本节内容html
学员管理系统练习python
Django ORM操做进阶sql
用户认证express
带着项目需求学习是最有趣和效率最高的,今天就来基于下面的需求来继续学习Django django
项目需求:app
1.分讲师\学员\课程顾问角色,
2.学员能够属于多个班级,学员成绩按课程分别统计
3.每一个班级至少包含一个或多个讲师
4.一个学员要有状态转化的过程 ,好比未报名前,报名后,毕业老学员
5.客户要有咨询纪录, 后续的按期跟踪纪录也要保存
6.每一个学员的全部上课出勤状况\学习成绩都要保存
7.学校能够有分校区,默认每一个校区的员工只能查看和管理本身校区的学员
8.客户咨询要区分来源
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>>>
from
blog.models
import
Blog
>>> b
=
Blog(name
=
'Beatles Blog'
, tagline
=
'All the latest Beatles news.'
)
>>> b.save()
|
This performs an INSERT
SQL statement behind the scenes. Django doesn’t hit the database until you explicitly call save()
.less
The save()
method has no return value.ide
ForeignKey的关联
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>>>
from
blog.models
import
Entry
>>> entry
=
Entry.objects.get(pk
=
1
)
>>> cheese_blog
=
Blog.objects.get(name
=
"Cheddar Talk"
)
>>> entry.blog
=
cheese_blog
>>> entry.save()
|
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>>>
from
blog.models
import
Author
>>> joe
=
Author.objects.create(name
=
"Joe"
)
>>> entry.authors.add(joe)
|
添加多个ManyToMany对象学习
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>>> john
=
Author.objects.create(name
=
"John"
)
>>> paul
=
Author.objects.create(name
=
"Paul"
)
>>> george
=
Author.objects.create(name
=
"George"
)
>>> ringo
=
Author.objects.create(name
=
"Ringo"
)
>>> entry.authors.add(john, paul, george, ringo)
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1 all_entries = Entry.objects.all() #查询全部 2 Entry.objects.filter(pub_date__year=2006) #查询全部pub_date为2006年的纪录 3 Entry.objects.all().filter(pub_date__year=2006) #与上面那句同样 4 >>> Entry.objects.filter( #链式查询 5 ... headline__startswith='What' 6 ... ).exclude( 7 ... pub_date__gte=datetime.date.today() 8 ... ).filter( 9 ... pub_date__gte=datetime(2005, 1, 30) 10 ... ) 11 12 one_entry = Entry.objects.get(pk=1) #单条查询 13 14 Entry.objects.all()[:5] #查询前5条 15 Entry.objects.all()[5:10] #你猜 16 17 Entry.objects.order_by('headline')[0] #按headline排序取第一条 18 19 Entry.objects.filter(pub_date__lte='2006-01-01') #至关于sql语句SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01'; 20 21 Entry.objects.get(headline__exact="Cat bites dog") #至关于SELECT ... WHERE headline = 'Cat bites dog'; 22 Blog.objects.get(name__iexact="beatles blog") #与上面相同,只是大小写不敏感 23 24 Entry.objects.get(headline__contains='Lennon') #至关 于SELECT ... WHERE headline LIKE '%Lennon%';
#This example retrieves all Entry objects with a Blog whose name is 'Beatles Blog': Entry.objects.filter(blog__name='Beatles Blog') Blog.objects.filter(entry__headline__contains='Lennon')
对同一表内不一样的字段进行对比查询,In the examples given so far, we have constructed filters that compare the value of a model field with a constant. But what if you want to compare the value of a model field with another field on the same model?ui
Django provides F expressions
to allow such comparisons. Instances of F()
act as a reference to a model field within a query. These references can then be used in query filters to compare the values of two different fields on the same model instance.
For example, to find a list of all blog entries that have had more comments than pingbacks, we construct an F()
object to reference the pingback count, and use that F()
object in the query:
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>>>
from
django.db.models
import
F
>>> Entry.objects.
filter
(n_comments__gt
=
F(
'n_pingbacks'
))
|
Django supports the use of addition, subtraction, multiplication, division, modulo, and power arithmetic with F()
objects, both with constants and with other F()
objects. To find all the blog entries with more than twice as many comments as pingbacks, we modify the query:
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|
>>> Entry.objects.
filter
(n_comments__gt
=
F(
'n_pingbacks'
)
*
2
)
|
To find all the entries where the rating of the entry is less than the sum of the pingback count and comment count, we would issue the query:
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|
>>> Entry.objects.
filter
(rating__lt
=
F(
'n_comments'
)
+
F(
'n_pingbacks'
))
|
For date and date/time fields, you can add or subtract a timedelta
object. The following would return all entries that were modified more than 3 days after they were published:
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>>>
from
datetime
import
timedelta
>>> Entry.objects.
filter
(mod_date__gt
=
F(
'pub_date'
)
+
timedelta(days
=
3
))
|
QuerySet
sEach QuerySet
contains a cache to minimize database access. Understanding how it works will allow you to write the most efficient code.
In a newly created QuerySet
, the cache is empty. The first time a QuerySet
is evaluated – and, hence, a database query happens – Django saves the query results in the QuerySet
’s cache and returns the results that have been explicitly requested (e.g., the next element, if the QuerySet
is being iterated over). Subsequent evaluations of the QuerySet
reuse the cached results.
Keep this caching behavior in mind, because it may bite you if you don’t use your QuerySet
s correctly. For example, the following will create two QuerySet
s, evaluate them, and throw them away:
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>>>
print
([e.headline
for
e
in
Entry.objects.
all
()])
>>>
print
([e.pub_date
for
e
in
Entry.objects.
all
()])
|
That means the same database query will be executed twice, effectively doubling your database load. Also, there’s a possibility the two lists may not include the same database records, because an Entry
may have been added or deleted in the split second between the two requests.
To avoid this problem, simply save the QuerySet
and reuse it:
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>>> queryset
=
Entry.objects.
all
()
>>>
print
([p.headline
for
p
in
queryset])
# Evaluate the query set.
>>>
print
([p.pub_date
for
p
in
queryset])
# Re-use the cache from the evaluation.
|
QuerySet
s are not cached¶Querysets do not always cache their results. When evaluating only part of the queryset, the cache is checked, but if it is not populated then the items returned by the subsequent query are not cached. Specifically, this means that limiting the querysetusing an array slice or an index will not populate the cache.
For example, repeatedly getting a certain index in a queryset object will query the database each time:
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>>> queryset
=
Entry.objects.
all
()
>>>
print
queryset[
5
]
# Queries the database
>>>
print
queryset[
5
]
# Queries the database again
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However, if the entire queryset has already been evaluated, the cache will be checked instead:
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>>> queryset
=
Entry.objects.
all
()
>>> [entry
for
entry
in
queryset]
# Queries the database
>>>
print
queryset[
5
]
# Uses cache
>>>
print
queryset[
5
]
# Uses cache
|
Q
objects(复杂查询)filter()
, etc. – are “AND”ed together. If you need to execute more complex queries (for example, queries with OR
statements), you can use Q objects
.A Q object
(django.db.models.Q
) is an object used to encapsulate a collection of keyword arguments. These keyword arguments are specified as in “Field lookups” above.
For example, this Q
object encapsulates a single LIKE
query:
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from
django.db.models
import
Q
Q(question__startswith
=
'What'
)
|
Q
objects can be combined using the &
and |
operators. When an operator is used on two Q
objects, it yields a new Q
object.
For example, this statement yields a single Q
object that represents the “OR” of two "question__startswith"
queries:
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|
Q(question__startswith
=
'Who'
) | Q(question__startswith
=
'What'
)
|
This is equivalent to the following SQL WHERE
clause:
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|
WHERE
question
LIKE
'Who%'
OR
question
LIKE
'What%'
|
You can compose statements of arbitrary complexity by combining Q
objects with the &
and |
operators and use parenthetical grouping. Also, Q
objects can be negated using the ~
operator, allowing for combined lookups that combine both a normal query and a negated (NOT
) query:
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|
Q(question__startswith
=
'Who'
) | ~Q(pub_date__year
=
2005
)
|
Each lookup function that takes keyword-arguments (e.g. filter()
, exclude()
, get()
) can also be passed one or more Q
objects as positional (not-named) arguments. If you provide multiple Q
object arguments to a lookup function, the arguments will be “AND”ed together. For example:
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Poll.objects.get(
Q(question__startswith
=
'Who'
),
Q(pub_date
=
date(
2005
,
5
,
2
)) | Q(pub_date
=
date(
2005
,
5
,
6
))
)
|
... roughly translates into the SQL:
SELECT * from polls WHERE question LIKE 'Who%' AND (pub_date = '2005-05-02' OR pub_date = '2005-05-06')
Lookup functions can mix the use of Q
objects and keyword arguments. All arguments provided to a lookup function (be they keyword arguments or Q
objects) are “AND”ed together. However, if a Q
object is provided, it must precede the definition of any keyword arguments. For example:
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Poll.objects.get(
Q(pub_date
=
date(
2005
,
5
,
2
)) | Q(pub_date
=
date(
2005
,
5
,
6
)),
question__startswith
=
'Who'
)
|
... would be a valid query, equivalent to the previous example; but:
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# INVALID QUERY
Poll.objects.get(
question__startswith
=
'Who'
,
Q(pub_date
=
date(
2005
,
5
,
2
)) | Q(pub_date
=
date(
2005
,
5
,
6
)))
|
... would not be valid.
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# Update all the headlines with pub_date in 2007.
Entry.objects.
filter
(pub_date__year
=
2007
).update(headline
=
'Everything is the same'
)
|
Calls to update can also use F expressions
to update one field based on the value of another field in the model. This is especially useful for incrementing counters based upon their current value. For example, to increment the pingback count for every entry in the blog:
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|
>>> Entry.objects.
all
().update(n_pingbacks
=
F(
'n_pingbacks'
)
+
1
)
|
However, unlike F()
objects in filter and exclude clauses, you can’t introduce joins when you use F()
objects in an update – you can only reference fields local to the model being updated. If you attempt to introduce a join with an F()
object, a FieldError
will be raised:
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# THIS WILL RAISE A FieldError
>>> Entry.objects.update(headline
=
F(
'blog__name'
))
|
更多聚合查询例子:https://docs.djangoproject.com/en/1.9/topics/db/aggregation/
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from
django.contrib.auth
import
authenticate
user
=
authenticate(username
=
'john'
, password
=
'secret'
)
if
user
is
not
None
:
# the password verified for the user
if
user.is_active:
print
(
"User is valid, active and authenticated"
)
else
:
print
(
"The password is valid, but the account has been disabled!"
)
else
:
# the authentication system was unable to verify the username and password
print
(
"The username and password were incorrect."
)
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from
django.contrib.auth
import
logout
def
logout_view(request):
logout(request)
# Redirect to a success page.
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-----from old boy