In my opinion, for your scenario "I want to update one column of all the lines based on other column values.", the best option is to use Conditional update

Let's suppose this model:

class Person(models.Model):
    f1 = models.IntegerField()
    f2 = models.IntegerField()
    f3 = models.IntegerField()
    f4 = models.IntegerField()

You can update it in this way:

rom django.db.models import F, When, Case

new_value = Case(
    When(f1__gte=F('f2'), then=F('f1')),
    default=F('f2') 
)

Person.objects.update(f3=new_value)

This raise a simple update sql statement:

>>> import logging
>>> l = logging.getLogger('django.db.backends')
>>> l.setLevel(logging.DEBUG)
>>> l.addHandler(logging.StreamHandler())
>>> Person.objects.update(f3=c)
(0.000) UPDATE "tt_person" SET "f3" = CASE WHEN ("tt_person"."f1" >= "tt_person"."f2") THEN "tt_person"."f1" ELSE "tt_person"."f2" END; args=()
0

The out-of-the-box django feature to do bulk update is bulk_update(). Here an example:

myModel = MyModel.objects.all()

for l in myModel:
    if c1=='ChkVal1' and c2 < c3:    
        c4='Value 1'
    elif c1=='ChkVal2' and c2 b> c3:
        c4='Value 2'
    else
        c4='Value 3'

MyModel.objects.bulk_update(myModel, update_fields = ['c4'])

Remember, quoting docs:

• You cannot update the model’s primary key.
• Each model’s save() method isn’t called, and the pre_save and post_save signals aren’t sent.
• If updating a large number of columns in a large number of rows, the SQL generated can be very large. Avoid this by specifying a suitable batch_size.
• Updating fields defined on multi-table inheritance ancestors will incur an extra query per ancestor.
• When an individual batch contains duplicates, only the first instance in that batch will result in an update.