:
resource = 60
if 'resource_size' in options:
resource_size = int(options['resource_size'])
else:
resource_size = 5
if 'components' in options:
components = int(options['components'])
else:
components = 200
if 'components_per' in options:
components_per = int(options['components_per'])
else:
components_per = 5
if components == 0:
components_per = 0
if 'deliver_lt' in options:
deliver_lt = int(options['deliver_lt'])
else:
deliver_lt = 30
if 'procure_lt' in options:
procure_lt = int(options['procure_lt'])
else:
procure_lt = 40
if 'currentdate' in options:
currentdate = options['currentdate'] or datetime.strftime(
date.today(), '%Y-%m-%d')
else:
currentdate = datetime.strftime(date.today(), '%Y-%m-%d')
if 'database' in options:
database = options['database'] or DEFAULT_DB_ALIAS
else:
database = DEFAULT_DB_ALIAS
if database not in settings.DATABASES:
raise CommandError("No database settings known for '%s'" %
database)
if 'user' in options and options['user']:
try:
user = User.objects.all().using(database).get(
username=options['user'])
except:
raise CommandError("User '%s' not found" % options['user'])
else:
user = None
random.seed(100) # Initialize random seed to get reproducible results
now = datetime.now()
task = None
try:
# Initialize the task
if 'task' in options and options['task']:
try:
task = Task.objects.all().using(database).get(
pk=options['task'])
except:
raise CommandError("Task identifier not found")
if task.started or task.finished or task.status != "Waiting" or task.name != 'generate model':
raise CommandError("Invalid task identifier")
task.status = '0%'
task.started = now
else:
task = Task(name='generate model',
submitted=now,
started=now,
status='0%',
user=user)
task.arguments = "--cluster=%s --demand=%s --forecast_per_item=%s --level=%s --resource=%s " \
"--resource_size=%s --components=%s --components_per=%s --deliver_lt=%s --procure_lt=%s" % (
cluster, demand, forecast_per_item, level, resource,
resource_size, components, components_per, deliver_lt, procure_lt
)
task.save(using=database)
# Pick up the startdate
try:
startdate = datetime.strptime(currentdate, '%Y-%m-%d')
except:
raise CommandError(
"current date is not matching format YYYY-MM-DD")
# Check whether the database is empty
if Buffer.objects.using(database).count(
) > 0 or Item.objects.using(database).count() > 0:
raise CommandError(
"Database must be empty before creating a model")
# Plan start date
if verbosity > 0:
print("Updating current date...")
Parameter.objects.using(database).create(name="currentdate",
value=datetime.strftime(
startdate,
"%Y-%m-%d %H:%M:%S"))
Parameter.objects.using(database).create(name="plan.loglevel",
value="3")
# Planning horizon
# minimum 10 daily buckets, weekly buckets till 40 days after current
if verbosity > 0:
print("Updating buckets...")
management.call_command('frepple_createbuckets',
user=user,
database=database)
task.status = '2%'
task.save(using=database)
# Weeks calendar
if verbosity > 0:
print("Creating weeks calendar...")
with transaction.atomic(using=database):
weeks = Calendar.objects.using(database).create(name="Weeks",
defaultvalue=0)
for i in BucketDetail.objects.using(database).filter(
bucket="week").all():
CalendarBucket(startdate=i.startdate,
enddate=i.enddate,
value=1,
calendar=weeks).save(using=database)
task.status = '4%'
task.save(using=database)
# Working days calendar
if verbosity > 0:
print("Creating working days...")
with transaction.atomic(using=database):
workingdays = Calendar.objects.using(database).create(
name="Working Days", defaultvalue=0)
minmax = BucketDetail.objects.using(database).filter(
bucket="week").aggregate(Min('startdate'),
Max('startdate'))
CalendarBucket(startdate=minmax['startdate__min'],
enddate=minmax['startdate__max'],
value=1,
calendar=workingdays,
priority=1,
saturday=False,
sunday=False).save(using=database)
task.status = '6%'
task.save(using=database)
# Parent location
loc = Location.objects.using(database).create(
name="Factory", available=workingdays)
# Create a random list of categories to choose from
categories = [
'cat A', 'cat B', 'cat C', 'cat D', 'cat E', 'cat F', 'cat G'
]
# Create customers
if verbosity > 0:
print("Creating customers...")
with transaction.atomic(using=database):
cust = []
for i in range(100):
c = Customer.objects.using(database).create(
name='Cust %03d' % i)
cust.append(c)
task.status = '8%'
task.save(using=database)
# Create resources and their calendars
if verbosity > 0:
print("Creating resources and calendars...")
with transaction.atomic(using=database):
res = []
for i in range(resource):
cal = Calendar.objects.using(database).create(
name='capacity for res %03d' % i,
category='capacity',
defaultvalue=0)
CalendarBucket.objects.using(database).create(
startdate=startdate, value=resource_size, calendar=cal)
r = Resource.objects.using(database).create(
name='Res %03d' % i,
maximum_calendar=cal,
location=loc)
res.append(r)
task.status = '10%'
task.save(using=database)
random.shuffle(res)
# Create the components
if verbosity > 0:
print("Creating raw materials...")
with transaction.atomic(using=database):
comps = []
compsupplier = Supplier.objects.using(database).create(
name='component supplier')
for i in range(components):
it = Item.objects.using(database).create(
name='Component %04d' % i,
category='Procured',
price=str(round(random.uniform(0, 100))))
ld = abs(
round(random.normalvariate(procure_lt,
procure_lt / 3)))
Buffer.objects.using(database).create(
name='%s @ %s' % (it.name, loc.name),
location=loc,
category='Procured',
item=it,
minimum=20,
onhand=str(
round(forecast_per_item * random.uniform(1, 3) *
ld / 30)),
)
ItemSupplier.objects.using(database).create(
item=it,
location=loc,
supplier=compsupplier,
leadtime=timedelta(days=ld),
sizeminimum=80,
sizemultiple=10,
priority=1,
cost=it.price)
comps.append(it)
task.status = '12%'
task.save(using=database)
# Loop over all clusters
durations = [timedelta(days=i) for i in range(1, 6)]
progress = 88.0 / cluster
for i in range(cluster):
with transaction.atomic(using=database):
if verbosity > 0:
print("Creating supply chain for end item %d..." % i)
# Item
it = Item.objects.using(database).create(
name='Itm %05d' % i,
category=random.choice(categories),
price=str(round(random.uniform(100, 200))))
# Level 0 buffer
buf = Buffer.objects.using(database).create(
name='%s @ %s' % (it.name, loc.name),
item=it,
location=loc,
category='00')
# Demand
for j in range(demand):
Demand.objects.using(database).create(
name='Dmd %05d %05d' % (i, j),
item=it,
location=loc,
quantity=int(random.uniform(1, 6)),
# Exponential distribution of due dates, with an average of deliver_lt days.
due=startdate + timedelta(days=round(
random.expovariate(float(1) / deliver_lt /
24)) / 24),
# Orders have higher priority than forecast
priority=random.choice([1, 2]),
customer=random.choice(cust),
category=random.choice(categories))
# Create upstream operations and buffers
ops = []
previtem = it
for k in range(level):
if k == 1 and res:
# Create a resource load for operations on level 1
oper = Operation.objects.using(database).create(
name='Oper %05d L%02d' % (i, k),
type='time_per',
location=loc,
duration_per=timedelta(days=1),
sizemultiple=1,
item=previtem)
if resource < cluster and i < resource:
# When there are more cluster than resources, we try to assure
# that each resource is loaded by at least 1 operation.
OperationResource.objects.using(
database).create(resource=res[i],
operation=oper)
else:
OperationResource.objects.using(
database).create(
resource=random.choice(res),
operation=oper)
else:
oper = Operation.objects.using(database).create(
name='Oper %05d L%02d' % (i, k),
duration=random.choice(durations),
sizemultiple=1,
location=loc,
item=previtem)
ops.append(oper)
# Some inventory in random buffers
if random.uniform(0, 1) > 0.8:
buf.onhand = int(random.uniform(5, 20))
buf.save(using=database)
OperationMaterial.objects.using(database).create(
operation=oper,
item=previtem,
quantity=1,
type="end")
if k != level - 1:
# Consume from the next level in the bill of material
it_tmp = Item.objects.using(database).create(
name='Itm %05d L%02d' % (i, k + 1),
category=random.choice(categories),
price=str(round(random.uniform(100, 200))))
buf = Buffer.objects.using(database).create(
name='%s @ %s' % (it_tmp.name, loc.name),
item=it_tmp,
location=loc,
category='%02d' % (k + 1))
OperationMaterial.objects.using(database).create(
operation=oper, item=it_tmp, quantity=-1)
previtem = it_tmp
# Consume raw materials / components
c = []
for j in range(components_per):
o = random.choice(ops)
b = random.choice(comps)
while (o, b) in c:
# A flow with the same operation and buffer already exists
o = random.choice(ops)
b = random.choice(comps)
c.append((o, b))
OperationMaterial.objects.using(database).create(
operation=o,
item=b,
quantity=random.choice([-1, -1, -1, -2, -3]))
# Commit the current cluster
task.status = '%d%%' % (12 + progress * (i + 1))
task.save(using=database)
# Task update
task.status = 'Done'
task.finished = datetime.now()
except Exception as e:
if task:
task.status = 'Failed'
task.message = '%s' % e
task.finished = datetime.now()
task.save(using=database)
raise e
finally:
if task:
task.save(using=database)
settings.DEBUG = tmp_debug
def handle(self, **options):
# Make sure the debug flag is not set!
# When it is set, the django database wrapper collects a list of all sql
# statements executed and their timings. This consumes plenty of memory
# and cpu time.
tmp_debug = settings.DEBUG
settings.DEBUG = False
# Pick up the options
verbosity = int(options["verbosity"])
cluster = int(options["cluster"])
demand = int(options["demand"])
forecast_per_item = int(options["forecast_per_item"])
level = int(options["level"])
resource = int(options["resource"])
resource_size = int(options["resource_size"])
components = int(options["components"])
components_per = int(options["components_per"])
if components <= 0:
components_per = 0
deliver_lt = int(options["deliver_lt"])
procure_lt = int(options["procure_lt"])
if options["currentdate"]:
currentdate = options["currentdate"]
else:
currentdate = datetime.strftime(date.today(), "%Y-%m-%d")
database = options["database"]
if database not in settings.DATABASES:
raise CommandError("No database settings known for '%s'" %
database)
if options["user"]:
try:
user = User.objects.all().using(database).get(
username=options["user"])
except Exception:
raise CommandError("User '%s' not found" % options["user"])
else:
user = None
random.seed(100) # Initialize random seed to get reproducible results
now = datetime.now()
task = None
try:
# Initialize the task
if options["task"]:
try:
task = Task.objects.all().using(database).get(
pk=options["task"])
except Exception:
raise CommandError("Task identifier not found")
if (task.started or task.finished or task.status != "Waiting"
or task.name
not in ("frepple_createmodel", "createmodel")):
raise CommandError("Invalid task identifier")
task.status = "0%"
task.started = now
else:
task = Task(
name="createmodel",
submitted=now,
started=now,
status="0%",
user=user,
)
task.arguments = (
"--cluster=%s --demand=%s --forecast_per_item=%s --level=%s --resource=%s "
"--resource_size=%s --components=%s --components_per=%s --deliver_lt=%s --procure_lt=%s"
% (
cluster,
demand,
forecast_per_item,
level,
resource,
resource_size,
components,
components_per,
deliver_lt,
procure_lt,
))
task.save(using=database)
# Pick up the startdate
try:
startdate = datetime.strptime(currentdate, "%Y-%m-%d")
except Exception:
raise CommandError(
"current date is not matching format YYYY-MM-DD")
# Check whether the database is empty
if (Buffer.objects.using(database).count() > 0
or Item.objects.using(database).count() > 0):
raise CommandError(
"Database must be empty before creating a model")
# Plan start date
if verbosity > 0:
print("Updating current date...")
param = Parameter.objects.using(database).get_or_create(
name="currentdate")[0]
param.value = datetime.strftime(startdate, "%Y-%m-%d %H:%M:%S")
param.save(using=database)
# Planning horizon
# minimum 10 daily buckets, weekly buckets till 40 days after current
if verbosity > 0:
print("Updating buckets...")
management.call_command("createbuckets",
user=user,
database=database)
task.status = "2%"
task.save(using=database)
# Weeks calendar
if verbosity > 0:
print("Creating weeks calendar...")
with transaction.atomic(using=database):
weeks = Calendar.objects.using(database).create(name="Weeks",
defaultvalue=0)
for i in (BucketDetail.objects.using(database).filter(
bucket="week").all()):
CalendarBucket(
startdate=i.startdate,
enddate=i.enddate,
value=1,
calendar=weeks,
).save(using=database)
task.status = "4%"
task.save(using=database)
# Working days calendar
if verbosity > 0:
print("Creating working days...")
with transaction.atomic(using=database):
workingdays = Calendar.objects.using(database).create(
name="Working Days", defaultvalue=0)
minmax = (BucketDetail.objects.using(database).filter(
bucket="week").aggregate(Min("startdate"),
Max("startdate")))
CalendarBucket(
startdate=minmax["startdate__min"],
enddate=minmax["startdate__max"],
value=1,
calendar=workingdays,
priority=1,
saturday=False,
sunday=False,
).save(using=database)
task.status = "6%"
task.save(using=database)
# Parent location
loc = Location.objects.using(database).create(
name="Factory", available=workingdays)
# Create a random list of categories to choose from
categories = [
"cat A", "cat B", "cat C", "cat D", "cat E", "cat F", "cat G"
]
# Create customers
if verbosity > 0:
print("Creating customers...")
with transaction.atomic(using=database):
cust = []
for i in range(100):
c = Customer.objects.using(database).create(
name="Cust %03d" % i)
cust.append(c)
task.status = "8%"
task.save(using=database)
# Create resources and their calendars
if verbosity > 0:
print("Creating resources and calendars...")
with transaction.atomic(using=database):
res = []
for i in range(resource):
cal = Calendar.objects.using(database).create(
name="capacity for res %03d" % i,
category="capacity",
defaultvalue=0,
)
CalendarBucket.objects.using(database).create(
startdate=startdate, value=resource_size, calendar=cal)
r = Resource.objects.using(database).create(
name="Res %03d" % i,
maximum_calendar=cal,
location=loc)
res.append(r)
task.status = "10%"
task.save(using=database)
random.shuffle(res)
# Create the components
if verbosity > 0:
print("Creating raw materials...")
with transaction.atomic(using=database):
comps = []
compsupplier = Supplier.objects.using(database).create(
name="component supplier")
for i in range(components):
it = Item.objects.using(database).create(
name="Component %04d" % i,
category="Procured",
cost=str(round(random.uniform(0, 100))),
)
ld = abs(
round(random.normalvariate(procure_lt,
procure_lt / 3)))
Buffer.objects.using(database).create(
location=loc,
category="Procured",
item=it,
minimum=20,
onhand=str(
round(forecast_per_item * random.uniform(1, 3) *
ld / 30)),
)
ItemSupplier.objects.using(database).create(
item=it,
location=loc,
supplier=compsupplier,
leadtime=timedelta(days=ld),
sizeminimum=80,
sizemultiple=10,
priority=1,
cost=it.cost,
)
comps.append(it)
task.status = "12%"
task.save(using=database)
# Loop over all clusters
durations = [timedelta(days=i) for i in range(1, 6)]
progress = 88.0 / cluster
for i in range(cluster):
with transaction.atomic(using=database):
if verbosity > 0:
print("Creating supply chain for end item %d..." % i)
# Item
it = Item.objects.using(database).create(
name="Itm %05d" % i,
category=random.choice(categories),
cost=str(round(random.uniform(100, 200))),
)
# Level 0 buffer
buf = Buffer.objects.using(database).create(item=it,
location=loc,
category="00")
# Demand
for j in range(demand):
Demand.objects.using(database).create(
name="Dmd %05d %05d" % (i, j),
item=it,
location=loc,
quantity=int(random.uniform(1, 6)),
# Exponential distribution of due dates, with an average of deliver_lt days.
due=startdate + timedelta(days=round(
random.expovariate(float(1) / deliver_lt /
24)) / 24),
# Orders have higher priority than forecast
priority=random.choice([1, 2]),
customer=random.choice(cust),
category=random.choice(categories),
)
# Create upstream operations and buffers
ops = []
previtem = it
for k in range(level):
if k == 1 and res:
# Create a resource load for operations on level 1
oper = Operation.objects.using(database).create(
name="Oper %05d L%02d" % (i, k),
type="time_per",
location=loc,
duration_per=timedelta(days=1),
sizemultiple=1,
item=previtem,
)
if resource < cluster and i < resource:
# When there are more cluster than resources, we try to assure
# that each resource is loaded by at least 1 operation.
OperationResource.objects.using(
database).create(resource=res[i],
operation=oper)
else:
OperationResource.objects.using(
database).create(
resource=random.choice(res),
operation=oper)
else:
oper = Operation.objects.using(database).create(
name="Oper %05d L%02d" % (i, k),
duration=random.choice(durations),
sizemultiple=1,
location=loc,
item=previtem,
)
ops.append(oper)
# Some inventory in random buffers
if random.uniform(0, 1) > 0.8:
buf.onhand = int(random.uniform(5, 20))
buf.save(using=database)
OperationMaterial.objects.using(database).create(
operation=oper,
item=previtem,
quantity=1,
type="end")
if k != level - 1:
# Consume from the next level in the bill of material
it_tmp = Item.objects.using(database).create(
name="Itm %05d L%02d" % (i, k + 1),
category=random.choice(categories),
cost=str(round(random.uniform(100, 200))),
)
buf = Buffer.objects.using(database).create(
item=it_tmp,
location=loc,
category="%02d" % (k + 1))
OperationMaterial.objects.using(database).create(
operation=oper, item=it_tmp, quantity=-1)
previtem = it_tmp
# Consume raw materials / components
c = []
for j in range(components_per):
o = random.choice(ops)
b = random.choice(comps)
while (o, b) in c:
# A flow with the same operation and buffer already exists
o = random.choice(ops)
b = random.choice(comps)
c.append((o, b))
OperationMaterial.objects.using(database).create(
operation=o,
item=b,
quantity=random.choice([-1, -1, -1, -2, -3]),
)
# Commit the current cluster
task.status = "%d%%" % (12 + progress * (i + 1))
task.save(using=database)
# Task update
task.status = "Done"
task.finished = datetime.now()
except Exception as e:
if task:
task.status = "Failed"
task.message = "%s" % e
task.finished = datetime.now()
task.save(using=database)
raise e
finally:
if task:
task.save(using=database)
settings.DEBUG = tmp_debug
def handle(self, **options):
# Make sure the debug flag is not set!
# When it is set, the django database wrapper collects a list of all sql
# statements executed and their timings. This consumes plenty of memory
# and cpu time.
tmp_debug = settings.DEBUG
settings.DEBUG = False
# Pick up the options
if 'verbosity' in options:
verbosity = int(options['verbosity'])
else:
verbosity = 1
if 'cluster' in options:
cluster = int(options['cluster'])
else:
cluster = 100
if 'demand' in options:
demand = int(options['demand'])
else:
demand = 30
if 'forecast_per_item' in options:
forecast_per_item = int(options['forecast_per_item'])
else:
forecast_per_item = 50
if 'level' in options:
level = int(options['level'])
else:
level = 5
if 'resource' in options:
resource = int(options['resource'])
else:
resource = 60
if 'resource_size' in options:
resource_size = int(options['resource_size'])
else:
resource_size = 5
if 'components' in options:
components = int(options['components'])
else:
components = 200
if 'components_per' in options:
components_per = int(options['components_per'])
else:
components_per = 5
if components == 0:
components_per = 0
if 'deliver_lt' in options:
deliver_lt = int(options['deliver_lt'])
else:
deliver_lt = 30
if 'procure_lt' in options:
procure_lt = int(options['procure_lt'])
else:
procure_lt = 40
if 'currentdate' in options:
currentdate = options['currentdate'] or datetime.strftime(date.today(), '%Y-%m-%d')
else:
currentdate = datetime.strftime(date.today(), '%Y-%m-%d')
if 'database' in options:
database = options['database'] or DEFAULT_DB_ALIAS
else:
database = DEFAULT_DB_ALIAS
if not database in settings.DATABASES:
raise CommandError("No database settings known for '%s'" % database )
if 'user' in options and options['user']:
try:
user = User.objects.all().using(database).get(username=options['user'])
except:
raise CommandError("User '%s' not found" % options['user'] )
else:
user = None
random.seed(100) # Initialize random seed to get reproducible results
now = datetime.now()
task = None
try:
# Initialize the task
if 'task' in options and options['task']:
try:
task = Task.objects.all().using(database).get(pk=options['task'])
except:
raise CommandError("Task identifier not found")
if task.started or task.finished or task.status != "Waiting" or task.name != 'generate model':
raise CommandError("Invalid task identifier")
task.status = '0%'
task.started = now
else:
task = Task(name='generate model', submitted=now, started=now, status='0%', user=user)
task.arguments = "--cluster=%s --demand=%s --forecast_per_item=%s --level=%s --resource=%s " \
"--resource_size=%s --components=%s --components_per=%s --deliver_lt=%s --procure_lt=%s" % (
cluster, demand, forecast_per_item, level, resource,
resource_size, components, components_per, deliver_lt, procure_lt
)
task.save(using=database)
transaction.commit(using=database)
# Pick up the startdate
try:
startdate = datetime.strptime(currentdate, '%Y-%m-%d')
except:
raise CommandError("current date is not matching format YYYY-MM-DD")
# Check whether the database is empty
if Buffer.objects.using(database).count() > 0 or Item.objects.using(database).count() > 0:
raise CommandError("Database must be empty before creating a model")
# Plan start date
if verbosity > 0:
print("Updating current date...")
param = Parameter.objects.using(database).create(name="currentdate")
param.value = datetime.strftime(startdate, "%Y-%m-%d %H:%M:%S")
param.save(using=database)
# Planning horizon
# minimum 10 daily buckets, weekly buckets till 40 days after current
if verbosity > 0:
print("Updating buckets...")
management.call_command('frepple_createbuckets', user=user, database=database)
if verbosity > 0:
print("Updating horizon telescope...")
updateTelescope(10, 40, 730, database)
task.status = '2%'
task.save(using=database)
# Weeks calendar
if verbosity > 0:
print("Creating weeks calendar...")
with transaction.atomic(using=database):
weeks = Calendar.objects.using(database).create(name="Weeks", defaultvalue=0)
for i in BucketDetail.objects.using(database).filter(bucket="week").all():
CalendarBucket(
startdate=i.startdate, enddate=i.enddate, value=1, calendar=weeks
).save(using=database)
task.status = '4%'
task.save(using=database)
# Working days calendar
if verbosity > 0:
print("Creating working days...")
with transaction.atomic(using=database):
workingdays = Calendar.objects.using(database).create(name="Working Days", defaultvalue=0)
minmax = BucketDetail.objects.using(database).filter(bucket="week").aggregate(Min('startdate'), Max('startdate'))
CalendarBucket(
startdate=minmax['startdate__min'], enddate=minmax['startdate__max'],
value=1, calendar=workingdays, priority=1, saturday=False, sunday=False
).save(using=database)
task.status = '6%'
task.save(using=database)
# Create a random list of categories to choose from
categories = [
'cat A', 'cat B', 'cat C', 'cat D', 'cat E', 'cat F', 'cat G'
]
# Create customers
if verbosity > 0:
print("Creating customers...")
with transaction.atomic(using=database):
cust = []
for i in range(100):
c = Customer.objects.using(database).create(name='Cust %03d' % i)
cust.append(c)
task.status = '8%'
task.save(using=database)
# Create resources and their calendars
if verbosity > 0:
print("Creating resources and calendars...")
with transaction.atomic(using=database):
res = []
for i in range(resource):
loc = Location(name='Loc %05d' % int(random.uniform(1, cluster)))
loc.save(using=database)
cal = Calendar(name='capacity for res %03d' % i, category='capacity', defaultvalue=0)
bkt = CalendarBucket(startdate=startdate, value=resource_size, calendar=cal)
cal.save(using=database)
bkt.save(using=database)
r = Resource.objects.using(database).create(
name='Res %03d' % i, maximum_calendar=cal, location=loc
)
res.append(r)
task.status = '10%'
task.save(using=database)
random.shuffle(res)
# Create the components
if verbosity > 0:
print("Creating raw materials...")
with transaction.atomic(using=database):
comps = []
comploc = Location.objects.using(database).create(name='Procured materials')
for i in range(components):
it = Item.objects.using(database).create(
name='Component %04d' % i,
category='Procured',
price=str(round(random.uniform(0, 100)))
)
ld = abs(round(random.normalvariate(procure_lt, procure_lt / 3)))
c = Buffer.objects.using(database).create(
name='Component %04d' % i,
location=comploc,
category='Procured',
item=it,
type='procure',
min_inventory=20,
max_inventory=100,
size_multiple=10,
leadtime=str(ld * 86400),
onhand=str(round(forecast_per_item * random.uniform(1, 3) * ld / 30)),
)
comps.append(c)
task.status = '12%'
task.save(using=database)
# Loop over all clusters
durations = [ 86400, 86400 * 2, 86400 * 3, 86400 * 5, 86400 * 6 ]
progress = 88.0 / cluster
for i in range(cluster):
with transaction.atomic(using=database):
if verbosity > 0:
print("Creating supply chain for end item %d..." % i)
# location
loc = Location.objects.using(database).get_or_create(name='Loc %05d' % i)[0]
loc.available = workingdays
loc.save(using=database)
# Item and delivery operation
oper = Operation.objects.using(database).create(name='Del %05d' % i, sizemultiple=1, location=loc)
it = Item.objects.using(database).create(
name='Itm %05d' % i,
operation=oper,
category=random.choice(categories),
price=str(round(random.uniform(100, 200)))
)
# Level 0 buffer
buf = Buffer.objects.using(database).create(
name='Buf %05d L00' % i,
item=it,
location=loc,
category='00'
)
Flow.objects.using(database).create(operation=oper, thebuffer=buf, quantity=-1)
# Demand
for j in range(demand):
Demand.objects.using(database).create(
name='Dmd %05d %05d' % (i, j),
item=it,
quantity=int(random.uniform(1, 6)),
# Exponential distribution of due dates, with an average of deliver_lt days.
due=startdate + timedelta(days=round(random.expovariate(float(1) / deliver_lt / 24)) / 24),
# Orders have higher priority than forecast
priority=random.choice([1, 2]),
customer=random.choice(cust),
category=random.choice(categories)
)
# Create upstream operations and buffers
ops = []
for k in range(level):
if k == 1 and res:
# Create a resource load for operations on level 1
oper = Operation.objects.using(database).create(
name='Oper %05d L%02d' % (i, k),
type='time_per',
location=loc,
duration_per=86400,
sizemultiple=1,
)
if resource < cluster and i < resource:
# When there are more cluster than resources, we try to assure
# that each resource is loaded by at least 1 operation.
Load.objects.using(database).create(resource=res[i], operation=oper)
else:
Load.objects.using(database).create(resource=random.choice(res), operation=oper)
else:
oper = Operation.objects.using(database).create(
name='Oper %05d L%02d' % (i, k),
duration=random.choice(durations),
sizemultiple=1,
location=loc,
)
ops.append(oper)
buf.producing = oper
# Some inventory in random buffers
if random.uniform(0, 1) > 0.8:
buf.onhand = int(random.uniform(5, 20))
buf.save(using=database)
Flow(operation=oper, thebuffer=buf, quantity=1, type="end").save(using=database)
if k != level - 1:
# Consume from the next level in the bill of material
buf = Buffer.objects.using(database).create(
name='Buf %05d L%02d' % (i, k + 1),
item=it,
location=loc,
category='%02d' % (k + 1)
)
Flow.objects.using(database).create(operation=oper, thebuffer=buf, quantity=-1)
# Consume raw materials / components
c = []
for j in range(components_per):
o = random.choice(ops)
b = random.choice(comps)
while (o, b) in c:
# A flow with the same operation and buffer already exists
o = random.choice(ops)
b = random.choice(comps)
c.append( (o, b) )
Flow.objects.using(database).create(
operation=o, thebuffer=b,
quantity=random.choice([-1, -1, -1, -2, -3])
)
# Commit the current cluster
task.status = '%d%%' % (12 + progress * (i + 1))
task.save(using=database)
# Task update
task.status = 'Done'
task.finished = datetime.now()
except Exception as e:
if task:
task.status = 'Failed'
task.message = '%s' % e
task.finished = datetime.now()
task.save(using=database)
raise e
finally:
if task:
task.save(using=database)
settings.DEBUG = tmp_debug