{"title":"Pencarian teks penuh","version":"3.2","locale":"id","docname":"ref/contrib/postgres/search","url":"/id/3.2/ref/contrib/postgres/search/","canonical":"https://djangodocs.dev/id/3.2/ref/contrib/postgres/search/","summary":"Fungsi-fungsi basisdata dalam modul django.contrib.postgres.search kemudahan penggunaan full text search engine PostgreSQL. Sebagai contoh dalam dokumen ini, kami…","html":"

Pencarian teks penuhLink to this heading#

\n

Fungsi-fungsi basisdata dalam modul django.contrib.postgres.search kemudahan penggunaan full text search engine PostgreSQL.

\n

Sebagai contoh dalam dokumen ini, kami akan menggunakan model ditentukan dalam Membuat query.

\n\n
\n

Pencarian searchLink to this heading#

\n

A common way to use full text search is to search a single term against a\nsingle column in the database. For example:

\n
Code
>>> Entry.objects.filter(body_text__search='Cheese')\n[<Entry: Cheese on Toast recipes>, <Entry: Pizza Recipes>]\n
\n

Ini membuat sebuah to_tsvector dalam basisdata dari bidang body_text dan plainto_tsquery dari istilah pencarian 'Cheese', kedua menggunakan konfigurasi pencarian basisdata awalan. Hasil didapatkan dengan mencocokkan permintaan dan vektor.

\n

Untuk menggunakan pencarian search, 'django.contrib.postgres' harus berada dalam INSTALLED_APPS anda.

\n\n
\n
\n

SearchVectorLink to this heading#

\n
\n
\nclass SearchVector(*expressions, config=None, weight=None)Link to this definition#
\n
\n\n

Pencarian terhadap bidang tunggal lebih hebat tetapi agak terbatas. Contoh-contoh Entry kami sedang cari milik sebuah Blog, yang mempunyai bidang tagline. Untuk meminta terhadap kedua bidang, gunakan SearchVector:

\n
Code
>>> from django.contrib.postgres.search import SearchVector\n>>> Entry.objects.annotate(\n...     search=SearchVector('body_text', 'blog__tagline'),\n... ).filter(search='Cheese')\n[<Entry: Cheese on Toast recipes>, <Entry: Pizza Recipes>]\n
\n

Argumen-argumen pada SearchVector dapat berupa Expression apapun atau nama dari sebuah bidang. Banyak argumen akan dihubungkan bersama menggunakan sebuah ruang sehingga pencarian dokumen menyertakan mereka semua.

\n

Vektor SearchVector dapat dipadukan bersama-sama, mengizinkan anda menggunakan kembali mereka. Sebagai contoh:

\n
Code
>>> Entry.objects.annotate(\n...     search=SearchVector('body_text') + SearchVector('blog__tagline'),\n... ).filter(search='Cheese')\n[<Entry: Cheese on Toast recipes>, <Entry: Pizza Recipes>]\n
\n

Lihat Merubah konfigurasi pencarian dan Meminta pembobotan untuk sebuah penjelasan dari parameter config dan weight.

\n
\n
\n

SearchQueryLink to this heading#

\n
\n
\nclass SearchQuery(value, config=None, search_type='plain')Link to this definition#
\n
\n\n

SearchQuery menterjemahkan istilah pengguna sediakan kedalam obyek permintaan pencarian yang basisdata bandingkan pada pencarian vektor. Secara awalan, semua kata pengguna sediakan dilewatkan melalui algoritma berasal, dan kemudian itu mencari kecocokan untuk semua istilah yang dihasilkan.

\n

If search_type is 'plain', which is the default, the terms are treated\nas separate keywords. If search_type is 'phrase', the terms are treated\nas a single phrase. If search_type is 'raw', then you can provide a\nformatted search query with terms and operators. If search_type is\n'websearch', then you can provide a formatted search query, similar to the\none used by web search engines. 'websearch' requires PostgreSQL ≥ 11. Read\nPostgreSQL's Full Text Search docs to learn about differences and syntax.\nExamples:

\n
Code
>>> from django.contrib.postgres.search import SearchQuery\n>>> SearchQuery('red tomato')  # two keywords\n>>> SearchQuery('tomato red')  # same results as above\n>>> SearchQuery('red tomato', search_type='phrase')  # a phrase\n>>> SearchQuery('tomato red', search_type='phrase')  # a different phrase\n>>> SearchQuery("'tomato' & ('red' | 'green')", search_type='raw')  # boolean operators\n>>> SearchQuery("'tomato' ('red' OR 'green')", search_type='websearch')  # websearch operators\n
\n

Istilah SearchQuery dapat dipadukan secara logika untuk menyediakan keluwesan lebih:

\n
Code
>>> from django.contrib.postgres.search import SearchQuery\n>>> SearchQuery('meat') & SearchQuery('cheese')  # AND\n>>> SearchQuery('meat') | SearchQuery('cheese')  # OR\n>>> ~SearchQuery('meat')  # NOT\n
\n

Lihat Merubah konfigurasi pencarian untuk sebuah penjelasan dari parameter config.

\n\n
\n
\n

SearchRankLink to this heading#

\n
\n
\nclass SearchRank(vector, query, weights=None, normalization=None, cover_density=False)Link to this definition#
\n
\n\n

So far, we've returned the results for which any match between the vector and\nthe query are possible. It's likely you may wish to order the results by some\nsort of relevancy. PostgreSQL provides a ranking function which takes into\naccount how often the query terms appear in the document, how close together\nthe terms are in the document, and how important the part of the document is\nwhere they occur. The better the match, the higher the value of the rank. To\norder by relevancy:

\n
Code
>>> from django.contrib.postgres.search import SearchQuery, SearchRank, SearchVector\n>>> vector = SearchVector('body_text')\n>>> query = SearchQuery('cheese')\n>>> Entry.objects.annotate(rank=SearchRank(vector, query)).order_by('-rank')\n[<Entry: Cheese on Toast recipes>, <Entry: Pizza recipes>]\n
\n

Lihat Meminta pembobotan untuk penjelasan dari parameter weights.

\n

Set the cover_density parameter to True to enable the cover density\nranking, which means that the proximity of matching query terms is taken into\naccount.

\n

Provide an integer to the normalization parameter to control rank\nnormalization. This integer is a bit mask, so you can combine multiple\nbehaviors:

\n
Code
>>> from django.db.models import Value\n>>> Entry.objects.annotate(\n...     rank=SearchRank(\n...         vector,\n...         query,\n...         normalization=Value(2).bitor(Value(4)),\n...     )\n... )\n
\n

The PostgreSQL documentation has more details about different rank\nnormalization options.

\n\n
\n
\n

SearchHeadlineLink to this heading#

\n\n
\n
\nclass SearchHeadline(expression, query, config=None, start_sel=None, stop_sel=None, max_words=None, min_words=None, short_word=None, highlight_all=None, max_fragments=None, fragment_delimiter=None)Link to this definition#
\n
\n\n

Accepts a single text field or an expression, a query, a config, and a set of\noptions. Returns highlighted search results.

\n

Set the start_sel and stop_sel parameters to the string values to be\nused to wrap highlighted query terms in the document. PostgreSQL's defaults are\n<b> and </b>.

\n

Provide integer values to the max_words and min_words parameters to\ndetermine the longest and shortest headlines. PostgreSQL's defaults are 35 and\n15.

\n

Provide an integer value to the short_word parameter to discard words of\nthis length or less in each headline. PostgreSQL's default is 3.

\n

Set the highlight_all parameter to True to use the whole document in\nplace of a fragment and ignore max_words, min_words, and short_word\nparameters. That's disabled by default in PostgreSQL.

\n

Provide a non-zero integer value to the max_fragments to set the maximum\nnumber of fragments to display. That's disabled by default in PostgreSQL.

\n

Set the fragment_delimiter string parameter to configure the delimiter\nbetween fragments. PostgreSQL's default is " ... ".

\n

The PostgreSQL documentation has more details on highlighting search\nresults.

\n

Contoh penggunaan:

\n
Code
>>> from django.contrib.postgres.search import SearchHeadline, SearchQuery\n>>> query = SearchQuery('red tomato')\n>>> entry = Entry.objects.annotate(\n...     headline=SearchHeadline(\n...         'body_text',\n...         query,\n...         start_sel='<span>',\n...         stop_sel='</span>',\n...     ),\n... ).get()\n>>> print(entry.headline)\nSandwich with <span>tomato</span> and <span>red</span> cheese.\n
\n

Lihat Merubah konfigurasi pencarian untuk sebuah penjelasan dari parameter config.

\n
\n
\n

Merubah konfigurasi pencarianLink to this heading#

\n

Anda dapat menentukan atribut config pada SearchVector dan SearchQuery untuk menggunakan konfigurasi pencarian berbeda. Ini mengizinkan menggunakan pengurai bahasa berbeda dan dictionary sebagai ditentukan oleh basisdata:

\n
Code
>>> from django.contrib.postgres.search import SearchQuery, SearchVector\n>>> Entry.objects.annotate(\n...     search=SearchVector('body_text', config='french'),\n... ).filter(search=SearchQuery('œuf', config='french'))\n[<Entry: Pain perdu>]\n
\n

Nilai dari config dapat juga disimpan dalam kolom lain:

\n
Code
>>> from django.db.models import F\n>>> Entry.objects.annotate(\n...     search=SearchVector('body_text', config=F('blog__language')),\n... ).filter(search=SearchQuery('œuf', config=F('blog__language')))\n[<Entry: Pain perdu>]\n
\n
\n
\n

Meminta pembobotanLink to this heading#

\n

Setiap bidang mungkin tidak memiliki hubungan dalam sebuah permintaan, jadi anda dapat mensetel berat dari beragam vektor sebelum anda mamadukan mereka:

\n
Code
>>> from django.contrib.postgres.search import SearchQuery, SearchRank, SearchVector\n>>> vector = SearchVector('body_text', weight='A') + SearchVector('blog__tagline', weight='B')\n>>> query = SearchQuery('cheese')\n>>> Entry.objects.annotate(rank=SearchRank(vector, query)).filter(rank__gte=0.3).order_by('rank')\n
\n

Berat harus beupa satu dari huruf berikut: D, C, B, A. Secara awalan, berat ini mengacu pada angka 0.1, 0.2, 0.4, dan 1.0, masing-masing. Jika anda berharap pada berat mereka berbeda, lewatkan daftar dari float emapt kami ke SearchRank sebagai weights dalam urutan sama diatas:

\n
Code
>>> rank = SearchRank(vector, query, weights=[0.2, 0.4, 0.6, 0.8])\n>>> Entry.objects.annotate(rank=rank).filter(rank__gte=0.3).order_by('-rank')\n
\n
\n
\n

PenampilanLink to this heading#

\n

Konfigurasi basisdata khusus tidak diperlukan untuk menggunakan fungsi ini apapun, bagaimapun, jika anda sedang mencari lebih dari sedikit ratusan rekaman, anda mungkin berjalan kedalam masalah penampilan. Pencarian teks penuh adalah pengolahan lebih intensif daripada membandingkan ukuran dari integer, sebagai contoh.

\n

Pada kegiatan dimana semua bidang anda sedang minta mengandung dalam satu model tertentu, anda dapat membuat sebuah indeks kegunaan yang cocok vektor pencarian anda ingin gunakan. Dokumentasi PostgreSQL mempunyai rincian pada creating indexes for full text search.

\n
\n

SearchVectorFieldLink to this heading#

\n
\n
\nclass SearchVectorFieldLink to this definition#
\n
\n\n

Jika pendekatan ini menjadi terlalu lambat, anda dapat menambahkan SearchVectorField ke model anda. Anda akan butuh menjaga itu dikumpulkan dengan pemicu, sebagai contoh, seperti digambarkan dalam PostgreSQL documentation. Anda kemudian dapat meminta bidang seperti jika itu dinyatakan SearchVector:

\n
Code
>>> Entry.objects.update(search_vector=SearchVector('body_text'))\n>>> Entry.objects.filter(search_vector='cheese')\n[<Entry: Cheese on Toast recipes>, <Entry: Pizza recipes>]\n
\n
\n
\n
\n

Kemiripan trigramLink to this heading#

\n

Pendekatan lain untuk mencari adalah kemiripan trigram. Trigram adalah kelompok dari tiga karakter berurutan. Sebagai tambahan pada pencarian trigram_similar, anda dapat menggunakan sepasang pernyataan lain.

\n

Untuk menggunakan mereka, anda butuh mengaktifkan pg_trgm extension pada PostgreSQL. Anda dapat memasang itu menggunakan tindakan perpindahan TrigramExtension.

\n
\n

TrigramSimilarityLink to this heading#

\n
\n
\nclass TrigramSimilarity(expression, string, **extra)Link to this definition#
\n
\n\n

Menerima nama bidang atau pernyataan, dan string atau pernyataan. Mengembalikan kemiripan trigram diantara dua argumen.

\n

Contoh penggunaan:

\n
Code
>>> from django.contrib.postgres.search import TrigramSimilarity\n>>> Author.objects.create(name='Katy Stevens')\n>>> Author.objects.create(name='Stephen Keats')\n>>> test = 'Katie Stephens'\n>>> Author.objects.annotate(\n...     similarity=TrigramSimilarity('name', test),\n... ).filter(similarity__gt=0.3).order_by('-similarity')\n[<Author: Katy Stevens>, <Author: Stephen Keats>]\n
\n
\n
\n

TrigramDistanceLink to this heading#

\n
\n
\nclass TrigramDistance(expression, string, **extra)Link to this definition#
\n
\n\n

Menerima nama bidang atau pernyataan, dan string atau pernyataan. mengembalikan jarak trigram diantara dua argumen.

\n

Contoh penggunaan:

\n
Code
>>> from django.contrib.postgres.search import TrigramDistance\n>>> Author.objects.create(name='Katy Stevens')\n>>> Author.objects.create(name='Stephen Keats')\n>>> test = 'Katie Stephens'\n>>> Author.objects.annotate(\n...     distance=TrigramDistance('name', test),\n... ).filter(distance__lte=0.7).order_by('distance')\n[<Author: Katy Stevens>, <Author: Stephen Keats>]\n
\n
\n
","rootId":"full-text-search","toc":[{"title":"Pencarian search","anchor":"the-search-lookup","children":[]},{"title":"SearchVector","anchor":"searchvector","children":[]},{"title":"SearchQuery","anchor":"searchquery","children":[]},{"title":"SearchRank","anchor":"searchrank","children":[]},{"title":"SearchHeadline","anchor":"searchheadline","children":[]},{"title":"Merubah konfigurasi pencarian","anchor":"changing-the-search-configuration","children":[]},{"title":"Meminta pembobotan","anchor":"weighting-queries","children":[]},{"title":"Penampilan","anchor":"performance","children":[{"title":"SearchVectorField","anchor":"searchvectorfield","children":[]}]},{"title":"Kemiripan trigram","anchor":"trigram-similarity","children":[{"title":"TrigramSimilarity","anchor":"trigramsimilarity","children":[]},{"title":"TrigramDistance","anchor":"trigramdistance","children":[]}]}],"breadcrumbs":[{"docname":"ref/index","title":"Acuan API","url":"/id/3.2/ref/"},{"docname":"ref/contrib/index","title":"Paket contrib","url":"/id/3.2/ref/contrib/"},{"docname":"ref/contrib/postgres/index","title":"django.contrib.postgres","url":"/id/3.2/ref/contrib/postgres/"}],"prev":{"docname":"ref/contrib/postgres/operations","title":"Tindakan perpindahan basisdata","url":"/id/3.2/ref/contrib/postgres/operations/"},"next":{"docname":"ref/contrib/postgres/validators","title":"Pengesah","url":"/id/3.2/ref/contrib/postgres/validators/"},"formats":{"html":"/id/3.2/ref/contrib/postgres/search/","markdown":"/id/3.2/ref/contrib/postgres/search.md","json":"/id/3.2/ref/contrib/postgres/search.json"},"source":"https://github.com/django/django/blob/stable/3.2.x/docs/ref/contrib/postgres/search.txt","official":"https://docs.djangoproject.com/id/3.2/ref/contrib/postgres/search/","inVersions":["6.1","6.0","5.2","5.1","5.0","4.2","4.1","4.0","3.2","3.1","3.0","2.2","2.1","2.0","1.11","1.10"],"inLocales":["en","zh-hans","fr","ja","id","it","pt-br","ko","es","el","pl"]}