Querying API¶
Constructing queries¶
Queries in peewee are constructed one piece at a time.
The “pieces” of a peewee query are generally representative of clauses you might find in a SQL query. Most methods are chainable, so you build your query up one clause at a time. This way, rather complex queries are possible.
Here is a barebones select query:
>>> user_q = User.select() # <-- query is not executed
>>> user_q
<peewee.SelectQuery object at 0x7f6b0810c610>
>>> [u.username for u in user_q] # <-- query is evaluated here
[u'admin', u'staff', u'editor']
We can build up the query by adding some clauses to it:
>>> user_q = user_q.where(username__in=['admin', 'editor'])
>>> user_q = user_q.order_by(('username', 'desc'))
>>> [u.username for u in user_q] # <-- query is re-evaluated here
[u'editor', u'admin']
Django-style queries¶
If you are already familiar with the Django ORM, you can construct SelectQuery
instances
using the familiar “double-underscore” syntax to generate the proper JOINs
and
WHERE
clauses.
Comparing the two methods of querying¶
- Get active users:
User.select().where(active=True) User.filter(active=True)
- Get users who are either staff or superusers:
User.select().where(Q(is_staff=True) | Q(is_superuser=True)) User.filter(Q(is_staff=True) | Q(is_superuser=True))
- Get tweets by user named “charlie”:
Tweet.select().join(User).where(username='charlie') Tweet.filter(user__username='charlie')
- Get tweets by staff or superusers (assumes FK relationship):
Tweet.select().join(User).where( Q(is_staff=True) | Q(is_superuser=True) ) Tweet.filter(Q(user__is_staff=True) | Q(user__is_superuser=True))
Where clause¶
All queries except InsertQuery
support the where()
method. If you are
familiar with Django’s ORM, it is analagous to the filter()
method.
>>> User.select().where(is_staff=True).sql()
('SELECT * FROM user WHERE is_staff = ?', [1])
Note
User.select()
is equivalent to SelectQuery(User)
.
The where()
method acts on the Model
that is the current “query context”.
This is either:
- the model the query class was initialized with
- the model most recently JOINed on
Here is an example using JOINs:
>>> User.select().where(is_staff=True).join(Blog).where(status=LIVE)
This query grabs all staff users who have a blog that is “LIVE”. This does the opposite, grabs all the blogs that are live whose author is a staffer:
>>> Blog.select().where(status=LIVE).join(User).where(is_staff=True)
Note
to join()
from one model to another there must be a ForeignKeyField
linking the two.
Another way to write the above query would be:
>>> Blog.select().where(
... status=LIVE,
... user__in=User.select().where(is_staff=True)
... )
The above bears a little bit of explanation. First off the SQL generated will
not perform any explicit JOIN
- it will rather use a subquery in the WHERE
clause:
# using subqueries
SELECT * FROM blog
WHERE (
status = ? AND
user_id IN (
SELECT t1.id FROM user AS t1 WHERE t1.is_staff = ?
)
)
And here it is using joins:
# using joins
SELECT t1.* FROM blog AS t1
INNER JOIN user AS t2
ON t1.user_id = t2.id
WHERE
t1.status = ? AND
t2.is_staff = ?
Column lookups¶
The other bit that’s unique about the query is that it specifies "user__in"
.
Users familiar with Django will recognize this syntax - lookups other than “=”
are signified by a double-underscore followed by the lookup type. The following
lookup types are available in peewee:
__eq
:- x = y, the default
__lt
:- x < y
__lte
:- x <= y
__gt
:- x > y
__gte
:- x >= y
__ne
:- x != y
__is
:- x IS y, used for testing against NULL values
__contains
:- case-sensitive check for substring
__icontains
:- case-insensitive check for substring
__in
:- x IN y, where y is either a list of values or a
SelectQuery
Performing advanced queries¶
As you may have noticed, all the examples up to now have shown queries that
combine multiple clauses with “AND”. Taking another page from Django’s ORM,
peewee allows the creation of arbitrarily complex queries using a special
notation called Q
objects.
>>> sq = User.select().where(Q(is_staff=True) | Q(is_superuser=True))
>>> print sq.sql()[0]
SELECT * FROM user WHERE (is_staff = ? OR is_superuser = ?)
Q
objects can be combined using the bitwise “or” and “and” operators. In order
to negate a Q
object, use the bitwise “invert” operator:
>>> staff_users = User.select().where(is_staff=True)
>>> Blog.select().where(~Q(user__in=staff_users))
This query generates the following SQL:
SELECT * FROM blog
WHERE
NOT user_id IN (
SELECT t1.id FROM user AS t1 WHERE t1.is_staff = ?
)
Rather complex lookups are possible:
>>> sq = User.select().where(
... (Q(is_staff=True) | Q(is_superuser=True)) &
... (Q(join_date__gte=datetime(2009, 1, 1)) | Q(join_date__lt=datetime(2005, 1 1)))
... )
>>> print sq.sql()[0] # cleaned up
SELECT * FROM user
WHERE (
(is_staff = ? OR is_superuser = ?) AND
(join_date >= ? OR join_date < ?)
)
This query selects all staff or super users who joined after 2009 or before 2005.
Note
If you need more power, check out RawQuery
Comparing against column data¶
Suppose you have a model that looks like the following:
class WorkerProfiles(Model):
salary = IntegerField()
desired = IntegerField()
What if we want to query WorkerProfiles
to find all the rows where “salary” is greater
than “desired” (maybe you want to find out who may be looking for a raise)?
To solve this problem, peewee borrows the notion of F
objects from the django
orm. An F
object allows you to query against arbitrary data present in
another column:
WorkerProfile.select().where(salary__gt=F('desired'))
That’s it. If the other column exists on a model that is accessed via a JOIN,
you will need to specify that model as the second argument to the F
object. Let’s supposed that the “desired” salary exists on a separate model:
WorkerProfile.select().join(Desired).where(desired_salary__lt=F('salary', WorkerProfile))
Atomic updates¶
The F
object also works for updating data. Suppose you cache counts of tweets for
every user in a special table to avoid an expensive COUNT() query. You want to
update the cache table every time a user tweets, but do so atomically:
cache_row = CacheCount.get(user=some_user)
update_query = cache_row.update(tweet_count=F('tweet_count') + 1)
update_query.execute()
Aggregating records¶
Suppose you have some blogs and want to get a list of them along with the count of entries in each. First I will show you the shortcut:
query = Blog.select().annotate(Entry)
This is equivalent to the following:
query = Blog.select({
Blog: ['*'],
Entry: [Count('id')],
}).group_by(Blog).join(Entry)
The resulting query will return Blog
objects with all their normal attributes
plus an additional attribute ‘count’ which will contain the number of entries.
By default it uses an inner join if the foreign key is not nullable, which means
blogs without entries won’t appear in the list. To remedy this, manually specify
the type of join to include blogs with 0 entries:
query = Blog.select().join(Entry, 'left outer').annotate(Entry)
You can also specify a custom aggregator:
query = Blog.select().annotate(Entry, peewee.Max('pub_date', 'max_pub_date'))
Conversely, sometimes you want to perform an aggregate query that returns a
scalar value, like the “max id”. Queries like this can be executed by using
the aggregate()
method:
max_id = Blog.select().aggregate(Max('id'))
SQL Functions, “Raw expressions” and the R() object¶
If you’ve been reading in order, you will have already seen the Q
and
F
objects. The R
object is the final query helper and its
purpose is to allow you to express arbitrary expressions as part of your structured
query without having to result to using a RawQuery
.
Selecting users whose username begins with “a”:
# select the users' id, username and the first letter of their username, lower-cased
query = User.select(['id', 'username', R('LOWER(SUBSTR(username, 1, 1))', 'first_letter')])
# now filter this list to include only users whose username begins with "a"
a_users = query.where(R('first_letter=%s', 'a'))
>>> for user in a_users:
... print user.first_letter, user.username
a alpha
A Alton
This same functionality could be easily exposed as part of the where clause, the only difference being that the first letter is not selected and therefore not an attribute of the model instance:
a_users = User.filter(R('LOWER(SUBSTR(username, 1, 1)) = %s', 'a'))
We can query for multiple values using R
objects, for example selecting
users whose usernames begin with a range of letters “b” through “d”:
letters = ('b', 'c', 'd')
bcd_users = User.filter(R('LOWER(SUBSTR(username, 1, 1)) IN (%s, %s, %s)', *letters))
We can write subqueries as part of a SelectQuery
, for example counting
the number of entries on a blog:
entry_query = R('(SELECT COUNT(*) FROM entry WHERE entry.blog_id=blog.id)', 'entry_count')
blogs = Blog.select(['id', 'title', entry_query]).order_by(('entry_count', 'desc'))
for blog in blogs:
print blog.title, blog.entry_count
It is also possible to use subqueries as part of a where clause, for example finding blogs that have no entries:
no_entry_query = R('NOT EXISTS (SELECT * FROM entry WHERE entry.blog_id=blog.id)')
blogs = Blog.filter(no_entry_query)
for blog in blogs:
print blog.title, ' has no entries'
Speeding up simple select queries¶
Simple select queries can get a performance boost (especially when iterating over large
result sets) by calling naive()
. This method simply patches all
attributes directly from the cursor onto the model. For simple queries this should have
no noticeable impact. The main difference is when multiple tables are queried, as in the
previous example:
# above example
entries = Entry.select({
Entry: ['*'],
Blog: ['*'],
}).order_by(('pub_date', 'desc')).join(Blog)
for entry in entries.limit(10):
print '%s, posted on %s' % (entry.title, entry.blog.title)
And here is how you would do the same if using a naive query:
# very similar query to the above -- main difference is we're
# aliasing the blog title to "blog_title"
entries = Entry.select({
Entry: ['*'],
Blog: [('title', 'blog_title')],
}).order_by(('pub_date', 'desc')).join(Blog)
entries = entries.naive()
# now instead of calling "entry.blog.title" the blog's title
# is exposed directly on the entry model as "blog_title" and
# no blog instance is created
for entry in entries.limit(10):
print '%s, posted on %s' % (entry.title, entry.blog_title)
Query evaluation¶
In order to execute a query, it is always necessary to call the execute()
method.
To get a better idea of how querying works let’s look at some example queries and their return values:
>>> dq = User.delete().where(active=False) # <-- returns a DeleteQuery
>>> dq
<peewee.DeleteQuery object at 0x7fc866ada4d0>
>>> dq.execute() # <-- executes the query and returns number of rows deleted
3
>>> uq = User.update(active=True).where(id__gt=3) # <-- returns an UpdateQuery
>>> uq
<peewee.UpdateQuery object at 0x7fc865beff50>
>>> uq.execute() # <-- executes the query and returns number of rows updated
2
>>> iq = User.insert(username='new user') # <-- returns an InsertQuery
>>> iq
<peewee.InsertQuery object at 0x7fc865beff10>
>>> iq.execute() # <-- executes query and returns the new row's PK
3
>>> sq = User.select().where(active=True) # <-- returns a SelectQuery
>>> sq
<peewee.SelectQuery object at 0x7fc865b7a510>
>>> qr = sq.execute() # <-- executes query and returns a QueryResultWrapper
>>> qr
<peewee.QueryResultWrapper object at 0x7fc865b7a6d0>
>>> [u.id for u in qr]
[1, 2, 3, 4, 7, 8]
>>> [u.id for u in qr] # <-- re-iterating over qr does not re-execute query
[1, 2, 3, 4, 7, 8]
>>> [u.id for u in sq] # <-- as a shortcut, you can iterate directly over
>>> # a SelectQuery (which uses a QueryResultWrapper
>>> # behind-the-scenes)
[1, 2, 3, 4, 7, 8]
Note
Iterating over a SelectQuery
will cause it to be evaluated, but iterating
over it multiple times will not result in the query being executed again.
QueryResultWrapper¶
As I hope the previous bit showed, Delete
, Insert
and Update
queries are all
pretty straightforward. Select
queries are a little bit tricky in that they
return a special object called a QueryResultWrapper
. The sole purpose of this
class is to allow the results of a query to be iterated over efficiently. In
general it should not need to be dealt with explicitly.
The preferred method of iterating over a result set is to iterate directly over
the SelectQuery
, allowing it to manage the QueryResultWrapper
internally.
SelectQuery¶
-
class
SelectQuery
¶ By far the most complex of the 4 query classes available in peewee. It supports
JOIN
operations on other tables, aggregation viaGROUP BY
andHAVING
clauses, ordering viaORDER BY
, and can be iterated and sliced to return only a subset of results.-
__init__
(model, query=None)¶ Parameters: - model – a
Model
class to perform query on - query – either a dictionary, keyed by model with a list of columns, or a string of columns
If no query is provided, it will default to
'*'
. this parameter can be either a dictionary or a string:>>> sq = SelectQuery(Blog, {Blog: ['id', 'title']}) >>> sq = SelectQuery(Blog, { ... Blog: ['*'], ... Entry: [peewee.Count('id')] ... }).group_by('id').join(Entry) >>> print sq.sql()[0] # formatted SELECT t1.*, COUNT(t2.id) AS count FROM blog AS t1 INNER JOIN entry AS t2 ON t1.id = t2.blog_id GROUP BY t1.id >>> sq = SelectQuery(Blog, 'id, title') >>> print sq.sql()[0] SELECT id, title FROM blog
- model – a
-
filter
(*args, **kwargs)¶ Parameters: - args – a list of
Q
orNode
objects - kwargs – a mapping of column + lookup to value, e.g. “age__gt=55”
Return type: a
SelectQuery
instanceProvides a django-like syntax for building a query. The key difference between
filter()
andwhere()
is thatfilter
supports traversing joins using django’s “double-underscore” syntax:>>> sq = SelectQuery(Entry).filter(blog__title='Some Blog')
This method is chainable:
>>> base_q = User.filter(active=True) >>> some_user = base_q.filter(username='charlie')
- args – a list of
-
get
(*args, **kwargs)¶ Parameters: - args – a list of
Q
orNode
objects - kwargs – a mapping of column + lookup to value, e.g. “age__gt=55”
Return type: Model
instance or raisesDoesNotExist
exceptionGet a single row from the database that matches the given query. Raises a
<model-class>.DoesNotExist
if no rows are returned:>>> active = User.select().where(active=True) >>> try: ... user = active.get(username=username, password=password) ... except User.DoesNotExist: ... user = None
This method is also exposed via the
Model
api:>>> user = User.get(username=username, password=password)
- args – a list of
-
where
(*args, **kwargs)¶ Parameters: - args – a list of
Q
orNode
objects - kwargs – a mapping of column + lookup to value, e.g. “age__gt=55”
Return type: a
SelectQuery
instanceCalling
where()
will act on the model that is currently thequery context
. Unlikefilter()
, only columns from the current query context are exposed:>>> sq = SelectQuery(Blog).where(title='some title', author=some_user) >>> sq = SelectQuery(Blog).where(Q(title='some title') | Q(title='other title'))
Note
where()
calls are chainable- args – a list of
-
join
(model, join_type=None, on=None, alias=None)¶ Parameters: - model – the model to join on. there must be a
ForeignKeyField
between the currentquery context
and the model passed in. - join_type – allows the type of
JOIN
used to be specified explicitly - on – if multiple foreign keys exist between two models, this parameter is a string containing the name of the ForeignKeyField to join on.
- alias – if provided, will be the name used to alias columns from this table in query
Return type: a
SelectQuery
instanceGenerate a
JOIN
clause from the currentquery context
to themodel
passed in, and establishesmodel
as the newquery context
.>>> sq = SelectQuery(Blog).join(Entry).where(title='Some Entry') >>> sq = SelectQuery(User).join(Relationship, on='to_user_id').where(from_user=self)
- model – the model to join on. there must be a
-
naive
()¶ Return type: SelectQuery
indicates that this query should only attempt to reconstruct a single model instance for every row returned by the cursor. if multiple tables were queried, the columns returned are patched directly onto the single model instance.
Note
this can provide a significant speed improvement when doing simple iteration over a large result set.
-
switch
(model)¶ Parameters: model – model to switch the query context
to.Return type: a SelectQuery
instanceSwitches the
query context
to the given model. Raises an exception if the model has not been selected or joined on previously.>>> sq = SelectQuery(Blog).join(Entry).switch(Blog).where(title='Some Blog')
-
count
()¶ Return type: an integer representing the number of rows in the current query >>> sq = SelectQuery(Blog) >>> sq.count() 45 # <-- number of blogs >>> sq.where(status=DELETED) >>> sq.count() 3 # <-- number of blogs that are marked as deleted
-
exists
()¶ Return type: boolean whether the current query will return any rows. uses an optimized lookup, so use this rather than get()
.>>> sq = User.select().where(active=True) >>> if sq.where(username=username, password=password).exists(): ... authenticated = True
-
annotate
(related_model, aggregation=None)¶ Parameters: - related_model – related
Model
on which to perform aggregation, must be linked byForeignKeyField
. - aggregation – the type of aggregation to use, e.g.
Max('pub_date', 'max_pub')
Return type: Annotate a query with an aggregation performed on a related model, for example, “get a list of blogs with the number of entries on each”:
>>> Blog.select().annotate(Entry)
if
aggregation
is None, it will default toCount(related_model, 'count')
, but can be anything:>>> blog_with_latest = Blog.select().annotate(Entry, Max('pub_date', 'max_pub'))
Note
If the
ForeignKeyField
isnullable
, then aLEFT OUTER
join will be used, otherwise the join is anINNER
join. If anINNER
join is used, in the above example blogs with no entries would not be returned. To avoid this, you can explicitly join before callingannotate()
:>>> Blog.select().join(Entry, 'left outer').annotate(Entry)
- related_model – related
-
aggregate
(aggregation)¶ Parameters: aggregation – a function specifying what aggregation to perform, for example Max('id')
. This can be a 3-tuple if you would like to perform a custom aggregation:("Max", "id", "max_id")
.Method to look at an aggregate of rows using a given function and return a scalar value, such as the count of all rows or the average value of a particular column.
-
group_by
(clause)¶ Parameters: clause – either a single field name or a list of field names, in which case it takes its context from the current query_context. it can also be a model class, in which case all that models fields will be included in the GROUP BY
clauseReturn type: SelectQuery
>>> # get a list of blogs with the count of entries each has >>> sq = Blog.select({ ... Blog: ['*'], ... Entry: [Count('id')] ... }).group_by('id').join(Entry) >>> # slightly more complex, get a list of blogs ordered by most recent pub_date >>> sq = Blog.select({ ... Blog: ['*'], ... Entry: [Max('pub_date', 'max_pub_date')], ... }).join(Entry) >>> # now, group by the entry's blog id, followed by all the blog fields >>> sq = sq.group_by('blog_id').group_by(Blog) >>> # finally, order our results by max pub date >>> sq = sq.order_by(peewee.desc('max_pub_date'))
-
having
(clause)¶ Parameters: clause – Expression to use as the HAVING
clauseReturn type: SelectQuery
>>> sq = Blog.select({ ... Blog: ['*'], ... Entry: [Count('id', 'num_entries')] ... }).group_by('id').join(Entry).having('num_entries > 10')
-
order_by
(*clauses)¶ Parameters: clauses – Expression(s) to use as the ORDER BY
clause, see notes belowReturn type: SelectQuery
Note
Adds the provided clause (a field name or alias) to the query’s
ORDER BY
clause. It can be either a single field name, in which case it will apply to the current query context, or a 2- or 3-tuple.The 2-tuple can be either
(Model, 'field_name')
or('field_name', 'ASC'/'DESC')
.The 3-tuple is
(Model, 'field_name', 'ASC'/'DESC')
.If the field is not found on the model evaluated against, it will be treated as an alias.
example:
>>> sq = Blog.select().order_by('title') >>> sq = Blog.select({ ... Blog: ['*'], ... Entry: [Max('pub_date', 'max_pub')] ... }).join(Entry).order_by(desc('max_pub'))
slightly more complex example:
>>> sq = Entry.select().join(Blog).order_by( ... (Blog, 'title'), # order by blog title ascending ... (Entry, 'pub_date', 'DESC'), # then order by entry pub date desc ... )
check out how the
query context
applies to ordering:>>> blog_title = Blog.select().order_by('title').join(Entry) >>> print blog_title.sql()[0] SELECT t1.* FROM blog AS t1 INNER JOIN entry AS t2 ON t1.id = t2.blog_id ORDER BY t1.title >>> entry_title = Blog.select().join(Entry).order_by('title') >>> print entry_title.sql()[0] SELECT t1.* FROM blog AS t1 INNER JOIN entry AS t2 ON t1.id = t2.blog_id ORDER BY t2.title # <-- note that it's using the title on Entry this time
-
paginate
(page_num, paginate_by=20)¶ Parameters: - page_num – a 1-based page number to use for paginating results
- paginate_by – number of results to return per-page
Return type: applies a
LIMIT
andOFFSET
to the query.>>> Blog.select().order_by('username').paginate(3, 20) # <-- get blogs 41-60
-
distinct
()¶ Return type: SelectQuery
indicates that this query should only return distinct rows. results in a
SELECT DISTINCT
query.
-
execute
()¶ Return type: QueryResultWrapper
Executes the query and returns a
QueryResultWrapper
for iterating over the result set. The results are managed internally by the query and whenever a clause is added that would possibly alter the result set, the query is marked for re-execution.
-
__iter__
()¶ Executes the query:
>>> for user in User.select().where(active=True): ... print user.username
-
UpdateQuery¶
-
class
UpdateQuery
¶ Used for updating rows in the database.
-
__init__
(model, **kwargs)¶ Parameters: - model –
Model
class on which to perform update - kwargs – mapping of field/value pairs containing columns and values to update
>>> uq = UpdateQuery(User, active=False).where(registration_expired=True) >>> print uq.sql() ('UPDATE user SET active=? WHERE registration_expired = ?', [0, True])
>>> atomic_update = UpdateQuery(User, message_count=F('message_count') + 1).where(id=3) >>> print atomic_update.sql() ('UPDATE user SET message_count=(message_count + 1) WHERE id = ?', [3])
- model –
-
where
(*args, **kwargs)¶ Parameters: - args – a list of
Q
orNode
objects - kwargs – a mapping of column + lookup to value, e.g. “age__gt=55”
Return type: a
UpdateQuery
instanceNote
where()
calls are chainable- args – a list of
-
execute
()¶ Return type: Number of rows updated Performs the query
-
DeleteQuery¶
-
class
DeleteQuery
¶ Deletes rows of the given model.
Note
It will not traverse foreign keys or ensure that constraints are obeyed, so use it with care.
-
__init__
(model)¶ creates a
DeleteQuery
instance for the given model:>>> dq = DeleteQuery(User).where(active=False) >>> print dq.sql() ('DELETE FROM user WHERE active = ?', [0])
-
where
(*args, **kwargs)¶ Parameters: - args – a list of
Q
orNode
objects - kwargs – a mapping of column + lookup to value, e.g. “age__gt=55”
Return type: a
DeleteQuery
instanceNote
where()
calls are chainable- args – a list of
-
execute
()¶ Return type: Number of rows deleted Performs the query
-
InsertQuery¶
-
class
InsertQuery
¶ Creates a new row for the given model.
-
__init__
(model, **kwargs)¶ creates an
InsertQuery
instance for the given model where kwargs is a dictionary of field name to value:>>> iq = InsertQuery(User, username='admin', password='test', active=True) >>> print iq.sql() ('INSERT INTO user (username, password, active) VALUES (?, ?, ?)', ['admin', 'test', 1])
-
execute
()¶ Return type: primary key of the new row Performs the query
-
RawQuery¶
-
class
RawQuery
¶ Allows execution of an arbitrary
SELECT
query and returns instances of the model via aQueryResultsWrapper
.-
__init__
(model, query, *params)¶ creates a
RawQuery
instance for the given model which, when executed, will run the given query with the given parameters and return model instances:>>> rq = RawQuery(User, 'SELECT * FROM users WHERE username = ?', 'admin') >>> for obj in rq.execute(): ... print obj <User: admin>
-
execute
()¶ Return type: a QueryResultWrapper
for iterating over the result set. The results are instances of the given model.Performs the query
-