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3,600
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/views.py
|
AddAvailabilitySlotView.form_valid
|
def form_valid(self, form):
'''
Create slots and return success message.
'''
startDate = form.cleaned_data['startDate']
endDate = form.cleaned_data['endDate']
startTime = form.cleaned_data['startTime']
endTime = form.cleaned_data['endTime']
instructor = form.cleaned_data['instructorId']
interval_minutes = getConstant('privateLessons__lessonLengthInterval')
this_date = startDate
while this_date <= endDate:
this_time = startTime
while this_time < endTime:
InstructorAvailabilitySlot.objects.create(
instructor=instructor,
startTime=ensure_localtime(datetime.combine(this_date, this_time)),
duration=interval_minutes,
location=form.cleaned_data.get('location'),
room=form.cleaned_data.get('room'),
pricingTier=form.cleaned_data.get('pricingTier'),
)
this_time = (ensure_localtime(datetime.combine(this_date, this_time)) + timedelta(minutes=interval_minutes)).time()
this_date += timedelta(days=1)
return JsonResponse({'valid': True})
|
python
|
def form_valid(self, form):
'''
Create slots and return success message.
'''
startDate = form.cleaned_data['startDate']
endDate = form.cleaned_data['endDate']
startTime = form.cleaned_data['startTime']
endTime = form.cleaned_data['endTime']
instructor = form.cleaned_data['instructorId']
interval_minutes = getConstant('privateLessons__lessonLengthInterval')
this_date = startDate
while this_date <= endDate:
this_time = startTime
while this_time < endTime:
InstructorAvailabilitySlot.objects.create(
instructor=instructor,
startTime=ensure_localtime(datetime.combine(this_date, this_time)),
duration=interval_minutes,
location=form.cleaned_data.get('location'),
room=form.cleaned_data.get('room'),
pricingTier=form.cleaned_data.get('pricingTier'),
)
this_time = (ensure_localtime(datetime.combine(this_date, this_time)) + timedelta(minutes=interval_minutes)).time()
this_date += timedelta(days=1)
return JsonResponse({'valid': True})
|
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Create slots and return success message.
|
[
"Create",
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/views.py#L61-L88
|
3,601
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/views.py
|
UpdateAvailabilitySlotView.form_valid
|
def form_valid(self, form):
'''
Modify or delete the availability slot as requested and return success message.
'''
slotIds = form.cleaned_data['slotIds']
deleteSlot = form.cleaned_data.get('deleteSlot', False)
these_slots = InstructorAvailabilitySlot.objects.filter(id__in=slotIds)
if deleteSlot:
these_slots.delete()
else:
for this_slot in these_slots:
this_slot.location = form.cleaned_data['updateLocation']
this_slot.room = form.cleaned_data['updateRoom']
this_slot.status = form.cleaned_data['updateStatus']
this_slot.pricingTier = form.cleaned_data.get('updatePricing')
this_slot.save()
return JsonResponse({'valid': True})
|
python
|
def form_valid(self, form):
'''
Modify or delete the availability slot as requested and return success message.
'''
slotIds = form.cleaned_data['slotIds']
deleteSlot = form.cleaned_data.get('deleteSlot', False)
these_slots = InstructorAvailabilitySlot.objects.filter(id__in=slotIds)
if deleteSlot:
these_slots.delete()
else:
for this_slot in these_slots:
this_slot.location = form.cleaned_data['updateLocation']
this_slot.room = form.cleaned_data['updateRoom']
this_slot.status = form.cleaned_data['updateStatus']
this_slot.pricingTier = form.cleaned_data.get('updatePricing')
this_slot.save()
return JsonResponse({'valid': True})
|
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Modify or delete the availability slot as requested and return success message.
|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/views.py#L101-L120
|
3,602
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/views.py
|
BookPrivateLessonView.get_form_kwargs
|
def get_form_kwargs(self, **kwargs):
'''
Pass the current user to the form to render the payAtDoor field if applicable.
'''
kwargs = super(BookPrivateLessonView, self).get_form_kwargs(**kwargs)
kwargs['user'] = self.request.user if hasattr(self.request,'user') else None
return kwargs
|
python
|
def get_form_kwargs(self, **kwargs):
'''
Pass the current user to the form to render the payAtDoor field if applicable.
'''
kwargs = super(BookPrivateLessonView, self).get_form_kwargs(**kwargs)
kwargs['user'] = self.request.user if hasattr(self.request,'user') else None
return kwargs
|
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Pass the current user to the form to render the payAtDoor field if applicable.
|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/views.py#L137-L143
|
3,603
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/views.py
|
PrivateLessonStudentInfoView.dispatch
|
def dispatch(self,request,*args,**kwargs):
'''
Handle the session data passed by the prior view.
'''
lessonSession = request.session.get(PRIVATELESSON_VALIDATION_STR,{})
try:
self.lesson = PrivateLessonEvent.objects.get(id=lessonSession.get('lesson'))
except (ValueError, ObjectDoesNotExist):
messages.error(request,_('Invalid lesson identifier passed to sign-up form.'))
return HttpResponseRedirect(reverse('bookPrivateLesson'))
expiry = parse_datetime(lessonSession.get('expiry',''),)
if not expiry or expiry < timezone.now():
messages.info(request,_('Your registration session has expired. Please try again.'))
return HttpResponseRedirect(reverse('bookPrivateLesson'))
self.payAtDoor = lessonSession.get('payAtDoor',False)
return super(PrivateLessonStudentInfoView,self).dispatch(request,*args,**kwargs)
|
python
|
def dispatch(self,request,*args,**kwargs):
'''
Handle the session data passed by the prior view.
'''
lessonSession = request.session.get(PRIVATELESSON_VALIDATION_STR,{})
try:
self.lesson = PrivateLessonEvent.objects.get(id=lessonSession.get('lesson'))
except (ValueError, ObjectDoesNotExist):
messages.error(request,_('Invalid lesson identifier passed to sign-up form.'))
return HttpResponseRedirect(reverse('bookPrivateLesson'))
expiry = parse_datetime(lessonSession.get('expiry',''),)
if not expiry or expiry < timezone.now():
messages.info(request,_('Your registration session has expired. Please try again.'))
return HttpResponseRedirect(reverse('bookPrivateLesson'))
self.payAtDoor = lessonSession.get('payAtDoor',False)
return super(PrivateLessonStudentInfoView,self).dispatch(request,*args,**kwargs)
|
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Handle the session data passed by the prior view.
|
[
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/views.py#L308-L327
|
3,604
|
django-danceschool/django-danceschool
|
danceschool/guestlist/views.py
|
GuestListView.get_object
|
def get_object(self, queryset=None):
''' Get the guest list from the URL '''
return get_object_or_404(
GuestList.objects.filter(id=self.kwargs.get('guestlist_id')))
|
python
|
def get_object(self, queryset=None):
''' Get the guest list from the URL '''
return get_object_or_404(
GuestList.objects.filter(id=self.kwargs.get('guestlist_id')))
|
[
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] |
Get the guest list from the URL
|
[
"Get",
"the",
"guest",
"list",
"from",
"the",
"URL"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/guestlist/views.py#L18-L21
|
3,605
|
django-danceschool/django-danceschool
|
danceschool/guestlist/views.py
|
GuestListView.get_context_data
|
def get_context_data(self,**kwargs):
''' Add the list of names for the given guest list '''
event = Event.objects.filter(id=self.kwargs.get('event_id')).first()
if self.kwargs.get('event_id') and not self.object.appliesToEvent(event):
raise Http404(_('Invalid event.'))
# Use the most current event if nothing has been specified.
if not event:
event = self.object.currentEvent
context = {
'guestList': self.object,
'event': event,
'names': self.object.getListForEvent(event),
}
context.update(kwargs)
return super(GuestListView,self).get_context_data(**context)
|
python
|
def get_context_data(self,**kwargs):
''' Add the list of names for the given guest list '''
event = Event.objects.filter(id=self.kwargs.get('event_id')).first()
if self.kwargs.get('event_id') and not self.object.appliesToEvent(event):
raise Http404(_('Invalid event.'))
# Use the most current event if nothing has been specified.
if not event:
event = self.object.currentEvent
context = {
'guestList': self.object,
'event': event,
'names': self.object.getListForEvent(event),
}
context.update(kwargs)
return super(GuestListView,self).get_context_data(**context)
|
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Add the list of names for the given guest list
|
[
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/guestlist/views.py#L23-L39
|
3,606
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
PrivateLessonEvent.getBasePrice
|
def getBasePrice(self,**kwargs):
'''
This method overrides the method of the base Event class by
checking the pricingTier associated with this PrivateLessonEvent and getting
the appropriate price for it.
'''
if not self.pricingTier:
return None
return self.pricingTier.getBasePrice(**kwargs) * max(self.numSlots,1)
|
python
|
def getBasePrice(self,**kwargs):
'''
This method overrides the method of the base Event class by
checking the pricingTier associated with this PrivateLessonEvent and getting
the appropriate price for it.
'''
if not self.pricingTier:
return None
return self.pricingTier.getBasePrice(**kwargs) * max(self.numSlots,1)
|
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This method overrides the method of the base Event class by
checking the pricingTier associated with this PrivateLessonEvent and getting
the appropriate price for it.
|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L48-L56
|
3,607
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
PrivateLessonEvent.customers
|
def customers(self):
'''
List both any individuals signed up via the registration and payment system,
and any individuals signed up without payment.
'''
return Customer.objects.filter(
Q(privatelessoncustomer__lesson=self) |
Q(registration__eventregistration__event=self)
).distinct()
|
python
|
def customers(self):
'''
List both any individuals signed up via the registration and payment system,
and any individuals signed up without payment.
'''
return Customer.objects.filter(
Q(privatelessoncustomer__lesson=self) |
Q(registration__eventregistration__event=self)
).distinct()
|
[
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"(",
"registration__eventregistration__event",
"=",
"self",
")",
")",
".",
"distinct",
"(",
")"
] |
List both any individuals signed up via the registration and payment system,
and any individuals signed up without payment.
|
[
"List",
"both",
"any",
"individuals",
"signed",
"up",
"via",
"the",
"registration",
"and",
"payment",
"system",
"and",
"any",
"individuals",
"signed",
"up",
"without",
"payment",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L122-L130
|
3,608
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
PrivateLessonEvent.save
|
def save(self, *args, **kwargs):
''' Set registration status to hidden if it is not specified otherwise '''
if not self.status:
self.status == Event.RegStatus.hidden
super(PrivateLessonEvent,self).save(*args,**kwargs)
|
python
|
def save(self, *args, **kwargs):
''' Set registration status to hidden if it is not specified otherwise '''
if not self.status:
self.status == Event.RegStatus.hidden
super(PrivateLessonEvent,self).save(*args,**kwargs)
|
[
"def",
"save",
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"*",
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",",
"*",
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"kwargs",
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":",
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",",
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")",
".",
"save",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
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] |
Set registration status to hidden if it is not specified otherwise
|
[
"Set",
"registration",
"status",
"to",
"hidden",
"if",
"it",
"is",
"not",
"specified",
"otherwise"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L172-L176
|
3,609
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
InstructorAvailabilitySlot.availableDurations
|
def availableDurations(self):
'''
A lesson can always be booked for the length of a single slot, but this method
checks if multiple slots are available. This method requires that slots are
non-overlapping, which needs to be enforced on slot save.
'''
potential_slots = InstructorAvailabilitySlot.objects.filter(
instructor=self.instructor,
location=self.location,
room=self.room,
pricingTier=self.pricingTier,
startTime__gte=self.startTime,
startTime__lte=self.startTime + timedelta(minutes=getConstant('privateLessons__maximumLessonLength')),
).exclude(id=self.id).order_by('startTime')
duration_list = [self.duration,]
last_start = self.startTime
last_duration = self.duration
max_duration = self.duration
for slot in potential_slots:
if max_duration + slot.duration > getConstant('privateLessons__maximumLessonLength'):
break
if (
slot.startTime == last_start + timedelta(minutes=last_duration) and
slot.isAvailable
):
duration_list.append(max_duration + slot.duration)
last_start = slot.startTime
last_duration = slot.duration
max_duration += slot.duration
return duration_list
|
python
|
def availableDurations(self):
'''
A lesson can always be booked for the length of a single slot, but this method
checks if multiple slots are available. This method requires that slots are
non-overlapping, which needs to be enforced on slot save.
'''
potential_slots = InstructorAvailabilitySlot.objects.filter(
instructor=self.instructor,
location=self.location,
room=self.room,
pricingTier=self.pricingTier,
startTime__gte=self.startTime,
startTime__lte=self.startTime + timedelta(minutes=getConstant('privateLessons__maximumLessonLength')),
).exclude(id=self.id).order_by('startTime')
duration_list = [self.duration,]
last_start = self.startTime
last_duration = self.duration
max_duration = self.duration
for slot in potential_slots:
if max_duration + slot.duration > getConstant('privateLessons__maximumLessonLength'):
break
if (
slot.startTime == last_start + timedelta(minutes=last_duration) and
slot.isAvailable
):
duration_list.append(max_duration + slot.duration)
last_start = slot.startTime
last_duration = slot.duration
max_duration += slot.duration
return duration_list
|
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] |
A lesson can always be booked for the length of a single slot, but this method
checks if multiple slots are available. This method requires that slots are
non-overlapping, which needs to be enforced on slot save.
|
[
"A",
"lesson",
"can",
"always",
"be",
"booked",
"for",
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"of",
"a",
"single",
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"-",
"overlapping",
"which",
"needs",
"to",
"be",
"enforced",
"on",
"slot",
"save",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L252-L284
|
3,610
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
InstructorAvailabilitySlot.availableRoles
|
def availableRoles(self):
'''
Some instructors only offer private lessons for certain roles, so we should only allow booking
for the roles that have been selected for the instructor.
'''
if not hasattr(self.instructor,'instructorprivatelessondetails'):
return []
return [
[x.id,x.name] for x in
self.instructor.instructorprivatelessondetails.roles.all()
]
|
python
|
def availableRoles(self):
'''
Some instructors only offer private lessons for certain roles, so we should only allow booking
for the roles that have been selected for the instructor.
'''
if not hasattr(self.instructor,'instructorprivatelessondetails'):
return []
return [
[x.id,x.name] for x in
self.instructor.instructorprivatelessondetails.roles.all()
]
|
[
"def",
"availableRoles",
"(",
"self",
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"self",
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"instructor",
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"roles",
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"(",
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"]"
] |
Some instructors only offer private lessons for certain roles, so we should only allow booking
for the roles that have been selected for the instructor.
|
[
"Some",
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"only",
"offer",
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"roles",
"that",
"have",
"been",
"selected",
"for",
"the",
"instructor",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L287-L297
|
3,611
|
django-danceschool/django-danceschool
|
danceschool/private_lessons/models.py
|
InstructorAvailabilitySlot.checkIfAvailable
|
def checkIfAvailable(self, dateTime=timezone.now()):
'''
Available slots are available, but also tentative slots that have been held as tentative
past their expiration date
'''
return (
self.startTime >= dateTime + timedelta(days=getConstant('privateLessons__closeBookingDays')) and
self.startTime <= dateTime + timedelta(days=getConstant('privateLessons__openBookingDays')) and not
self.eventRegistration and (
self.status == self.SlotStatus.available or (
self.status == self.SlotStatus.tentative and
getattr(getattr(self.temporaryEventRegistration,'registration',None),'expirationDate',timezone.now()) <= timezone.now()
)
)
)
|
python
|
def checkIfAvailable(self, dateTime=timezone.now()):
'''
Available slots are available, but also tentative slots that have been held as tentative
past their expiration date
'''
return (
self.startTime >= dateTime + timedelta(days=getConstant('privateLessons__closeBookingDays')) and
self.startTime <= dateTime + timedelta(days=getConstant('privateLessons__openBookingDays')) and not
self.eventRegistration and (
self.status == self.SlotStatus.available or (
self.status == self.SlotStatus.tentative and
getattr(getattr(self.temporaryEventRegistration,'registration',None),'expirationDate',timezone.now()) <= timezone.now()
)
)
)
|
[
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"(",
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")"
] |
Available slots are available, but also tentative slots that have been held as tentative
past their expiration date
|
[
"Available",
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"available",
"but",
"also",
"tentative",
"slots",
"that",
"have",
"been",
"held",
"as",
"tentative",
"past",
"their",
"expiration",
"date"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_lessons/models.py#L299-L313
|
3,612
|
django-danceschool/django-danceschool
|
danceschool/private_events/feeds.py
|
json_event_feed
|
def json_event_feed(request,location_id=None,room_id=None):
'''
The Jquery fullcalendar app requires a JSON news feed, so this function
creates the feed from upcoming PrivateEvent objects
'''
if not getConstant('calendar__privateCalendarFeedEnabled') or not request.user.is_staff:
return JsonResponse({})
this_user = request.user
startDate = request.GET.get('start','')
endDate = request.GET.get('end','')
timeZone = request.GET.get('timezone',getattr(settings,'TIME_ZONE','UTC'))
time_filter_dict_events = {}
if startDate:
time_filter_dict_events['startTime__gte'] = ensure_timezone(datetime.strptime(startDate,'%Y-%m-%d'))
if endDate:
time_filter_dict_events['endTime__lte'] = ensure_timezone(datetime.strptime(endDate,'%Y-%m-%d')) + timedelta(days=1)
instructor_groups = list(this_user.groups.all().values_list('id',flat=True))
filters = Q(event__privateevent__isnull=False) & (
Q(event__privateevent__displayToGroup__in=instructor_groups) |
Q(event__privateevent__displayToUsers=this_user) |
(Q(event__privateevent__displayToGroup__isnull=True) & Q(event__privateevent__displayToUsers__isnull=True))
)
if location_id:
filters = filters & Q(event__location__id=location_id)
if room_id:
filters = filters & Q(event__room_id=room_id)
occurrences = EventOccurrence.objects.filter(filters).filter(**time_filter_dict_events).order_by('-startTime')
eventlist = [EventFeedItem(x,timeZone=timeZone).__dict__ for x in occurrences]
return JsonResponse(eventlist,safe=False)
|
python
|
def json_event_feed(request,location_id=None,room_id=None):
'''
The Jquery fullcalendar app requires a JSON news feed, so this function
creates the feed from upcoming PrivateEvent objects
'''
if not getConstant('calendar__privateCalendarFeedEnabled') or not request.user.is_staff:
return JsonResponse({})
this_user = request.user
startDate = request.GET.get('start','')
endDate = request.GET.get('end','')
timeZone = request.GET.get('timezone',getattr(settings,'TIME_ZONE','UTC'))
time_filter_dict_events = {}
if startDate:
time_filter_dict_events['startTime__gte'] = ensure_timezone(datetime.strptime(startDate,'%Y-%m-%d'))
if endDate:
time_filter_dict_events['endTime__lte'] = ensure_timezone(datetime.strptime(endDate,'%Y-%m-%d')) + timedelta(days=1)
instructor_groups = list(this_user.groups.all().values_list('id',flat=True))
filters = Q(event__privateevent__isnull=False) & (
Q(event__privateevent__displayToGroup__in=instructor_groups) |
Q(event__privateevent__displayToUsers=this_user) |
(Q(event__privateevent__displayToGroup__isnull=True) & Q(event__privateevent__displayToUsers__isnull=True))
)
if location_id:
filters = filters & Q(event__location__id=location_id)
if room_id:
filters = filters & Q(event__room_id=room_id)
occurrences = EventOccurrence.objects.filter(filters).filter(**time_filter_dict_events).order_by('-startTime')
eventlist = [EventFeedItem(x,timeZone=timeZone).__dict__ for x in occurrences]
return JsonResponse(eventlist,safe=False)
|
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"(",
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",",
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] |
The Jquery fullcalendar app requires a JSON news feed, so this function
creates the feed from upcoming PrivateEvent objects
|
[
"The",
"Jquery",
"fullcalendar",
"app",
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"function",
"creates",
"the",
"feed",
"from",
"upcoming",
"PrivateEvent",
"objects"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/private_events/feeds.py#L122-L159
|
3,613
|
django-danceschool/django-danceschool
|
danceschool/prerequisites/handlers.py
|
checkRequirements
|
def checkRequirements(sender,**kwargs):
'''
Check that the customer meets all prerequisites for the items in the registration.
'''
if not getConstant('requirements__enableRequirements'):
return
logger.debug('Signal to check RegistrationContactForm handled by prerequisites app.')
formData = kwargs.get('formData',{})
first = formData.get('firstName')
last = formData.get('lastName')
email = formData.get('email')
request = kwargs.get('request',{})
registration = kwargs.get('registration',None)
customer = Customer.objects.filter(
first_name=first,
last_name=last,
email=email).first()
requirement_warnings = []
requirement_errors = []
for ter in registration.temporaryeventregistration_set.all():
if hasattr(ter.event,'getRequirements'):
for req in ter.event.getRequirements():
if not req.customerMeetsRequirement(
customer=customer,
danceRole=ter.role
):
if req.enforcementMethod == Requirement.EnforcementChoice.error:
requirement_errors.append((ter.event.name, req.name))
if req.enforcementMethod == Requirement.EnforcementChoice.warning:
requirement_warnings.append((ter.event.name,req.name))
if requirement_errors:
raise ValidationError(format_html(
'<p>{}</p> <ul>{}</ul> <p>{}</p>',
ugettext('Unfortunately, you do not meet the following requirements/prerequisites for the items you have chosen:\n'),
mark_safe(''.join(['<li><em>%s:</em> %s</li>\n' % x for x in requirement_errors])),
getConstant('requirements__errorMessage') or '',
))
if requirement_warnings:
messages.warning(request,format_html(
'<p>{}</p> <ul>{}</ul> <p>{}</p>',
mark_safe(ugettext('<strong>Please Note:</strong> It appears that you do not meet the following requirements/prerequisites for the items you have chosen:\n')),
mark_safe(''.join(['<li><em>%s:</em> %s</li>\n' % x for x in requirement_warnings])),
getConstant('requirements__warningMessage') or '',
))
|
python
|
def checkRequirements(sender,**kwargs):
'''
Check that the customer meets all prerequisites for the items in the registration.
'''
if not getConstant('requirements__enableRequirements'):
return
logger.debug('Signal to check RegistrationContactForm handled by prerequisites app.')
formData = kwargs.get('formData',{})
first = formData.get('firstName')
last = formData.get('lastName')
email = formData.get('email')
request = kwargs.get('request',{})
registration = kwargs.get('registration',None)
customer = Customer.objects.filter(
first_name=first,
last_name=last,
email=email).first()
requirement_warnings = []
requirement_errors = []
for ter in registration.temporaryeventregistration_set.all():
if hasattr(ter.event,'getRequirements'):
for req in ter.event.getRequirements():
if not req.customerMeetsRequirement(
customer=customer,
danceRole=ter.role
):
if req.enforcementMethod == Requirement.EnforcementChoice.error:
requirement_errors.append((ter.event.name, req.name))
if req.enforcementMethod == Requirement.EnforcementChoice.warning:
requirement_warnings.append((ter.event.name,req.name))
if requirement_errors:
raise ValidationError(format_html(
'<p>{}</p> <ul>{}</ul> <p>{}</p>',
ugettext('Unfortunately, you do not meet the following requirements/prerequisites for the items you have chosen:\n'),
mark_safe(''.join(['<li><em>%s:</em> %s</li>\n' % x for x in requirement_errors])),
getConstant('requirements__errorMessage') or '',
))
if requirement_warnings:
messages.warning(request,format_html(
'<p>{}</p> <ul>{}</ul> <p>{}</p>',
mark_safe(ugettext('<strong>Please Note:</strong> It appears that you do not meet the following requirements/prerequisites for the items you have chosen:\n')),
mark_safe(''.join(['<li><em>%s:</em> %s</li>\n' % x for x in requirement_warnings])),
getConstant('requirements__warningMessage') or '',
))
|
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Check that the customer meets all prerequisites for the items in the registration.
|
[
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"for",
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"registration",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/prerequisites/handlers.py#L22-L74
|
3,614
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
EmailRecipientMixin.get_email_context
|
def get_email_context(self,**kwargs):
'''
This method can be overridden in classes that inherit from this mixin
so that additional object-specific context is provided to the email
template. This should return a dictionary. By default, only general
financial context variables are added to the dictionary, and kwargs are
just passed directly.
Note also that it is in general not a good idea for security reasons
to pass model instances in the context here, since these methods can be
accessed by logged in users who use the SendEmailView. So, In the default
models of this app, the values of fields and properties are passed
directly instead.
'''
context = kwargs
context.update({
'currencyCode': getConstant('general__currencyCode'),
'currencySymbol': getConstant('general__currencySymbol'),
'businessName': getConstant('contact__businessName'),
'site_url': getConstant('email__linkProtocol') + '://' + Site.objects.get_current().domain,
})
return context
|
python
|
def get_email_context(self,**kwargs):
'''
This method can be overridden in classes that inherit from this mixin
so that additional object-specific context is provided to the email
template. This should return a dictionary. By default, only general
financial context variables are added to the dictionary, and kwargs are
just passed directly.
Note also that it is in general not a good idea for security reasons
to pass model instances in the context here, since these methods can be
accessed by logged in users who use the SendEmailView. So, In the default
models of this app, the values of fields and properties are passed
directly instead.
'''
context = kwargs
context.update({
'currencyCode': getConstant('general__currencyCode'),
'currencySymbol': getConstant('general__currencySymbol'),
'businessName': getConstant('contact__businessName'),
'site_url': getConstant('email__linkProtocol') + '://' + Site.objects.get_current().domain,
})
return context
|
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] |
This method can be overridden in classes that inherit from this mixin
so that additional object-specific context is provided to the email
template. This should return a dictionary. By default, only general
financial context variables are added to the dictionary, and kwargs are
just passed directly.
Note also that it is in general not a good idea for security reasons
to pass model instances in the context here, since these methods can be
accessed by logged in users who use the SendEmailView. So, In the default
models of this app, the values of fields and properties are passed
directly instead.
|
[
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"properties",
"are",
"passed",
"directly",
"instead",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L107-L128
|
3,615
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
GroupRequiredByFieldMixin.get_group_required
|
def get_group_required(self):
''' Get the group_required value from the object '''
this_object = self.model_object
if hasattr(this_object,self.group_required_field):
if hasattr(getattr(this_object,self.group_required_field),'name'):
return [getattr(this_object,self.group_required_field).name]
return ['']
|
python
|
def get_group_required(self):
''' Get the group_required value from the object '''
this_object = self.model_object
if hasattr(this_object,self.group_required_field):
if hasattr(getattr(this_object,self.group_required_field),'name'):
return [getattr(this_object,self.group_required_field).name]
return ['']
|
[
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] |
Get the group_required value from the object
|
[
"Get",
"the",
"group_required",
"value",
"from",
"the",
"object"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L179-L185
|
3,616
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
GroupRequiredByFieldMixin.check_membership
|
def check_membership(self, groups):
''' Allows for objects with no required groups '''
if not groups or groups == ['']:
return True
if self.request.user.is_superuser:
return True
user_groups = self.request.user.groups.values_list("name", flat=True)
return set(groups).intersection(set(user_groups))
|
python
|
def check_membership(self, groups):
''' Allows for objects with no required groups '''
if not groups or groups == ['']:
return True
if self.request.user.is_superuser:
return True
user_groups = self.request.user.groups.values_list("name", flat=True)
return set(groups).intersection(set(user_groups))
|
[
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Allows for objects with no required groups
|
[
"Allows",
"for",
"objects",
"with",
"no",
"required",
"groups"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L187-L194
|
3,617
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
GroupRequiredByFieldMixin.dispatch
|
def dispatch(self, request, *args, **kwargs):
'''
This override of dispatch ensures that if no group is required, then
the request still goes through without being logged in.
'''
self.request = request
in_group = False
required_group = self.get_group_required()
if not required_group or required_group == ['']:
in_group = True
elif self.request.user.is_authenticated():
in_group = self.check_membership(required_group)
if not in_group:
if self.raise_exception:
raise PermissionDenied
else:
return redirect_to_login(
request.get_full_path(),
self.get_login_url(),
self.get_redirect_field_name())
return super(GroupRequiredMixin, self).dispatch(
request, *args, **kwargs)
|
python
|
def dispatch(self, request, *args, **kwargs):
'''
This override of dispatch ensures that if no group is required, then
the request still goes through without being logged in.
'''
self.request = request
in_group = False
required_group = self.get_group_required()
if not required_group or required_group == ['']:
in_group = True
elif self.request.user.is_authenticated():
in_group = self.check_membership(required_group)
if not in_group:
if self.raise_exception:
raise PermissionDenied
else:
return redirect_to_login(
request.get_full_path(),
self.get_login_url(),
self.get_redirect_field_name())
return super(GroupRequiredMixin, self).dispatch(
request, *args, **kwargs)
|
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This override of dispatch ensures that if no group is required, then
the request still goes through without being logged in.
|
[
"This",
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"of",
"dispatch",
"ensures",
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"is",
"required",
"then",
"the",
"request",
"still",
"goes",
"through",
"without",
"being",
"logged",
"in",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L196-L218
|
3,618
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
TemplateChoiceField.validate
|
def validate(self,value):
'''
Check for empty values, and for an existing template, but do not check if
this is one of the initial choices provided.
'''
super(ChoiceField,self).validate(value)
try:
get_template(value)
except TemplateDoesNotExist:
raise ValidationError(_('%s is not a valid template.' % value))
|
python
|
def validate(self,value):
'''
Check for empty values, and for an existing template, but do not check if
this is one of the initial choices provided.
'''
super(ChoiceField,self).validate(value)
try:
get_template(value)
except TemplateDoesNotExist:
raise ValidationError(_('%s is not a valid template.' % value))
|
[
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"_",
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] |
Check for empty values, and for an existing template, but do not check if
this is one of the initial choices provided.
|
[
"Check",
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"one",
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"the",
"initial",
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"provided",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L242-L252
|
3,619
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
PluginTemplateMixin.render
|
def render(self, context, instance, placeholder):
''' Permits setting of the template in the plugin instance configuration '''
if instance and instance.template:
self.render_template = instance.template
return super(PluginTemplateMixin,self).render(context,instance,placeholder)
|
python
|
def render(self, context, instance, placeholder):
''' Permits setting of the template in the plugin instance configuration '''
if instance and instance.template:
self.render_template = instance.template
return super(PluginTemplateMixin,self).render(context,instance,placeholder)
|
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Permits setting of the template in the plugin instance configuration
|
[
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L261-L265
|
3,620
|
django-danceschool/django-danceschool
|
danceschool/core/mixins.py
|
SiteHistoryMixin.get_return_page
|
def get_return_page(self,prior=False):
''' This is just a wrapper for the getReturnPage helper function. '''
siteHistory = self.request.session.get('SITE_HISTORY',{})
return getReturnPage(siteHistory,prior=prior)
|
python
|
def get_return_page(self,prior=False):
''' This is just a wrapper for the getReturnPage helper function. '''
siteHistory = self.request.session.get('SITE_HISTORY',{})
return getReturnPage(siteHistory,prior=prior)
|
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This is just a wrapper for the getReturnPage helper function.
|
[
"This",
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/mixins.py#L487-L490
|
3,621
|
django-danceschool/django-danceschool
|
danceschool/core/forms.py
|
RegistrationContactForm.is_valid
|
def is_valid(self):
'''
For this form to be considered valid, there must be not only no errors, but also no messages on
the request that need to be shown.
'''
valid = super(RegistrationContactForm,self).is_valid()
msgs = messages.get_messages(self._request)
# We only want validation messages to show up once, so pop messages that have already show up
# before checking to see if any messages remain to be shown.
prior_messages = self._session.pop('prior_messages',[])
remaining_messages = []
for m in msgs:
m_dict = {'message': m.message, 'level': m.level, 'extra_tags': m.extra_tags}
if m_dict not in prior_messages:
remaining_messages.append(m_dict)
if remaining_messages:
self._session['prior_messages'] = remaining_messages
self._request.session.modified = True
return False
return valid
|
python
|
def is_valid(self):
'''
For this form to be considered valid, there must be not only no errors, but also no messages on
the request that need to be shown.
'''
valid = super(RegistrationContactForm,self).is_valid()
msgs = messages.get_messages(self._request)
# We only want validation messages to show up once, so pop messages that have already show up
# before checking to see if any messages remain to be shown.
prior_messages = self._session.pop('prior_messages',[])
remaining_messages = []
for m in msgs:
m_dict = {'message': m.message, 'level': m.level, 'extra_tags': m.extra_tags}
if m_dict not in prior_messages:
remaining_messages.append(m_dict)
if remaining_messages:
self._session['prior_messages'] = remaining_messages
self._request.session.modified = True
return False
return valid
|
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For this form to be considered valid, there must be not only no errors, but also no messages on
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/forms.py#L378-L401
|
3,622
|
django-danceschool/django-danceschool
|
danceschool/core/forms.py
|
RefundForm.clean_total_refund_amount
|
def clean_total_refund_amount(self):
'''
The Javascript should ensure that the hidden input is updated, but double check it here.
'''
initial = self.cleaned_data.get('initial_refund_amount', 0)
total = self.cleaned_data['total_refund_amount']
summed_refunds = sum([v for k,v in self.cleaned_data.items() if k.startswith('item_refundamount_')])
if not self.cleaned_data.get('id'):
raise ValidationError('ID not in cleaned data')
if summed_refunds != total:
raise ValidationError(_('Passed value does not match sum of allocated refunds.'))
elif summed_refunds > self.cleaned_data['id'].amountPaid + self.cleaned_data['id'].refunds:
raise ValidationError(_('Total refunds allocated exceed revenue received.'))
elif total < initial:
raise ValidationError(_('Cannot reduce the total amount of the refund.'))
return total
|
python
|
def clean_total_refund_amount(self):
'''
The Javascript should ensure that the hidden input is updated, but double check it here.
'''
initial = self.cleaned_data.get('initial_refund_amount', 0)
total = self.cleaned_data['total_refund_amount']
summed_refunds = sum([v for k,v in self.cleaned_data.items() if k.startswith('item_refundamount_')])
if not self.cleaned_data.get('id'):
raise ValidationError('ID not in cleaned data')
if summed_refunds != total:
raise ValidationError(_('Passed value does not match sum of allocated refunds.'))
elif summed_refunds > self.cleaned_data['id'].amountPaid + self.cleaned_data['id'].refunds:
raise ValidationError(_('Total refunds allocated exceed revenue received.'))
elif total < initial:
raise ValidationError(_('Cannot reduce the total amount of the refund.'))
return total
|
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The Javascript should ensure that the hidden input is updated, but double check it here.
|
[
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/forms.py#L662-L679
|
3,623
|
django-danceschool/django-danceschool
|
danceschool/core/forms.py
|
SubstituteReportingForm.clean
|
def clean(self):
'''
This code prevents multiple individuals from substituting for the
same class and class teacher. It also prevents an individual from
substituting for a class in which they are a teacher.
'''
super(SubstituteReportingForm,self).clean()
occurrences = self.cleaned_data.get('occurrences',[])
staffMember = self.cleaned_data.get('staffMember')
replacementFor = self.cleaned_data.get('replacedStaffMember',[])
event = self.cleaned_data.get('event')
for occ in occurrences:
for this_sub in occ.eventstaffmember_set.all():
if this_sub.replacedStaffMember == replacementFor:
self.add_error('occurrences',ValidationError(_('One or more classes you have selected already has a substitute teacher for that class.'),code='invalid'))
if event and staffMember:
if staffMember in [x.staffMember for x in event.eventstaffmember_set.filter(category__in=[getConstant('general__eventStaffCategoryAssistant'),getConstant('general__eventStaffCategoryInstructor')])]:
self.add_error('event',ValidationError(_('You cannot substitute teach for a class in which you were an instructor.'),code='invalid'))
|
python
|
def clean(self):
'''
This code prevents multiple individuals from substituting for the
same class and class teacher. It also prevents an individual from
substituting for a class in which they are a teacher.
'''
super(SubstituteReportingForm,self).clean()
occurrences = self.cleaned_data.get('occurrences',[])
staffMember = self.cleaned_data.get('staffMember')
replacementFor = self.cleaned_data.get('replacedStaffMember',[])
event = self.cleaned_data.get('event')
for occ in occurrences:
for this_sub in occ.eventstaffmember_set.all():
if this_sub.replacedStaffMember == replacementFor:
self.add_error('occurrences',ValidationError(_('One or more classes you have selected already has a substitute teacher for that class.'),code='invalid'))
if event and staffMember:
if staffMember in [x.staffMember for x in event.eventstaffmember_set.filter(category__in=[getConstant('general__eventStaffCategoryAssistant'),getConstant('general__eventStaffCategoryInstructor')])]:
self.add_error('event',ValidationError(_('You cannot substitute teach for a class in which you were an instructor.'),code='invalid'))
|
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This code prevents multiple individuals from substituting for the
same class and class teacher. It also prevents an individual from
substituting for a class in which they are a teacher.
|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/forms.py#L868-L888
|
3,624
|
django-danceschool/django-danceschool
|
danceschool/core/forms.py
|
SubstituteReportingForm.save
|
def save(self, commit=True):
'''
If a staff member is reporting substitute teaching for a second time, then we should update
the list of occurrences for which they are a substitute on their existing EventStaffMember
record, rather than creating a new record and creating database issues.
'''
existing_record = EventStaffMember.objects.filter(
staffMember=self.cleaned_data.get('staffMember'),
event=self.cleaned_data.get('event'),
category=getConstant('general__eventStaffCategorySubstitute'),
replacedStaffMember=self.cleaned_data.get('replacedStaffMember'),
)
if existing_record.exists():
record = existing_record.first()
for x in self.cleaned_data.get('occurrences'):
record.occurrences.add(x)
record.save()
return record
else:
return super(SubstituteReportingForm,self).save()
|
python
|
def save(self, commit=True):
'''
If a staff member is reporting substitute teaching for a second time, then we should update
the list of occurrences for which they are a substitute on their existing EventStaffMember
record, rather than creating a new record and creating database issues.
'''
existing_record = EventStaffMember.objects.filter(
staffMember=self.cleaned_data.get('staffMember'),
event=self.cleaned_data.get('event'),
category=getConstant('general__eventStaffCategorySubstitute'),
replacedStaffMember=self.cleaned_data.get('replacedStaffMember'),
)
if existing_record.exists():
record = existing_record.first()
for x in self.cleaned_data.get('occurrences'):
record.occurrences.add(x)
record.save()
return record
else:
return super(SubstituteReportingForm,self).save()
|
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If a staff member is reporting substitute teaching for a second time, then we should update
the list of occurrences for which they are a substitute on their existing EventStaffMember
record, rather than creating a new record and creating database issues.
|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/forms.py#L898-L917
|
3,625
|
django-danceschool/django-danceschool
|
danceschool/core/forms.py
|
StaffMemberBioChangeForm.save
|
def save(self, commit=True):
''' If the staff member is an instructor, also update the availableForPrivates field on the Instructor record. '''
if getattr(self.instance,'instructor',None):
self.instance.instructor.availableForPrivates = self.cleaned_data.pop('availableForPrivates',self.instance.instructor.availableForPrivates)
self.instance.instructor.save(update_fields=['availableForPrivates',])
super(StaffMemberBioChangeForm,self).save(commit=True)
|
python
|
def save(self, commit=True):
''' If the staff member is an instructor, also update the availableForPrivates field on the Instructor record. '''
if getattr(self.instance,'instructor',None):
self.instance.instructor.availableForPrivates = self.cleaned_data.pop('availableForPrivates',self.instance.instructor.availableForPrivates)
self.instance.instructor.save(update_fields=['availableForPrivates',])
super(StaffMemberBioChangeForm,self).save(commit=True)
|
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] |
If the staff member is an instructor, also update the availableForPrivates field on the Instructor record.
|
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"record",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/forms.py#L942-L947
|
3,626
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
DanceRole.save
|
def save(self, *args, **kwargs):
''' Just add "s" if no plural name given. '''
if not self.pluralName:
self.pluralName = self.name + 's'
super(self.__class__, self).save(*args, **kwargs)
|
python
|
def save(self, *args, **kwargs):
''' Just add "s" if no plural name given. '''
if not self.pluralName:
self.pluralName = self.name + 's'
super(self.__class__, self).save(*args, **kwargs)
|
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] |
Just add "s" if no plural name given.
|
[
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L83-L89
|
3,627
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
PricingTier.getBasePrice
|
def getBasePrice(self,**kwargs):
'''
This handles the logic of finding the correct price. If more sophisticated
discounting systems are needed, then this PricingTier model can be subclassed,
or the discounts and vouchers apps can be used.
'''
payAtDoor = kwargs.get('payAtDoor', False)
dropIns = kwargs.get('dropIns', 0)
if dropIns:
return dropIns * self.dropinPrice
if payAtDoor:
return self.doorPrice
return self.onlinePrice
|
python
|
def getBasePrice(self,**kwargs):
'''
This handles the logic of finding the correct price. If more sophisticated
discounting systems are needed, then this PricingTier model can be subclassed,
or the discounts and vouchers apps can be used.
'''
payAtDoor = kwargs.get('payAtDoor', False)
dropIns = kwargs.get('dropIns', 0)
if dropIns:
return dropIns * self.dropinPrice
if payAtDoor:
return self.doorPrice
return self.onlinePrice
|
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This handles the logic of finding the correct price. If more sophisticated
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|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L432-L445
|
3,628
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Event.availableRoles
|
def availableRoles(self):
'''
Returns the set of roles for this event. Since roles are not always custom specified for
event, this looks for the set of available roles in multiple places. If no roles are found,
then the method returns an empty list, in which case it can be assumed that the event's registration
is not role-specific.
'''
eventRoles = self.eventrole_set.filter(capacity__gt=0)
if eventRoles.count() > 0:
return [x.role for x in eventRoles]
elif isinstance(self,Series):
return self.classDescription.danceTypeLevel.danceType.roles.all()
return []
|
python
|
def availableRoles(self):
'''
Returns the set of roles for this event. Since roles are not always custom specified for
event, this looks for the set of available roles in multiple places. If no roles are found,
then the method returns an empty list, in which case it can be assumed that the event's registration
is not role-specific.
'''
eventRoles = self.eventrole_set.filter(capacity__gt=0)
if eventRoles.count() > 0:
return [x.role for x in eventRoles]
elif isinstance(self,Series):
return self.classDescription.danceTypeLevel.danceType.roles.all()
return []
|
[
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Returns the set of roles for this event. Since roles are not always custom specified for
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is not role-specific.
|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L952-L964
|
3,629
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Event.numRegisteredForRole
|
def numRegisteredForRole(self, role, includeTemporaryRegs=False):
'''
Accepts a DanceRole object and returns the number of registrations of that role.
'''
count = self.eventregistration_set.filter(cancelled=False,dropIn=False,role=role).count()
if includeTemporaryRegs:
count += self.temporaryeventregistration_set.filter(dropIn=False,role=role).exclude(
registration__expirationDate__lte=timezone.now()).count()
return count
|
python
|
def numRegisteredForRole(self, role, includeTemporaryRegs=False):
'''
Accepts a DanceRole object and returns the number of registrations of that role.
'''
count = self.eventregistration_set.filter(cancelled=False,dropIn=False,role=role).count()
if includeTemporaryRegs:
count += self.temporaryeventregistration_set.filter(dropIn=False,role=role).exclude(
registration__expirationDate__lte=timezone.now()).count()
return count
|
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Accepts a DanceRole object and returns the number of registrations of that role.
|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L967-L975
|
3,630
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Event.capacityForRole
|
def capacityForRole(self,role):
'''
Accepts a DanceRole object and determines the capacity for that role at this event.this
Since roles are not always custom specified for events, this looks for the set of
available roles in multiple places, and only returns the overall capacity of the event
if roles are not found elsewhere.
'''
if isinstance(role, DanceRole):
role_id = role.id
else:
role_id = role
eventRoles = self.eventrole_set.filter(capacity__gt=0)
if eventRoles.count() > 0 and role_id not in [x.role.id for x in eventRoles]:
''' Custom role capacities exist but role this is not one of them. '''
return 0
elif eventRoles.count() > 0:
''' The role is a match to custom roles, so check the capacity. '''
return eventRoles.get(role=role).capacity
# No custom roles for this event, so get the danceType roles and use the overall
# capacity divided by the number of roles
if isinstance(self,Series):
try:
availableRoles = self.classDescription.danceTypeLevel.danceType.roles.all()
if availableRoles.count() > 0 and role_id not in [x.id for x in availableRoles]:
''' DanceType roles specified and this is not one of them '''
return 0
elif availableRoles.count() > 0 and self.capacity:
# Divide the total capacity by the number of roles and round up.
return ceil(self.capacity / availableRoles.count())
except ObjectDoesNotExist as e:
logger.error('Error in calculating capacity for role: %s' % e)
# No custom roles and no danceType to get roles from, so return the overall capacity
return self.capacity
|
python
|
def capacityForRole(self,role):
'''
Accepts a DanceRole object and determines the capacity for that role at this event.this
Since roles are not always custom specified for events, this looks for the set of
available roles in multiple places, and only returns the overall capacity of the event
if roles are not found elsewhere.
'''
if isinstance(role, DanceRole):
role_id = role.id
else:
role_id = role
eventRoles = self.eventrole_set.filter(capacity__gt=0)
if eventRoles.count() > 0 and role_id not in [x.role.id for x in eventRoles]:
''' Custom role capacities exist but role this is not one of them. '''
return 0
elif eventRoles.count() > 0:
''' The role is a match to custom roles, so check the capacity. '''
return eventRoles.get(role=role).capacity
# No custom roles for this event, so get the danceType roles and use the overall
# capacity divided by the number of roles
if isinstance(self,Series):
try:
availableRoles = self.classDescription.danceTypeLevel.danceType.roles.all()
if availableRoles.count() > 0 and role_id not in [x.id for x in availableRoles]:
''' DanceType roles specified and this is not one of them '''
return 0
elif availableRoles.count() > 0 and self.capacity:
# Divide the total capacity by the number of roles and round up.
return ceil(self.capacity / availableRoles.count())
except ObjectDoesNotExist as e:
logger.error('Error in calculating capacity for role: %s' % e)
# No custom roles and no danceType to get roles from, so return the overall capacity
return self.capacity
|
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Accepts a DanceRole object and determines the capacity for that role at this event.this
Since roles are not always custom specified for events, this looks for the set of
available roles in multiple places, and only returns the overall capacity of the event
if roles are not found elsewhere.
|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L986-L1022
|
3,631
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Event.soldOutForRole
|
def soldOutForRole(self,role,includeTemporaryRegs=False):
'''
Accepts a DanceRole object and responds if the number of registrations for that
role exceeds the capacity for that role at this event.
'''
return self.numRegisteredForRole(
role,includeTemporaryRegs=includeTemporaryRegs) >= (self.capacityForRole(role) or 0)
|
python
|
def soldOutForRole(self,role,includeTemporaryRegs=False):
'''
Accepts a DanceRole object and responds if the number of registrations for that
role exceeds the capacity for that role at this event.
'''
return self.numRegisteredForRole(
role,includeTemporaryRegs=includeTemporaryRegs) >= (self.capacityForRole(role) or 0)
|
[
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] |
Accepts a DanceRole object and responds if the number of registrations for that
role exceeds the capacity for that role at this event.
|
[
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1024-L1030
|
3,632
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
EventOccurrence.allDayForDate
|
def allDayForDate(self,this_date,timeZone=None):
'''
This method determines whether the occurrence lasts the entirety of
a specified day in the specified time zone. If no time zone is specified,
then it uses the default time zone). Also, give a grace period of a few
minutes to account for issues with the way events are sometimes entered.
'''
if isinstance(this_date,datetime):
d = this_date.date()
else:
d = this_date
date_start = datetime(d.year,d.month,d.day)
naive_start = self.startTime if timezone.is_naive(self.startTime) else timezone.make_naive(self.startTime, timezone=timeZone)
naive_end = self.endTime if timezone.is_naive(self.endTime) else timezone.make_naive(self.endTime, timezone=timeZone)
return (
# Ensure that all comparisons are done in local time
naive_start <= date_start and
naive_end >= date_start + timedelta(days=1,minutes=-30)
)
|
python
|
def allDayForDate(self,this_date,timeZone=None):
'''
This method determines whether the occurrence lasts the entirety of
a specified day in the specified time zone. If no time zone is specified,
then it uses the default time zone). Also, give a grace period of a few
minutes to account for issues with the way events are sometimes entered.
'''
if isinstance(this_date,datetime):
d = this_date.date()
else:
d = this_date
date_start = datetime(d.year,d.month,d.day)
naive_start = self.startTime if timezone.is_naive(self.startTime) else timezone.make_naive(self.startTime, timezone=timeZone)
naive_end = self.endTime if timezone.is_naive(self.endTime) else timezone.make_naive(self.endTime, timezone=timeZone)
return (
# Ensure that all comparisons are done in local time
naive_start <= date_start and
naive_end >= date_start + timedelta(days=1,minutes=-30)
)
|
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This method determines whether the occurrence lasts the entirety of
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minutes to account for issues with the way events are sometimes entered.
|
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1191-L1211
|
3,633
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
EventStaffMember.netHours
|
def netHours(self):
'''
For regular event staff, this is the net hours worked for financial purposes.
For Instructors, netHours is caclulated net of any substitutes.
'''
if self.specifiedHours is not None:
return self.specifiedHours
elif self.category in [getConstant('general__eventStaffCategoryAssistant'),getConstant('general__eventStaffCategoryInstructor')]:
return self.event.duration - sum([sub.netHours for sub in self.replacementFor.all()])
else:
return sum([x.duration for x in self.occurrences.filter(cancelled=False)])
|
python
|
def netHours(self):
'''
For regular event staff, this is the net hours worked for financial purposes.
For Instructors, netHours is caclulated net of any substitutes.
'''
if self.specifiedHours is not None:
return self.specifiedHours
elif self.category in [getConstant('general__eventStaffCategoryAssistant'),getConstant('general__eventStaffCategoryInstructor')]:
return self.event.duration - sum([sub.netHours for sub in self.replacementFor.all()])
else:
return sum([x.duration for x in self.occurrences.filter(cancelled=False)])
|
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For regular event staff, this is the net hours worked for financial purposes.
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|
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"net",
"of",
"any",
"substitutes",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1284-L1294
|
3,634
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Series.shortDescription
|
def shortDescription(self):
'''
Overrides property from Event base class.
'''
cd = getattr(self,'classDescription',None)
if cd:
sd = getattr(cd,'shortDescription','')
d = getattr(cd,'description','')
return sd if sd else d
return ''
|
python
|
def shortDescription(self):
'''
Overrides property from Event base class.
'''
cd = getattr(self,'classDescription',None)
if cd:
sd = getattr(cd,'shortDescription','')
d = getattr(cd,'description','')
return sd if sd else d
return ''
|
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Overrides property from Event base class.
|
[
"Overrides",
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"Event",
"base",
"class",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1360-L1369
|
3,635
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
SeriesTeacher.netHours
|
def netHours(self):
'''
For regular event staff, this is the net hours worked for financial purposes.
For Instructors, netHours is calculated net of any substitutes.
'''
if self.specifiedHours is not None:
return self.specifiedHours
return self.event.duration - sum([sub.netHours for sub in self.replacementFor.all()])
|
python
|
def netHours(self):
'''
For regular event staff, this is the net hours worked for financial purposes.
For Instructors, netHours is calculated net of any substitutes.
'''
if self.specifiedHours is not None:
return self.specifiedHours
return self.event.duration - sum([sub.netHours for sub in self.replacementFor.all()])
|
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For regular event staff, this is the net hours worked for financial purposes.
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|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1466-L1473
|
3,636
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
TemporaryRegistration.getTimeOfClassesRemaining
|
def getTimeOfClassesRemaining(self,numClasses=0):
'''
For checking things like prerequisites, it's useful to check if a requirement is 'almost' met
'''
occurrences = EventOccurrence.objects.filter(
cancelled=False,
event__in=[x.event for x in self.temporaryeventregistration_set.filter(event__series__isnull=False)],
).order_by('-endTime')
if occurrences.count() > numClasses:
return occurrences[numClasses].endTime
else:
return occurrences.last().startTime
|
python
|
def getTimeOfClassesRemaining(self,numClasses=0):
'''
For checking things like prerequisites, it's useful to check if a requirement is 'almost' met
'''
occurrences = EventOccurrence.objects.filter(
cancelled=False,
event__in=[x.event for x in self.temporaryeventregistration_set.filter(event__series__isnull=False)],
).order_by('-endTime')
if occurrences.count() > numClasses:
return occurrences[numClasses].endTime
else:
return occurrences.last().startTime
|
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1952-L1963
|
3,637
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
TemporaryRegistration.finalize
|
def finalize(self,**kwargs):
'''
This method is called when the payment process has been completed and a registration
is ready to be finalized. It also fires the post-registration signal
'''
dateTime = kwargs.pop('dateTime', timezone.now())
# If sendEmail is passed as False, then we won't send an email
sendEmail = kwargs.pop('sendEmail', True)
customer, created = Customer.objects.update_or_create(
first_name=self.firstName,last_name=self.lastName,
email=self.email,defaults={'phone': self.phone}
)
regArgs = {
'customer': customer,
'firstName': self.firstName,
'lastName': self.lastName,
'dateTime': dateTime,
'temporaryRegistration': self
}
for key in ['comments', 'howHeardAboutUs', 'student', 'priceWithDiscount','payAtDoor']:
regArgs[key] = kwargs.pop(key, getattr(self,key,None))
# All other passed kwargs are put into the data JSON
regArgs['data'] = self.data
regArgs['data'].update(kwargs)
realreg = Registration(**regArgs)
realreg.save()
logger.debug('Created registration with id: ' + str(realreg.id))
for er in self.temporaryeventregistration_set.all():
logger.debug('Creating eventreg for event: ' + str(er.event.id))
realer = EventRegistration(registration=realreg,event=er.event,
customer=customer,role=er.role,
price=er.price,
dropIn=er.dropIn,
data=er.data
)
realer.save()
# Mark this temporary registration as expired, so that it won't
# be counted twice against the number of in-progress registrations
# in the future when another customer tries to register.
self.expirationDate = timezone.now()
self.save()
# This signal can, for example, be caught by the vouchers app to keep track of any vouchers
# that were applied
post_registration.send(
sender=TemporaryRegistration,
registration=realreg
)
if sendEmail:
if getConstant('email__disableSiteEmails'):
logger.info('Sending of confirmation emails is disabled.')
else:
logger.info('Sending confirmation email.')
template = getConstant('email__registrationSuccessTemplate')
realreg.email_recipient(
subject=template.subject,
content=template.content,
html_content=template.html_content,
send_html=template.send_html,
from_address=template.defaultFromAddress,
from_name=template.defaultFromName,
cc=template.defaultCC,
)
# Return the newly-created finalized registration object
return realreg
|
python
|
def finalize(self,**kwargs):
'''
This method is called when the payment process has been completed and a registration
is ready to be finalized. It also fires the post-registration signal
'''
dateTime = kwargs.pop('dateTime', timezone.now())
# If sendEmail is passed as False, then we won't send an email
sendEmail = kwargs.pop('sendEmail', True)
customer, created = Customer.objects.update_or_create(
first_name=self.firstName,last_name=self.lastName,
email=self.email,defaults={'phone': self.phone}
)
regArgs = {
'customer': customer,
'firstName': self.firstName,
'lastName': self.lastName,
'dateTime': dateTime,
'temporaryRegistration': self
}
for key in ['comments', 'howHeardAboutUs', 'student', 'priceWithDiscount','payAtDoor']:
regArgs[key] = kwargs.pop(key, getattr(self,key,None))
# All other passed kwargs are put into the data JSON
regArgs['data'] = self.data
regArgs['data'].update(kwargs)
realreg = Registration(**regArgs)
realreg.save()
logger.debug('Created registration with id: ' + str(realreg.id))
for er in self.temporaryeventregistration_set.all():
logger.debug('Creating eventreg for event: ' + str(er.event.id))
realer = EventRegistration(registration=realreg,event=er.event,
customer=customer,role=er.role,
price=er.price,
dropIn=er.dropIn,
data=er.data
)
realer.save()
# Mark this temporary registration as expired, so that it won't
# be counted twice against the number of in-progress registrations
# in the future when another customer tries to register.
self.expirationDate = timezone.now()
self.save()
# This signal can, for example, be caught by the vouchers app to keep track of any vouchers
# that were applied
post_registration.send(
sender=TemporaryRegistration,
registration=realreg
)
if sendEmail:
if getConstant('email__disableSiteEmails'):
logger.info('Sending of confirmation emails is disabled.')
else:
logger.info('Sending confirmation email.')
template = getConstant('email__registrationSuccessTemplate')
realreg.email_recipient(
subject=template.subject,
content=template.content,
html_content=template.html_content,
send_html=template.send_html,
from_address=template.defaultFromAddress,
from_name=template.defaultFromName,
cc=template.defaultCC,
)
# Return the newly-created finalized registration object
return realreg
|
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This method is called when the payment process has been completed and a registration
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|
[
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L1987-L2061
|
3,638
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
EmailTemplate.save
|
def save(self, *args, **kwargs):
'''
If this is an HTML template, then set the non-HTML content to be the stripped version of the HTML.
If this is a plain text template, then set the HTML content to be null.
'''
if self.send_html:
self.content = get_text_for_html(self.html_content)
else:
self.html_content = None
super(EmailTemplate, self).save(*args, **kwargs)
|
python
|
def save(self, *args, **kwargs):
'''
If this is an HTML template, then set the non-HTML content to be the stripped version of the HTML.
If this is a plain text template, then set the HTML content to be null.
'''
if self.send_html:
self.content = get_text_for_html(self.html_content)
else:
self.html_content = None
super(EmailTemplate, self).save(*args, **kwargs)
|
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L2469-L2479
|
3,639
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Invoice.create_from_registration
|
def create_from_registration(cls, reg, **kwargs):
'''
Handles the creation of an Invoice as well as one InvoiceItem per
assodciated TemporaryEventRegistration or registration. Also handles taxes
appropriately.
'''
submissionUser = kwargs.pop('submissionUser', None)
collectedByUser = kwargs.pop('collectedByUser', None)
status = kwargs.pop('status',Invoice.PaymentStatus.unpaid)
new_invoice = cls(
firstName=reg.firstName,
lastName=reg.lastName,
email=reg.email,
grossTotal=reg.totalPrice,
total=reg.priceWithDiscount,
submissionUser=submissionUser,
collectedByUser=collectedByUser,
buyerPaysSalesTax=getConstant('registration__buyerPaysSalesTax'),
status=status,
data=kwargs,
)
if isinstance(reg, Registration):
new_invoice.finalRegistration = reg
ter_set = reg.eventregistration_set.all()
elif isinstance(reg, TemporaryRegistration):
new_invoice.temporaryRegistration = reg
ter_set = reg.temporaryeventregistration_set.all()
else:
raise ValueError('Object passed is not a registration.')
new_invoice.calculateTaxes()
new_invoice.save()
# Now, create InvoiceItem records for each EventRegistration
for ter in ter_set:
# Discounts and vouchers are always applied equally to all items at initial
# invoice creation.
item_kwargs = {
'invoice': new_invoice,
'grossTotal': ter.price,
}
if new_invoice.grossTotal > 0:
item_kwargs.update({
'total': ter.price * (new_invoice.total / new_invoice.grossTotal),
'taxes': new_invoice.taxes * (ter.price / new_invoice.grossTotal),
'fees': new_invoice.fees * (ter.price / new_invoice.grossTotal),
})
else:
item_kwargs.update({
'total': ter.price,
'taxes': new_invoice.taxes,
'fees': new_invoice.fees,
})
if isinstance(ter,TemporaryEventRegistration):
item_kwargs['temporaryEventRegistration'] = ter
elif isinstance(ter,EventRegistration):
item_kwargs['finalEventRegistration'] = ter
this_item = InvoiceItem(**item_kwargs)
this_item.save()
return new_invoice
|
python
|
def create_from_registration(cls, reg, **kwargs):
'''
Handles the creation of an Invoice as well as one InvoiceItem per
assodciated TemporaryEventRegistration or registration. Also handles taxes
appropriately.
'''
submissionUser = kwargs.pop('submissionUser', None)
collectedByUser = kwargs.pop('collectedByUser', None)
status = kwargs.pop('status',Invoice.PaymentStatus.unpaid)
new_invoice = cls(
firstName=reg.firstName,
lastName=reg.lastName,
email=reg.email,
grossTotal=reg.totalPrice,
total=reg.priceWithDiscount,
submissionUser=submissionUser,
collectedByUser=collectedByUser,
buyerPaysSalesTax=getConstant('registration__buyerPaysSalesTax'),
status=status,
data=kwargs,
)
if isinstance(reg, Registration):
new_invoice.finalRegistration = reg
ter_set = reg.eventregistration_set.all()
elif isinstance(reg, TemporaryRegistration):
new_invoice.temporaryRegistration = reg
ter_set = reg.temporaryeventregistration_set.all()
else:
raise ValueError('Object passed is not a registration.')
new_invoice.calculateTaxes()
new_invoice.save()
# Now, create InvoiceItem records for each EventRegistration
for ter in ter_set:
# Discounts and vouchers are always applied equally to all items at initial
# invoice creation.
item_kwargs = {
'invoice': new_invoice,
'grossTotal': ter.price,
}
if new_invoice.grossTotal > 0:
item_kwargs.update({
'total': ter.price * (new_invoice.total / new_invoice.grossTotal),
'taxes': new_invoice.taxes * (ter.price / new_invoice.grossTotal),
'fees': new_invoice.fees * (ter.price / new_invoice.grossTotal),
})
else:
item_kwargs.update({
'total': ter.price,
'taxes': new_invoice.taxes,
'fees': new_invoice.fees,
})
if isinstance(ter,TemporaryEventRegistration):
item_kwargs['temporaryEventRegistration'] = ter
elif isinstance(ter,EventRegistration):
item_kwargs['finalEventRegistration'] = ter
this_item = InvoiceItem(**item_kwargs)
this_item.save()
return new_invoice
|
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Handles the creation of an Invoice as well as one InvoiceItem per
assodciated TemporaryEventRegistration or registration. Also handles taxes
appropriately.
|
[
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L2591-L2656
|
3,640
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Invoice.url
|
def url(self):
'''
Because invoice URLs are generally emailed, this
includes the default site URL and the protocol specified in
settings.
'''
if self.id:
return '%s://%s%s' % (
getConstant('email__linkProtocol'),
Site.objects.get_current().domain,
reverse('viewInvoice', args=[self.id,]),
)
|
python
|
def url(self):
'''
Because invoice URLs are generally emailed, this
includes the default site URL and the protocol specified in
settings.
'''
if self.id:
return '%s://%s%s' % (
getConstant('email__linkProtocol'),
Site.objects.get_current().domain,
reverse('viewInvoice', args=[self.id,]),
)
|
[
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Because invoice URLs are generally emailed, this
includes the default site URL and the protocol specified in
settings.
|
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"URL",
"and",
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L2710-L2721
|
3,641
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Invoice.calculateTaxes
|
def calculateTaxes(self):
'''
Updates the tax field to reflect the amount of taxes depending on
the local rate as well as whether the buyer or seller pays sales tax.
'''
tax_rate = (getConstant('registration__salesTaxRate') or 0) / 100
if tax_rate > 0:
if self.buyerPaysSalesTax:
# If the buyer pays taxes, then taxes are just added as a fraction of the price
self.taxes = self.total * tax_rate
else:
# If the seller pays sales taxes, then adjusted_total will be their net revenue,
# and under this calculation adjusted_total + taxes = the price charged
adjusted_total = self.total / (1 + tax_rate)
self.taxes = adjusted_total * tax_rate
|
python
|
def calculateTaxes(self):
'''
Updates the tax field to reflect the amount of taxes depending on
the local rate as well as whether the buyer or seller pays sales tax.
'''
tax_rate = (getConstant('registration__salesTaxRate') or 0) / 100
if tax_rate > 0:
if self.buyerPaysSalesTax:
# If the buyer pays taxes, then taxes are just added as a fraction of the price
self.taxes = self.total * tax_rate
else:
# If the seller pays sales taxes, then adjusted_total will be their net revenue,
# and under this calculation adjusted_total + taxes = the price charged
adjusted_total = self.total / (1 + tax_rate)
self.taxes = adjusted_total * tax_rate
|
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Updates the tax field to reflect the amount of taxes depending on
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|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L2777-L2793
|
3,642
|
django-danceschool/django-danceschool
|
danceschool/core/models.py
|
Invoice.allocateFees
|
def allocateFees(self):
'''
Fees are allocated across invoice items based on their discounted
total price net of adjustments as a proportion of the overall
invoice's total price
'''
items = list(self.invoiceitem_set.all())
# Check that totals and adjusments match. If they do not, raise an error.
if self.total != sum([x.total for x in items]):
msg = _('Invoice item totals do not match invoice total. Unable to allocate fees.')
logger.error(str(msg))
raise ValidationError(msg)
if self.adjustments != sum([x.adjustments for x in items]):
msg = _('Invoice item adjustments do not match invoice adjustments. Unable to allocate fees.')
logger.error(str(msg))
raise ValidationError(msg)
for item in items:
saveFlag = False
if self.total - self.adjustments > 0:
item.fees = self.fees * ((item.total - item.adjustments) / (self.total - self.adjustments))
saveFlag = True
# In the case of full refunds, allocate fees according to the
# initial total price of the item only.
elif self.total - self.adjustments == 0 and self.total > 0:
item.fees = self.fees * (item.total / self.total)
saveFlag = True
# In the unexpected event of fees with no total, just divide
# the fees equally among the items.
elif self.fees:
item.fees = self.fees * (1 / len(items))
saveFlag = True
if saveFlag:
item.save()
|
python
|
def allocateFees(self):
'''
Fees are allocated across invoice items based on their discounted
total price net of adjustments as a proportion of the overall
invoice's total price
'''
items = list(self.invoiceitem_set.all())
# Check that totals and adjusments match. If they do not, raise an error.
if self.total != sum([x.total for x in items]):
msg = _('Invoice item totals do not match invoice total. Unable to allocate fees.')
logger.error(str(msg))
raise ValidationError(msg)
if self.adjustments != sum([x.adjustments for x in items]):
msg = _('Invoice item adjustments do not match invoice adjustments. Unable to allocate fees.')
logger.error(str(msg))
raise ValidationError(msg)
for item in items:
saveFlag = False
if self.total - self.adjustments > 0:
item.fees = self.fees * ((item.total - item.adjustments) / (self.total - self.adjustments))
saveFlag = True
# In the case of full refunds, allocate fees according to the
# initial total price of the item only.
elif self.total - self.adjustments == 0 and self.total > 0:
item.fees = self.fees * (item.total / self.total)
saveFlag = True
# In the unexpected event of fees with no total, just divide
# the fees equally among the items.
elif self.fees:
item.fees = self.fees * (1 / len(items))
saveFlag = True
if saveFlag:
item.save()
|
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Fees are allocated across invoice items based on their discounted
total price net of adjustments as a proportion of the overall
invoice's total price
|
[
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/core/models.py#L2865-L2903
|
3,643
|
django-danceschool/django-danceschool
|
danceschool/discounts/models.py
|
DiscountCombo.applyAndAllocate
|
def applyAndAllocate(self,allocatedPrices,tieredTuples,payAtDoor=False):
'''
This method takes an initial allocation of prices across events, and
an identical length list of allocation tuples. It applies the rule
specified by this discount, allocates the discount across the listed
items, and returns both the price and the allocation
'''
initial_net_price = sum([x for x in allocatedPrices])
if self.discountType == self.DiscountType.flatPrice:
# Flat-price for all applicable items (partial application for items which are
# only partially needed to apply the discount). Flat prices ignore any previous discounts
# in other categories which may have been the best, but they only are applied if they are
# lower than the price that would be feasible by applying those prior discounts alone.
applicable_price = self.getFlatPrice(payAtDoor) or 0
this_price = applicable_price \
+ sum([x[0].event.getBasePrice(payAtDoor=payAtDoor) * x[1] if x[1] != 1 else x[0].price for x in tieredTuples])
# Flat prices are allocated equally across all events
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
elif self.discountType == self.DiscountType.dollarDiscount:
# Discount the set of applicable items by a specific number of dollars (currency units)
# Dollar discounts are allocated equally across all events.
this_price = initial_net_price - self.dollarDiscount
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
elif self.discountType == DiscountCombo.DiscountType.percentDiscount:
# Percentage off discounts, which may be applied to all items in the cart,
# or just to the items that were needed to apply the discount
if self.percentUniversallyApplied:
this_price = \
initial_net_price * (1 - (max(min(self.percentDiscount or 0,100),0) / 100))
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
else:
# Allocate the percentage discount based on the prior allocation from the prior category
this_price = 0
this_allocated_prices = []
for idx, val in enumerate(tieredTuples):
this_val = (
allocatedPrices[idx] *
(1 - val[1]) * (1 - (max(min(self.percentDiscount or 0,100),0) / 100)) +
allocatedPrices[idx] * val[1]
)
this_allocated_prices.append(this_val)
this_price += this_val
else:
raise KeyError(_('Invalid discount type.'))
if this_price < initial_net_price:
# Ensure no negative prices
this_price = max(this_price, 0)
return self.DiscountInfo(self, this_price, initial_net_price - this_price, this_allocated_prices)
|
python
|
def applyAndAllocate(self,allocatedPrices,tieredTuples,payAtDoor=False):
'''
This method takes an initial allocation of prices across events, and
an identical length list of allocation tuples. It applies the rule
specified by this discount, allocates the discount across the listed
items, and returns both the price and the allocation
'''
initial_net_price = sum([x for x in allocatedPrices])
if self.discountType == self.DiscountType.flatPrice:
# Flat-price for all applicable items (partial application for items which are
# only partially needed to apply the discount). Flat prices ignore any previous discounts
# in other categories which may have been the best, but they only are applied if they are
# lower than the price that would be feasible by applying those prior discounts alone.
applicable_price = self.getFlatPrice(payAtDoor) or 0
this_price = applicable_price \
+ sum([x[0].event.getBasePrice(payAtDoor=payAtDoor) * x[1] if x[1] != 1 else x[0].price for x in tieredTuples])
# Flat prices are allocated equally across all events
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
elif self.discountType == self.DiscountType.dollarDiscount:
# Discount the set of applicable items by a specific number of dollars (currency units)
# Dollar discounts are allocated equally across all events.
this_price = initial_net_price - self.dollarDiscount
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
elif self.discountType == DiscountCombo.DiscountType.percentDiscount:
# Percentage off discounts, which may be applied to all items in the cart,
# or just to the items that were needed to apply the discount
if self.percentUniversallyApplied:
this_price = \
initial_net_price * (1 - (max(min(self.percentDiscount or 0,100),0) / 100))
this_allocated_prices = [x * (this_price / initial_net_price) for x in allocatedPrices]
else:
# Allocate the percentage discount based on the prior allocation from the prior category
this_price = 0
this_allocated_prices = []
for idx, val in enumerate(tieredTuples):
this_val = (
allocatedPrices[idx] *
(1 - val[1]) * (1 - (max(min(self.percentDiscount or 0,100),0) / 100)) +
allocatedPrices[idx] * val[1]
)
this_allocated_prices.append(this_val)
this_price += this_val
else:
raise KeyError(_('Invalid discount type.'))
if this_price < initial_net_price:
# Ensure no negative prices
this_price = max(this_price, 0)
return self.DiscountInfo(self, this_price, initial_net_price - this_price, this_allocated_prices)
|
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This method takes an initial allocation of prices across events, and
an identical length list of allocation tuples. It applies the rule
specified by this discount, allocates the discount across the listed
items, and returns both the price and the allocation
|
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/discounts/models.py#L146-L201
|
3,644
|
django-danceschool/django-danceschool
|
danceschool/discounts/models.py
|
DiscountCombo.getComponentList
|
def getComponentList(self):
'''
This function just returns a list with items that are supposed to
be present in the the list multiple times as multiple elements
of the list. It simplifies checking whether a discount's conditions
are satisfied.
'''
component_list = []
for x in self.discountcombocomponent_set.all():
for y in range(0,x.quantity):
component_list += [x]
component_list.sort(key=lambda x: x.quantity, reverse=True)
return component_list
|
python
|
def getComponentList(self):
'''
This function just returns a list with items that are supposed to
be present in the the list multiple times as multiple elements
of the list. It simplifies checking whether a discount's conditions
are satisfied.
'''
component_list = []
for x in self.discountcombocomponent_set.all():
for y in range(0,x.quantity):
component_list += [x]
component_list.sort(key=lambda x: x.quantity, reverse=True)
return component_list
|
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This function just returns a list with items that are supposed to
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of the list. It simplifies checking whether a discount's conditions
are satisfied.
|
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"conditions",
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"satisfied",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/discounts/models.py#L215-L230
|
3,645
|
django-danceschool/django-danceschool
|
danceschool/discounts/models.py
|
DiscountCombo.save
|
def save(self, *args, **kwargs):
'''
Don't save any passed values related to a type of discount
that is not the specified type
'''
if self.discountType != self.DiscountType.flatPrice:
self.onlinePrice = None
self.doorPrice = None
if self.discountType != self.DiscountType.dollarDiscount:
self.dollarDiscount = None
if self.discountType != self.DiscountType.percentDiscount:
self.percentDiscount = None
self.percentUniversallyApplied = False
super(DiscountCombo, self).save(*args, **kwargs)
|
python
|
def save(self, *args, **kwargs):
'''
Don't save any passed values related to a type of discount
that is not the specified type
'''
if self.discountType != self.DiscountType.flatPrice:
self.onlinePrice = None
self.doorPrice = None
if self.discountType != self.DiscountType.dollarDiscount:
self.dollarDiscount = None
if self.discountType != self.DiscountType.percentDiscount:
self.percentDiscount = None
self.percentUniversallyApplied = False
super(DiscountCombo, self).save(*args, **kwargs)
|
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|
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bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/discounts/models.py#L232-L249
|
3,646
|
django-danceschool/django-danceschool
|
danceschool/vouchers/handlers.py
|
checkVoucherCode
|
def checkVoucherCode(sender,**kwargs):
'''
Check that the given voucher code is valid
'''
logger.debug('Signal to check RegistrationContactForm handled by vouchers app.')
formData = kwargs.get('formData',{})
request = kwargs.get('request',{})
registration = kwargs.get('registration',None)
session = getattr(request,'session',{}).get(REG_VALIDATION_STR,{})
id = formData.get('gift','')
first = formData.get('firstName')
last = formData.get('lastName')
email = formData.get('email')
# Clean out the session data relating to vouchers so that we can revalidate it.
session.pop('total_voucher_amount',0)
session.pop('voucher_names',None)
session.pop('gift',None)
if id == '':
return
if not getConstant('vouchers__enableVouchers'):
raise ValidationError({'gift': _('Vouchers are disabled.')})
if session.get('gift','') != '':
raise ValidationError({'gift': _('Can\'t have more than one voucher')})
eventids = [x.event.id for x in registration.temporaryeventregistration_set.exclude(dropIn=True)]
seriess = Series.objects.filter(id__in=eventids)
obj = Voucher.objects.filter(voucherId=id).first()
if not obj:
raise ValidationError({'gift':_('Invalid Voucher Id')})
else:
customer = Customer.objects.filter(
first_name=first,
last_name=last,
email=email).first()
# This will raise any other errors that may be relevant
try:
obj.validateForCustomerAndSeriess(customer,seriess)
except ValidationError as e:
# Ensures that the error is applied to the correct field
raise ValidationError({'gift': e})
# If we got this far, then the voucher is determined to be valid, so the registration
# can proceed with no errors.
return
|
python
|
def checkVoucherCode(sender,**kwargs):
'''
Check that the given voucher code is valid
'''
logger.debug('Signal to check RegistrationContactForm handled by vouchers app.')
formData = kwargs.get('formData',{})
request = kwargs.get('request',{})
registration = kwargs.get('registration',None)
session = getattr(request,'session',{}).get(REG_VALIDATION_STR,{})
id = formData.get('gift','')
first = formData.get('firstName')
last = formData.get('lastName')
email = formData.get('email')
# Clean out the session data relating to vouchers so that we can revalidate it.
session.pop('total_voucher_amount',0)
session.pop('voucher_names',None)
session.pop('gift',None)
if id == '':
return
if not getConstant('vouchers__enableVouchers'):
raise ValidationError({'gift': _('Vouchers are disabled.')})
if session.get('gift','') != '':
raise ValidationError({'gift': _('Can\'t have more than one voucher')})
eventids = [x.event.id for x in registration.temporaryeventregistration_set.exclude(dropIn=True)]
seriess = Series.objects.filter(id__in=eventids)
obj = Voucher.objects.filter(voucherId=id).first()
if not obj:
raise ValidationError({'gift':_('Invalid Voucher Id')})
else:
customer = Customer.objects.filter(
first_name=first,
last_name=last,
email=email).first()
# This will raise any other errors that may be relevant
try:
obj.validateForCustomerAndSeriess(customer,seriess)
except ValidationError as e:
# Ensures that the error is applied to the correct field
raise ValidationError({'gift': e})
# If we got this far, then the voucher is determined to be valid, so the registration
# can proceed with no errors.
return
|
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Check that the given voucher code is valid
|
[
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"the",
"given",
"voucher",
"code",
"is",
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] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/vouchers/handlers.py#L20-L71
|
3,647
|
django-danceschool/django-danceschool
|
danceschool/vouchers/handlers.py
|
applyVoucherCodeTemporarily
|
def applyVoucherCodeTemporarily(sender,**kwargs):
'''
When the core registration system creates a temporary registration with a voucher code,
the voucher app looks for vouchers that match that code and creates TemporaryVoucherUse
objects to keep track of the fact that the voucher may be used.
'''
logger.debug('Signal fired to apply temporary vouchers.')
reg = kwargs.pop('registration')
voucherId = reg.data.get('gift','')
try:
voucher = Voucher.objects.get(voucherId=voucherId)
except ObjectDoesNotExist:
logger.debug('No applicable vouchers found.')
return
tvu = TemporaryVoucherUse(voucher=voucher,registration=reg,amount=0)
tvu.save()
logger.debug('Temporary voucher use object created.')
|
python
|
def applyVoucherCodeTemporarily(sender,**kwargs):
'''
When the core registration system creates a temporary registration with a voucher code,
the voucher app looks for vouchers that match that code and creates TemporaryVoucherUse
objects to keep track of the fact that the voucher may be used.
'''
logger.debug('Signal fired to apply temporary vouchers.')
reg = kwargs.pop('registration')
voucherId = reg.data.get('gift','')
try:
voucher = Voucher.objects.get(voucherId=voucherId)
except ObjectDoesNotExist:
logger.debug('No applicable vouchers found.')
return
tvu = TemporaryVoucherUse(voucher=voucher,registration=reg,amount=0)
tvu.save()
logger.debug('Temporary voucher use object created.')
|
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When the core registration system creates a temporary registration with a voucher code,
the voucher app looks for vouchers that match that code and creates TemporaryVoucherUse
objects to keep track of the fact that the voucher may be used.
|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/vouchers/handlers.py#L75-L94
|
3,648
|
django-danceschool/django-danceschool
|
danceschool/vouchers/handlers.py
|
applyReferrerVouchersTemporarily
|
def applyReferrerVouchersTemporarily(sender,**kwargs):
'''
Unlike voucher codes which have to be manually supplied, referrer discounts are
automatically applied here, assuming that the referral program is enabled.
'''
# Only continue if the referral program is enabled
if not getConstant('referrals__enableReferralProgram'):
return
logger.debug('Signal fired to temporarily apply referrer vouchers.')
reg = kwargs.pop('registration')
# Email address is unique for users, so use that
try:
c = Customer.objects.get(user__email=reg.email)
vouchers = c.getReferralVouchers()
except ObjectDoesNotExist:
vouchers = None
if not vouchers:
logger.debug('No referral vouchers found.')
return
for v in vouchers:
TemporaryVoucherUse(voucher=v,registration=reg,amount=0).save()
|
python
|
def applyReferrerVouchersTemporarily(sender,**kwargs):
'''
Unlike voucher codes which have to be manually supplied, referrer discounts are
automatically applied here, assuming that the referral program is enabled.
'''
# Only continue if the referral program is enabled
if not getConstant('referrals__enableReferralProgram'):
return
logger.debug('Signal fired to temporarily apply referrer vouchers.')
reg = kwargs.pop('registration')
# Email address is unique for users, so use that
try:
c = Customer.objects.get(user__email=reg.email)
vouchers = c.getReferralVouchers()
except ObjectDoesNotExist:
vouchers = None
if not vouchers:
logger.debug('No referral vouchers found.')
return
for v in vouchers:
TemporaryVoucherUse(voucher=v,registration=reg,amount=0).save()
|
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|
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"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/vouchers/handlers.py#L98-L124
|
3,649
|
django-danceschool/django-danceschool
|
danceschool/vouchers/handlers.py
|
applyVoucherCodesFinal
|
def applyVoucherCodesFinal(sender,**kwargs):
'''
Once a registration has been completed, vouchers are used and referrers are awarded
'''
logger.debug('Signal fired to mark voucher codes as applied.')
finalReg = kwargs.pop('registration')
tr = finalReg.temporaryRegistration
tvus = TemporaryVoucherUse.objects.filter(registration=tr)
for tvu in tvus:
vu = VoucherUse(voucher=tvu.voucher,registration=finalReg,amount=tvu.amount)
vu.save()
if getConstant('referrals__enableReferralProgram'):
awardReferrers(vu)
|
python
|
def applyVoucherCodesFinal(sender,**kwargs):
'''
Once a registration has been completed, vouchers are used and referrers are awarded
'''
logger.debug('Signal fired to mark voucher codes as applied.')
finalReg = kwargs.pop('registration')
tr = finalReg.temporaryRegistration
tvus = TemporaryVoucherUse.objects.filter(registration=tr)
for tvu in tvus:
vu = VoucherUse(voucher=tvu.voucher,registration=finalReg,amount=tvu.amount)
vu.save()
if getConstant('referrals__enableReferralProgram'):
awardReferrers(vu)
|
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Once a registration has been completed, vouchers are used and referrers are awarded
|
[
"Once",
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"been",
"completed",
"vouchers",
"are",
"used",
"and",
"referrers",
"are",
"awarded"
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/vouchers/handlers.py#L170-L185
|
3,650
|
django-danceschool/django-danceschool
|
danceschool/vouchers/handlers.py
|
provideCustomerReferralCode
|
def provideCustomerReferralCode(sender,**kwargs):
'''
If the vouchers app is installed and referrals are enabled, then the customer's profile page can show their voucher referral code.
'''
customer = kwargs.pop('customer')
if getConstant('vouchers__enableVouchers') and getConstant('referrals__enableReferralProgram'):
vrd = ensureReferralVouchersExist(customer)
return {
'referralVoucherId': vrd.referreeVoucher.voucherId
}
|
python
|
def provideCustomerReferralCode(sender,**kwargs):
'''
If the vouchers app is installed and referrals are enabled, then the customer's profile page can show their voucher referral code.
'''
customer = kwargs.pop('customer')
if getConstant('vouchers__enableVouchers') and getConstant('referrals__enableReferralProgram'):
vrd = ensureReferralVouchersExist(customer)
return {
'referralVoucherId': vrd.referreeVoucher.voucherId
}
|
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"'referralVoucherId'",
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"referreeVoucher",
".",
"voucherId",
"}"
] |
If the vouchers app is installed and referrals are enabled, then the customer's profile page can show their voucher referral code.
|
[
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"profile",
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"can",
"show",
"their",
"voucher",
"referral",
"code",
"."
] |
bb08cbf39017a812a5a94bdb4ea34170bf1a30ba
|
https://github.com/django-danceschool/django-danceschool/blob/bb08cbf39017a812a5a94bdb4ea34170bf1a30ba/danceschool/vouchers/handlers.py#L189-L199
|
3,651
|
orcasgit/django-fernet-fields
|
fernet_fields/fields.py
|
get_prep_lookup
|
def get_prep_lookup(self):
"""Raise errors for unsupported lookups"""
raise FieldError("{} '{}' does not support lookups".format(
self.lhs.field.__class__.__name__, self.lookup_name))
|
python
|
def get_prep_lookup(self):
"""Raise errors for unsupported lookups"""
raise FieldError("{} '{}' does not support lookups".format(
self.lhs.field.__class__.__name__, self.lookup_name))
|
[
"def",
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"\"{} '{}' does not support lookups\"",
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"__class__",
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"__name__",
",",
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"lookup_name",
")",
")"
] |
Raise errors for unsupported lookups
|
[
"Raise",
"errors",
"for",
"unsupported",
"lookups"
] |
888777e5bdb93c72339663e7464f6ceaf4f5e7dd
|
https://github.com/orcasgit/django-fernet-fields/blob/888777e5bdb93c72339663e7464f6ceaf4f5e7dd/fernet_fields/fields.py#L93-L96
|
3,652
|
orcasgit/django-fernet-fields
|
fernet_fields/hkdf.py
|
derive_fernet_key
|
def derive_fernet_key(input_key):
"""Derive a 32-bit b64-encoded Fernet key from arbitrary input key."""
hkdf = HKDF(
algorithm=hashes.SHA256(),
length=32,
salt=salt,
info=info,
backend=backend,
)
return base64.urlsafe_b64encode(hkdf.derive(force_bytes(input_key)))
|
python
|
def derive_fernet_key(input_key):
"""Derive a 32-bit b64-encoded Fernet key from arbitrary input key."""
hkdf = HKDF(
algorithm=hashes.SHA256(),
length=32,
salt=salt,
info=info,
backend=backend,
)
return base64.urlsafe_b64encode(hkdf.derive(force_bytes(input_key)))
|
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Derive a 32-bit b64-encoded Fernet key from arbitrary input key.
|
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"."
] |
888777e5bdb93c72339663e7464f6ceaf4f5e7dd
|
https://github.com/orcasgit/django-fernet-fields/blob/888777e5bdb93c72339663e7464f6ceaf4f5e7dd/fernet_fields/hkdf.py#L14-L23
|
3,653
|
xnd-project/gumath
|
python/gumath/__init__.py
|
reduce_cpu
|
def reduce_cpu(f, x, axes, dtype):
"""NumPy's reduce in terms of fold."""
axes = _get_axes(axes, x.ndim)
if not axes:
return x
permute = [n for n in range(x.ndim) if n not in axes]
permute = axes + permute
T = x.transpose(permute=permute)
N = len(axes)
t = T.type.at(N, dtype=dtype)
acc = x.empty(t, device=x.device)
if f.identity is not None:
_copyto(acc, f.identity)
tl = T
elif N == 1 and T.type.shape[0] > 0:
hd, tl = T[0], T[1:]
acc[()] = hd
else:
raise ValueError(
"reduction not possible for function without an identity element")
return fold(f, acc, tl)
|
python
|
def reduce_cpu(f, x, axes, dtype):
"""NumPy's reduce in terms of fold."""
axes = _get_axes(axes, x.ndim)
if not axes:
return x
permute = [n for n in range(x.ndim) if n not in axes]
permute = axes + permute
T = x.transpose(permute=permute)
N = len(axes)
t = T.type.at(N, dtype=dtype)
acc = x.empty(t, device=x.device)
if f.identity is not None:
_copyto(acc, f.identity)
tl = T
elif N == 1 and T.type.shape[0] > 0:
hd, tl = T[0], T[1:]
acc[()] = hd
else:
raise ValueError(
"reduction not possible for function without an identity element")
return fold(f, acc, tl)
|
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NumPy's reduce in terms of fold.
|
[
"NumPy",
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"of",
"fold",
"."
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath/__init__.py#L93-L118
|
3,654
|
xnd-project/gumath
|
python/gumath/__init__.py
|
reduce_cuda
|
def reduce_cuda(g, x, axes, dtype):
"""Reductions in CUDA use the thrust library for speed and have limited
functionality."""
if axes != 0:
raise NotImplementedError("'axes' keyword is not implemented for CUDA")
return g(x, dtype=dtype)
|
python
|
def reduce_cuda(g, x, axes, dtype):
"""Reductions in CUDA use the thrust library for speed and have limited
functionality."""
if axes != 0:
raise NotImplementedError("'axes' keyword is not implemented for CUDA")
return g(x, dtype=dtype)
|
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")",
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"(",
"x",
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"dtype",
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] |
Reductions in CUDA use the thrust library for speed and have limited
functionality.
|
[
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"CUDA",
"use",
"the",
"thrust",
"library",
"for",
"speed",
"and",
"have",
"limited",
"functionality",
"."
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath/__init__.py#L120-L126
|
3,655
|
xnd-project/gumath
|
python/gumath_aux.py
|
maxlevel
|
def maxlevel(lst):
"""Return maximum nesting depth"""
maxlev = 0
def f(lst, level):
nonlocal maxlev
if isinstance(lst, list):
level += 1
maxlev = max(level, maxlev)
for item in lst:
f(item, level)
f(lst, 0)
return maxlev
|
python
|
def maxlevel(lst):
"""Return maximum nesting depth"""
maxlev = 0
def f(lst, level):
nonlocal maxlev
if isinstance(lst, list):
level += 1
maxlev = max(level, maxlev)
for item in lst:
f(item, level)
f(lst, 0)
return maxlev
|
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Return maximum nesting depth
|
[
"Return",
"maximum",
"nesting",
"depth"
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath_aux.py#L101-L112
|
3,656
|
xnd-project/gumath
|
python/gumath_aux.py
|
getitem
|
def getitem(lst, indices):
"""Definition for multidimensional slicing and indexing on arbitrarily
shaped nested lists.
"""
if not indices:
return lst
i, indices = indices[0], indices[1:]
item = list.__getitem__(lst, i)
if isinstance(i, int):
return getitem(item, indices)
# Empty slice: check if all subsequent indices are in range for the
# full slice, raise IndexError otherwise. This is NumPy's behavior.
if not item:
if lst:
_ = getitem(lst, (slice(None),) + indices)
elif any(isinstance(k, int) for k in indices):
raise IndexError
return []
return [getitem(x, indices) for x in item]
|
python
|
def getitem(lst, indices):
"""Definition for multidimensional slicing and indexing on arbitrarily
shaped nested lists.
"""
if not indices:
return lst
i, indices = indices[0], indices[1:]
item = list.__getitem__(lst, i)
if isinstance(i, int):
return getitem(item, indices)
# Empty slice: check if all subsequent indices are in range for the
# full slice, raise IndexError otherwise. This is NumPy's behavior.
if not item:
if lst:
_ = getitem(lst, (slice(None),) + indices)
elif any(isinstance(k, int) for k in indices):
raise IndexError
return []
return [getitem(x, indices) for x in item]
|
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] |
Definition for multidimensional slicing and indexing on arbitrarily
shaped nested lists.
|
[
"Definition",
"for",
"multidimensional",
"slicing",
"and",
"indexing",
"on",
"arbitrarily",
"shaped",
"nested",
"lists",
"."
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath_aux.py#L114-L136
|
3,657
|
xnd-project/gumath
|
python/gumath_aux.py
|
genslices
|
def genslices(n):
"""Generate all possible slices for a single dimension."""
def range_with_none():
yield None
yield from range(-n, n+1)
for t in product(range_with_none(), range_with_none(), range_with_none()):
s = slice(*t)
if s.step != 0:
yield s
|
python
|
def genslices(n):
"""Generate all possible slices for a single dimension."""
def range_with_none():
yield None
yield from range(-n, n+1)
for t in product(range_with_none(), range_with_none(), range_with_none()):
s = slice(*t)
if s.step != 0:
yield s
|
[
"def",
"genslices",
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")",
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Generate all possible slices for a single dimension.
|
[
"Generate",
"all",
"possible",
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"for",
"a",
"single",
"dimension",
"."
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath_aux.py#L276-L285
|
3,658
|
xnd-project/gumath
|
python/gumath_aux.py
|
genslices_ndim
|
def genslices_ndim(ndim, shape):
"""Generate all possible slice tuples for 'shape'."""
iterables = [genslices(shape[n]) for n in range(ndim)]
yield from product(*iterables)
|
python
|
def genslices_ndim(ndim, shape):
"""Generate all possible slice tuples for 'shape'."""
iterables = [genslices(shape[n]) for n in range(ndim)]
yield from product(*iterables)
|
[
"def",
"genslices_ndim",
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"ndim",
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"]",
"yield",
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] |
Generate all possible slice tuples for 'shape'.
|
[
"Generate",
"all",
"possible",
"slice",
"tuples",
"for",
"shape",
"."
] |
a20ed5621db566ef805b8fb27ba4d8487f48c6b5
|
https://github.com/xnd-project/gumath/blob/a20ed5621db566ef805b8fb27ba4d8487f48c6b5/python/gumath_aux.py#L287-L290
|
3,659
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
mutator
|
def mutator(mutate):
"""Return an inspyred mutator function based on the given function.
This function generator takes a function that operates on only
one candidate to produce a single mutated candidate. The generator
handles the iteration over each candidate in the set to be mutated.
The given function ``mutate`` must have the following signature::
mutant = mutate(random, candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@mutator
def mutate(random, candidate, args):
# Implementation of mutation
pass
The generated function also contains an attribute named
``single_mutation`` which holds the original mutation function.
In this way, the original single-candidate function can be
retrieved if necessary.
"""
@functools.wraps(mutate)
def inspyred_mutator(random, candidates, args):
mutants = []
for i, cs in enumerate(candidates):
mutants.append(mutate(random, cs, args))
return mutants
inspyred_mutator.single_mutation = mutate
return inspyred_mutator
|
python
|
def mutator(mutate):
"""Return an inspyred mutator function based on the given function.
This function generator takes a function that operates on only
one candidate to produce a single mutated candidate. The generator
handles the iteration over each candidate in the set to be mutated.
The given function ``mutate`` must have the following signature::
mutant = mutate(random, candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@mutator
def mutate(random, candidate, args):
# Implementation of mutation
pass
The generated function also contains an attribute named
``single_mutation`` which holds the original mutation function.
In this way, the original single-candidate function can be
retrieved if necessary.
"""
@functools.wraps(mutate)
def inspyred_mutator(random, candidates, args):
mutants = []
for i, cs in enumerate(candidates):
mutants.append(mutate(random, cs, args))
return mutants
inspyred_mutator.single_mutation = mutate
return inspyred_mutator
|
[
"def",
"mutator",
"(",
"mutate",
")",
":",
"@",
"functools",
".",
"wraps",
"(",
"mutate",
")",
"def",
"inspyred_mutator",
"(",
"random",
",",
"candidates",
",",
"args",
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"return",
"mutants",
"inspyred_mutator",
".",
"single_mutation",
"=",
"mutate",
"return",
"inspyred_mutator"
] |
Return an inspyred mutator function based on the given function.
This function generator takes a function that operates on only
one candidate to produce a single mutated candidate. The generator
handles the iteration over each candidate in the set to be mutated.
The given function ``mutate`` must have the following signature::
mutant = mutate(random, candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@mutator
def mutate(random, candidate, args):
# Implementation of mutation
pass
The generated function also contains an attribute named
``single_mutation`` which holds the original mutation function.
In this way, the original single-candidate function can be
retrieved if necessary.
|
[
"Return",
"an",
"inspyred",
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"function",
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"given",
"function",
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"generator",
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"iteration",
"over",
"each",
"candidate",
"in",
"the",
"set",
"to",
"be",
"mutated",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L33-L65
|
3,660
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
bit_flip_mutation
|
def bit_flip_mutation(random, candidate, args):
"""Return the mutants produced by bit-flip mutation on the candidates.
This function performs bit-flip mutation. If a candidate solution contains
non-binary values, this function leaves it unchanged.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on a bit by bit basis.
"""
rate = args.setdefault('mutation_rate', 0.1)
mutant = copy.copy(candidate)
if len(mutant) == len([x for x in mutant if x in [0, 1]]):
for i, m in enumerate(mutant):
if random.random() < rate:
mutant[i] = (m + 1) % 2
return mutant
|
python
|
def bit_flip_mutation(random, candidate, args):
"""Return the mutants produced by bit-flip mutation on the candidates.
This function performs bit-flip mutation. If a candidate solution contains
non-binary values, this function leaves it unchanged.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on a bit by bit basis.
"""
rate = args.setdefault('mutation_rate', 0.1)
mutant = copy.copy(candidate)
if len(mutant) == len([x for x in mutant if x in [0, 1]]):
for i, m in enumerate(mutant):
if random.random() < rate:
mutant[i] = (m + 1) % 2
return mutant
|
[
"def",
"bit_flip_mutation",
"(",
"random",
",",
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"args",
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":",
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"=",
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",",
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"i",
"]",
"=",
"(",
"m",
"+",
"1",
")",
"%",
"2",
"return",
"mutant"
] |
Return the mutants produced by bit-flip mutation on the candidates.
This function performs bit-flip mutation. If a candidate solution contains
non-binary values, this function leaves it unchanged.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on a bit by bit basis.
|
[
"Return",
"the",
"mutants",
"produced",
"by",
"bit",
"-",
"flip",
"mutation",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L69-L93
|
3,661
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
random_reset_mutation
|
def random_reset_mutation(random, candidate, args):
"""Return the mutants produced by randomly choosing new values.
This function performs random-reset mutation. It assumes that
candidate solutions are composed of discrete values. This function
makes use of the bounder function as specified in the EC's
``evolve`` method, and it assumes that the bounder contains
an attribute called *values* (which is true for instances of
``DiscreteBounder``).
The mutation moves through a candidate solution and, with rate
equal to the *mutation_rate*, randomly chooses a value from the
set of allowed values to be used in that location. Note that this
value may be the same as the original value.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on an element by element basis.
"""
bounder = args['_ec'].bounder
try:
values = bounder.values
except AttributeError:
values = None
if values is not None:
rate = args.setdefault('mutation_rate', 0.1)
mutant = copy.copy(candidate)
for i, m in enumerate(mutant):
if random.random() < rate:
mutant[i] = random.choice(values)
return mutant
else:
return candidate
|
python
|
def random_reset_mutation(random, candidate, args):
"""Return the mutants produced by randomly choosing new values.
This function performs random-reset mutation. It assumes that
candidate solutions are composed of discrete values. This function
makes use of the bounder function as specified in the EC's
``evolve`` method, and it assumes that the bounder contains
an attribute called *values* (which is true for instances of
``DiscreteBounder``).
The mutation moves through a candidate solution and, with rate
equal to the *mutation_rate*, randomly chooses a value from the
set of allowed values to be used in that location. Note that this
value may be the same as the original value.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on an element by element basis.
"""
bounder = args['_ec'].bounder
try:
values = bounder.values
except AttributeError:
values = None
if values is not None:
rate = args.setdefault('mutation_rate', 0.1)
mutant = copy.copy(candidate)
for i, m in enumerate(mutant):
if random.random() < rate:
mutant[i] = random.choice(values)
return mutant
else:
return candidate
|
[
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"args",
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"choice",
"(",
"values",
")",
"return",
"mutant",
"else",
":",
"return",
"candidate"
] |
Return the mutants produced by randomly choosing new values.
This function performs random-reset mutation. It assumes that
candidate solutions are composed of discrete values. This function
makes use of the bounder function as specified in the EC's
``evolve`` method, and it assumes that the bounder contains
an attribute called *values* (which is true for instances of
``DiscreteBounder``).
The mutation moves through a candidate solution and, with rate
equal to the *mutation_rate*, randomly chooses a value from the
set of allowed values to be used in that location. Note that this
value may be the same as the original value.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied on an element by element basis.
|
[
"Return",
"the",
"mutants",
"produced",
"by",
"randomly",
"choosing",
"new",
"values",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L97-L137
|
3,662
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
scramble_mutation
|
def scramble_mutation(random, candidate, args):
"""Return the mutants created by scramble mutation on the candidates.
This function performs scramble mutation. It randomly chooses two
locations along the candidate and scrambles the values within that
slice.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied to the candidate as a whole (i.e., it
either mutates or it does not, based on the rate).
"""
rate = args.setdefault('mutation_rate', 0.1)
if random.random() < rate:
size = len(candidate)
p = random.randint(0, size-1)
q = random.randint(0, size-1)
p, q = min(p, q), max(p, q)
s = candidate[p:q+1]
random.shuffle(s)
return candidate[:p] + s[::-1] + candidate[q+1:]
else:
return candidate
|
python
|
def scramble_mutation(random, candidate, args):
"""Return the mutants created by scramble mutation on the candidates.
This function performs scramble mutation. It randomly chooses two
locations along the candidate and scrambles the values within that
slice.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied to the candidate as a whole (i.e., it
either mutates or it does not, based on the rate).
"""
rate = args.setdefault('mutation_rate', 0.1)
if random.random() < rate:
size = len(candidate)
p = random.randint(0, size-1)
q = random.randint(0, size-1)
p, q = min(p, q), max(p, q)
s = candidate[p:q+1]
random.shuffle(s)
return candidate[:p] + s[::-1] + candidate[q+1:]
else:
return candidate
|
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"1",
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"else",
":",
"return",
"candidate"
] |
Return the mutants created by scramble mutation on the candidates.
This function performs scramble mutation. It randomly chooses two
locations along the candidate and scrambles the values within that
slice.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
The mutation rate is applied to the candidate as a whole (i.e., it
either mutates or it does not, based on the rate).
|
[
"Return",
"the",
"mutants",
"created",
"by",
"scramble",
"mutation",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L141-L171
|
3,663
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
gaussian_mutation
|
def gaussian_mutation(random, candidate, args):
"""Return the mutants created by Gaussian mutation on the candidates.
This function performs Gaussian mutation. This function
makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
- *gaussian_mean* -- the mean used in the Gaussian function (default 0)
- *gaussian_stdev* -- the standard deviation used in the Gaussian function
(default 1)
The mutation rate is applied on an element by element basis.
"""
mut_rate = args.setdefault('mutation_rate', 0.1)
mean = args.setdefault('gaussian_mean', 0.0)
stdev = args.setdefault('gaussian_stdev', 1.0)
bounder = args['_ec'].bounder
mutant = copy.copy(candidate)
for i, m in enumerate(mutant):
if random.random() < mut_rate:
mutant[i] += random.gauss(mean, stdev)
mutant = bounder(mutant, args)
return mutant
|
python
|
def gaussian_mutation(random, candidate, args):
"""Return the mutants created by Gaussian mutation on the candidates.
This function performs Gaussian mutation. This function
makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
- *gaussian_mean* -- the mean used in the Gaussian function (default 0)
- *gaussian_stdev* -- the standard deviation used in the Gaussian function
(default 1)
The mutation rate is applied on an element by element basis.
"""
mut_rate = args.setdefault('mutation_rate', 0.1)
mean = args.setdefault('gaussian_mean', 0.0)
stdev = args.setdefault('gaussian_stdev', 1.0)
bounder = args['_ec'].bounder
mutant = copy.copy(candidate)
for i, m in enumerate(mutant):
if random.random() < mut_rate:
mutant[i] += random.gauss(mean, stdev)
mutant = bounder(mutant, args)
return mutant
|
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] |
Return the mutants created by Gaussian mutation on the candidates.
This function performs Gaussian mutation. This function
makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *mutation_rate* -- the rate at which mutation is performed (default 0.1)
- *gaussian_mean* -- the mean used in the Gaussian function (default 0)
- *gaussian_stdev* -- the standard deviation used in the Gaussian function
(default 1)
The mutation rate is applied on an element by element basis.
|
[
"Return",
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"mutants",
"created",
"by",
"Gaussian",
"mutation",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L208-L239
|
3,664
|
aarongarrett/inspyred
|
inspyred/ec/variators/mutators.py
|
nonuniform_mutation
|
def nonuniform_mutation(random, candidate, args):
"""Return the mutants produced by nonuniform mutation on the candidates.
The function performs nonuniform mutation as specified in
(Michalewicz, "Genetic Algorithms + Data Structures = Evolution
Programs," Springer, 1996). This function also makes use of the
bounder function as specified in the EC's ``evolve`` method.
.. note::
This function **requires** that *max_generations* be specified in
the *args* dictionary. Therefore, it is best to use this operator
in conjunction with the ``generation_termination`` terminator.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *max_generations* -- the maximum number of generations for which
evolution should take place
Optional keyword arguments in args:
- *mutation_strength* -- the strength of the mutation, where higher
values correspond to greater variation (default 1)
"""
bounder = args['_ec'].bounder
num_gens = args['_ec'].num_generations
max_gens = args['max_generations']
strength = args.setdefault('mutation_strength', 1)
exponent = (1.0 - num_gens / float(max_gens)) ** strength
mutant = copy.copy(candidate)
for i, (c, lo, hi) in enumerate(zip(candidate, bounder.lower_bound, bounder.upper_bound)):
if random.random() <= 0.5:
new_value = c + (hi - c) * (1.0 - random.random() ** exponent)
else:
new_value = c - (c - lo) * (1.0 - random.random() ** exponent)
mutant[i] = new_value
return mutant
|
python
|
def nonuniform_mutation(random, candidate, args):
"""Return the mutants produced by nonuniform mutation on the candidates.
The function performs nonuniform mutation as specified in
(Michalewicz, "Genetic Algorithms + Data Structures = Evolution
Programs," Springer, 1996). This function also makes use of the
bounder function as specified in the EC's ``evolve`` method.
.. note::
This function **requires** that *max_generations* be specified in
the *args* dictionary. Therefore, it is best to use this operator
in conjunction with the ``generation_termination`` terminator.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *max_generations* -- the maximum number of generations for which
evolution should take place
Optional keyword arguments in args:
- *mutation_strength* -- the strength of the mutation, where higher
values correspond to greater variation (default 1)
"""
bounder = args['_ec'].bounder
num_gens = args['_ec'].num_generations
max_gens = args['max_generations']
strength = args.setdefault('mutation_strength', 1)
exponent = (1.0 - num_gens / float(max_gens)) ** strength
mutant = copy.copy(candidate)
for i, (c, lo, hi) in enumerate(zip(candidate, bounder.lower_bound, bounder.upper_bound)):
if random.random() <= 0.5:
new_value = c + (hi - c) * (1.0 - random.random() ** exponent)
else:
new_value = c - (c - lo) * (1.0 - random.random() ** exponent)
mutant[i] = new_value
return mutant
|
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] |
Return the mutants produced by nonuniform mutation on the candidates.
The function performs nonuniform mutation as specified in
(Michalewicz, "Genetic Algorithms + Data Structures = Evolution
Programs," Springer, 1996). This function also makes use of the
bounder function as specified in the EC's ``evolve`` method.
.. note::
This function **requires** that *max_generations* be specified in
the *args* dictionary. Therefore, it is best to use this operator
in conjunction with the ``generation_termination`` terminator.
.. Arguments:
random -- the random number generator object
candidate -- the candidate solution
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *max_generations* -- the maximum number of generations for which
evolution should take place
Optional keyword arguments in args:
- *mutation_strength* -- the strength of the mutation, where higher
values correspond to greater variation (default 1)
|
[
"Return",
"the",
"mutants",
"produced",
"by",
"nonuniform",
"mutation",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/mutators.py#L243-L285
|
3,665
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
crossover
|
def crossover(cross):
"""Return an inspyred crossover function based on the given function.
This function generator takes a function that operates on only
two parent candidates to produce an iterable sequence of offspring
(typically two). The generator handles the pairing of selected
parents and collecting of all offspring.
The generated function chooses every odd candidate as a 'mom' and
every even as a 'dad' (discounting the last candidate if there is
an odd number). For each mom-dad pair, offspring are produced via
the `cross` function.
The given function ``cross`` must have the following signature::
offspring = cross(random, mom, dad, args)
This function is most commonly used as a function decorator with
the following usage::
@crossover
def cross(random, mom, dad, args):
# Implementation of paired crossing
pass
The generated function also contains an attribute named
``single_crossover`` which holds the original crossover function.
In this way, the original single-set-of-parents function can be
retrieved if necessary.
"""
@functools.wraps(cross)
def inspyred_crossover(random, candidates, args):
if len(candidates) % 2 == 1:
candidates = candidates[:-1]
moms = candidates[::2]
dads = candidates[1::2]
children = []
for i, (mom, dad) in enumerate(zip(moms, dads)):
cross.index = i
offspring = cross(random, mom, dad, args)
for o in offspring:
children.append(o)
return children
inspyred_crossover.single_crossover = cross
return inspyred_crossover
|
python
|
def crossover(cross):
"""Return an inspyred crossover function based on the given function.
This function generator takes a function that operates on only
two parent candidates to produce an iterable sequence of offspring
(typically two). The generator handles the pairing of selected
parents and collecting of all offspring.
The generated function chooses every odd candidate as a 'mom' and
every even as a 'dad' (discounting the last candidate if there is
an odd number). For each mom-dad pair, offspring are produced via
the `cross` function.
The given function ``cross`` must have the following signature::
offspring = cross(random, mom, dad, args)
This function is most commonly used as a function decorator with
the following usage::
@crossover
def cross(random, mom, dad, args):
# Implementation of paired crossing
pass
The generated function also contains an attribute named
``single_crossover`` which holds the original crossover function.
In this way, the original single-set-of-parents function can be
retrieved if necessary.
"""
@functools.wraps(cross)
def inspyred_crossover(random, candidates, args):
if len(candidates) % 2 == 1:
candidates = candidates[:-1]
moms = candidates[::2]
dads = candidates[1::2]
children = []
for i, (mom, dad) in enumerate(zip(moms, dads)):
cross.index = i
offspring = cross(random, mom, dad, args)
for o in offspring:
children.append(o)
return children
inspyred_crossover.single_crossover = cross
return inspyred_crossover
|
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"inspyred_crossover",
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"single_crossover",
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"return",
"inspyred_crossover"
] |
Return an inspyred crossover function based on the given function.
This function generator takes a function that operates on only
two parent candidates to produce an iterable sequence of offspring
(typically two). The generator handles the pairing of selected
parents and collecting of all offspring.
The generated function chooses every odd candidate as a 'mom' and
every even as a 'dad' (discounting the last candidate if there is
an odd number). For each mom-dad pair, offspring are produced via
the `cross` function.
The given function ``cross`` must have the following signature::
offspring = cross(random, mom, dad, args)
This function is most commonly used as a function decorator with
the following usage::
@crossover
def cross(random, mom, dad, args):
# Implementation of paired crossing
pass
The generated function also contains an attribute named
``single_crossover`` which holds the original crossover function.
In this way, the original single-set-of-parents function can be
retrieved if necessary.
|
[
"Return",
"an",
"inspyred",
"crossover",
"function",
"based",
"on",
"the",
"given",
"function",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L38-L83
|
3,666
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
n_point_crossover
|
def n_point_crossover(random, mom, dad, args):
"""Return the offspring of n-point crossover on the candidates.
This function performs n-point crossover (NPX). It selects *n*
random points without replacement at which to 'cut' the candidate
solutions and recombine them.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *num_crossover_points* -- the number of crossover points used (default 1)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
num_crossover_points = args.setdefault('num_crossover_points', 1)
children = []
if random.random() < crossover_rate:
num_cuts = min(len(mom)-1, num_crossover_points)
cut_points = random.sample(range(1, len(mom)), num_cuts)
cut_points.sort()
bro = copy.copy(dad)
sis = copy.copy(mom)
normal = True
for i, (m, d) in enumerate(zip(mom, dad)):
if i in cut_points:
normal = not normal
if not normal:
bro[i] = m
sis[i] = d
normal = not normal
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
python
|
def n_point_crossover(random, mom, dad, args):
"""Return the offspring of n-point crossover on the candidates.
This function performs n-point crossover (NPX). It selects *n*
random points without replacement at which to 'cut' the candidate
solutions and recombine them.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *num_crossover_points* -- the number of crossover points used (default 1)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
num_crossover_points = args.setdefault('num_crossover_points', 1)
children = []
if random.random() < crossover_rate:
num_cuts = min(len(mom)-1, num_crossover_points)
cut_points = random.sample(range(1, len(mom)), num_cuts)
cut_points.sort()
bro = copy.copy(dad)
sis = copy.copy(mom)
normal = True
for i, (m, d) in enumerate(zip(mom, dad)):
if i in cut_points:
normal = not normal
if not normal:
bro[i] = m
sis[i] = d
normal = not normal
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
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] |
Return the offspring of n-point crossover on the candidates.
This function performs n-point crossover (NPX). It selects *n*
random points without replacement at which to 'cut' the candidate
solutions and recombine them.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *num_crossover_points* -- the number of crossover points used (default 1)
|
[
"Return",
"the",
"offspring",
"of",
"n",
"-",
"point",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L87-L129
|
3,667
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
uniform_crossover
|
def uniform_crossover(random, mom, dad, args):
"""Return the offspring of uniform crossover on the candidates.
This function performs uniform crossover (UX). For each element
of the parents, a biased coin is flipped to determine whether
the first offspring gets the 'mom' or the 'dad' element. An
optional keyword argument in args, ``ux_bias``, determines the bias.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ux_bias* -- the bias toward the first candidate in the crossover
(default 0.5)
"""
ux_bias = args.setdefault('ux_bias', 0.5)
crossover_rate = args.setdefault('crossover_rate', 1.0)
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
for i, (m, d) in enumerate(zip(mom, dad)):
if random.random() < ux_bias:
bro[i] = m
sis[i] = d
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
python
|
def uniform_crossover(random, mom, dad, args):
"""Return the offspring of uniform crossover on the candidates.
This function performs uniform crossover (UX). For each element
of the parents, a biased coin is flipped to determine whether
the first offspring gets the 'mom' or the 'dad' element. An
optional keyword argument in args, ``ux_bias``, determines the bias.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ux_bias* -- the bias toward the first candidate in the crossover
(default 0.5)
"""
ux_bias = args.setdefault('ux_bias', 0.5)
crossover_rate = args.setdefault('crossover_rate', 1.0)
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
for i, (m, d) in enumerate(zip(mom, dad)):
if random.random() < ux_bias:
bro[i] = m
sis[i] = d
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
[
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] |
Return the offspring of uniform crossover on the candidates.
This function performs uniform crossover (UX). For each element
of the parents, a biased coin is flipped to determine whether
the first offspring gets the 'mom' or the 'dad' element. An
optional keyword argument in args, ``ux_bias``, determines the bias.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ux_bias* -- the bias toward the first candidate in the crossover
(default 0.5)
|
[
"Return",
"the",
"offspring",
"of",
"uniform",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L133-L170
|
3,668
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
partially_matched_crossover
|
def partially_matched_crossover(random, mom, dad, args):
"""Return the offspring of partially matched crossover on the candidates.
This function performs partially matched crossover (PMX). This type of
crossover assumes that candidates are composed of discrete values that
are permutations of a given set (typically integers). It produces offspring
that are themselves permutations of the set.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
if random.random() < crossover_rate:
size = len(mom)
points = random.sample(range(size), 2)
x, y = min(points), max(points)
bro = copy.copy(dad)
bro[x:y+1] = mom[x:y+1]
sis = copy.copy(mom)
sis[x:y+1] = dad[x:y+1]
for parent, child in zip([dad, mom], [bro, sis]):
for i in range(x, y+1):
if parent[i] not in child[x:y+1]:
spot = i
while x <= spot <= y:
spot = parent.index(child[spot])
child[spot] = parent[i]
return [bro, sis]
else:
return [mom, dad]
|
python
|
def partially_matched_crossover(random, mom, dad, args):
"""Return the offspring of partially matched crossover on the candidates.
This function performs partially matched crossover (PMX). This type of
crossover assumes that candidates are composed of discrete values that
are permutations of a given set (typically integers). It produces offspring
that are themselves permutations of the set.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
if random.random() < crossover_rate:
size = len(mom)
points = random.sample(range(size), 2)
x, y = min(points), max(points)
bro = copy.copy(dad)
bro[x:y+1] = mom[x:y+1]
sis = copy.copy(mom)
sis[x:y+1] = dad[x:y+1]
for parent, child in zip([dad, mom], [bro, sis]):
for i in range(x, y+1):
if parent[i] not in child[x:y+1]:
spot = i
while x <= spot <= y:
spot = parent.index(child[spot])
child[spot] = parent[i]
return [bro, sis]
else:
return [mom, dad]
|
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] |
Return the offspring of partially matched crossover on the candidates.
This function performs partially matched crossover (PMX). This type of
crossover assumes that candidates are composed of discrete values that
are permutations of a given set (typically integers). It produces offspring
that are themselves permutations of the set.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
|
[
"Return",
"the",
"offspring",
"of",
"partially",
"matched",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L174-L212
|
3,669
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
arithmetic_crossover
|
def arithmetic_crossover(random, mom, dad, args):
"""Return the offspring of arithmetic crossover on the candidates.
This function performs arithmetic crossover (AX), which is similar to a
generalized weighted averaging of the candidate elements. The allele
of each parent is weighted by the *ax_alpha* keyword argument, and
the allele of the complement parent is weighted by 1 - *ax_alpha*.
This averaging is only done on the alleles listed in the *ax_points*
keyword argument. If this argument is ``None``, then all alleles
are used. This means that if this function is used with all default
values, then offspring are simple averages of their parents.
This function also makes use of the bounder function as specified
in the EC's ``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ax_alpha* -- the weight for the averaging (default 0.5)
- *ax_points* -- a list of points specifying the alleles to
recombine (default None)
"""
ax_alpha = args.setdefault('ax_alpha', 0.5)
ax_points = args.setdefault('ax_points', None)
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
if ax_points is None:
ax_points = list(range(min(len(bro), len(sis))))
for i in ax_points:
bro[i] = ax_alpha * mom[i] + (1 - ax_alpha) * dad[i]
sis[i] = ax_alpha * dad[i] + (1 - ax_alpha) * mom[i]
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
python
|
def arithmetic_crossover(random, mom, dad, args):
"""Return the offspring of arithmetic crossover on the candidates.
This function performs arithmetic crossover (AX), which is similar to a
generalized weighted averaging of the candidate elements. The allele
of each parent is weighted by the *ax_alpha* keyword argument, and
the allele of the complement parent is weighted by 1 - *ax_alpha*.
This averaging is only done on the alleles listed in the *ax_points*
keyword argument. If this argument is ``None``, then all alleles
are used. This means that if this function is used with all default
values, then offspring are simple averages of their parents.
This function also makes use of the bounder function as specified
in the EC's ``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ax_alpha* -- the weight for the averaging (default 0.5)
- *ax_points* -- a list of points specifying the alleles to
recombine (default None)
"""
ax_alpha = args.setdefault('ax_alpha', 0.5)
ax_points = args.setdefault('ax_points', None)
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
if ax_points is None:
ax_points = list(range(min(len(bro), len(sis))))
for i in ax_points:
bro[i] = ax_alpha * mom[i] + (1 - ax_alpha) * dad[i]
sis[i] = ax_alpha * dad[i] + (1 - ax_alpha) * mom[i]
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
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] |
Return the offspring of arithmetic crossover on the candidates.
This function performs arithmetic crossover (AX), which is similar to a
generalized weighted averaging of the candidate elements. The allele
of each parent is weighted by the *ax_alpha* keyword argument, and
the allele of the complement parent is weighted by 1 - *ax_alpha*.
This averaging is only done on the alleles listed in the *ax_points*
keyword argument. If this argument is ``None``, then all alleles
are used. This means that if this function is used with all default
values, then offspring are simple averages of their parents.
This function also makes use of the bounder function as specified
in the EC's ``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *ax_alpha* -- the weight for the averaging (default 0.5)
- *ax_points* -- a list of points specifying the alleles to
recombine (default None)
|
[
"Return",
"the",
"offspring",
"of",
"arithmetic",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L216-L265
|
3,670
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
blend_crossover
|
def blend_crossover(random, mom, dad, args):
"""Return the offspring of blend crossover on the candidates.
This function performs blend crossover (BLX), which is similar to
arithmetic crossover with a bit of mutation. It creates offspring
whose values are chosen randomly from a range bounded by the
parent alleles but that is also extended by some amount proportional
to the *blx_alpha* keyword argument. It is this extension of the
range that provides the additional exploration. This averaging is
only done on the alleles listed in the *blx_points* keyword argument.
If this argument is ``None``, then all alleles are used. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *blx_alpha* -- the blending rate (default 0.1)
- *blx_points* -- a list of points specifying the alleles to
recombine (default None)
"""
blx_alpha = args.setdefault('blx_alpha', 0.1)
blx_points = args.setdefault('blx_points', None)
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
if blx_points is None:
blx_points = list(range(min(len(bro), len(sis))))
for i in blx_points:
smallest, largest = min(mom[i], dad[i]), max(mom[i], dad[i])
delta = blx_alpha * (largest - smallest)
bro[i] = smallest - delta + random.random() * (largest - smallest + 2 * delta)
sis[i] = smallest - delta + random.random() * (largest - smallest + 2 * delta)
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
python
|
def blend_crossover(random, mom, dad, args):
"""Return the offspring of blend crossover on the candidates.
This function performs blend crossover (BLX), which is similar to
arithmetic crossover with a bit of mutation. It creates offspring
whose values are chosen randomly from a range bounded by the
parent alleles but that is also extended by some amount proportional
to the *blx_alpha* keyword argument. It is this extension of the
range that provides the additional exploration. This averaging is
only done on the alleles listed in the *blx_points* keyword argument.
If this argument is ``None``, then all alleles are used. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *blx_alpha* -- the blending rate (default 0.1)
- *blx_points* -- a list of points specifying the alleles to
recombine (default None)
"""
blx_alpha = args.setdefault('blx_alpha', 0.1)
blx_points = args.setdefault('blx_points', None)
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
children = []
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
if blx_points is None:
blx_points = list(range(min(len(bro), len(sis))))
for i in blx_points:
smallest, largest = min(mom[i], dad[i]), max(mom[i], dad[i])
delta = blx_alpha * (largest - smallest)
bro[i] = smallest - delta + random.random() * (largest - smallest + 2 * delta)
sis[i] = smallest - delta + random.random() * (largest - smallest + 2 * delta)
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
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")",
"children",
".",
"append",
"(",
"dad",
")",
"return",
"children"
] |
Return the offspring of blend crossover on the candidates.
This function performs blend crossover (BLX), which is similar to
arithmetic crossover with a bit of mutation. It creates offspring
whose values are chosen randomly from a range bounded by the
parent alleles but that is also extended by some amount proportional
to the *blx_alpha* keyword argument. It is this extension of the
range that provides the additional exploration. This averaging is
only done on the alleles listed in the *blx_points* keyword argument.
If this argument is ``None``, then all alleles are used. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. Arguments:
random -- the random number generator object
mom -- the first parent candidate
dad -- the second parent candidate
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
- *blx_alpha* -- the blending rate (default 0.1)
- *blx_points* -- a list of points specifying the alleles to
recombine (default None)
|
[
"Return",
"the",
"offspring",
"of",
"blend",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L269-L320
|
3,671
|
aarongarrett/inspyred
|
inspyred/ec/variators/crossovers.py
|
heuristic_crossover
|
def heuristic_crossover(random, candidates, args):
"""Return the offspring of heuristic crossover on the candidates.
It performs heuristic crossover (HX), which is similar to the
update rule used in particle swarm optimization. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. note::
This function assumes that candidates can be pickled (for hashing
as keys to a dictionary).
.. Arguments:
random -- the random number generator object
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
if len(candidates) % 2 == 1:
candidates = candidates[:-1]
# Since we don't have fitness information in the candidates, we need
# to make a dictionary containing the candidate and its corresponding
# individual in the population.
population = list(args['_ec'].population)
lookup = dict(zip([pickle.dumps(p.candidate, 1) for p in population], population))
moms = candidates[::2]
dads = candidates[1::2]
children = []
for mom, dad in zip(moms, dads):
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
mom_is_better = lookup[pickle.dumps(mom, 1)] > lookup[pickle.dumps(dad, 1)]
for i, (m, d) in enumerate(zip(mom, dad)):
negpos = 1 if mom_is_better else -1
val = d if mom_is_better else m
bro[i] = val + random.random() * negpos * (m - d)
sis[i] = val + random.random() * negpos * (m - d)
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
python
|
def heuristic_crossover(random, candidates, args):
"""Return the offspring of heuristic crossover on the candidates.
It performs heuristic crossover (HX), which is similar to the
update rule used in particle swarm optimization. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. note::
This function assumes that candidates can be pickled (for hashing
as keys to a dictionary).
.. Arguments:
random -- the random number generator object
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
"""
crossover_rate = args.setdefault('crossover_rate', 1.0)
bounder = args['_ec'].bounder
if len(candidates) % 2 == 1:
candidates = candidates[:-1]
# Since we don't have fitness information in the candidates, we need
# to make a dictionary containing the candidate and its corresponding
# individual in the population.
population = list(args['_ec'].population)
lookup = dict(zip([pickle.dumps(p.candidate, 1) for p in population], population))
moms = candidates[::2]
dads = candidates[1::2]
children = []
for mom, dad in zip(moms, dads):
if random.random() < crossover_rate:
bro = copy.copy(dad)
sis = copy.copy(mom)
mom_is_better = lookup[pickle.dumps(mom, 1)] > lookup[pickle.dumps(dad, 1)]
for i, (m, d) in enumerate(zip(mom, dad)):
negpos = 1 if mom_is_better else -1
val = d if mom_is_better else m
bro[i] = val + random.random() * negpos * (m - d)
sis[i] = val + random.random() * negpos * (m - d)
bro = bounder(bro, args)
sis = bounder(sis, args)
children.append(bro)
children.append(sis)
else:
children.append(mom)
children.append(dad)
return children
|
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"append",
"(",
"mom",
")",
"children",
".",
"append",
"(",
"dad",
")",
"return",
"children"
] |
Return the offspring of heuristic crossover on the candidates.
It performs heuristic crossover (HX), which is similar to the
update rule used in particle swarm optimization. This function
also makes use of the bounder function as specified in the EC's
``evolve`` method.
.. note::
This function assumes that candidates can be pickled (for hashing
as keys to a dictionary).
.. Arguments:
random -- the random number generator object
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Optional keyword arguments in args:
- *crossover_rate* -- the rate at which crossover is performed
(default 1.0)
|
[
"Return",
"the",
"offspring",
"of",
"heuristic",
"crossover",
"on",
"the",
"candidates",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/variators/crossovers.py#L323-L379
|
3,672
|
aarongarrett/inspyred
|
docs/moonshot.py
|
gravitational_force
|
def gravitational_force(position_a, mass_a, position_b, mass_b):
"""Returns the gravitational force between the two bodies a and b."""
distance = distance_between(position_a, position_b)
# Calculate the direction and magnitude of the force.
angle = math.atan2(position_a[1] - position_b[1], position_a[0] - position_b[0])
magnitude = G * mass_a * mass_b / (distance**2)
# Find the x and y components of the force.
# Determine sign based on which one is the larger body.
sign = -1 if mass_b > mass_a else 1
x_force = sign * magnitude * math.cos(angle)
y_force = sign * magnitude * math.sin(angle)
return x_force, y_force
|
python
|
def gravitational_force(position_a, mass_a, position_b, mass_b):
"""Returns the gravitational force between the two bodies a and b."""
distance = distance_between(position_a, position_b)
# Calculate the direction and magnitude of the force.
angle = math.atan2(position_a[1] - position_b[1], position_a[0] - position_b[0])
magnitude = G * mass_a * mass_b / (distance**2)
# Find the x and y components of the force.
# Determine sign based on which one is the larger body.
sign = -1 if mass_b > mass_a else 1
x_force = sign * magnitude * math.cos(angle)
y_force = sign * magnitude * math.sin(angle)
return x_force, y_force
|
[
"def",
"gravitational_force",
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"position_a",
",",
"mass_a",
",",
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",",
"mass_b",
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"=",
"distance_between",
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"position_a",
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"# Calculate the direction and magnitude of the force.",
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"(",
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"*",
"math",
".",
"sin",
"(",
"angle",
")",
"return",
"x_force",
",",
"y_force"
] |
Returns the gravitational force between the two bodies a and b.
|
[
"Returns",
"the",
"gravitational",
"force",
"between",
"the",
"two",
"bodies",
"a",
"and",
"b",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/docs/moonshot.py#L37-L50
|
3,673
|
aarongarrett/inspyred
|
docs/moonshot.py
|
force_on_satellite
|
def force_on_satellite(position, mass):
"""Returns the total gravitational force acting on the body from the Earth and Moon."""
earth_grav_force = gravitational_force(position, mass, earth_position, earth_mass)
moon_grav_force = gravitational_force(position, mass, moon_position, moon_mass)
F_x = earth_grav_force[0] + moon_grav_force[0]
F_y = earth_grav_force[1] + moon_grav_force[1]
return F_x, F_y
|
python
|
def force_on_satellite(position, mass):
"""Returns the total gravitational force acting on the body from the Earth and Moon."""
earth_grav_force = gravitational_force(position, mass, earth_position, earth_mass)
moon_grav_force = gravitational_force(position, mass, moon_position, moon_mass)
F_x = earth_grav_force[0] + moon_grav_force[0]
F_y = earth_grav_force[1] + moon_grav_force[1]
return F_x, F_y
|
[
"def",
"force_on_satellite",
"(",
"position",
",",
"mass",
")",
":",
"earth_grav_force",
"=",
"gravitational_force",
"(",
"position",
",",
"mass",
",",
"earth_position",
",",
"earth_mass",
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"moon_grav_force",
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"gravitational_force",
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",",
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",",
"moon_position",
",",
"moon_mass",
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"F_y",
"=",
"earth_grav_force",
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"1",
"]",
"+",
"moon_grav_force",
"[",
"1",
"]",
"return",
"F_x",
",",
"F_y"
] |
Returns the total gravitational force acting on the body from the Earth and Moon.
|
[
"Returns",
"the",
"total",
"gravitational",
"force",
"acting",
"on",
"the",
"body",
"from",
"the",
"Earth",
"and",
"Moon",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/docs/moonshot.py#L52-L58
|
3,674
|
aarongarrett/inspyred
|
docs/moonshot.py
|
acceleration_of_satellite
|
def acceleration_of_satellite(position, mass):
"""Returns the acceleration based on all forces acting upon the body."""
F_x, F_y = force_on_satellite(position, mass)
return F_x / mass, F_y / mass
|
python
|
def acceleration_of_satellite(position, mass):
"""Returns the acceleration based on all forces acting upon the body."""
F_x, F_y = force_on_satellite(position, mass)
return F_x / mass, F_y / mass
|
[
"def",
"acceleration_of_satellite",
"(",
"position",
",",
"mass",
")",
":",
"F_x",
",",
"F_y",
"=",
"force_on_satellite",
"(",
"position",
",",
"mass",
")",
"return",
"F_x",
"/",
"mass",
",",
"F_y",
"/",
"mass"
] |
Returns the acceleration based on all forces acting upon the body.
|
[
"Returns",
"the",
"acceleration",
"based",
"on",
"all",
"forces",
"acting",
"upon",
"the",
"body",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/docs/moonshot.py#L60-L63
|
3,675
|
aarongarrett/inspyred
|
inspyred/ec/evaluators.py
|
evaluator
|
def evaluator(evaluate):
"""Return an inspyred evaluator function based on the given function.
This function generator takes a function that evaluates only one
candidate. The generator handles the iteration over each candidate
to be evaluated.
The given function ``evaluate`` must have the following signature::
fitness = evaluate(candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@evaluator
def evaluate(candidate, args):
# Implementation of evaluation
pass
The generated function also contains an attribute named
``single_evaluation`` which holds the original evaluation function.
In this way, the original single-candidate function can be
retrieved if necessary.
"""
@functools.wraps(evaluate)
def inspyred_evaluator(candidates, args):
fitness = []
for candidate in candidates:
fitness.append(evaluate(candidate, args))
return fitness
inspyred_evaluator.single_evaluation = evaluate
return inspyred_evaluator
|
python
|
def evaluator(evaluate):
"""Return an inspyred evaluator function based on the given function.
This function generator takes a function that evaluates only one
candidate. The generator handles the iteration over each candidate
to be evaluated.
The given function ``evaluate`` must have the following signature::
fitness = evaluate(candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@evaluator
def evaluate(candidate, args):
# Implementation of evaluation
pass
The generated function also contains an attribute named
``single_evaluation`` which holds the original evaluation function.
In this way, the original single-candidate function can be
retrieved if necessary.
"""
@functools.wraps(evaluate)
def inspyred_evaluator(candidates, args):
fitness = []
for candidate in candidates:
fitness.append(evaluate(candidate, args))
return fitness
inspyred_evaluator.single_evaluation = evaluate
return inspyred_evaluator
|
[
"def",
"evaluator",
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"evaluate",
")",
":",
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"functools",
".",
"wraps",
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"inspyred_evaluator",
"(",
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"fitness",
"inspyred_evaluator",
".",
"single_evaluation",
"=",
"evaluate",
"return",
"inspyred_evaluator"
] |
Return an inspyred evaluator function based on the given function.
This function generator takes a function that evaluates only one
candidate. The generator handles the iteration over each candidate
to be evaluated.
The given function ``evaluate`` must have the following signature::
fitness = evaluate(candidate, args)
This function is most commonly used as a function decorator with
the following usage::
@evaluator
def evaluate(candidate, args):
# Implementation of evaluation
pass
The generated function also contains an attribute named
``single_evaluation`` which holds the original evaluation function.
In this way, the original single-candidate function can be
retrieved if necessary.
|
[
"Return",
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"the",
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"over",
"each",
"candidate",
"to",
"be",
"evaluated",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/evaluators.py#L45-L77
|
3,676
|
aarongarrett/inspyred
|
inspyred/ec/evaluators.py
|
parallel_evaluation_pp
|
def parallel_evaluation_pp(candidates, args):
"""Evaluate the candidates in parallel using Parallel Python.
This function allows parallel evaluation of candidate solutions.
It uses the `Parallel Python <http://www.parallelpython.com>`_ (pp)
library to accomplish the parallelization. This library must already
be installed in order to use this function. The function assigns the
evaluation of each candidate to its own job, all of which are then
distributed to the available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *pp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *pp_dependencies* -- tuple of functional dependencies of the serial
evaluator (default ())
- *pp_modules* -- tuple of modules that must be imported for the
functional dependencies (default ())
- *pp_servers* -- tuple of servers (on a cluster) that will be used
for parallel processing (default ("*",))
- *pp_secret* -- string representing the secret key needed to authenticate
on a worker node (default "inspyred")
- *pp_nprocs* -- integer representing the number of worker processes to
start on the local machine (default "autodetect", which sets it to the
number of processors in the system)
For more information about these arguments, please consult the
documentation for `Parallel Python <http://www.parallelpython.com>`_.
"""
import pp
logger = args['_ec'].logger
try:
evaluator = args['pp_evaluator']
except KeyError:
logger.error('parallel_evaluation_pp requires \'pp_evaluator\' be defined in the keyword arguments list')
raise
secret_key = args.setdefault('pp_secret', 'inspyred')
try:
job_server = args['_pp_job_server']
except KeyError:
pp_servers = args.get('pp_servers', ("*",))
pp_nprocs = args.get('pp_nprocs', 'autodetect')
job_server = pp.Server(ncpus=pp_nprocs, ppservers=pp_servers, secret=secret_key)
args['_pp_job_server'] = job_server
pp_depends = args.setdefault('pp_dependencies', ())
pp_modules = args.setdefault('pp_modules', ())
pickled_args = {}
for key in args:
try:
pickle.dumps(args[key])
pickled_args[key] = args[key]
except (TypeError, pickle.PickleError, pickle.PicklingError):
logger.debug('unable to pickle args parameter {0} in parallel_evaluation_pp'.format(key))
pass
func_template = pp.Template(job_server, evaluator, pp_depends, pp_modules)
jobs = [func_template.submit([c], pickled_args) for c in candidates]
fitness = []
for i, job in enumerate(jobs):
r = job()
try:
fitness.append(r[0])
except TypeError:
logger.warning('parallel_evaluation_pp generated an invalid fitness for candidate {0}'.format(candidates[i]))
fitness.append(None)
return fitness
|
python
|
def parallel_evaluation_pp(candidates, args):
"""Evaluate the candidates in parallel using Parallel Python.
This function allows parallel evaluation of candidate solutions.
It uses the `Parallel Python <http://www.parallelpython.com>`_ (pp)
library to accomplish the parallelization. This library must already
be installed in order to use this function. The function assigns the
evaluation of each candidate to its own job, all of which are then
distributed to the available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *pp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *pp_dependencies* -- tuple of functional dependencies of the serial
evaluator (default ())
- *pp_modules* -- tuple of modules that must be imported for the
functional dependencies (default ())
- *pp_servers* -- tuple of servers (on a cluster) that will be used
for parallel processing (default ("*",))
- *pp_secret* -- string representing the secret key needed to authenticate
on a worker node (default "inspyred")
- *pp_nprocs* -- integer representing the number of worker processes to
start on the local machine (default "autodetect", which sets it to the
number of processors in the system)
For more information about these arguments, please consult the
documentation for `Parallel Python <http://www.parallelpython.com>`_.
"""
import pp
logger = args['_ec'].logger
try:
evaluator = args['pp_evaluator']
except KeyError:
logger.error('parallel_evaluation_pp requires \'pp_evaluator\' be defined in the keyword arguments list')
raise
secret_key = args.setdefault('pp_secret', 'inspyred')
try:
job_server = args['_pp_job_server']
except KeyError:
pp_servers = args.get('pp_servers', ("*",))
pp_nprocs = args.get('pp_nprocs', 'autodetect')
job_server = pp.Server(ncpus=pp_nprocs, ppservers=pp_servers, secret=secret_key)
args['_pp_job_server'] = job_server
pp_depends = args.setdefault('pp_dependencies', ())
pp_modules = args.setdefault('pp_modules', ())
pickled_args = {}
for key in args:
try:
pickle.dumps(args[key])
pickled_args[key] = args[key]
except (TypeError, pickle.PickleError, pickle.PicklingError):
logger.debug('unable to pickle args parameter {0} in parallel_evaluation_pp'.format(key))
pass
func_template = pp.Template(job_server, evaluator, pp_depends, pp_modules)
jobs = [func_template.submit([c], pickled_args) for c in candidates]
fitness = []
for i, job in enumerate(jobs):
r = job()
try:
fitness.append(r[0])
except TypeError:
logger.warning('parallel_evaluation_pp generated an invalid fitness for candidate {0}'.format(candidates[i]))
fitness.append(None)
return fitness
|
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] |
Evaluate the candidates in parallel using Parallel Python.
This function allows parallel evaluation of candidate solutions.
It uses the `Parallel Python <http://www.parallelpython.com>`_ (pp)
library to accomplish the parallelization. This library must already
be installed in order to use this function. The function assigns the
evaluation of each candidate to its own job, all of which are then
distributed to the available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *pp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *pp_dependencies* -- tuple of functional dependencies of the serial
evaluator (default ())
- *pp_modules* -- tuple of modules that must be imported for the
functional dependencies (default ())
- *pp_servers* -- tuple of servers (on a cluster) that will be used
for parallel processing (default ("*",))
- *pp_secret* -- string representing the secret key needed to authenticate
on a worker node (default "inspyred")
- *pp_nprocs* -- integer representing the number of worker processes to
start on the local machine (default "autodetect", which sets it to the
number of processors in the system)
For more information about these arguments, please consult the
documentation for `Parallel Python <http://www.parallelpython.com>`_.
|
[
"Evaluate",
"the",
"candidates",
"in",
"parallel",
"using",
"Parallel",
"Python",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/evaluators.py#L80-L162
|
3,677
|
aarongarrett/inspyred
|
inspyred/ec/evaluators.py
|
parallel_evaluation_mp
|
def parallel_evaluation_mp(candidates, args):
"""Evaluate the candidates in parallel using ``multiprocessing``.
This function allows parallel evaluation of candidate solutions.
It uses the standard multiprocessing library to accomplish the
parallelization. The function assigns the evaluation of each
candidate to its own job, all of which are then distributed to the
available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *mp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *mp_nprocs* -- number of processors that will be used (default machine
cpu count)
"""
import time
import multiprocessing
logger = args['_ec'].logger
try:
evaluator = args['mp_evaluator']
except KeyError:
logger.error('parallel_evaluation_mp requires \'mp_evaluator\' be defined in the keyword arguments list')
raise
try:
nprocs = args['mp_nprocs']
except KeyError:
nprocs = multiprocessing.cpu_count()
pickled_args = {}
for key in args:
try:
pickle.dumps(args[key])
pickled_args[key] = args[key]
except (TypeError, pickle.PickleError, pickle.PicklingError):
logger.debug('unable to pickle args parameter {0} in parallel_evaluation_mp'.format(key))
pass
start = time.time()
try:
pool = multiprocessing.Pool(processes=nprocs)
results = [pool.apply_async(evaluator, ([c], pickled_args)) for c in candidates]
pool.close()
pool.join()
return [r.get()[0] for r in results]
except (OSError, RuntimeError) as e:
logger.error('failed parallel_evaluation_mp: {0}'.format(str(e)))
raise
else:
end = time.time()
logger.debug('completed parallel_evaluation_mp in {0} seconds'.format(end - start))
|
python
|
def parallel_evaluation_mp(candidates, args):
"""Evaluate the candidates in parallel using ``multiprocessing``.
This function allows parallel evaluation of candidate solutions.
It uses the standard multiprocessing library to accomplish the
parallelization. The function assigns the evaluation of each
candidate to its own job, all of which are then distributed to the
available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *mp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *mp_nprocs* -- number of processors that will be used (default machine
cpu count)
"""
import time
import multiprocessing
logger = args['_ec'].logger
try:
evaluator = args['mp_evaluator']
except KeyError:
logger.error('parallel_evaluation_mp requires \'mp_evaluator\' be defined in the keyword arguments list')
raise
try:
nprocs = args['mp_nprocs']
except KeyError:
nprocs = multiprocessing.cpu_count()
pickled_args = {}
for key in args:
try:
pickle.dumps(args[key])
pickled_args[key] = args[key]
except (TypeError, pickle.PickleError, pickle.PicklingError):
logger.debug('unable to pickle args parameter {0} in parallel_evaluation_mp'.format(key))
pass
start = time.time()
try:
pool = multiprocessing.Pool(processes=nprocs)
results = [pool.apply_async(evaluator, ([c], pickled_args)) for c in candidates]
pool.close()
pool.join()
return [r.get()[0] for r in results]
except (OSError, RuntimeError) as e:
logger.error('failed parallel_evaluation_mp: {0}'.format(str(e)))
raise
else:
end = time.time()
logger.debug('completed parallel_evaluation_mp in {0} seconds'.format(end - start))
|
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] |
Evaluate the candidates in parallel using ``multiprocessing``.
This function allows parallel evaluation of candidate solutions.
It uses the standard multiprocessing library to accomplish the
parallelization. The function assigns the evaluation of each
candidate to its own job, all of which are then distributed to the
available processing units.
.. note::
All arguments to the evaluation function must be pickleable.
Those that are not will not be sent through the ``args`` variable
and will be unavailable to your function.
.. Arguments:
candidates -- the candidate solutions
args -- a dictionary of keyword arguments
Required keyword arguments in args:
- *mp_evaluator* -- actual evaluation function to be used (This function
should have the same signature as any other inspyred evaluation function.)
Optional keyword arguments in args:
- *mp_nprocs* -- number of processors that will be used (default machine
cpu count)
|
[
"Evaluate",
"the",
"candidates",
"in",
"parallel",
"using",
"multiprocessing",
"."
] |
d5976ab503cc9d51c6f586cbb7bb601a38c01128
|
https://github.com/aarongarrett/inspyred/blob/d5976ab503cc9d51c6f586cbb7bb601a38c01128/inspyred/ec/evaluators.py#L165-L230
|
3,678
|
djsutho/django-debug-toolbar-request-history
|
ddt_request_history/panels/request_history.py
|
allow_ajax
|
def allow_ajax(request):
"""
Default function to determine whether to show the toolbar on a given page.
"""
if request.META.get('REMOTE_ADDR', None) not in settings.INTERNAL_IPS:
return False
if toolbar_version < LooseVersion('1.8') \
and request.get_full_path().startswith(DEBUG_TOOLBAR_URL_PREFIX) \
and request.GET.get('panel_id', None) != 'RequestHistoryPanel':
return False
return bool(settings.DEBUG)
|
python
|
def allow_ajax(request):
"""
Default function to determine whether to show the toolbar on a given page.
"""
if request.META.get('REMOTE_ADDR', None) not in settings.INTERNAL_IPS:
return False
if toolbar_version < LooseVersion('1.8') \
and request.get_full_path().startswith(DEBUG_TOOLBAR_URL_PREFIX) \
and request.GET.get('panel_id', None) != 'RequestHistoryPanel':
return False
return bool(settings.DEBUG)
|
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Default function to determine whether to show the toolbar on a given page.
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"the",
"toolbar",
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"."
] |
b3da3e12762d68c23a307ffb279e6047f80ba695
|
https://github.com/djsutho/django-debug-toolbar-request-history/blob/b3da3e12762d68c23a307ffb279e6047f80ba695/ddt_request_history/panels/request_history.py#L104-L114
|
3,679
|
djsutho/django-debug-toolbar-request-history
|
ddt_request_history/panels/request_history.py
|
RequestHistoryPanel.content
|
def content(self):
""" Content of the panel when it's displayed in full screen. """
toolbars = OrderedDict()
for id, toolbar in DebugToolbar._store.items():
content = {}
for panel in toolbar.panels:
panel_id = None
nav_title = ''
nav_subtitle = ''
try:
panel_id = panel.panel_id
nav_title = panel.nav_title
nav_subtitle = panel.nav_subtitle() if isinstance(
panel.nav_subtitle, Callable) else panel.nav_subtitle
except Exception:
logger.debug('Error parsing panel info:', exc_info=True)
if panel_id is not None:
content.update({
panel_id: {
'panel_id': panel_id,
'nav_title': nav_title,
'nav_subtitle': nav_subtitle,
}
})
toolbars[id] = {
'toolbar': toolbar,
'content': content
}
return get_template().render(Context({
'toolbars': OrderedDict(reversed(list(toolbars.items()))),
'trunc_length': CONFIG.get('RH_POST_TRUNC_LENGTH', 0)
}))
|
python
|
def content(self):
""" Content of the panel when it's displayed in full screen. """
toolbars = OrderedDict()
for id, toolbar in DebugToolbar._store.items():
content = {}
for panel in toolbar.panels:
panel_id = None
nav_title = ''
nav_subtitle = ''
try:
panel_id = panel.panel_id
nav_title = panel.nav_title
nav_subtitle = panel.nav_subtitle() if isinstance(
panel.nav_subtitle, Callable) else panel.nav_subtitle
except Exception:
logger.debug('Error parsing panel info:', exc_info=True)
if panel_id is not None:
content.update({
panel_id: {
'panel_id': panel_id,
'nav_title': nav_title,
'nav_subtitle': nav_subtitle,
}
})
toolbars[id] = {
'toolbar': toolbar,
'content': content
}
return get_template().render(Context({
'toolbars': OrderedDict(reversed(list(toolbars.items()))),
'trunc_length': CONFIG.get('RH_POST_TRUNC_LENGTH', 0)
}))
|
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",",
"0",
")",
"}",
")",
")"
] |
Content of the panel when it's displayed in full screen.
|
[
"Content",
"of",
"the",
"panel",
"when",
"it",
"s",
"displayed",
"in",
"full",
"screen",
"."
] |
b3da3e12762d68c23a307ffb279e6047f80ba695
|
https://github.com/djsutho/django-debug-toolbar-request-history/blob/b3da3e12762d68c23a307ffb279e6047f80ba695/ddt_request_history/panels/request_history.py#L184-L215
|
3,680
|
AlexMathew/scrapple
|
scrapple/selectors/selector.py
|
Selector.extract_content
|
def extract_content(self, selector='', attr='', default='', connector='', *args, **kwargs):
"""
Method for performing the content extraction for the particular selector type. \
If the selector is "url", the URL of the current web page is returned.
Otherwise, the selector expression is used to extract content. The particular \
attribute to be extracted ("text", "href", etc.) is specified in the method \
arguments, and this is used to extract the required content. If the content \
extracted is a link (from an attr value of "href" or "src"), the URL is parsed \
to convert the relative path into an absolute path.
If the selector does not fetch any content, the default value is returned. \
If no default value is specified, an exception is raised.
:param selector: The XPath expression
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param connector: String connector for list of data returned for a particular selector
:return: The extracted content
"""
try:
if selector.lower() == "url":
return self.url
if attr.lower() == "text":
tag = self.get_tree_tag(selector=selector, get_one=True)
content = connector.join([make_ascii(x).strip() for x in tag.itertext()])
content = content.replace("\n", " ").strip()
else:
tag = self.get_tree_tag(selector=selector, get_one=True)
content = tag.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
return content
except IndexError:
if default is not "":
return default
raise Exception("There is no content for the %s selector - %s" % (self.__selector_type__, selector))
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
|
python
|
def extract_content(self, selector='', attr='', default='', connector='', *args, **kwargs):
"""
Method for performing the content extraction for the particular selector type. \
If the selector is "url", the URL of the current web page is returned.
Otherwise, the selector expression is used to extract content. The particular \
attribute to be extracted ("text", "href", etc.) is specified in the method \
arguments, and this is used to extract the required content. If the content \
extracted is a link (from an attr value of "href" or "src"), the URL is parsed \
to convert the relative path into an absolute path.
If the selector does not fetch any content, the default value is returned. \
If no default value is specified, an exception is raised.
:param selector: The XPath expression
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param connector: String connector for list of data returned for a particular selector
:return: The extracted content
"""
try:
if selector.lower() == "url":
return self.url
if attr.lower() == "text":
tag = self.get_tree_tag(selector=selector, get_one=True)
content = connector.join([make_ascii(x).strip() for x in tag.itertext()])
content = content.replace("\n", " ").strip()
else:
tag = self.get_tree_tag(selector=selector, get_one=True)
content = tag.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
return content
except IndexError:
if default is not "":
return default
raise Exception("There is no content for the %s selector - %s" % (self.__selector_type__, selector))
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
|
[
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"\"Invalid %s selector - %s\"",
"%",
"(",
"self",
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",",
"selector",
")",
")"
] |
Method for performing the content extraction for the particular selector type. \
If the selector is "url", the URL of the current web page is returned.
Otherwise, the selector expression is used to extract content. The particular \
attribute to be extracted ("text", "href", etc.) is specified in the method \
arguments, and this is used to extract the required content. If the content \
extracted is a link (from an attr value of "href" or "src"), the URL is parsed \
to convert the relative path into an absolute path.
If the selector does not fetch any content, the default value is returned. \
If no default value is specified, an exception is raised.
:param selector: The XPath expression
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param connector: String connector for list of data returned for a particular selector
:return: The extracted content
|
[
"Method",
"for",
"performing",
"the",
"content",
"extraction",
"for",
"the",
"particular",
"selector",
"type",
".",
"\\"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/selectors/selector.py#L81-L119
|
3,681
|
AlexMathew/scrapple
|
scrapple/selectors/selector.py
|
Selector.extract_links
|
def extract_links(self, selector='', *args, **kwargs):
"""
Method for performing the link extraction for the crawler. \
The selector passed as the argument is a selector to point to the anchor tags \
that the crawler should pass through. A list of links is obtained, and the links \
are iterated through. The relative paths are converted into absolute paths and \
a ``XpathSelector``/``CssSelector`` object (as is the case) is created with the URL of the next page as the argument \
and this created object is yielded.
The extract_links method basically generates ``XpathSelector``/``CssSelector`` objects for all of \
the links to be crawled through.
:param selector: The selector for the anchor tags to be crawled through
:return: A ``XpathSelector``/``CssSelector`` object for every page to be crawled through
"""
try:
links = self.get_tree_tag(selector=selector)
for link in links:
next_url = urljoin(self.url, link.get('href'))
yield type(self)(next_url)
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except Exception:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
|
python
|
def extract_links(self, selector='', *args, **kwargs):
"""
Method for performing the link extraction for the crawler. \
The selector passed as the argument is a selector to point to the anchor tags \
that the crawler should pass through. A list of links is obtained, and the links \
are iterated through. The relative paths are converted into absolute paths and \
a ``XpathSelector``/``CssSelector`` object (as is the case) is created with the URL of the next page as the argument \
and this created object is yielded.
The extract_links method basically generates ``XpathSelector``/``CssSelector`` objects for all of \
the links to be crawled through.
:param selector: The selector for the anchor tags to be crawled through
:return: A ``XpathSelector``/``CssSelector`` object for every page to be crawled through
"""
try:
links = self.get_tree_tag(selector=selector)
for link in links:
next_url = urljoin(self.url, link.get('href'))
yield type(self)(next_url)
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except Exception:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
|
[
"def",
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"(",
"\"Invalid %s selector - %s\"",
"%",
"(",
"self",
".",
"__selector_type__",
",",
"selector",
")",
")"
] |
Method for performing the link extraction for the crawler. \
The selector passed as the argument is a selector to point to the anchor tags \
that the crawler should pass through. A list of links is obtained, and the links \
are iterated through. The relative paths are converted into absolute paths and \
a ``XpathSelector``/``CssSelector`` object (as is the case) is created with the URL of the next page as the argument \
and this created object is yielded.
The extract_links method basically generates ``XpathSelector``/``CssSelector`` objects for all of \
the links to be crawled through.
:param selector: The selector for the anchor tags to be crawled through
:return: A ``XpathSelector``/``CssSelector`` object for every page to be crawled through
|
[
"Method",
"for",
"performing",
"the",
"link",
"extraction",
"for",
"the",
"crawler",
".",
"\\"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/selectors/selector.py#L122-L147
|
3,682
|
AlexMathew/scrapple
|
scrapple/selectors/selector.py
|
Selector.extract_tabular
|
def extract_tabular(self, header='', prefix='', suffix='', table_type='', *args, **kwargs):
"""
Method for performing the tabular data extraction. \
:param result: A dictionary containing the extracted data so far
:param table_type: Can be "rows" or "columns". This determines the type of table to be extracted. \
A row extraction is when there is a single row to be extracted and mapped to a set of headers. \
A column extraction is when a set of rows have to be extracted, giving a list of header-value mappings.
:param header: The headers to be used for the table. This can be a list of headers, or a selector that gives the list of headers
:param prefix: A prefix to be added to each header
:param suffix: A suffix to be added to each header
:param selector: For row extraction, this is a selector that gives the row to be extracted. \
For column extraction, this is a list of selectors for each column.
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param verbosity: The verbosity set as the argument for scrapple run
:return: A 2-tuple containing the list of all the column headers extracted and the list of \
dictionaries which contain (header, content) pairs
"""
if type(header) in [str, unicode]:
try:
header_list = self.get_tree_tag(header)
table_headers = [prefix + h.text + suffix for h in header_list]
except XPathError:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
except Exception:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
else:
table_headers = [prefix + h + suffix for h in header]
if len(table_headers) == 0:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
if table_type not in ["rows", "columns"]:
raise Exception("Specify 'rows' or 'columns' in table_type")
if table_type == "rows":
result_list = self.extract_rows(table_headers=table_headers, *args, **kwargs)
else:
result_list = self.extract_columns(table_headers=table_headers, *args, **kwargs)
return table_headers, result_list
|
python
|
def extract_tabular(self, header='', prefix='', suffix='', table_type='', *args, **kwargs):
"""
Method for performing the tabular data extraction. \
:param result: A dictionary containing the extracted data so far
:param table_type: Can be "rows" or "columns". This determines the type of table to be extracted. \
A row extraction is when there is a single row to be extracted and mapped to a set of headers. \
A column extraction is when a set of rows have to be extracted, giving a list of header-value mappings.
:param header: The headers to be used for the table. This can be a list of headers, or a selector that gives the list of headers
:param prefix: A prefix to be added to each header
:param suffix: A suffix to be added to each header
:param selector: For row extraction, this is a selector that gives the row to be extracted. \
For column extraction, this is a list of selectors for each column.
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param verbosity: The verbosity set as the argument for scrapple run
:return: A 2-tuple containing the list of all the column headers extracted and the list of \
dictionaries which contain (header, content) pairs
"""
if type(header) in [str, unicode]:
try:
header_list = self.get_tree_tag(header)
table_headers = [prefix + h.text + suffix for h in header_list]
except XPathError:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
except Exception:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
else:
table_headers = [prefix + h + suffix for h in header]
if len(table_headers) == 0:
raise Exception("Invalid %s selector for table header - %s" % (self.__selector_type__, header))
if table_type not in ["rows", "columns"]:
raise Exception("Specify 'rows' or 'columns' in table_type")
if table_type == "rows":
result_list = self.extract_rows(table_headers=table_headers, *args, **kwargs)
else:
result_list = self.extract_columns(table_headers=table_headers, *args, **kwargs)
return table_headers, result_list
|
[
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",",
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")",
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",",
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] |
Method for performing the tabular data extraction. \
:param result: A dictionary containing the extracted data so far
:param table_type: Can be "rows" or "columns". This determines the type of table to be extracted. \
A row extraction is when there is a single row to be extracted and mapped to a set of headers. \
A column extraction is when a set of rows have to be extracted, giving a list of header-value mappings.
:param header: The headers to be used for the table. This can be a list of headers, or a selector that gives the list of headers
:param prefix: A prefix to be added to each header
:param suffix: A suffix to be added to each header
:param selector: For row extraction, this is a selector that gives the row to be extracted. \
For column extraction, this is a list of selectors for each column.
:param attr: The attribute to be extracted from the selected tag
:param default: The default value to be used if the selector does not return any data
:param verbosity: The verbosity set as the argument for scrapple run
:return: A 2-tuple containing the list of all the column headers extracted and the list of \
dictionaries which contain (header, content) pairs
|
[
"Method",
"for",
"performing",
"the",
"tabular",
"data",
"extraction",
".",
"\\"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/selectors/selector.py#L150-L187
|
3,683
|
AlexMathew/scrapple
|
scrapple/selectors/selector.py
|
Selector.extract_rows
|
def extract_rows(self, result={}, selector='', table_headers=[], attr='', connector='', default='', verbosity=0, *args, **kwargs):
"""
Row data extraction for extract_tabular
"""
result_list = []
try:
values = self.get_tree_tag(selector)
if len(table_headers) >= len(values):
from itertools import izip_longest
pairs = izip_longest(table_headers, values, fillvalue=default)
else:
from itertools import izip
pairs = izip(table_headers, values)
for head, val in pairs:
if verbosity > 1:
print("\nExtracting", head, "attribute", sep=' ', end='')
if attr.lower() == "text":
try:
content = connector.join([make_ascii(x).strip() for x in val.itertext()])
except Exception:
content = default
content = content.replace("\n", " ").strip()
else:
content = val.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
result[head] = content
result_list.append(result)
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except TypeError:
raise Exception("Selector expression string to be provided. Got " + selector)
return result_list
|
python
|
def extract_rows(self, result={}, selector='', table_headers=[], attr='', connector='', default='', verbosity=0, *args, **kwargs):
"""
Row data extraction for extract_tabular
"""
result_list = []
try:
values = self.get_tree_tag(selector)
if len(table_headers) >= len(values):
from itertools import izip_longest
pairs = izip_longest(table_headers, values, fillvalue=default)
else:
from itertools import izip
pairs = izip(table_headers, values)
for head, val in pairs:
if verbosity > 1:
print("\nExtracting", head, "attribute", sep=' ', end='')
if attr.lower() == "text":
try:
content = connector.join([make_ascii(x).strip() for x in val.itertext()])
except Exception:
content = default
content = content.replace("\n", " ").strip()
else:
content = val.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
result[head] = content
result_list.append(result)
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except TypeError:
raise Exception("Selector expression string to be provided. Got " + selector)
return result_list
|
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"val",
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"\"\\nExtracting\"",
",",
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"\"attribute\"",
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":",
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"Exception",
"(",
"\"Selector expression string to be provided. Got \"",
"+",
"selector",
")",
"return",
"result_list"
] |
Row data extraction for extract_tabular
|
[
"Row",
"data",
"extraction",
"for",
"extract_tabular"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/selectors/selector.py#L190-L224
|
3,684
|
AlexMathew/scrapple
|
scrapple/selectors/selector.py
|
Selector.extract_columns
|
def extract_columns(self, result={}, selector='', table_headers=[], attr='', connector='', default='', verbosity=0, *args, **kwargs):
"""
Column data extraction for extract_tabular
"""
result_list = []
try:
if type(selector) in [str, unicode]:
selectors = [selector]
elif type(selector) == list:
selectors = selector[:]
else:
raise Exception("Use a list of selector expressions for the various columns")
from itertools import izip, count
pairs = izip(table_headers, selectors)
columns = {}
for head, selector in pairs:
columns[head] = self.get_tree_tag(selector)
try:
for i in count(start=0):
r = result.copy()
for head in columns.keys():
if verbosity > 1:
print("\nExtracting", head, "attribute", sep=' ', end='')
col = columns[head][i]
if attr == "text":
try:
content = connector.join([make_ascii(x).strip() for x in col.itertext()])
except Exception:
content = default
content = content.replace("\n", " ").strip()
else:
content = col.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
r[head] = content
result_list.append(r)
except IndexError:
pass
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except TypeError:
raise Exception("Selector expression string to be provided. Got " + selector)
return result_list
|
python
|
def extract_columns(self, result={}, selector='', table_headers=[], attr='', connector='', default='', verbosity=0, *args, **kwargs):
"""
Column data extraction for extract_tabular
"""
result_list = []
try:
if type(selector) in [str, unicode]:
selectors = [selector]
elif type(selector) == list:
selectors = selector[:]
else:
raise Exception("Use a list of selector expressions for the various columns")
from itertools import izip, count
pairs = izip(table_headers, selectors)
columns = {}
for head, selector in pairs:
columns[head] = self.get_tree_tag(selector)
try:
for i in count(start=0):
r = result.copy()
for head in columns.keys():
if verbosity > 1:
print("\nExtracting", head, "attribute", sep=' ', end='')
col = columns[head][i]
if attr == "text":
try:
content = connector.join([make_ascii(x).strip() for x in col.itertext()])
except Exception:
content = default
content = content.replace("\n", " ").strip()
else:
content = col.get(attr)
if attr in ["href", "src"]:
content = urljoin(self.url, content)
r[head] = content
result_list.append(r)
except IndexError:
pass
except XPathError:
raise Exception("Invalid %s selector - %s" % (self.__selector_type__, selector))
except TypeError:
raise Exception("Selector expression string to be provided. Got " + selector)
return result_list
|
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":",
"raise",
"Exception",
"(",
"\"Selector expression string to be provided. Got \"",
"+",
"selector",
")",
"return",
"result_list"
] |
Column data extraction for extract_tabular
|
[
"Column",
"data",
"extraction",
"for",
"extract_tabular"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/selectors/selector.py#L227-L271
|
3,685
|
AlexMathew/scrapple
|
scrapple/cmd.py
|
runCLI
|
def runCLI():
"""
The starting point for the execution of the Scrapple command line tool.
runCLI uses the docstring as the usage description for the scrapple command. \
The class for the required command is selected by a dynamic dispatch, and the \
command is executed through the execute_command() method of the command class.
"""
args = docopt(__doc__, version='0.3.0')
try:
check_arguments(args)
command_list = ['genconfig', 'run', 'generate']
select = itemgetter('genconfig', 'run', 'generate')
selectedCommand = command_list[select(args).index(True)]
cmdClass = get_command_class(selectedCommand)
obj = cmdClass(args)
obj.execute_command()
except POSSIBLE_EXCEPTIONS as e:
print('\n', e, '\n')
|
python
|
def runCLI():
"""
The starting point for the execution of the Scrapple command line tool.
runCLI uses the docstring as the usage description for the scrapple command. \
The class for the required command is selected by a dynamic dispatch, and the \
command is executed through the execute_command() method of the command class.
"""
args = docopt(__doc__, version='0.3.0')
try:
check_arguments(args)
command_list = ['genconfig', 'run', 'generate']
select = itemgetter('genconfig', 'run', 'generate')
selectedCommand = command_list[select(args).index(True)]
cmdClass = get_command_class(selectedCommand)
obj = cmdClass(args)
obj.execute_command()
except POSSIBLE_EXCEPTIONS as e:
print('\n', e, '\n')
|
[
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":",
"args",
"=",
"docopt",
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"__doc__",
",",
"version",
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"command_list",
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"'run'",
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"as",
"e",
":",
"print",
"(",
"'\\n'",
",",
"e",
",",
"'\\n'",
")"
] |
The starting point for the execution of the Scrapple command line tool.
runCLI uses the docstring as the usage description for the scrapple command. \
The class for the required command is selected by a dynamic dispatch, and the \
command is executed through the execute_command() method of the command class.
|
[
"The",
"starting",
"point",
"for",
"the",
"execution",
"of",
"the",
"Scrapple",
"command",
"line",
"tool",
"."
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/cmd.py#L49-L67
|
3,686
|
AlexMathew/scrapple
|
scrapple/utils/exceptions.py
|
check_arguments
|
def check_arguments(args):
"""
Validates the arguments passed through the CLI commands.
:param args: The arguments passed in the CLI, parsed by the docopt module
:return: None
"""
projectname_re = re.compile(r'[^a-zA-Z0-9_]')
if args['genconfig']:
if args['--type'] not in ['scraper', 'crawler']:
raise InvalidType("--type has to be 'scraper' or 'crawler'")
if args['--selector'] not in ['xpath', 'css']:
raise InvalidSelector("--selector has to be 'xpath' or 'css'")
if args['generate'] or args['run']:
if args['--output_type'] not in ['json', 'csv']:
raise InvalidOutputType("--output_type has to be 'json' or 'csv'")
if args['genconfig'] or args['generate'] or args['run']:
if projectname_re.search(args['<projectname>']) is not None:
message = "<projectname> should consist of letters, digits or _"
raise InvalidProjectName(message)
try:
if int(args['--levels']) < 1:
message = "--levels should be greater than, or equal to 1"
raise InvalidLevels(message)
except (TypeError, ValueError):
message = " ".join([
"--levels should be an integer and not of type",
"{}".format(type(args['--levels']))
])
raise InvalidLevels(message)
|
python
|
def check_arguments(args):
"""
Validates the arguments passed through the CLI commands.
:param args: The arguments passed in the CLI, parsed by the docopt module
:return: None
"""
projectname_re = re.compile(r'[^a-zA-Z0-9_]')
if args['genconfig']:
if args['--type'] not in ['scraper', 'crawler']:
raise InvalidType("--type has to be 'scraper' or 'crawler'")
if args['--selector'] not in ['xpath', 'css']:
raise InvalidSelector("--selector has to be 'xpath' or 'css'")
if args['generate'] or args['run']:
if args['--output_type'] not in ['json', 'csv']:
raise InvalidOutputType("--output_type has to be 'json' or 'csv'")
if args['genconfig'] or args['generate'] or args['run']:
if projectname_re.search(args['<projectname>']) is not None:
message = "<projectname> should consist of letters, digits or _"
raise InvalidProjectName(message)
try:
if int(args['--levels']) < 1:
message = "--levels should be greater than, or equal to 1"
raise InvalidLevels(message)
except (TypeError, ValueError):
message = " ".join([
"--levels should be an integer and not of type",
"{}".format(type(args['--levels']))
])
raise InvalidLevels(message)
|
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")",
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")",
"raise",
"InvalidLevels",
"(",
"message",
")"
] |
Validates the arguments passed through the CLI commands.
:param args: The arguments passed in the CLI, parsed by the docopt module
:return: None
|
[
"Validates",
"the",
"arguments",
"passed",
"through",
"the",
"CLI",
"commands",
"."
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/exceptions.py#L36-L66
|
3,687
|
AlexMathew/scrapple
|
scrapple/utils/form.py
|
form_to_json
|
def form_to_json(form):
"""
Takes the form from the POST request in the web interface, and generates the JSON config\
file
:param form: The form from the POST request
:return: None
"""
config = dict()
if form['project_name'] == "":
raise Exception('Project name cannot be empty.')
if form['selector_type'] not in ["css", "xpath"]:
raise Exception('Selector type has to css or xpath')
config['project_name'] = form['project_name']
config['selector_type'] = form['selector_type']
config['scraping'] = dict()
if form['url'] == "":
raise Exception('URL cannot be empty')
config['scraping']['url'] = form['url']
config['scraping']['data'] = list()
for i in itertools.count(start=1):
try:
data = {
'field': form['field_' + str(i)],
'selector': form['selector_' + str(i)],
'attr': form['attribute_' + str(i)],
'default': form['default_' + str(i)]
}
config['scraping']['data'].append(data)
except KeyError:
break
# TODO : Crawler 'next' parameter handling
with open(os.path.join(os.getcwd(), form['project_name'] + '.json'), 'w') as f:
json.dump(config, f)
return
|
python
|
def form_to_json(form):
"""
Takes the form from the POST request in the web interface, and generates the JSON config\
file
:param form: The form from the POST request
:return: None
"""
config = dict()
if form['project_name'] == "":
raise Exception('Project name cannot be empty.')
if form['selector_type'] not in ["css", "xpath"]:
raise Exception('Selector type has to css or xpath')
config['project_name'] = form['project_name']
config['selector_type'] = form['selector_type']
config['scraping'] = dict()
if form['url'] == "":
raise Exception('URL cannot be empty')
config['scraping']['url'] = form['url']
config['scraping']['data'] = list()
for i in itertools.count(start=1):
try:
data = {
'field': form['field_' + str(i)],
'selector': form['selector_' + str(i)],
'attr': form['attribute_' + str(i)],
'default': form['default_' + str(i)]
}
config['scraping']['data'].append(data)
except KeyError:
break
# TODO : Crawler 'next' parameter handling
with open(os.path.join(os.getcwd(), form['project_name'] + '.json'), 'w') as f:
json.dump(config, f)
return
|
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"return"
] |
Takes the form from the POST request in the web interface, and generates the JSON config\
file
:param form: The form from the POST request
:return: None
|
[
"Takes",
"the",
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"JSON",
"config",
"\\",
"file"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/form.py#L13-L48
|
3,688
|
AlexMathew/scrapple
|
scrapple/commands/run.py
|
RunCommand.execute_command
|
def execute_command(self):
"""
The run command implements the web content extractor corresponding to the given \
configuration file.
The execute_command() validates the input project name and opens the JSON \
configuration file. The run() method handles the execution of the extractor run.
The extractor implementation follows these primary steps :
1. Selects the appropriate :ref:`selector class <implementation-selectors>` through \
a dynamic dispatch, with the selector_type argument from the CLI input.
#. Iterate through the data section in level-0 of the configuration file. \
On each data item, call the extract_content() method from the selector class to \
extract the content according to the specified extractor rule.
#. If there are multiple levels of the extractor, i.e, if there is a 'next' \
attribute in the configuration file, call the traverse_next() \
:ref:`utility function <implementation-utils>` and parse through successive levels \
of the configuration file.
#. According to the --output_type argument, the result data is saved in a JSON \
document or a CSV document.
"""
try:
self.args['--verbosity'] = int(self.args['--verbosity'])
if self.args['--verbosity'] not in [0, 1, 2]:
raise ValueError
if self.args['--verbosity'] > 0:
print(Back.GREEN + Fore.BLACK + "Scrapple Run")
print(Back.RESET + Fore.RESET)
import json
with open(self.args['<projectname>'] + '.json', 'r') as f:
self.config = json.load(f)
validate_config(self.config)
self.run()
except ValueError:
print(Back.WHITE + Fore.RED + "Use 0, 1 or 2 for verbosity." \
+ Back.RESET + Fore.RESET, sep="")
except IOError:
print(Back.WHITE + Fore.RED + self.args['<projectname>'], ".json does not ", \
"exist. Use ``scrapple genconfig``." + Back.RESET + Fore.RESET, sep="")
except InvalidConfigException as e:
print(Back.WHITE + Fore.RED + e + Back.RESET + Fore.RESET, sep="")
|
python
|
def execute_command(self):
"""
The run command implements the web content extractor corresponding to the given \
configuration file.
The execute_command() validates the input project name and opens the JSON \
configuration file. The run() method handles the execution of the extractor run.
The extractor implementation follows these primary steps :
1. Selects the appropriate :ref:`selector class <implementation-selectors>` through \
a dynamic dispatch, with the selector_type argument from the CLI input.
#. Iterate through the data section in level-0 of the configuration file. \
On each data item, call the extract_content() method from the selector class to \
extract the content according to the specified extractor rule.
#. If there are multiple levels of the extractor, i.e, if there is a 'next' \
attribute in the configuration file, call the traverse_next() \
:ref:`utility function <implementation-utils>` and parse through successive levels \
of the configuration file.
#. According to the --output_type argument, the result data is saved in a JSON \
document or a CSV document.
"""
try:
self.args['--verbosity'] = int(self.args['--verbosity'])
if self.args['--verbosity'] not in [0, 1, 2]:
raise ValueError
if self.args['--verbosity'] > 0:
print(Back.GREEN + Fore.BLACK + "Scrapple Run")
print(Back.RESET + Fore.RESET)
import json
with open(self.args['<projectname>'] + '.json', 'r') as f:
self.config = json.load(f)
validate_config(self.config)
self.run()
except ValueError:
print(Back.WHITE + Fore.RED + "Use 0, 1 or 2 for verbosity." \
+ Back.RESET + Fore.RESET, sep="")
except IOError:
print(Back.WHITE + Fore.RED + self.args['<projectname>'], ".json does not ", \
"exist. Use ``scrapple genconfig``." + Back.RESET + Fore.RESET, sep="")
except InvalidConfigException as e:
print(Back.WHITE + Fore.RED + e + Back.RESET + Fore.RESET, sep="")
|
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"RESET",
"+",
"Fore",
".",
"RESET",
",",
"sep",
"=",
"\"\"",
")"
] |
The run command implements the web content extractor corresponding to the given \
configuration file.
The execute_command() validates the input project name and opens the JSON \
configuration file. The run() method handles the execution of the extractor run.
The extractor implementation follows these primary steps :
1. Selects the appropriate :ref:`selector class <implementation-selectors>` through \
a dynamic dispatch, with the selector_type argument from the CLI input.
#. Iterate through the data section in level-0 of the configuration file. \
On each data item, call the extract_content() method from the selector class to \
extract the content according to the specified extractor rule.
#. If there are multiple levels of the extractor, i.e, if there is a 'next' \
attribute in the configuration file, call the traverse_next() \
:ref:`utility function <implementation-utils>` and parse through successive levels \
of the configuration file.
#. According to the --output_type argument, the result data is saved in a JSON \
document or a CSV document.
|
[
"The",
"run",
"command",
"implements",
"the",
"web",
"content",
"extractor",
"corresponding",
"to",
"the",
"given",
"\\",
"configuration",
"file",
"."
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/commands/run.py#L29-L74
|
3,689
|
AlexMathew/scrapple
|
scrapple/utils/config.py
|
traverse_next
|
def traverse_next(page, nextx, results, tabular_data_headers=[], verbosity=0):
"""
Recursive generator to traverse through the next attribute and \
crawl through the links to be followed.
:param page: The current page being parsed
:param next: The next attribute of the current scraping dict
:param results: The current extracted content, stored in a dict
:return: The extracted content, through a generator
"""
for link in page.extract_links(selector=nextx['follow_link']):
if verbosity > 0:
print('\n')
print(Back.YELLOW + Fore.BLUE + "Loading page ", link.url + Back.RESET + Fore.RESET, end='')
r = results.copy()
for attribute in nextx['scraping'].get('data'):
if attribute['field'] != "":
if verbosity > 1:
print("\nExtracting", attribute['field'], "attribute", sep=' ', end='')
r[attribute['field']] = link.extract_content(**attribute)
if not nextx['scraping'].get('table'):
result_list = [r]
else:
tables = nextx['scraping'].get('table', [])
for table in tables:
table.update({
'result': r,
'verbosity': verbosity
})
table_headers, result_list = link.extract_tabular(**table)
tabular_data_headers.extend(table_headers)
if not nextx['scraping'].get('next'):
for r in result_list:
yield (tabular_data_headers, r)
else:
for nextx2 in nextx['scraping'].get('next'):
for tdh, result in traverse_next(link, nextx2, r, tabular_data_headers=tabular_data_headers, verbosity=verbosity):
yield (tdh, result)
|
python
|
def traverse_next(page, nextx, results, tabular_data_headers=[], verbosity=0):
"""
Recursive generator to traverse through the next attribute and \
crawl through the links to be followed.
:param page: The current page being parsed
:param next: The next attribute of the current scraping dict
:param results: The current extracted content, stored in a dict
:return: The extracted content, through a generator
"""
for link in page.extract_links(selector=nextx['follow_link']):
if verbosity > 0:
print('\n')
print(Back.YELLOW + Fore.BLUE + "Loading page ", link.url + Back.RESET + Fore.RESET, end='')
r = results.copy()
for attribute in nextx['scraping'].get('data'):
if attribute['field'] != "":
if verbosity > 1:
print("\nExtracting", attribute['field'], "attribute", sep=' ', end='')
r[attribute['field']] = link.extract_content(**attribute)
if not nextx['scraping'].get('table'):
result_list = [r]
else:
tables = nextx['scraping'].get('table', [])
for table in tables:
table.update({
'result': r,
'verbosity': verbosity
})
table_headers, result_list = link.extract_tabular(**table)
tabular_data_headers.extend(table_headers)
if not nextx['scraping'].get('next'):
for r in result_list:
yield (tabular_data_headers, r)
else:
for nextx2 in nextx['scraping'].get('next'):
for tdh, result in traverse_next(link, nextx2, r, tabular_data_headers=tabular_data_headers, verbosity=verbosity):
yield (tdh, result)
|
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Recursive generator to traverse through the next attribute and \
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:param page: The current page being parsed
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:param results: The current extracted content, stored in a dict
:return: The extracted content, through a generator
|
[
"Recursive",
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"\\",
"crawl",
"through",
"the",
"links",
"to",
"be",
"followed",
"."
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/config.py#L20-L58
|
3,690
|
AlexMathew/scrapple
|
scrapple/utils/config.py
|
validate_config
|
def validate_config(config):
"""
Validates the extractor configuration file. Ensures that there are no duplicate field names, etc.
:param config: The configuration file that contains the specification of the extractor
:return: True if config is valid, else raises a exception that specifies the correction to be made
"""
fields = [f for f in get_fields(config)]
if len(fields) != len(set(fields)):
raise InvalidConfigException(
"Invalid configuration file - %d duplicate field names" % len(fields) - len(set(fields))
)
return True
|
python
|
def validate_config(config):
"""
Validates the extractor configuration file. Ensures that there are no duplicate field names, etc.
:param config: The configuration file that contains the specification of the extractor
:return: True if config is valid, else raises a exception that specifies the correction to be made
"""
fields = [f for f in get_fields(config)]
if len(fields) != len(set(fields)):
raise InvalidConfigException(
"Invalid configuration file - %d duplicate field names" % len(fields) - len(set(fields))
)
return True
|
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Validates the extractor configuration file. Ensures that there are no duplicate field names, etc.
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|
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"."
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/config.py#L61-L74
|
3,691
|
AlexMathew/scrapple
|
scrapple/utils/config.py
|
get_fields
|
def get_fields(config):
"""
Recursive generator that yields the field names in the config file
:param config: The configuration file that contains the specification of the extractor
:return: The field names in the config file, through a generator
"""
for data in config['scraping']['data']:
if data['field'] != '':
yield data['field']
if 'next' in config['scraping']:
for n in config['scraping']['next']:
for f in get_fields(n):
yield f
|
python
|
def get_fields(config):
"""
Recursive generator that yields the field names in the config file
:param config: The configuration file that contains the specification of the extractor
:return: The field names in the config file, through a generator
"""
for data in config['scraping']['data']:
if data['field'] != '':
yield data['field']
if 'next' in config['scraping']:
for n in config['scraping']['next']:
for f in get_fields(n):
yield f
|
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Recursive generator that yields the field names in the config file
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|
[
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"field",
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"in",
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"file"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/config.py#L77-L91
|
3,692
|
AlexMathew/scrapple
|
scrapple/utils/config.py
|
extract_fieldnames
|
def extract_fieldnames(config):
"""
Function to return a list of unique field names from the config file
:param config: The configuration file that contains the specification of the extractor
:return: A list of field names from the config file
"""
fields = []
for x in get_fields(config):
if x in fields:
fields.append(x + '_' + str(fields.count(x) + 1))
else:
fields.append(x)
return fields
|
python
|
def extract_fieldnames(config):
"""
Function to return a list of unique field names from the config file
:param config: The configuration file that contains the specification of the extractor
:return: A list of field names from the config file
"""
fields = []
for x in get_fields(config):
if x in fields:
fields.append(x + '_' + str(fields.count(x) + 1))
else:
fields.append(x)
return fields
|
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] |
Function to return a list of unique field names from the config file
:param config: The configuration file that contains the specification of the extractor
:return: A list of field names from the config file
|
[
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"a",
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"field",
"names",
"from",
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"file"
] |
eeb604601b155d6cc7e035855ff4d3f48f8bed74
|
https://github.com/AlexMathew/scrapple/blob/eeb604601b155d6cc7e035855ff4d3f48f8bed74/scrapple/utils/config.py#L94-L108
|
3,693
|
CQCL/pytket
|
pytket/qiskit/tket_pass.py
|
TketPass.run
|
def run(self, dag:DAGCircuit) -> DAGCircuit:
"""
Run one pass of optimisation on the circuit and route for the given backend.
:param dag: The circuit to optimise and route
:return: The modified circuit
"""
circ = dagcircuit_to_tk(dag, _DROP_CONDS=self.DROP_CONDS,_BOX_UNKNOWN=self.BOX_UNKNOWN)
circ, circlay = self.process_circ(circ)
newdag = tk_to_dagcircuit(circ)
newdag.name = dag.name
finlay = dict()
for i, qi in enumerate(circlay):
finlay[('q', i)] = ('q', qi)
newdag.final_layout = finlay
return newdag
|
python
|
def run(self, dag:DAGCircuit) -> DAGCircuit:
"""
Run one pass of optimisation on the circuit and route for the given backend.
:param dag: The circuit to optimise and route
:return: The modified circuit
"""
circ = dagcircuit_to_tk(dag, _DROP_CONDS=self.DROP_CONDS,_BOX_UNKNOWN=self.BOX_UNKNOWN)
circ, circlay = self.process_circ(circ)
newdag = tk_to_dagcircuit(circ)
newdag.name = dag.name
finlay = dict()
for i, qi in enumerate(circlay):
finlay[('q', i)] = ('q', qi)
newdag.final_layout = finlay
return newdag
|
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Run one pass of optimisation on the circuit and route for the given backend.
:param dag: The circuit to optimise and route
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] |
ae68f7402dcb5fb45221832cc6185d267bdd7a71
|
https://github.com/CQCL/pytket/blob/ae68f7402dcb5fb45221832cc6185d267bdd7a71/pytket/qiskit/tket_pass.py#L51-L68
|
3,694
|
CQCL/pytket
|
pytket/cirq/qubits.py
|
_sort_row_col
|
def _sort_row_col(qubits: Iterator[GridQubit]) -> List[GridQubit]:
"""Sort grid qubits first by row then by column"""
return sorted(qubits, key=lambda x: (x.row, x.col))
|
python
|
def _sort_row_col(qubits: Iterator[GridQubit]) -> List[GridQubit]:
"""Sort grid qubits first by row then by column"""
return sorted(qubits, key=lambda x: (x.row, x.col))
|
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Sort grid qubits first by row then by column
|
[
"Sort",
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"by",
"row",
"then",
"by",
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] |
ae68f7402dcb5fb45221832cc6185d267bdd7a71
|
https://github.com/CQCL/pytket/blob/ae68f7402dcb5fb45221832cc6185d267bdd7a71/pytket/cirq/qubits.py#L51-L54
|
3,695
|
CQCL/pytket
|
pytket/chemistry/aqua/qse.py
|
QSE.print_setting
|
def print_setting(self) -> str:
"""
Presents the QSE settings as a string.
:return: The formatted settings of the QSE instance
"""
ret = "\n"
ret += "==================== Setting of {} ============================\n".format(self.configuration['name'])
ret += "{}".format(self.setting)
ret += "===============================================================\n"
ret += "{}".format(self._var_form.setting)
ret += "===============================================================\n"
return ret
|
python
|
def print_setting(self) -> str:
"""
Presents the QSE settings as a string.
:return: The formatted settings of the QSE instance
"""
ret = "\n"
ret += "==================== Setting of {} ============================\n".format(self.configuration['name'])
ret += "{}".format(self.setting)
ret += "===============================================================\n"
ret += "{}".format(self._var_form.setting)
ret += "===============================================================\n"
return ret
|
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:return: The formatted settings of the QSE instance
|
[
"Presents",
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ae68f7402dcb5fb45221832cc6185d267bdd7a71
|
https://github.com/CQCL/pytket/blob/ae68f7402dcb5fb45221832cc6185d267bdd7a71/pytket/chemistry/aqua/qse.py#L117-L129
|
3,696
|
CQCL/pytket
|
pytket/chemistry/aqua/qse.py
|
QSE._energy_evaluation
|
def _energy_evaluation(self, operator):
"""
Evaluate the energy of the current input circuit with respect to the given operator.
:param operator: Hamiltonian of the system
:return: Energy of the Hamiltonian
"""
if self._quantum_state is not None:
input_circuit = self._quantum_state
else:
input_circuit = [self.opt_circuit]
if operator._paulis:
mean_energy, std_energy = operator.evaluate_with_result(self._operator_mode, input_circuit,
self._quantum_instance.backend, self.ret)
else:
mean_energy = 0.0
std_energy = 0.0
operator.disable_summarize_circuits()
logger.debug('Energy evaluation {} returned {}'.format(self._eval_count, np.real(mean_energy)))
return np.real(mean_energy), np.real(std_energy)
|
python
|
def _energy_evaluation(self, operator):
"""
Evaluate the energy of the current input circuit with respect to the given operator.
:param operator: Hamiltonian of the system
:return: Energy of the Hamiltonian
"""
if self._quantum_state is not None:
input_circuit = self._quantum_state
else:
input_circuit = [self.opt_circuit]
if operator._paulis:
mean_energy, std_energy = operator.evaluate_with_result(self._operator_mode, input_circuit,
self._quantum_instance.backend, self.ret)
else:
mean_energy = 0.0
std_energy = 0.0
operator.disable_summarize_circuits()
logger.debug('Energy evaluation {} returned {}'.format(self._eval_count, np.real(mean_energy)))
return np.real(mean_energy), np.real(std_energy)
|
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|
[
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] |
ae68f7402dcb5fb45221832cc6185d267bdd7a71
|
https://github.com/CQCL/pytket/blob/ae68f7402dcb5fb45221832cc6185d267bdd7a71/pytket/chemistry/aqua/qse.py#L131-L151
|
3,697
|
CQCL/pytket
|
pytket/chemistry/aqua/qse.py
|
QSE._run
|
def _run(self) -> dict:
"""
Runs the QSE algorithm to compute the eigenvalues of the Hamiltonian.
:return: Dictionary of results
"""
if not self._quantum_instance.is_statevector:
raise AquaError("Can only calculate state for QSE with statevector backends")
ret = self._quantum_instance.execute(self.opt_circuit)
self.ret = ret
self._eval_count = 0
self._solve()
self._ret['eval_count'] = self._eval_count
self._ret['eval_time'] = self._eval_time
return self._ret
|
python
|
def _run(self) -> dict:
"""
Runs the QSE algorithm to compute the eigenvalues of the Hamiltonian.
:return: Dictionary of results
"""
if not self._quantum_instance.is_statevector:
raise AquaError("Can only calculate state for QSE with statevector backends")
ret = self._quantum_instance.execute(self.opt_circuit)
self.ret = ret
self._eval_count = 0
self._solve()
self._ret['eval_count'] = self._eval_count
self._ret['eval_time'] = self._eval_time
return self._ret
|
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Runs the QSE algorithm to compute the eigenvalues of the Hamiltonian.
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|
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ae68f7402dcb5fb45221832cc6185d267bdd7a71
|
https://github.com/CQCL/pytket/blob/ae68f7402dcb5fb45221832cc6185d267bdd7a71/pytket/chemistry/aqua/qse.py#L260-L274
|
3,698
|
bkabrda/flask-whooshee
|
flask_whooshee.py
|
WhoosheeQuery.whooshee_search
|
def whooshee_search(self, search_string, group=whoosh.qparser.OrGroup, whoosheer=None,
match_substrings=True, limit=None, order_by_relevance=10):
"""Do a fulltext search on the query.
Returns a query filtered with results of the fulltext search.
:param search_string: The string to search for.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
"""
if not whoosheer:
### inspiration taken from flask-WhooshAlchemy
# find out all entities in join
entities = set()
# directly queried entities
for cd in self.column_descriptions:
entities.add(cd['type'])
# joined entities
if self._join_entities and isinstance(self._join_entities[0], Mapper):
# SQLAlchemy >= 0.8.0
entities.update(set([x.entity for x in self._join_entities]))
else:
# SQLAlchemy < 0.8.0
entities.update(set(self._join_entities))
# make sure we can work with aliased entities
unaliased = set()
for entity in entities:
if isinstance(entity, (AliasedClass, AliasedInsp)):
unaliased.add(inspect(entity).mapper.class_)
else:
unaliased.add(entity)
whoosheer = next(w for w in _get_config(self)['whoosheers']
if set(w.models) == unaliased)
# TODO what if unique field doesn't exist or there are multiple?
for fname, field in list(whoosheer.schema._fields.items()):
if field.unique:
uniq = fname
# TODO: use something more general than id
res = whoosheer.search(search_string=search_string,
values_of=uniq,
group=group,
match_substrings=match_substrings,
limit=limit)
if not res:
return self.filter(text('null'))
# transform unique field name into model attribute field
attr = None
if hasattr(whoosheer, '_is_model_whoosheer'):
attr = getattr(whoosheer.models[0], uniq)
else:
# non-model whoosheers must have unique field named
# model.__name__.lower + '_' + attr
for m in whoosheer.models:
if m.__name__.lower() == uniq.split('_')[0]:
attr = getattr(m, uniq.split('_')[1])
search_query = self.filter(attr.in_(res))
if order_by_relevance < 0: # we want all returned rows ordered
search_query = search_query.order_by(sqlalchemy.sql.expression.case(
[(attr == uniq_val, index) for index, uniq_val in enumerate(res)],
))
elif order_by_relevance > 0: # we want only number of specified rows ordered
search_query = search_query.order_by(sqlalchemy.sql.expression.case(
[(attr == uniq_val, index) for index, uniq_val in enumerate(res) if index < order_by_relevance],
else_=order_by_relevance
))
else: # no ordering
pass
return search_query
|
python
|
def whooshee_search(self, search_string, group=whoosh.qparser.OrGroup, whoosheer=None,
match_substrings=True, limit=None, order_by_relevance=10):
"""Do a fulltext search on the query.
Returns a query filtered with results of the fulltext search.
:param search_string: The string to search for.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
"""
if not whoosheer:
### inspiration taken from flask-WhooshAlchemy
# find out all entities in join
entities = set()
# directly queried entities
for cd in self.column_descriptions:
entities.add(cd['type'])
# joined entities
if self._join_entities and isinstance(self._join_entities[0], Mapper):
# SQLAlchemy >= 0.8.0
entities.update(set([x.entity for x in self._join_entities]))
else:
# SQLAlchemy < 0.8.0
entities.update(set(self._join_entities))
# make sure we can work with aliased entities
unaliased = set()
for entity in entities:
if isinstance(entity, (AliasedClass, AliasedInsp)):
unaliased.add(inspect(entity).mapper.class_)
else:
unaliased.add(entity)
whoosheer = next(w for w in _get_config(self)['whoosheers']
if set(w.models) == unaliased)
# TODO what if unique field doesn't exist or there are multiple?
for fname, field in list(whoosheer.schema._fields.items()):
if field.unique:
uniq = fname
# TODO: use something more general than id
res = whoosheer.search(search_string=search_string,
values_of=uniq,
group=group,
match_substrings=match_substrings,
limit=limit)
if not res:
return self.filter(text('null'))
# transform unique field name into model attribute field
attr = None
if hasattr(whoosheer, '_is_model_whoosheer'):
attr = getattr(whoosheer.models[0], uniq)
else:
# non-model whoosheers must have unique field named
# model.__name__.lower + '_' + attr
for m in whoosheer.models:
if m.__name__.lower() == uniq.split('_')[0]:
attr = getattr(m, uniq.split('_')[1])
search_query = self.filter(attr.in_(res))
if order_by_relevance < 0: # we want all returned rows ordered
search_query = search_query.order_by(sqlalchemy.sql.expression.case(
[(attr == uniq_val, index) for index, uniq_val in enumerate(res)],
))
elif order_by_relevance > 0: # we want only number of specified rows ordered
search_query = search_query.order_by(sqlalchemy.sql.expression.case(
[(attr == uniq_val, index) for index, uniq_val in enumerate(res) if index < order_by_relevance],
else_=order_by_relevance
))
else: # no ordering
pass
return search_query
|
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"# non-model whoosheers must have unique field named",
"# model.__name__.lower + '_' + attr",
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".",
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"sqlalchemy",
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"sql",
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"expression",
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"[",
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"uniq_val",
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"=",
"order_by_relevance",
")",
")",
"else",
":",
"# no ordering",
"pass",
"return",
"search_query"
] |
Do a fulltext search on the query.
Returns a query filtered with results of the fulltext search.
:param search_string: The string to search for.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
|
[
"Do",
"a",
"fulltext",
"search",
"on",
"the",
"query",
".",
"Returns",
"a",
"query",
"filtered",
"with",
"results",
"of",
"the",
"fulltext",
"search",
"."
] |
773fc51ed53043bd5e92c65eadef5663845ae8c4
|
https://github.com/bkabrda/flask-whooshee/blob/773fc51ed53043bd5e92c65eadef5663845ae8c4/flask_whooshee.py#L44-L123
|
3,699
|
bkabrda/flask-whooshee
|
flask_whooshee.py
|
AbstractWhoosheer.search
|
def search(cls, search_string, values_of='', group=whoosh.qparser.OrGroup, match_substrings=True, limit=None):
"""Searches the fields for given search_string.
Returns the found records if 'values_of' is left empty,
else the values of the given columns.
:param search_string: The string to search for.
:param values_of: If given, the method will not return the whole
records, but only values of given column.
Defaults to returning whole records.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise.
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
"""
index = Whooshee.get_or_create_index(_get_app(cls), cls)
prepped_string = cls.prep_search_string(search_string, match_substrings)
with index.searcher() as searcher:
parser = whoosh.qparser.MultifieldParser(cls.schema.names(), index.schema, group=group)
query = parser.parse(prepped_string)
results = searcher.search(query, limit=limit)
if values_of:
return [x[values_of] for x in results]
return results
|
python
|
def search(cls, search_string, values_of='', group=whoosh.qparser.OrGroup, match_substrings=True, limit=None):
"""Searches the fields for given search_string.
Returns the found records if 'values_of' is left empty,
else the values of the given columns.
:param search_string: The string to search for.
:param values_of: If given, the method will not return the whole
records, but only values of given column.
Defaults to returning whole records.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise.
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
"""
index = Whooshee.get_or_create_index(_get_app(cls), cls)
prepped_string = cls.prep_search_string(search_string, match_substrings)
with index.searcher() as searcher:
parser = whoosh.qparser.MultifieldParser(cls.schema.names(), index.schema, group=group)
query = parser.parse(prepped_string)
results = searcher.search(query, limit=limit)
if values_of:
return [x[values_of] for x in results]
return results
|
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"[",
"x",
"[",
"values_of",
"]",
"for",
"x",
"in",
"results",
"]",
"return",
"results"
] |
Searches the fields for given search_string.
Returns the found records if 'values_of' is left empty,
else the values of the given columns.
:param search_string: The string to search for.
:param values_of: If given, the method will not return the whole
records, but only values of given column.
Defaults to returning whole records.
:param group: The whoosh group to use for searching.
Defaults to :class:`whoosh.qparser.OrGroup` which
searches for all words in all columns.
:param match_substrings: ``True`` if you want to match substrings,
``False`` otherwise.
:param limit: The number of the top records to be returned.
Defaults to ``None`` and returns all records.
|
[
"Searches",
"the",
"fields",
"for",
"given",
"search_string",
".",
"Returns",
"the",
"found",
"records",
"if",
"values_of",
"is",
"left",
"empty",
"else",
"the",
"values",
"of",
"the",
"given",
"columns",
"."
] |
773fc51ed53043bd5e92c65eadef5663845ae8c4
|
https://github.com/bkabrda/flask-whooshee/blob/773fc51ed53043bd5e92c65eadef5663845ae8c4/flask_whooshee.py#L138-L163
|
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