I'm following the tutorial here: https://github.com/Jastor11/phresh-tutorial/tree/tutorial-part-11-marketplace-functionality-in-fastapi/backend/app and I had a question: I want to filter a model by different parameters so how would I do that?
The current situation is that I have a list of doctors and so I get all of them. Then depending on the filter query parameters, I filter doctors. I can't just do it all in one go because these query parameters are optional.
so I was thinking something like (psuedocode):
all_doctors = await self.db.fetch_all(query=GET_ALL_DOCTORS)
if language_id:
all_doctors = all_doctors.filter(d => doctor.language_id = language_id)
if area:
all_doctors = all_doctors.xyzabc
I'm trying out FastAPI according to that tutorial and couldn't figure out how to do this.
I have defined a model file for different models and am using SQLAlchemy.
One way I thought of is just getting the ids of all the doctors then at each filtering step, passing in the doctor ids from the last step and funneling them through different sql queries but this is filtering using the database and would result in one more query per filter parameter. I want to know how to use the ORM to filter in memory.
EDIT: So basically, in the tutorial I was following, no SQLAlchemy models were defined. The tutorial was using SQL statements. Anyways, to answer my own question: I would first need to define SQLAlchemy models before I can use them.
The SQLAlchemy query object (and its operations) returns itself, so you can keep building out the query conditionally inside if-statements:
query = db_session.query(Doctor)
if language_id:
query = query.filter(Doctor.language_id == language_id)
if area_id:
query = query.filter(Doctor.area_id == area_id)
return query.all()
The query doesn't run before you call all at the end. If neither argument is given, you'll get all the doctors.
Related
I am new to sqlalchemy and I have a question regarding my code:
query = db.query(Purchase.name,
func.sum(Purchase.price).label('total'),
func.count(Purchase.name).label('count'))
if date_start and date_end:
query = query.filter(Purchase.date >= date_start,
Purchase.date <= date_end)
query = query.group_by(Purchase.name)\
.order_by(sqlalchemy.desc('total'))[:limit]
result = [ItemDict(name=item.name, total=item.total,
count=item.count) for item in query]
Do I understand correctly that:
In this program there will be only one query to the database?
When we work with Query objects, we do NOT make additional queries to the database (i.e. the expression in the list does not make additional queries)?
Ad. 1: Yes, there should be only one query (there may also be a small query that does the "ping" command depending on your pool configuration)
Ad. 2: Additional queries depends on joining strategy. If you filter only one model without joining, you should always have single query. However, if you join other models and use lazy joining strategy, you can have many implicit additional queries (my short post about it)
You can use this smart context manager to count number of queries: How to count sqlalchemy queries in unit tests.
I created a view in my database model with 6 joins and 10 columns, and at the moment it shows around 86.000 rows.
I try to query all the rows by objects.all() and then filter according to user interaction (form data sent by POST and then choosing appropriate .filter(*args) querying)
After that I tried to get the length of the queryset by using count() since this method doesnt evaluate the query. But since views don't have indexes on the columns, the count() method takes to long.
I searched for the solution of materializing the view but that isn't possible in mysql.
Then I searched for a solution that might be able to replace the initial .all() by just using the 6 joins and filtering arguments in django rather than creating a view, so the indexes would still be available. But I couldn't find a solution to that problem.
Or maybe combining every row from the view with another table so I can use the index of the other table for faster querying?:
SELECT * FROM View LEFT JOIN Table ON (View.id = Table.id)
I appreciate every answer
Try this below:
from django.db import models
# I think below is your table structure
class Table(models.Model):
pass
class View(models.Model):
table = models.ForeignKey(to=Table)
qs = View.objects.select_related('table').filter(table__isnull=True)
for iterator in qs:
print(qs)
Thanks !
Let's say I have following models:
class Invoice(models.Model):
...
class Note(models.Model):
invoice = models.ForeignKey(Invoice, related_name='notes', on_delete=models.CASCADE)
text = models.TextField()
and I want to select Invoices that have some notes. I would write it using annotate/Exists like this:
Invoice.objects.annotate(
has_notes=Exists(Note.objects.filter(invoice_id=OuterRef('pk')))
).filter(has_notes=True)
This works well enough, filters only Invoices with notes. However, this method results in the field being present in the query result, which I don't need and means worse performance (SQL has to execute the subquery 2 times).
I realize I could write this using extra(where=) like this:
Invoice.objects.extra(where=['EXISTS(SELECT 1 FROM note WHERE invoice_id=invoice.id)'])
which would result in the ideal SQL, but in general it is discouraged to use extra / raw SQL.
Is there a better way to do this?
You can remove annotations from the SELECT clause using .values() query set method. The trouble with .values() is that you have to enumerate all names you want to keep instead of names you want to skip, and .values() returns dictionaries instead of model instances.
Django internaly keeps the track of removed annotations in
QuerySet.query.annotation_select_mask. So you can use it to tell Django, which annotations to skip even wihout .values():
class YourQuerySet(QuerySet):
def mask_annotations(self, *names):
if self.query.annotation_select_mask is None:
self.query.set_annotation_mask(set(self.query.annotations.keys()) - set(names))
else:
self.query.set_annotation_mask(self.query.annotation_select_mask - set(names))
return self
Then you can write:
invoices = (Invoice.objects
.annotate(has_notes=Exists(Note.objects.filter(invoice_id=OuterRef('pk'))))
.filter(has_notes=True)
.mask_annotations('has_notes')
)
to skip has_notes from the SELECT clause and still geting filtered invoice instances. The resulting SQL query will be something like:
SELECT invoice.id, invoice.foo FROM invoice
WHERE EXISTS(SELECT note.id, note.bar FROM notes WHERE note.invoice_id = invoice.id) = True
Just note that annotation_select_mask is internal Django API that can change in future versions without a warning.
Ok, I've just noticed in Django 3.0 docs, that they've updated how Exists works and can be used directly in filter:
Invoice.objects.filter(Exists(Note.objects.filter(invoice_id=OuterRef('pk'))))
This will ensure that the subquery will not be added to the SELECT columns, which may result in a better performance.
Changed in Django 3.0:
In previous versions of Django, it was necessary to first annotate and then filter against the annotation. This resulted in the annotated value always being present in the query result, and often resulted in a query that took more time to execute.
Still, if someone knows a better way for Django 1.11, I would appreciate it. We really need to upgrade :(
We can filter for Invoices that have, when we perform a LEFT OUTER JOIN, no NULL as Note, and make the query distinct (to avoid returning the same Invoice twice).
Invoice.objects.filter(notes__isnull=False).distinct()
This is best optimize code if you want to get data from another table which primary key reference stored in another table
Invoice.objects.filter(note__invoice_id=OuterRef('pk'),)
We should be able to clear the annotated field using the below method.
Invoice.objects.annotate(
has_notes=Exists(Note.objects.filter(invoice_id=OuterRef('pk')))
).filter(has_notes=True).query.annotations.clear()
When querying my database, I only want to load specified columns. Creating a query with with_entities requires a reference to the model column attribute, while creating a query with load_only requires a string corresponding to the column name. I would prefer to use load_only because it is easier to create a dynamic query using strings. What is the difference between the two?
load_only documentation
with_entities documentation
There are a few differences. The most important one when discarding unwanted columns (as in the question) is that using load_only will still result in creation of an object (a Model instance), while using with_entities will just get you tuples with values of chosen columns.
>>> query = User.query
>>> query.options(load_only('email', 'id')).all()
[<User 1 using e-mail: n#d.com>, <User 2 using e-mail: n#d.org>]
>>> query.with_entities(User.email, User.id).all()
[('n#d.org', 1), ('n#d.com', 2)]
load_only
load_only() defers loading of particular columns from your models.
It removes columns from query. You can still access all the other columns later, but an additional query (in the background) will be performed just when you try to access them.
"Load only" is useful when you store things like pictures of users in your database but you do not want to waste time transferring the images when not needed. For example, when displaying a list of users this might suffice:
User.query.options(load_only('name', 'fullname'))
with_entities
with_entities() can either add or remove (simply: replace) models or columns; you can even use it to modify the query, to replace selected entities with your own function like func.count():
query = User.query
count_query = query.with_entities(func.count(User.id)))
count = count_query.scalar()
Note that the resulting query is not the same as of query.count(), which would probably be slower - at least in MySQL (as it generates a subquery).
Another example of the extra capabilities of with_entities would be:
query = (
Page.query
.filter(<a lot of page filters>)
.join(Author).filter(<some author filters>)
)
pages = query.all()
# ok, I got the pages. Wait, what? I want the authors too!
# how to do it without generating the query again?
pages_and_authors = query.with_entities(Page, Author).all()
What is the preferred way to filter query set with '__in' in Django?
providers = Provider.objects.filter(age__gt=10)
consumers = Consumer.objects.filter(consumer__in=providers)
or
providers_ids = Provider.objects.filter(age__gt=10).values_list('id', flat=True)
consumers = Consumer.objects.filter(consumer__in=providers_ids)
These should be totally equivalent. Underneath the hood Django will optimize both of these to a subselect query in SQL. See the QuerySet API reference on in:
This queryset will be evaluated as subselect statement:
SELECT ... WHERE consumer.id IN (SELECT id FROM ... WHERE _ IN _)
However you can force a lookup based on passing in explicit values for the primary keys by calling list on your values_list, like so:
providers_ids = list(Provider.objects.filter(age__gt=10).values_list('id', flat=True))
consumers = Consumer.objects.filter(consumer__in=providers_ids)
This could be more performant in some cases, for example, when you have few providers, but it will be totally dependent on what your data is like and what database you're using. See the "Performance Considerations" note in the link above.
I Agree with Wilduck. However couple of notes
You can combine a filter such as these into one like this:
consumers = Consumer.objects.filter(consumer__age__gt=10)
This would give you the same result set - in a single query.
The second thing, to analyze the generated query, you can use the .query clause at the end.
Example:
print Provider.objects.filter(age__gt=10).query
would print the query the ORM would be generating to fetch the resultset.