Membuat queryLink to this heading

Sekali anda telah membuat data models 1 anda, Django otomatis memberikan anda pemisahan API yang membuat anda membuat, mengambil, memperbaharui dan menghapus obyek. Dokumen ini menjelaskan bagaimana menggunakan API ini. mengacu pada data model reference 2 untuk rincian penuh dari beragam pilihan pencarian model.

Throughout this guide (and in the reference), we'll refer to the following models, which comprise a blog application:

Python
from datetime import date

from django.db import models


class Blog(models.Model):
    name = models.CharField(max_length=100)
    tagline = models.TextField()

    def __str__(self):
        return self.name


class Author(models.Model):
    name = models.CharField(max_length=200)
    email = models.EmailField()

    def __str__(self):
        return self.name


class Entry(models.Model):
    blog = models.ForeignKey(Blog, on_delete=models.CASCADE)
    headline = models.CharField(max_length=255)
    body_text = models.TextField()
    pub_date = models.DateField()
    mod_date = models.DateField(default=date.today)
    authors = models.ManyToManyField(Author)
    number_of_comments = models.IntegerField(default=0)
    number_of_pingbacks = models.IntegerField(default=0)
    rating = models.IntegerField(default=5)

    def __str__(self):
        return self.headline

Membuat obyekLink to this heading

Untuk mewakili data tabel-basisdata dalam obyek Python, Django menggunakan sistem intuitif: Sebuah kelas model mewakili sebuah tabel basisdata, dan sebuah instance dari kelas itu mewakili rekaman tertentu dalam tabel basisdata.

Untuk membuat sebuah obyek, instansiasi itu menggunakan argumen katakunci pada kelas model, kemudian memanggil save() untuk menyimpan itu ke basisdata.

Dengan asumsi model berada di berkas models.py di dalam aplikasi Django blog, ini adalah sebuah contoh:

Python console
>>> from blog.models import Blog
>>> b = Blog(name="Beatles Blog", tagline="All the latest Beatles news.")
>>> b.save()

Ini melakukan pernyataan SQL INSERT dibelakang layar. Django tidak mengenai basisdata sampai anda secara jelas memanggil save().

Cara save() tidak mempunyai nilai kembalian.

Menyimpan perubahan ke obyekLink to this heading

Untuk menyimpan perubahan ke sebuah obyek yang sudah ada di basisdata gunakan save().

Given a Blog instance b5 that has already been saved to the database, this example changes its name and updates its record in the database:

Python console
>>> b5.name = "New name"
>>> b5.save()

Ini melakukan pernyataan SQL UPDATE dibelakang layar. Django tidak mengenai basisdata sampai anda secara jelas memanggil save().

Menyimpan bidang ForeignKey dan ManyToManyFieldLink to this heading

Updating a ForeignKey field works exactly the same way as saving a normal field -- assign an object of the right type to the field in question. This example updates the blog attribute of an Entry instance entry, assuming appropriate instances of Entry and Blog are already saved to the database (so we can retrieve them below):

Python console
>>> from blog.models import Blog, Entry
>>> entry = Entry.objects.get(pk=1)
>>> cheese_blog = Blog.objects.get(name="Cheddar Talk")
>>> entry.blog = cheese_blog
>>> entry.save()

Updating a ManyToManyField works a little differently -- use the add() method on the field to add a record to the relation. This example adds the Author instance joe to the entry object:

Python console
>>> from blog.models import Author
>>> joe = Author.objects.create(name="Joe")
>>> entry.authors.add(joe)

To add multiple records to a ManyToManyField in one go, include multiple arguments in the call to add(), like this:

Python console
>>> 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)

Django akan mengeluh jika anda mencoba memberikan atau menambahkan sebuah obyek dari jenis salah.

Mengambil obyekLink to this heading

Untuk mengambil obyek-obyek dari basisdata anda, bangun sebuah QuerySet melalui Manager pada kelas model anda.

Sebuah QuerySet mewakili sebuah kumpulan dari ibyek-obyek dari basisdata anda. itu dapat memiliki nol, satu atau banyak penyaring. Penyaring mempersempit hasil permintaan berdasarkan pada parameter yang diberikan. Dalam istilah SQL, QuerySet menyamakan pada pernyataan SELECT, dan penyaring membatasi klausa seperti WHERE atau LIMIT.

You get a QuerySet by using your model's Manager. Each model has at least one Manager, and it's called objects by default. Access it directly via the model class, like so:

Python console
>>> Blog.objects
<django.db.models.manager.Manager object at ...>
>>> b = Blog(name="Foo", tagline="Bar")
>>> b.objects
Traceback:
    ...
AttributeError: "Manager isn't accessible via Blog instances."

The Manager is the main source of querysets for a model. For example, Blog.objects.all() returns a QuerySet that contains all Blog objects in the database.

Mengambil semua obyekLink to this heading

The simplest way to retrieve objects from a table is to get all of them. To do this, use the all() method on a Manager:

Python console
>>> all_entries = Entry.objects.all()

Metode all() mengembalikan semua QuerySet dari semua obyek dalam basisdata.

Mengambil obyek spesifik dengan menyaringLink to this heading

QuerySet dibalikkan oleh all() menggambarkan semua obyek-obyek dalam tabel basisdata. Biasanya, meskipun, anda akan butuh memilih hanya sub kumpulan dari kumpulan lengkap dari obyek.

Untuk membuat semacam sub kumpulan, anda menyaring QuerySet awalan, menambahkan kondisi penyaringan. Dua cara paling umum untuk menyaring QuerySet adalah:

filter(**kwargs)

Mengembalikan QuerySet baru mengandung obyek-obyek yang cocok dari parameter pencarian yang diberikan.

exclude(**kwargs)

Mengembalikan QuerySet baru mengandung obyek-obyek yang tidak cocok dari parameter pencarian yang diberikan.

Parameter pencarian (**kwargs dalam penertian fungsi diatas) harus berupa dalam bentuk digambarkan dalam Field lookups dibawah.

Sebagai contoh, untuk mendapatkan QuerySet dari masukan blog dari tahun 2006, gunakan filter() seperti itu:

Code
Entry.objects.filter(pub_date__year=2006)

Dengan kelas pengelola awalan, itu adalah sama seperti:

Code
Entry.objects.all().filter(pub_date__year=2006)

Menambatkan penyaringanLink to this heading

The result of refining a QuerySet is itself a QuerySet, so it's possible to chain refinements together. For example:

Python console
>>> Entry.objects.filter(headline__startswith="What").exclude(
...     pub_date__gte=datetime.date.today()
... ).filter(pub_date__gte=datetime.date(2005, 1, 30))

Ini mengambil awal QuerySet dari semua masukan dalam basisdata, tambah sebuah penyaring, kemudian sebuah pengecualian, kemudian penyaring lain. Hasil akhir adalah sebuah QuerySet mengandung semua masukan dengan judul yang mulai dengan "What", yang diterbitkan diantara 30 Januari 2005, dan hari saat ini.

Disaring QuerySet adalah unikLink to this heading

Setiap kali anda menyaring sebuah QuerySet, anda mendapatkan QuerySet merek-baru yaitu tidak ada cara mengikat ke QuerySet sebelumnya. Setiap penyaringan membuat QuerySet terpisah dan berbeda yang dapat disimpan, digunakan dan digunakan kembali.

Example:

Python console
>>> q1 = Entry.objects.filter(headline__startswith="What")
>>> q2 = q1.exclude(pub_date__gte=datetime.date.today())
>>> q3 = q1.filter(pub_date__gte=datetime.date.today())

These three querysets are separate. The first is a base QuerySet containing all entries that contain a headline starting with "What". The second is a subset of the first, with an additional criteria that excludes records whose pub_date is today or in the future. The third is a subset of the first, with an additional criteria that selects only the records whose pub_date is today or in the future. The initial QuerySet (q1) is unaffected by the refinement process.

QuerySet adalah lazyLink to this heading

QuerySet objects are lazy -- the act of creating a QuerySet doesn't involve any database activity. You can stack filters together all day long, and Django won't actually run the query until the QuerySet is evaluated. Take a look at this example:

Python console
>>> q = Entry.objects.filter(headline__startswith="What")
>>> q = q.filter(pub_date__lte=datetime.date.today())
>>> q = q.exclude(body_text__icontains="food")
>>> print(q)

Meskipun ini terlihat mengenai basisdata tiga kali, sebenarnya itu mengenai basisdata hanya sekali, pada baris terakhir (print(q)). Secara umum, hasil dari QuerySet tidak diambil dari basisdata sampai anda "meminta" untuk mereka. Ketika anda melakukan, QuerySet dinilai dengan mengakses basisdata. Untuk rincian lebih pada sebenarnya ketika penilaian mengambil tempat, lihat Ketika QuerySet dinilai.

Mengambil obyek tunggal dengan get()Link to this heading

filter() akan selalu memberikan anda QuerySet, bahkan jika hanya obyek tunggal yang cocok permintaan - dalam kasus ini, itu akan berupa QuerySet mengandung unsur tunggal.

If you know there is only one object that matches your query, you can use the get() method on a Manager which returns the object directly:

Python console
>>> one_entry = Entry.objects.get(pk=1)

Anda dapat menggunakan pernyataan permintaan apapun dengan get(), seperti dengan filter() - kembali, lihat Field lookups dibawah.

Catat bahwa ada perbedaan diantara menggunakan get(), dan menggunakan filter() dengan potongan [0]. Jika tidak ada hasil yang cocok dengan permintaan, get() akan memunculkan pengecualian DoesNotExist. Pengecualian ini adalah sebuah atribut dari kelas model yang permintaan sedang dilakukan - jadi dalam kode diatas, jika tidak ada obyek Entry dengan primary key dari 1, Django akan memunculkan Entry.DoesNotExist.

Demikain pula, Django akan mengeluh jika lebih dari satu barang cocok permintaan get(). Dalam kasus ini, itu akan memunculkan MultipleObjectsReturned, yang kembali adalah sebuah atribut dari kelas model itu sendiri.

Cara QuerySet lainLink to this heading

Kebanyakan waktu anda akan gunakan all(), get(), filter() dan exclude() ketika anda butuh mencari obyek-obyek dari basisdata. Bagaimanapun, itu jauh dari semua yang ada; lihat QuerySet API Reference untuk daftar lengkap dari semua ragam metode QuerySet.

Membatasi QuerySetLink to this heading

Gunakan sub kumpulan dari sintaksis memotong-array Python untuk membatasi QuerySet anda pada nomor tertentu dari hasil. Ini adalah setara daro klausa LIMIT dan OFFSET SQL.

For example, this returns the first 5 objects (LIMIT 5):

Python console
>>> Entry.objects.all()[:5]

This returns the sixth through tenth objects (OFFSET 5 LIMIT 5):

Python console
>>> Entry.objects.all()[5:10]

Pengindeksan negatif (yaitu Entry.objects.all()[-1]) tidak didukung.

Generally, slicing a QuerySet returns a new QuerySet -- it doesn't evaluate the query. An exception is if you use the "step" parameter of Python slice syntax. For example, this would actually execute the query in order to return a list of every second object of the first 10:

Python console
>>> Entry.objects.all()[:10:2]

Penyaring atau pengurut lebih lanjut dari irisan queryset dilarang karena sifat ambigu dari bagaimana itu mungkin bekerja.

To retrieve a single object rather than a list (e.g. SELECT foo FROM bar LIMIT 1), use an index instead of a slice. For example, this returns the first Entry in the database, after ordering entries alphabetically by headline:

Python console
>>> Entry.objects.order_by("headline")[0]

This is roughly equivalent to:

Python console
>>> Entry.objects.order_by("headline")[0:1].get()

Catat, bagaimanapun, yang pertama dari ini akan memunculkan IndexError selagi kedua akan memunculkan DoesNotExist jika tidak ada obyek cocok dari kriteria yang diberikan. Lihat get() untuk rincian lebih.

Bidang pencarianLink to this heading

Pencarian bidang adalah bagaimana anda menentukan isi dari sebuah klausa SQL WHERE. Mereka ditentukan sebagai argumen kata kunci pada QuerySet metode metode filter(), exclude() dan get().

Basic lookups keyword arguments take the form field__lookuptype=value. (That's a double-underscore). For example:

Python console
>>> Entry.objects.filter(pub_date__lte="2006-01-01")

terjemahan (kurang lebih) ke dalam SQL berikut:

SQL
SELECT * FROM blog_entry WHERE pub_date <= '2006-01-01';

Bidang ditentukan dalam pencarian harus berupa nama dari bidang model. meskipun ada satu pengecualian, dalam kasus dari ForeignKey anda dapat menentukan nama bidang akhiran dengan _id. Dalam kasus ini, parameter nilai diharapkan mengandung nilai mentah dari foreign primary key model. Sebagai contoh:

Python console
>>> Entry.objects.filter(blog_id=4)

Jika anda melewatkan argumen kata kunci tidak sah, fungsi pencarian akan memunculkan TypeError.

API basisdata mendukung sekitar dua lusin jenis pencarian; acuan lengkap dapat ditemukan dalam field lookup reference 1. Untuk memberikan anda selera dari apa yang tersedia, ini adalah beberapa dari pencarian lebih umum anda mungkin gunakan:

exact

An "exact" match. For example:

Python console
>>> Entry.objects.get(headline__exact="Cat bites dog")

Akan membangkitkan SQL bersama baris ini:

SQL
SELECT ... WHERE headline = 'Cat bites dog';

Jika anda tidak menyediakan jenis pencarian -- yaitu, jika argumen kata kunci anda tidak mengandung garis bawah ganda -- jenis pencarian dianggap tepat.

For example, the following two statements are equivalent:

Python console
>>> Blog.objects.get(id__exact=14)  # Explicit form
>>> Blog.objects.get(id=14)  # __exact is implied

Ini adalah untuk kenyamanan, karena pencarian exact adalah kasus umum.

iexact

A case-insensitive match. So, the query:

Python console
>>> Blog.objects.get(name__iexact="beatles blog")

Akan cocok Blog berjudul "Beatles Blog", "beatles blog", atau bahkan "BeAtlES blOG".

contains

Percobaan penahanan kasus-peka . Sebagai contoh:

Code
Entry.objects.get(headline__contains="Lennon")

Kurang lebih menterjemahkan ke SQL ini:

SQL
SELECT ... WHERE headline LIKE '%Lennon%';

Catat ini akan cocok dengan judul 'Today Lennon honored' tetapi tidak 'today lennon honored'.

Ada juga versi kasus-tidak-peka, icontains.

startswith, endswith

Pencarian mulai-dengan dan berakhir-dengan, masing-masing. Ada juga versi kasus-tidak-peka dipanggil istartswith dan iendswith.

Kembali, ini hanya menggores permukaan. Acuan lengkap dapat ditemukan di field lookup reference 1.

Pencarian yang menjangkau hubunganLink to this heading

Django offers a powerful and intuitive way to "follow" relationships in lookups, taking care of the SQL JOINs for you automatically, behind the scenes. To span a relationship, use the field name of related fields across models, separated by double underscores, until you get to the field you want.

This example retrieves all Entry objects with a Blog whose name is 'Beatles Blog':

Python console
>>> Entry.objects.filter(blog__name="Beatles Blog")

Jangkauan ini dapat sedalam anda sukai.

Itu bekerja kebelakang, juga. Selagi itu can be customized, secara awalan anda mengacu pada hubungan "reverse" dalam pencarian menggunakan nama huruf kecil dari model.

This example retrieves all Blog objects which have at least one Entry whose headline contains 'Lennon':

Python console
>>> Blog.objects.filter(entry__headline__contains="Lennon")

Jika anda menyaring terhadap banyak hubungan dan satu dari model mengengah tidak mempunyai nilai yang memenuhi kondisi penyaring, Django akan memperlakukan itu sebagai jika sebuah kosong (semua nilai adalah NULL), tetapi obyek sah disana. Semua ini berarti bahwa tidak ada kesalahan akan dimunculkan. Sebagi contoh, dalam penyaringan ini:

Code
Blog.objects.filter(entry__authors__name="Lennon")

(jika ada model Author terkait), jika tidak ada author terkait dengan sebuah masukan, itu akan diperlakukan seperti jika tidak ada juga name terlampir, daripada memunculkan kesalahan karena dari author hilang. Biasanya ini adalah tepatnya apa anda ingin miliki terjadi. Kasus satu-satunya dimana itu mungkin membingungkan adalah jika anda menggunakan isnull. Jadi:

Code
Blog.objects.filter(entry__authors__name__isnull=True)

akan mengembalikan obyek Blog yang mempunyai name kosong pada author dan juga itu yang mempunyai author kosong pada entry. Jika anda tidak ingin obyek terakhir itu, anda dapat menulis:

Code
Blog.objects.filter(entry__authors__isnull=False, entry__authors__name__isnull=True)

Membentangkan hubungan banyak-nilaiLink to this heading

When spanning a ManyToManyField or a reverse ForeignKey (such as from Blog to Entry), filtering on multiple attributes raises the question of whether to require each attribute to coincide in the same related object. We might seek blogs that have an entry from 2008 with “Lennon” in its headline, or we might seek blogs that merely have any entry from 2008 as well as some newer or older entry with “Lennon” in its headline.

To select all blogs containing at least one entry from 2008 having "Lennon" in its headline (the same entry satisfying both conditions), we would write:

Code
Blog.objects.filter(entry__headline__contains="Lennon", entry__pub_date__year=2008)

Otherwise, to perform a more permissive query selecting any blogs with merely some entry with "Lennon" in its headline and some entry from 2008, we would write:

Code
Blog.objects.filter(entry__headline__contains="Lennon").filter(
    entry__pub_date__year=2008
)

Suppose there is only one blog that has both entries containing "Lennon" and entries from 2008, but that none of the entries from 2008 contained "Lennon". The first query would not return any blogs, but the second query would return that one blog. (This is because the entries selected by the second filter may or may not be the same as the entries in the first filter. We are filtering the Blog items with each filter statement, not the Entry items.) In short, if each condition needs to match the same related object, then each should be contained in a single filter() call.

Penyaring dapat mengacu bidang pada modelLink to this heading

Dalam contoh yang diberikan sejauh ini, kami telah membangun berkas-berkas penyaring yang membandingkan nilai dari bidang model dengan ketetapan. Tetapi apa jika anda ingin membandingkan nilai dai bidang model dengan bidang lain pada model sama?

Django menyediakan F expressions untuk mengizinkan perbandingan. Instance dari F() bertindak sebagai sebuah acuan pada model dalam permintaan. Acuan ini kemudian dapat digunakan dalam penyaring permintaan untuk membandingkan nilai-nilai dari dua bidang berbeda pada instance model sama.

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:

Python console
>>> from django.db.models import F
>>> Entry.objects.filter(number_of_comments__gt=F("number_of_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:

Python console
>>> Entry.objects.filter(number_of_comments__gt=F("number_of_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:

Python console
>>> Entry.objects.filter(rating__lt=F("number_of_comments") + F("number_of_pingbacks"))

You can also use the double underscore notation to span relationships in an F() object. An F() object with a double underscore will introduce any joins needed to access the related object. For example, to retrieve all the entries where the author's name is the same as the blog name, we could issue the query:

Python console
>>> Entry.objects.filter(authors__name=F("blog__name"))

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:

Python console
>>> from datetime import timedelta
>>> Entry.objects.filter(mod_date__gt=F("pub_date") + timedelta(days=3))

The F() objects support bitwise operations by .bitand(), .bitor(), .bitxor(), .bitrightshift(), and .bitleftshift(). For example:

Python console
>>> F("somefield").bitand(16)

Expressions can reference transformsLink to this heading

Django supports using transforms in expressions.

For example, to find all Entry objects published in the same year as they were last modified:

Python console
>>> from django.db.models import F
>>> Entry.objects.filter(pub_date__year=F("mod_date__year"))

To find the earliest year an entry was published, we can issue the query:

Python console
>>> from django.db.models import Min
>>> Entry.objects.aggregate(first_published_year=Min("pub_date__year"))

This example finds the value of the highest rated entry and the total number of comments on all entries for each year:

Python console
>>> from django.db.models import OuterRef, Subquery, Sum
>>> Entry.objects.values("pub_date__year").annotate(
...     top_rating=Subquery(
...         Entry.objects.filter(
...             pub_date__year=OuterRef("pub_date__year"),
...         )
...         .order_by("-rating")
...         .values("rating")[:1]
...     ),
...     total_comments=Sum("number_of_comments"),
... )

Jalan pintas pencarian pkLink to this heading

Untuk kemudahan, Django menyediakan jalan pintas pencarian pk, yang berdiri untuk "primary key".

In the example Blog model, the primary key is the id field, so these three statements are equivalent:

Python console
>>> Blog.objects.get(id__exact=14)  # Explicit form
>>> Blog.objects.get(id=14)  # __exact is implied
>>> Blog.objects.get(pk=14)  # pk implies id__exact

The use of pk isn't limited to __exact queries -- any query term can be combined with pk to perform a query on the primary key of a model:

Python console
# Get blogs entries with id 1, 4 and 7
>>> Blog.objects.filter(pk__in=[1, 4, 7])

# Get all blog entries with id > 14
>>> Blog.objects.filter(pk__gt=14)

pk lookups also work across joins. For example, these three statements are equivalent:

Python console
>>> Entry.objects.filter(blog__id__exact=3)  # Explicit form
>>> Entry.objects.filter(blog__id=3)  # __exact is implied
>>> Entry.objects.filter(blog__pk=3)  # __pk implies __id__exact

Meloloskan tanda persen dan garis bawah dalam pernyataan LIKELink to this heading

Pencarian bidang yang menyerupai pernyataan SQL LIKE (iexact, contains, icontains, startswith, istartswith, endswith dan iendswith) akan otomatis meloloskan dua karakter khusus digunakan dalam pernyataan LIKE -- tanda persen dan garis bawah. (Dalam sebuah pernyataan Like, tanda persen menandakan wildcard banyak-karakter dan garis bawah menandakan wildcard karakter-tunggal.)

This means things should work intuitively, so the abstraction doesn't leak. For example, to retrieve all the entries that contain a percent sign, use the percent sign as any other character:

Python console
>>> Entry.objects.filter(headline__contains="%")

Django menangani dari pengutipan untuk anda; menghasilkan SQL akan mencari sesuatu seperti ini:

SQL
SELECT ... WHERE headline LIKE '%\%%';

Sama seperti garis bawah. Kedua tanda persen dan garis bawag ditangani untuk anda secara transparan.

Cache dan QuerySetLink to this heading

Setiap QuerySet mengandung sebuah tembolok untuk meminimalkan akses basisdata. Pahami bagaimana dia bekerja akan mengizinkan anda menulis kode paling efisien.

Dalam QuerySet baru dibuat, cache kosong. Pertama kali sebuah QuerySet dinilai -- dan, karena itu, sebuah permintaan basisdata terjadi -- Django menyimpan hasil permintaan dalam cache QuerySet dan mengembalikan hasil yang telah secara jelas diminta (sebagai contoh, unsur selanjutnya, jika ada QuerySet sedang diulang). Penilaian selanjutnya dari QuerySet menggunakan hasil ter cache.

Keep this caching behavior in mind, because it may bite you if you don't use your QuerySets correctly. For example, the following will create two QuerySets, evaluate them, and throw them away:

Python console
>>> print([e.headline for e in Entry.objects.all()])
>>> print([e.pub_date for e in Entry.objects.all()])

Itu berarti permintaan absisdata sama akan dijalankan dua kali, berhasil menggandakan muatan basisdata anda. Juga, ada kemungkinan dua daftar mungkin tidak meneyrtakan rekaman basisdata sama, karena Entry telah ditambahkan atau dihapus dalam pembagian kedua diantara dua permintaan.

To avoid this problem, save the QuerySet and reuse it:

Python console
>>> queryset = Entry.objects.all()
>>> print([p.headline for p in queryset])  # Evaluate the query set.
>>> print([p.pub_date for p in queryset])  # Reuse the cache from the evaluation.

Ketika QuerySet tidak di cacheLink to this heading

Queryset tidak selalu cache hasil mereka. Ketika menilai hanya bagian dari queryset, cache diperiksa, tetapi jika tidak dikumpulkan kemudian barang-barang dikembalikan oleh permintaan selanjutnya tidak di cache. Secara khusus, ini berarti bahwa limiting the queryset 1 menggunakan potongan senarai atau sebuah indeks tidak akan dikumpulkan cache.

For example, repeatedly getting a certain index in a queryset object will query the database each time:

Python console
>>> queryset = Entry.objects.all()
>>> print(queryset[5])  # Queries the database
>>> print(queryset[5])  # Queries the database again

However, if the entire queryset has already been evaluated, the cache will be checked instead:

Python console
>>> queryset = Entry.objects.all()
>>> [entry for entry in queryset]  # Queries the database
>>> print(queryset[5])  # Uses cache
>>> print(queryset[5])  # Uses cache

Here are some examples of other actions that will result in the entire queryset being evaluated and therefore populate the cache:

Python console
>>> [entry for entry in queryset]
>>> bool(queryset)
>>> entry in queryset
>>> list(queryset)

Asynchronous queriesLink to this heading

If you are writing asynchronous views or code, you cannot use the ORM for queries in quite the way we have described above, as you cannot call blocking synchronous code from asynchronous code - it will block up the event loop (or, more likely, Django will notice and raise a SynchronousOnlyOperation to stop that from happening).

Fortunately, you can do many queries using Django's asynchronous query APIs. Every method that might block - such as get() or delete() - has an asynchronous variant (aget() or adelete()), and when you iterate over results, you can use asynchronous iteration (async for) instead.

Query iterationLink to this heading

The default way of iterating over a query - with for - will result in a blocking database query behind the scenes as Django loads the results at iteration time. To fix this, you can swap to async for:

Code
async for entry in Authors.objects.filter(name__startswith="A"):
    ...

Be aware that you also can't do other things that might iterate over the queryset, such as wrapping list() around it to force its evaluation (you can use async for in a comprehension, if you want it).

Because QuerySet methods like filter() and exclude() do not actually run the query - they set up the queryset to run when it's iterated over - you can use those freely in asynchronous code. For a guide to which methods can keep being used like this, and which have asynchronous versions, read the next section.

QuerySet and manager methodsLink to this heading

Some methods on managers and querysets - like get() and first() - force execution of the queryset and are blocking. Some, like filter() and exclude(), don't force execution and so are safe to run from asynchronous code. But how are you supposed to tell the difference?

While you could poke around and see if there is an a-prefixed version of the method (for example, we have aget() but not afilter()), there is a more logical way - look up what kind of method it is in the QuerySet reference.

In there, you'll find the methods on QuerySets grouped into two sections:

  • Methods that return new querysets: These are the non-blocking ones, and don't have asynchronous versions. You're free to use these in any situation, though read the notes on defer() and only() before you use them.

  • Methods that do not return querysets: These are the blocking ones, and have asynchronous versions - the asynchronous name for each is noted in its documentation, though our standard pattern is to add an a prefix.

Using this distinction, you can work out when you need to use asynchronous versions, and when you don't. For example, here's a valid asynchronous query:

Code
user = await User.objects.filter(username=my_input).afirst()

filter() returns a queryset, and so it's fine to keep chaining it inside an asynchronous environment, whereas first() evaluates and returns a model instance - thus, we change to afirst(), and use await at the front of the whole expression in order to call it in an asynchronous-friendly way.

TransaksiLink to this heading

Transactions are not currently supported with asynchronous queries and updates. You will find that trying to use one raises SynchronousOnlyOperation.

If you wish to use a transaction, we suggest you write your ORM code inside a separate, synchronous function and then call that using sync_to_async - see Dukungan asinkronus for more.

Meminta JSONFieldLink to this heading

Lookups implementation is different in JSONField, mainly due to the existence of key transformations. To demonstrate, we will use the following example model:

Code
from django.db import models


class Dog(models.Model):
    name = models.CharField(max_length=200)
    data = models.JSONField(null=True)

    def __str__(self):
        return self.name

Menyimpan dan meminta untuk NoneLink to this heading

As with other fields, storing None as the field's value will store it as SQL NULL. While not recommended, it is possible to store JSON scalar null instead of SQL NULL by using Value(None, JSONField()).

Whichever of the values is stored, when retrieved from the database, the Python representation of the JSON scalar null is the same as SQL NULL, i.e. None. Therefore, it can be hard to distinguish between them.

This only applies to None as the top-level value of the field. If None is inside a list or dict, it will always be interpreted as JSON null.

When querying, None value will always be interpreted as JSON null. To query for SQL NULL, use isnull:

Python console
>>> Dog.objects.create(name="Max", data=None)  # SQL NULL.
<Dog: Max>
>>> Dog.objects.create(name="Archie", data=Value(None, JSONField()))  # JSON null.
<Dog: Archie>
>>> Dog.objects.filter(data=None)
<QuerySet [<Dog: Archie>]>
>>> Dog.objects.filter(data=Value(None, JSONField()))
<QuerySet [<Dog: Archie>]>
>>> Dog.objects.filter(data__isnull=True)
<QuerySet [<Dog: Max>]>
>>> Dog.objects.filter(data__isnull=False)
<QuerySet [<Dog: Archie>]>

Unless you are sure you wish to work with SQL NULL values, consider setting null=False and providing a suitable default for empty values, such as default=dict.

Key, index, and path transformsLink to this heading

To query based on a given dictionary key, use that key as the lookup name:

Python console
>>> Dog.objects.create(
...     name="Rufus",
...     data={
...         "breed": "labrador",
...         "owner": {
...             "name": "Bob",
...             "other_pets": [
...                 {
...                     "name": "Fishy",
...                 }
...             ],
...         },
...     },
... )
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": None})
<Dog: Meg>
>>> Dog.objects.filter(data__breed="collie")
<QuerySet [<Dog: Meg>]>

Multiple keys can be chained together to form a path lookup:

Python console
>>> Dog.objects.filter(data__owner__name="Bob")
<QuerySet [<Dog: Rufus>]>

If the key is an integer, it will be interpreted as an index transform in an array:

Python console
>>> Dog.objects.filter(data__owner__other_pets__0__name="Fishy")
<QuerySet [<Dog: Rufus>]>

If the key you wish to query by clashes with the name of another lookup, use the contains lookup instead.

To query for missing keys, use the isnull lookup:

Python console
>>> Dog.objects.create(name="Shep", data={"breed": "collie"})
<Dog: Shep>
>>> Dog.objects.filter(data__owner__isnull=True)
<QuerySet [<Dog: Shep>]>

KT() expressionsLink to this heading

class KT(lookup)Link to this definition

Represents the text value of a key, index, or path transform of JSONField. You can use the double underscore notation in lookup to chain dictionary key and index transforms.

Sebagai contoh:

Python console
>>> from django.db.models.fields.json import KT
>>> Dog.objects.create(
...     name="Shep",
...     data={
...         "owner": {"name": "Bob"},
...         "breed": ["collie", "lhasa apso"],
...     },
... )
<Dog: Shep>
>>> Dog.objects.annotate(
...     first_breed=KT("data__breed__1"), owner_name=KT("data__owner__name")
... ).filter(first_breed__startswith="lhasa", owner_name="Bob")
<QuerySet [<Dog: Shep>]>

Containment and key lookupsLink to this heading

containsLink to this heading

The contains lookup is overridden on JSONField. The returned objects are those where the given dict of key-value pairs are all contained in the top-level of the field. For example:

Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
<Dog: Meg>
>>> Dog.objects.create(name="Fred", data={})
<Dog: Fred>
>>> Dog.objects.create(
...     name="Merry", data={"breed": "pekingese", "tricks": ["fetch", "dance"]}
... )
>>> Dog.objects.filter(data__contains={"owner": "Bob"})
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>
>>> Dog.objects.filter(data__contains={"breed": "collie"})
<QuerySet [<Dog: Meg>]>
>>> Dog.objects.filter(data__contains={"tricks": ["dance"]})
<QuerySet [<Dog: Merry>]>

contained_byLink to this heading

This is the inverse of the contains lookup - the objects returned will be those where the key-value pairs on the object are a subset of those in the value passed. For example:

Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
<Dog: Meg>
>>> Dog.objects.create(name="Fred", data={})
<Dog: Fred>
>>> Dog.objects.create(
...     name="Merry", data={"breed": "pekingese", "tricks": ["fetch", "dance"]}
... )
>>> Dog.objects.filter(data__contained_by={"breed": "collie", "owner": "Bob"})
<QuerySet [<Dog: Meg>, <Dog: Fred>]>
>>> Dog.objects.filter(data__contained_by={"breed": "collie"})
<QuerySet [<Dog: Fred>]>
>>> Dog.objects.filter(
...     data__contained_by={"breed": "pekingese", "tricks": ["dance", "fetch", "hug"]}
... )
<QuerySet [<Dog: Merry>, <Dog: Fred>]>

has_keyLink to this heading

Returns objects where the given key is in the top-level of the data. For example:

Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
<Dog: Meg>
>>> Dog.objects.filter(data__has_key="owner")
<QuerySet [<Dog: Meg>]>

has_keysLink to this heading

Returns objects where all of the given keys are in the top-level of the data. For example:

Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
<Dog: Meg>
>>> Dog.objects.filter(data__has_keys=["breed", "owner"])
<QuerySet [<Dog: Meg>]>

has_any_keysLink to this heading

Returns objects where any of the given keys are in the top-level of the data. For example:

Python console
>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
<Dog: Rufus>
>>> Dog.objects.create(name="Meg", data={"owner": "Bob"})
<Dog: Meg>
>>> Dog.objects.filter(data__has_any_keys=["owner", "breed"])
<QuerySet [<Dog: Rufus>, <Dog: Meg>]>

Pencarian rumit dengan obyek QLink to this heading

Permintaan argumen katakunci -- dalam filter(), dll. -- adalah "AND" bersama-sama. Jika anda buth menjalankan permintaan lebih rumit (sebagai contoh, permintaan dengan pernyataan OR), anda dapat menggunakan Q objects.

Q object (django.db.models.Q) adalah sebuah obyek digunakan untuk membungkus koleksi dari argumen katakunci. Argumen katakunci ini ditentukan seperti dalam "Pencarian bidang" diatas.

Sebagai contoh, obyek Q ini membungkus permintaan LIKE tunggal:

Code
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.

Sebagai contoh, pernyataan ini menghasilkan obyek Q tunggal yang mewakili "OR" atau dua permintaan "question__startswith"

Code
Q(question__startswith="Who") | Q(question__startswith="What")

This is equivalent to the following SQL WHERE clause:

SQL
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:

Code
Q(question__startswith="Who") | ~Q(pub_date__year=2005)

Setiap fungsi pencarian yang mengambil argumen-kata kunci (sebagai contoh filter(), exclude(), get()) dapat juga melewatkan satu atau lebih obyek Q sebagai argumen (tidak-dinamai) kedudukan. Jika anda menyediakan banyak argumen obyek Q pada fungsi pencarian, argumen akan di "AND"kan bersama-sama. Sebagai contoh:

Code
Poll.objects.get(
    Q(question__startswith="Who"),
    Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)),
)

... kurang lebih diterjemahkan kedalam SQL:

SQL
SELECT * from polls WHERE question LIKE 'Who%'
    AND (pub_date = '2005-05-02' OR pub_date = '2005-05-06')

Fungsi pencarian dapat mencampurkan penggunaan obyek Q dan argumen kata kunci. Semua argumen disediakan untuk fungsi pencarian (menjadi mereka argumen kata kunci atau obyek Q) di "AND"kan bersama-sama. Bagaimanapun, jika obyek Q disediakan, dia harus mendahului pengertian dari argumen kata kunci apapun. Sebagai contoh:

Code
Poll.objects.get(
    Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)),
    question__startswith="Who",
)

... akan menjadi permintaan sah, sama pada contoh sebelumnya; tetapi:

Code
# INVALID QUERY
Poll.objects.get(
    question__startswith="Who",
    Q(pub_date=date(2005, 5, 2)) | Q(pub_date=date(2005, 5, 6)),
)

... tidak akan menjadi sah.

Membandingkan obyekLink to this heading

To compare two model instances, use the standard Python comparison operator, the double equals sign: ==. Behind the scenes, that compares the primary key values of two models.

Using the Entry example above, the following two statements are equivalent:

Python console
>>> some_entry == other_entry
>>> some_entry.id == other_entry.id

If a model's primary key isn't called id, no problem. Comparisons will always use the primary key, whatever it's called. For example, if a model's primary key field is called name, these two statements are equivalent:

Python console
>>> some_obj == other_obj
>>> some_obj.name == other_obj.name

menghapus obyekLink to this heading

The delete method, conveniently, is named delete(). This method immediately deletes the object and returns the number of objects deleted and a dictionary with the number of deletions per object type. Example:

Python console
>>> e.delete()
(1, {'blog.Entry': 1})

Anda dapat juga menghapus obyek dalam jumlah besar. Setiap QuerySet mempunyai sebuah delete() method, yang menghapus semua anggota dari QuerySet tersebut.

For example, this deletes all Entry objects with a pub_date year of 2005:

Python console
>>> Entry.objects.filter(pub_date__year=2005).delete()
(5, {'webapp.Entry': 5})

Ingat bahwa ini akan, ketika memungkinkan, akan dijalankan murni dalam SQL, dan juga cara delete() dari instance tidak akan perlu dipanggil selama pengolahan. Jika anda telah menyediakan cara delete() disesuaikan pada sebuah kelas model dan ingin memastikan bahwa dia dipanggil, anda akan butuh "secara manual" menghapus instance dari model tersebut (sebagai contoh, dengan perulangan terhadap QuerySet dan memanggil delete() pada setiap obyek secara tersendiri) daripada menggunakan dalam jumlah besar cara delete() dari sebuah QuerySet.

Ketika DJANGO menghapus sebuah obyek, secara awal dia meniru kebiasaan batasan SQL ON DELETE CASCADE -- dalam kata lain, obyek apapun yang mempunyai foreign key menunjuk pada obyek yang akan dihapus akan dihapus bersama dengannya. Sebagai contoh:

Code
b = Blog.objects.get(pk=1)
# This will delete the Blog and all of its Entry objects.
b.delete()

Kebiasaan turunan ini dapat di sesuaikan melalui argumen on_delete ke ForeignKey.

Catat bahwa delete() adalah hanya cara QuerySet yang tidak ditunjukkan pada Manager itu sendiri. Ini adalah mekanisme aman untuk mencegah anda dari kecelakaan permintaan Entry.objects.delete(), dan menghapus semua masukan. Jika anda ingin melakukan menghapus semua obyek, kemudian anda harus secara jelas meminta kumpulan permintaan lengkap:

Code
Entry.objects.all().delete()

Menyalin instance modelLink to this heading

Although there is no built-in method for copying model instances, it is possible to easily create new instance with all fields' values copied. In the simplest case, you can set pk to None and _state.adding to True. Using our blog example:

Code
blog = Blog(name="My blog", tagline="Blogging is easy")
blog.save()  # blog.pk == 1

blog.pk = None
blog._state.adding = True
blog.save()  # blog.pk == 2

Hal-hal dapat lebih rumit jika anda menggunakan warisan. Pertimbangkan subkelas dari Blog:

Code
class ThemeBlog(Blog):
    theme = models.CharField(max_length=200)


django_blog = ThemeBlog(name="Django", tagline="Django is easy", theme="python")
django_blog.save()  # django_blog.pk == 3

Due to how inheritance works, you have to set both pk and id to None, and _state.adding to True:

Code
django_blog.pk = None
django_blog.id = None
django_blog._state.adding = True
django_blog.save()  # django_blog.pk == 4

Pengolahan ini tidak menyalin hubungan yang bukan bagian dari tabel basisdata model. Sebagai contoh, Entry mempunyai ManyToManyField terhadap Author. Setelah menggandakan sebuah masukan, anda harus menyetel hubungan many-to-many untuk masukan baru:

Code
entry = Entry.objects.all()[0]  # some previous entry
old_authors = entry.authors.all()
entry.pk = None
entry._state.adding = True
entry.save()
entry.authors.set(old_authors)

Untuk OneToOneField, anda harus menggandakan obyek terkait dan memberikan itu ke bidang obyek baru untuk menghindari melanggar batasan untuk one-to-one. Sebagai contoh, menganggap entry sudah digandakan seperti diatas:

Code
detail = EntryDetail.objects.all()[0]
detail.pk = None
detail._state.adding = True
detail.entry = entry
detail.save()

Memperbaharui banyak obyek sekaligusLink to this heading

Terkadang anda ingin menyetel sebuah bidang ke nilai tertentu untuk semua obyek dalam QuerySet. Anda dapat melakukan ini dengan cara update(). Sebagai contoh:

Code
# Update all the headlines with pub_date in 2007.
Entry.objects.filter(pub_date__year=2007).update(headline="Everything is the same")

You can only set non-relation fields and ForeignKey fields using this method. To update a non-relation field, provide the new value as a constant. To update ForeignKey fields, set the new value to be the new model instance you want to point to. For example:

Python console
>>> b = Blog.objects.get(pk=1)

# Change every Entry so that it belongs to this Blog.
>>> Entry.objects.update(blog=b)

The update() method is applied instantly and returns the number of rows matched by the query (which may not be equal to the number of rows updated if some rows already have the new value). The only restriction on the QuerySet being updated is that it can only access one database table: the model's main table. You can filter based on related fields, but you can only update columns in the model's main table. Example:

Python console
>>> b = Blog.objects.get(pk=1)

# Update all the headlines belonging to this Blog.
>>> Entry.objects.filter(blog=b).update(headline="Everything is the same")

Be aware that the update() method is converted directly to an SQL statement. It is a bulk operation for direct updates. It doesn't run any save() methods on your models, or emit the pre_save or post_save signals (which are a consequence of calling save()), or honor the auto_now field option. If you want to save every item in a QuerySet and make sure that the save() method is called on each instance, you don't need any special function to handle that. Loop over them and call save():

Code
for item in my_queryset:
    item.save()

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:

Python console
>>> Entry.objects.update(number_of_pingbacks=F("number_of_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:

Python console
# This will raise a FieldError
>>> Entry.objects.update(headline=F("blog__name"))

Kembali ke mentah SQLLink to this heading

Jika anda menemukan anda sendiri butuh menulis permintaan SQL yang terlalu rumit untuk pemetaan-basisdata Django untuk ditangani, anda dapat kembali menulis SQL dengan tangan. Django mempunyai sepasang pilihan untuk menulis permintaan SQL mentah; lihat Melakukan permintaan SQL mentah.

Akhirnya, itu penting dicatat bahwa lapisan basisdata Django hanya antarmuka ke basisdata anda. Anda dapat mengakses basisdata anda melalui alat-alat lain, bahasa pemrograman atau kerangka basisdata; tidak ada spesifik-Django tentang basisdata anda.