This is sort of a duplicate, maybe, but I haven't found a solution that fits my needs.
I have a function which builds django-tables2. I pass in a parameter of a model_class as a string. Right now that can be 'application', 'database', or 'item', but there will eventually be many more. In order to configure the table, I set:
table = DatabaseTable(assets)
I would like to be able to pass in the model_class so that the table is dynamic based on the type of input it's getting. Something like:
table = model_class + Table(assets) (pseudo)
I don't want to hardcode the dictionary as I'm not sure how many values will eventually be added. I see people suggesting using exec, but those suggestions are all followed by other users threatening to murder those people's families.
This has been asked many times on stack and the answer is always the same: when you want an association between names and objects, the one obvious way to do it is with a dictionary.
I don't want to hardcode the dictionary as I'm not sure how many
values will eventually be added.
So you want to avoid a situation like this
lookup = {'application': ApplicationTable,
'database': DatabaseTable,
'item': ItemTable}
Because you don't want to have to maintain the lookup, right? That's fine, but it is not necessary to hardcode a dictionary like this in order to dynamically retrieve the objects.
If your eval is working as you've said it is above, then these names in scope like ApplicationTable, Itemtable etc must be coming from somewhere. Since I don't know where they are being defined and where new ones are going to appear, I will assume they are being imported from some module called MyTables
from MyTables import ApplicationTable, Itemtable, BlahTable ...
The trick here is to use the dict (read: namespace) from the module itself.
import MyTables
my_string = 'item'
table = getattr(MyTables, my_string.capitalize() + 'Table')
Is this allowed? It works.
table = eval(model_name.capitalize() + 'Table(assets)')
RequestConfig(request).configure(table)
Related
So I'm trying to use smart_query in web2py to find specific values in a db, but the only explanation I can find is in the web2py book and it's not very clear. The example GET request from the book is formatted like this:
def GET(search):
try:
rows = db.smart_query([db.person, db.pet], search).select()
return dict(result=rows)
except:
...
I'm confused as to what values I would put in place of db.person and db.pet. Here is what the book says on it:
The method db.smart_query takes two arguments:
a list of field or table that should be allowed in the query
a string containing the query expressed in natural language
I'm thinking the first value would be the database I'm searching, but then I don't know what the second value would be. The book makes it sound like it should be the string I'm searching for, but I think that that's what the variable search is for.
Could someone please help me understand what exactly each argument is supposed to do?
The first argument to smart_query is a list of DAL Table and/or Field objects (a Table object in the list will simply be expanded to include all of the table's fields). This list determines which fields can be included in the query.
The second argument is the query itself, which can include field names and comparison operators (and their natural language counterparts) as well as "and" and "or" to expression conjunctions and disjunctions. For an idea of what is allowed, you can examine the relevant code here.
The SQLFORM.grid advanced search widget generates queries that are ultimately parsed by smart_query, so to get a better idea of how to generate such queries, try creating a test SQLFORM.grid and play with the search widget in the UI to see the queries it generates.
I basically just need to know how to query by excluding selected columns. Is this possible?
Example: I have table which has id, name, age, address, location, birth, age, sex... etc.
Instead of citing out the columns to retrieve, I'd like to just exclude some columns in the query(exclude age for example).
Sample code:
db.session.query(User.username).filter_by(username = request.form['username'], password = request.form['password']).first()
Last thing I wanna do is to list down all the attributes on the query() method, since this would be pretty long especially when you have lots of attributes, thus I just wanna exclude some columns.
Not sure why you're not just fetching the model. When doing that, you can defer loading of certain columns so that they are only queried on access.
db.session.query(User).options(db.defer('location')).filter_by(...).first()
In this example, accessing User.location the first time on an instance will issue another query to get the data.
See the documentation on column deferral: http://sqlalchemy.readthedocs.org/en/rel_0_9/orm/mapper_config.html?highlight=defer#column-deferral-api
Note that unless you're loading huge amounts of data, you won't see any speedup with this. It might actually make things slower since another query will be issued later. I have queries that load thousands of rows with eager-loaded relationships in less than 200ms, so this might be a case of premature optimization.
We can use the Inspection API to get the model's columns, and then create a list of columns that we want.
exclude = {'age', 'registration_date'}
insp = sa.inspect(User)
include = [c for c in insp.columns if c.name not in exclude]
# Traditional ORM style
with Session() as s:
q = s.query(*include)
for row in q:
print(row.id, row.name)
print()
# 1.4 style
with Session() as s:
q = sa.select(*include)
for row in s.execute(q):
print(row.id, row.name)
print()
inspect returns the mapper for the model class; to work with non-column attributes like relationships use one of the mapper's other attributes, such as all_orm_descriptors.
If you're using an object deserializer like marshmallow, it is easier to omit the required fields during the deserialization.
https://marshmallow.readthedocs.io/en/latest/api_reference.html#marshmallow.EXCLUDE
The fields to be omitted can be formed dynamically and conditionally excluded. Example:
ModelSchema(exclude=(field1, field2,)).jsonify(records)
I am not aware of a method that does that directly, but you can always get the column keys, exclude your columns, then call the resulting list. You don't need to see what is in the list while doing that.
q = db.session.query(blah blah...)
exclude = ['age']
targ_cols = [x for x in q.first().keys() if x not in exclude]
q.with_entities(targ_cols).all()
I am new to Python and Pyramid. In a test application I am using to learn more about Pyramid, I want to query a database and create a dictionary based on the results of a sqlalchemy query object and finally send the dictionary to the chameleon template.
So far I have the following code (which works fine), but I wanted to know if there is a better way to create my dictionary.
...
index = 0
clients = {}
q = self.request.params['q']
for client in DBSession.query(Client).filter(Client.name.like('%%%s%%' % q)).all():
clients[index] = { "id": client.id, "name": client.name }
index += 1
output = { "clients": clients }
return output
While learning Python, I found a nice way to create a list in a for loop statement like the following:
myvar = [user.name for user in users]
So, the other question I had: is there a similar 'one line' way like the above to create a dictionary of a sqlalchemy query object?
Thanks in advance.
well, yes, we can tighten this up a bit.
First, this pattern:
index = 0
for item in seq:
frobnicate(index, item)
item += 1
is common enough that there's a builtin function that does it automatically, enumerate(), used like this:
for index, item in enumerate(seq):
frobnicate(index, item)
but, I'm not sure you need it, Associating things with an integer index starting from zero is the functionality of a list, you don't really need a dict for that; unless you want to have holes, or need some of the other special features of dicts, just do:
stuff = []
stuff.extend(seq)
when you're only interested in a small subset of the attributes of a database entity, it's a good idea to tell sqlalchemy to emit a query that returns only that:
query = DBSession.query(Client.id, Client.name) \
.filter(q in Client.name)
In the above i've also shortened the .name.like('%%%s%%' % q) into just q in name since they mean the same thing (sqlalchemy expands it into the correct LIKE expression for you)
Queries constructed in this way return a special thing that looks like a tuple, and can be easily turned into a dict by calling _asdict() on it:
so to put it all together
output = [row._asdict() for row in DBSession.query(Client.id, Client.name)
.filter(q in Client.name)]
or, if you really desperately need it to be a dict, you can use a dict comprehension:
output = {index: row._asdict()
for index, row
in enumerate(DBSession.query(Client.id, Client.name)
.filter(q in Client.name))}
#TokenMacGuy gave a nice and detailed answer to your question. However, I have a feeling you've asked a wrong question :)
You don't need to convert SQLALchemy objects to dictionaries before passing them to the template - that would be quite inconvenient. You can pass the result of a query as is and directly use SQLALchemy mapped objects in your template
q = self.request.params['q']
clients = DBSession.query(Client).filter(q in Client.name).all()
return {'clients': clients}
If you want to turn a SqlAlchemy object into a dict, you can use this code:
def obj_to_dict(obj):
return dict((col.name, getattr(obj, col.name)) for col in sqlalchemy_orm.class_mapper(obj.__class__).mapped_table.c)
there is another attribute of the mapped table that has the relationships in it , but the code gets dicey.
you don't need to cast an object into a dict for any of the template libraries, but if you decide to persist the data ( memcached, session, pickle, etc ) you'll either need to use dicts or write some code to 'merge' the persisted data back into the session.
a quick side note- if you render any of this data through json , you'll either need to have a custom json renderer that can handle datetime objects , or change the values in a function.
I build a list of Django model objects by making several queries. Then I want to remove any duplicates, (all of these objects are of the same type with an auto_increment int PK), but I can't use set() because they aren't hashable.
Is there a quick and easy way to do this? I'm considering using a dict instead of a list with the id as the key.
In general it's better to combine all your queries into a single query if possible. Ie.
q = Model.objects.filter(Q(field1=f1)|Q(field2=f2))
instead of
q1 = Models.object.filter(field1=f1)
q2 = Models.object.filter(field2=f2)
If the first query is returning duplicated Models then use distinct()
q = Model.objects.filter(Q(field1=f1)|Q(field2=f2)).distinct()
If your query really is impossible to execute with a single command, then you'll have to resort to using a dict or other technique recommended in the other answers. It might be helpful if you posted the exact query on SO and we could see if it would be possible to combine into a single query. In my experience, most queries can be done with a single queryset.
Is there a quick and easy way to do this? I'm considering using a dict instead of a list with the id as the key.
That's exactly what I would do if you were locked into your current structure of making several queries. Then a simply dictionary.values() will return your list back.
If you have a little more flexibility, why not use Q objects? Instead of actually making the queries, store each query in a Q object and use a bitwise or ("|") to execute a single query. This will achieve your goal and save database hits.
Django Q objects
You can use a set if you add the __hash__ function to your model definition so that it returns the id (assuming this doesn't interfere with other hash behaviour you may have in your app):
class MyModel(models.Model):
def __hash__(self):
return self.pk
If the order doesn't matter, use a dict.
Remove "duplicates" depends on how you define "duplicated".
If you want EVERY column (except the PK) to match, that's a pain in the neck -- it's a lot of comparing.
If, on the other hand, you have some "natural key" column (or short set of columns) than you can easily query and remove these.
master = MyModel.objects.get( id=theMasterKey )
dups = MyModel.objects.filter( fld1=master.fld1, fld2=master.fld2 )
dups.all().delete()
If you can identify some shorter set of key fields for duplicate identification, this works pretty well.
Edit
If the model objects haven't been saved to the database yet, you can make a dictionary on a tuple of these keys.
unique = {}
...
key = (anObject.fld1,anObject.fld2)
if key not in unique:
unique[key]= anObject
I use this one:
dict(zip(map(lambda x: x.pk,items),items)).values()
Given a class:
from django.db import models
class Person(models.Model):
name = models.CharField(max_length=20)
Is it possible, and if so how, to have a QuerySet that filters based on dynamic arguments? For example:
# Instead of:
Person.objects.filter(name__startswith='B')
# ... and:
Person.objects.filter(name__endswith='B')
# ... is there some way, given:
filter_by = '{0}__{1}'.format('name', 'startswith')
filter_value = 'B'
# ... that you can run the equivalent of this?
Person.objects.filter(filter_by=filter_value)
# ... which will throw an exception, since `filter_by` is not
# an attribute of `Person`.
Python's argument expansion may be used to solve this problem:
kwargs = {
'{0}__{1}'.format('name', 'startswith'): 'A',
'{0}__{1}'.format('name', 'endswith'): 'Z'
}
Person.objects.filter(**kwargs)
This is a very common and useful Python idiom.
A simplified example:
In a Django survey app, I wanted an HTML select list showing registered users. But because we have 5000 registered users, I needed a way to filter that list based on query criteria (such as just people who completed a certain workshop). In order for the survey element to be re-usable, I needed for the person creating the survey question to be able to attach those criteria to that question (don't want to hard-code the query into the app).
The solution I came up with isn't 100% user friendly (requires help from a tech person to create the query) but it does solve the problem. When creating the question, the editor can enter a dictionary into a custom field, e.g.:
{'is_staff':True,'last_name__startswith':'A',}
That string is stored in the database. In the view code, it comes back in as self.question.custom_query . The value of that is a string that looks like a dictionary. We turn it back into a real dictionary with eval() and then stuff it into the queryset with **kwargs:
kwargs = eval(self.question.custom_query)
user_list = User.objects.filter(**kwargs).order_by("last_name")
Additionally to extend on previous answer that made some requests for further code elements I am adding some working code that I am using
in my code with Q. Let's say that I in my request it is possible to have or not filter on fields like:
publisher_id
date_from
date_until
Those fields can appear in query but they may also be missed.
This is how I am building filters based on those fields on an aggregated query that cannot be further filtered after the initial queryset execution:
# prepare filters to apply to queryset
filters = {}
if publisher_id:
filters['publisher_id'] = publisher_id
if date_from:
filters['metric_date__gte'] = date_from
if date_until:
filters['metric_date__lte'] = date_until
filter_q = Q(**filters)
queryset = Something.objects.filter(filter_q)...
Hope this helps since I've spent quite some time to dig this up.
Edit:
As an additional benefit, you can use lists too. For previous example, if instead of publisher_id you have a list called publisher_ids, than you could use this piece of code:
if publisher_ids:
filters['publisher_id__in'] = publisher_ids
Django.db.models.Q is exactly what you want in a Django way.
This looks much more understandable to me:
kwargs = {
'name__startswith': 'A',
'name__endswith': 'Z',
***(Add more filters here)***
}
Person.objects.filter(**kwargs)
A really complex search forms usually indicates that a simpler model is trying to dig it's way out.
How, exactly, do you expect to get the values for the column name and operation?
Where do you get the values of 'name' an 'startswith'?
filter_by = '%s__%s' % ('name', 'startswith')
A "search" form? You're going to -- what? -- pick the name from a list of names? Pick the operation from a list of operations? While open-ended, most people find this confusing and hard-to-use.
How many columns have such filters? 6? 12? 18?
A few? A complex pick-list doesn't make sense. A few fields and a few if-statements make sense.
A large number? Your model doesn't sound right. It sounds like the "field" is actually a key to a row in another table, not a column.
Specific filter buttons. Wait... That's the way the Django admin works. Specific filters are turned into buttons. And the same analysis as above applies. A few filters make sense. A large number of filters usually means a kind of first normal form violation.
A lot of similar fields often means there should have been more rows and fewer fields.