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Direktori : /opt/alt/python38/lib64/python3.8/site-packages/playhouse/ |
Current File : //opt/alt/python38/lib64/python3.8/site-packages/playhouse/sqlite_ext.py |
""" Sqlite3 extensions ================== * Define custom aggregates, collations and functions * Basic support for virtual tables * Basic support for FTS3/4 * Specify isolation level in transactions Example usage of the Full-text search: class Document(FTSModel): title = TextField() # type affinities are ignored in FTS content = TextField() Document.create_table(tokenize='porter') # use the porter stemmer # populate the documents using normal operations. for doc in documents: Document.create(title=doc['title'], content=doc['content']) # use the "match" operation for FTS queries. matching_docs = Document.select().where(match(Document.title, 'some query')) # to sort by best match, use the custom "rank" function. best_docs = (Document .select(Document, Document.rank('score')) .where(match(Document.title, 'some query')) .order_by(SQL('score'))) # or use the shortcut method. best_docs = Document.match('some phrase') """ import glob import inspect import math import os import re import struct import sys try: import simplejson as json except ImportError: import json try: from vtfunc import TableFunction except ImportError: pass from peewee import * from peewee import EnclosedClause from peewee import Entity from peewee import Expression from peewee import Node from peewee import OP from peewee import SqliteQueryCompiler from peewee import _AutoPrimaryKeyField from peewee import sqlite3 # Import the best SQLite version. from peewee import transaction from peewee import _sqlite_date_part from peewee import _sqlite_date_trunc from peewee import _sqlite_regexp try: from playhouse import _sqlite_ext as _c_ext except ImportError: _c_ext = None if sys.version_info[0] == 3: basestring = str FTS_MATCHINFO_FORMAT = 'pcnalx' FTS_MATCHINFO_FORMAT_SIMPLE = 'pcx' FTS_VER = sqlite3.sqlite_version_info[:3] >= (3, 7, 4) and 'FTS4' or 'FTS3' FTS5_MIN_VERSION = (3, 9, 0) class RowIDField(_AutoPrimaryKeyField): """ Field used to access hidden primary key on FTS5 or any other SQLite table that does not have a separately-defined primary key. """ _column_name = 'rowid' class DocIDField(_AutoPrimaryKeyField): """Field used to access hidden primary key on FTS3/4 tables.""" _column_name = 'docid' class PrimaryKeyAutoIncrementField(PrimaryKeyField): """ SQLite by default uses MAX(primary key) + 1 to set the ID on a new row. Using the `AUTOINCREMENT` field, the IDs will increase monotonically even if rows are deleted. Use this if you need to guarantee IDs are not re-used in the event of deletion. """ def __ddl__(self, column_type): ddl = super(PrimaryKeyAutoIncrementField, self).__ddl__(column_type) return ddl + [SQL('AUTOINCREMENT')] class JSONField(TextField): def python_value(self, value): if value is not None: try: return json.loads(value) except (TypeError, ValueError): return value def db_value(self, value): if value is not None: return json.dumps(value) def clean_path(self, path): if path.startswith('[') or not path: return '$%s' % path return '$.%s' % path def length(self, path=None): if path: return fn.json_array_length(self, self.clean_path(path)) return fn.json_array_length(self) def extract(self, path): return fn.json_extract(self, self.clean_path(path)) def _value_for_insertion(self, value): if isinstance(value, (list, tuple, dict)): return fn.json(json.dumps(value)) return value def _insert_like(self, fn, pairs): npairs = len(pairs) if npairs % 2 != 0: raise ValueError('Mismatched path and value parameters.') accum = [] for i in range(0, npairs, 2): accum.append(self.clean_path(pairs[i])) accum.append(self._value_for_insertion(pairs[i + 1])) return fn(self, *accum) def insert(self, *pairs): return self._insert_like(fn.json_insert, pairs) def replace(self, *pairs): return self._insert_like(fn.json_replace, pairs) def set(self, *pairs): return self._insert_like(fn.json_set, pairs) def remove(self, *paths): return fn.json_remove(self, *[self.clean_path(path) for path in paths]) def json_type(self, path=None): if path: return fn.json_type(self, self.clean_path(path)) return fn.json_type(self) def children(self, path=None): """ Schema of `json_each` and `json_tree`: key, value, type TEXT (object, array, string, etc), atom (value for primitive/scalar types, NULL for array and object) id INTEGER (unique identifier for element) parent INTEGER (unique identifier of parent element or NULL) fullkey TEXT (full path describing element) path TEXT (path to the container of the current element) json JSON hidden (1st input parameter to function) root TEXT hidden (2nd input parameter, path at which to start) """ if path: return fn.json_each(self, self.clean_path(path)) return fn.json_each(self) def tree(self, path=None): if path: return fn.json_tree(self, self.clean_path(path)) return fn.json_tree(self) class SearchField(BareField): """ Field class to be used with full-text search extension. Since the FTS extensions do not support any field types besides `TEXT`, and furthermore do not support secondary indexes, using this field will prevent you from mistakenly creating the wrong kind of field on your FTS table. """ def __init__(self, unindexed=False, db_column=None, coerce=None, **_): kwargs = {'null': True, 'db_column': db_column, 'coerce': coerce} self._unindexed = unindexed if unindexed: kwargs['constraints'] = [SQL('UNINDEXED')] super(SearchField, self).__init__(**kwargs) def clone_base(self, **kwargs): clone = super(SearchField, self).clone_base(**kwargs) clone._unindexed = self._unindexed return clone class _VirtualFieldMixin(object): """ Field mixin to support virtual table attributes that may not correspond to actual columns in the database. """ def add_to_class(self, model_class, name): super(_VirtualFieldMixin, self).add_to_class(model_class, name) model_class._meta.remove_field(name) # Virtual field types that can be used to reference specially-created fields # on virtual tables. These fields are exposed as attributes on the model class, # but are not included in any `CREATE TABLE` statements or by default when # performing an `INSERT` or `UPDATE` query. class VirtualField(_VirtualFieldMixin, BareField): pass class VirtualIntegerField(_VirtualFieldMixin, IntegerField): pass class VirtualCharField(_VirtualFieldMixin, CharField): pass class VirtualFloatField(_VirtualFieldMixin, FloatField): pass class VirtualModel(Model): class Meta: virtual_table = True extension_module = None extension_options = {} @classmethod def clean_options(cls, **options): # Called by the QueryCompiler when generating the virtual table's # options clauses. return options @classmethod def create_table(cls, fail_silently=False, **options): # Modified to support **options, which are passed back to the # query compiler. if fail_silently and cls.table_exists(): return cls._meta.database.create_table(cls, options=options) cls._create_indexes() class BaseFTSModel(VirtualModel): @classmethod def clean_options(cls, **options): tokenize = options.get('tokenize') content = options.get('content') if tokenize: # Tokenizers need to be in quoted string. options['tokenize'] = '"%s"' % tokenize if isinstance(content, basestring) and content == '': # Special-case content-less full-text search tables. options['content'] = "''" return options class FTSModel(BaseFTSModel): """ VirtualModel class for creating tables that use either the FTS3 or FTS4 search extensions. Peewee automatically determines which version of the FTS extension is supported and will use FTS4 if possible. Note: because FTS5 is significantly different from FTS3 and FTS4, there is a separate model class for FTS5 virtual tables. """ # FTS3/4 does not support declared primary keys, but we can use the # implicit docid. docid = DocIDField() class Meta: extension_module = FTS_VER @classmethod def validate_model(cls): if cls._meta.primary_key.name != 'docid': raise ImproperlyConfigured( 'FTSModel classes must use the default `docid` primary key.') @classmethod def _fts_cmd(cls, cmd): tbl = cls._meta.db_table res = cls._meta.database.execute_sql( "INSERT INTO %s(%s) VALUES('%s');" % (tbl, tbl, cmd)) return res.fetchone() @classmethod def optimize(cls): return cls._fts_cmd('optimize') @classmethod def rebuild(cls): return cls._fts_cmd('rebuild') @classmethod def integrity_check(cls): return cls._fts_cmd('integrity-check') @classmethod def merge(cls, blocks=200, segments=8): return cls._fts_cmd('merge=%s,%s' % (blocks, segments)) @classmethod def automerge(cls, state=True): return cls._fts_cmd('automerge=%s' % (state and '1' or '0')) @classmethod def match(cls, term): """ Generate a `MATCH` expression appropriate for searching this table. """ return match(cls.as_entity(), term) @classmethod def rank(cls, *weights): return fn.fts_rank(fn.matchinfo( cls.as_entity(), FTS_MATCHINFO_FORMAT_SIMPLE), *weights) @classmethod def bm25(cls, *weights): match_info = fn.matchinfo(cls.as_entity(), FTS_MATCHINFO_FORMAT) return fn.fts_bm25(match_info, *weights) @classmethod def lucene(cls, *weights): match_info = fn.matchinfo(cls.as_entity(), FTS_MATCHINFO_FORMAT) return fn.fts_lucene(match_info, *weights) @classmethod def _search(cls, term, weights, with_score, score_alias, score_fn, explicit_ordering): if not weights: rank = score_fn() elif isinstance(weights, dict): weight_args = [] for field in cls._meta.declared_fields: weight_args.append( weights.get(field, weights.get(field.name, 1.0))) rank = score_fn(*weight_args) else: rank = score_fn(*weights) selection = () order_by = rank if with_score: selection = (cls, rank.alias(score_alias)) if with_score and not explicit_ordering: order_by = SQL(score_alias) return (cls .select(*selection) .where(cls.match(term)) .order_by(order_by)) @classmethod def search(cls, term, weights=None, with_score=False, score_alias='score', explicit_ordering=False): """Full-text search using selected `term`.""" return cls._search( term, weights, with_score, score_alias, cls.rank, explicit_ordering) @classmethod def search_bm25(cls, term, weights=None, with_score=False, score_alias='score', explicit_ordering=False): """Full-text search for selected `term` using BM25 algorithm.""" return cls._search( term, weights, with_score, score_alias, cls.bm25, explicit_ordering) @classmethod def search_lucene(cls, term, weights=None, with_score=False, score_alias='score', explicit_ordering=False): """Full-text search for selected `term` using BM25 algorithm.""" return cls._search( term, weights, with_score, score_alias, cls.lucene, explicit_ordering) _alphabet = 'abcdefghijklmnopqrstuvwxyz' _alphanum = set([ '\t', ' ', ',', '"', chr(26), # Substitution control character. '(', ')', '{', '}', '*', ':', '_', '+', ]) | set('0123456789') | set(_alphabet) | set(_alphabet.upper()) _invalid_ascii = set([chr(p) for p in range(128) if chr(p) not in _alphanum]) _quote_re = re.compile('(?:[^\s"]|"(?:\\.|[^"])*")+') class FTS5Model(BaseFTSModel): """ Requires SQLite >= 3.9.0. Table options: content: table name of external content, or empty string for "contentless" content_rowid: column name of external content primary key prefix: integer(s). Ex: '2' or '2 3 4' tokenize: porter, unicode61, ascii. Ex: 'porter unicode61' The unicode tokenizer supports the following parameters: * remove_diacritics (1 or 0, default is 1) * tokenchars (string of characters, e.g. '-_' * separators (string of characters) Parameters are passed as alternating parameter name and value, so: {'tokenize': "unicode61 remove_diacritics 0 tokenchars '-_'"} Content-less tables: If you don't need the full-text content in it's original form, you can specify a content-less table. Searches and auxiliary functions will work as usual, but the only values returned when SELECT-ing can be rowid. Also content-less tables do not support UPDATE or DELETE. External content tables: You can set up triggers to sync these, e.g. -- Create a table. And an external content fts5 table to index it. CREATE TABLE tbl(a INTEGER PRIMARY KEY, b); CREATE VIRTUAL TABLE ft USING fts5(b, content='tbl', content_rowid='a'); -- Triggers to keep the FTS index up to date. CREATE TRIGGER tbl_ai AFTER INSERT ON tbl BEGIN INSERT INTO ft(rowid, b) VALUES (new.a, new.b); END; CREATE TRIGGER tbl_ad AFTER DELETE ON tbl BEGIN INSERT INTO ft(fts_idx, rowid, b) VALUES('delete', old.a, old.b); END; CREATE TRIGGER tbl_au AFTER UPDATE ON tbl BEGIN INSERT INTO ft(fts_idx, rowid, b) VALUES('delete', old.a, old.b); INSERT INTO ft(rowid, b) VALUES (new.a, new.b); END; Built-in auxiliary functions: * bm25(tbl[, weight_0, ... weight_n]) * highlight(tbl, col_idx, prefix, suffix) * snippet(tbl, col_idx, prefix, suffix, ?, max_tokens) """ # FTS5 does not support declared primary keys, but we can use the # implicit rowid. rowid = RowIDField() class Meta: extension_module = 'fts5' _error_messages = { 'field_type': ('Besides the implicit `rowid` column, all columns must ' 'be instances of SearchField'), 'index': 'Secondary indexes are not supported for FTS5 models', 'pk': 'FTS5 models must use the default `rowid` primary key', } @classmethod def validate_model(cls): # Perform FTS5-specific validation and options post-processing. if cls._meta.primary_key.name != 'rowid': raise ImproperlyConfigured(cls._error_messages['pk']) for field in cls._meta.fields.values(): if not isinstance(field, (SearchField, RowIDField)): raise ImproperlyConfigured(cls._error_messages['field_type']) if cls._meta.indexes: raise ImproperlyConfigured(cls._error_messages['index']) @classmethod def fts5_installed(cls): if sqlite3.sqlite_version_info[:3] < FTS5_MIN_VERSION: return False # Test in-memory DB to determine if the FTS5 extension is installed. tmp_db = sqlite3.connect(':memory:') try: tmp_db.execute('CREATE VIRTUAL TABLE fts5test USING fts5 (data);') except: try: sqlite3.enable_load_extension(True) sqlite3.load_extension('fts5') except: return False else: cls._meta.database.load_extension('fts5') finally: tmp_db.close() return True @staticmethod def validate_query(query): """ Simple helper function to indicate whether a search query is a valid FTS5 query. Note: this simply looks at the characters being used, and is not guaranteed to catch all problematic queries. """ tokens = _quote_re.findall(query) for token in tokens: if token.startswith('"') and token.endswith('"'): continue if set(token) & _invalid_ascii: return False return True @staticmethod def clean_query(query, replace=chr(26)): """ Clean a query of invalid tokens. """ accum = [] any_invalid = False tokens = _quote_re.findall(query) for token in tokens: if token.startswith('"') and token.endswith('"'): accum.append(token) continue token_set = set(token) invalid_for_token = token_set & _invalid_ascii if invalid_for_token: any_invalid = True for c in invalid_for_token: token = token.replace(c, replace) accum.append(token) if any_invalid: return ' '.join(accum) return query @classmethod def match(cls, term): """ Generate a `MATCH` expression appropriate for searching this table. """ return match(cls.as_entity(), term) @classmethod def rank(cls, *args): if args: return cls.bm25(*args) else: return SQL('rank') @classmethod def bm25(cls, *weights): return fn.bm25(cls.as_entity(), *weights) @classmethod def search(cls, term, weights=None, with_score=False, score_alias='score', explicit_ordering=False): """Full-text search using selected `term`.""" return cls.search_bm25( FTS5Model.clean_query(term), weights, with_score, score_alias, explicit_ordering) @classmethod def search_bm25(cls, term, weights=None, with_score=False, score_alias='score', explicit_ordering=False): """Full-text search using selected `term`.""" if not weights: rank = SQL('rank') elif isinstance(weights, dict): weight_args = [] for field in cls._meta.declared_fields: weight_args.append( weights.get(field, weights.get(field.name, 1.0))) rank = fn.bm25(cls.as_entity(), *weight_args) else: rank = fn.bm25(cls.as_entity(), *weights) selection = () order_by = rank if with_score: selection = (cls, rank.alias(score_alias)) if with_score and not explicit_ordering: order_by = SQL(score_alias) return (cls .select(*selection) .where(cls.match(FTS5Model.clean_query(term))) .order_by(order_by)) @classmethod def _fts_cmd(cls, cmd, **extra_params): tbl = cls.as_entity() columns = [tbl] values = [cmd] for key, value in extra_params.items(): columns.append(Entity(key)) values.append(value) inner_clause = EnclosedClause(tbl) clause = Clause( SQL('INSERT INTO'), cls.as_entity(), EnclosedClause(*columns), SQL('VALUES'), EnclosedClause(*values)) return cls._meta.database.execute(clause) @classmethod def automerge(cls, level): if not (0 <= level <= 16): raise ValueError('level must be between 0 and 16') return cls._fts_cmd('automerge', rank=level) @classmethod def merge(cls, npages): return cls._fts_cmd('merge', rank=npages) @classmethod def set_pgsz(cls, pgsz): return cls._fts_cmd('pgsz', rank=pgsz) @classmethod def set_rank(cls, rank_expression): return cls._fts_cmd('rank', rank=rank_expression) @classmethod def delete_all(cls): return cls._fts_cmd('delete-all') @classmethod def VocabModel(cls, table_type='row', table_name=None): if table_type not in ('row', 'col'): raise ValueError('table_type must be either "row" or "col".') attr = '_vocab_model_%s' % table_type if not hasattr(cls, attr): class Meta: database = cls._meta.database db_table = table_name or cls._meta.db_table + '_v' extension_module = fn.fts5vocab( cls.as_entity(), SQL(table_type)) attrs = { 'term': BareField(), 'doc': IntegerField(), 'cnt': IntegerField(), 'rowid': RowIDField(), 'Meta': Meta, } if table_type == 'col': attrs['col'] = BareField() class_name = '%sVocab' % cls.__name__ setattr(cls, attr, type(class_name, (VirtualModel,), attrs)) return getattr(cls, attr) def ClosureTable(model_class, foreign_key=None): """Model factory for the transitive closure extension.""" if foreign_key is None: for field_obj in model_class._meta.rel.values(): if field_obj.rel_model is model_class: foreign_key = field_obj break else: raise ValueError('Unable to find self-referential foreign key.') primary_key = model_class._meta.primary_key class BaseClosureTable(VirtualModel): depth = VirtualIntegerField() id = VirtualIntegerField() idcolumn = VirtualIntegerField() parentcolumn = VirtualIntegerField() root = VirtualIntegerField() tablename = VirtualCharField() class Meta: extension_module = 'transitive_closure' @classmethod def descendants(cls, node, depth=None, include_node=False): query = (model_class .select(model_class, cls.depth.alias('depth')) .join(cls, on=(primary_key == cls.id)) .where(cls.root == node)) if depth is not None: query = query.where(cls.depth == depth) elif not include_node: query = query.where(cls.depth > 0) return query @classmethod def ancestors(cls, node, depth=None, include_node=False): query = (model_class .select(model_class, cls.depth.alias('depth')) .join(cls, on=(primary_key == cls.root)) .where(cls.id == node)) if depth: query = query.where(cls.depth == depth) elif not include_node: query = query.where(cls.depth > 0) return query @classmethod def siblings(cls, node, include_node=False): fk_value = node._data.get(foreign_key.name) query = model_class.select().where(foreign_key == fk_value) if not include_node: query = query.where(primary_key != node) return query class Meta: database = model_class._meta.database extension_options = { 'tablename': model_class._meta.db_table, 'idcolumn': model_class._meta.primary_key.db_column, 'parentcolumn': foreign_key.db_column} primary_key = False name = '%sClosure' % model_class.__name__ return type(name, (BaseClosureTable,), {'Meta': Meta}) class SqliteExtQueryCompiler(SqliteQueryCompiler): """ Subclass of QueryCompiler that can be used to construct virtual tables. """ def _create_table(self, model_class, safe=False, options=None): clause = super(SqliteExtQueryCompiler, self)._create_table( model_class, safe=safe) if issubclass(model_class, VirtualModel): statement = 'CREATE VIRTUAL TABLE' # If we are using a special extension, need to insert that after # the table name node. extension = model_class._meta.extension_module if isinstance(extension, Node): # If the `extension_module` attribute is a `Node` subclass, # then we assume the VirtualModel will be responsible for # defining not only the extension, but also the columns. parts = clause.nodes[:2] + [SQL('USING'), extension] clause = Clause(*parts) else: # The extension name is a simple string. clause.nodes.insert(2, SQL('USING %s' % extension)) else: statement = 'CREATE TABLE' if safe: statement += ' IF NOT EXISTS' clause.nodes[0] = SQL(statement) # Overwrite the statement. table_options = self.clean_options(model_class, clause, options) if table_options: columns_constraints = clause.nodes[-1] for k, v in sorted(table_options.items()): if isinstance(v, Field): # Special hack here for FTS5. We want to include the # fully-qualified column entity in most cases, but for # FTS5 we only want the string column name. v = v.as_entity(extension != 'fts5') elif inspect.isclass(v) and issubclass(v, Model): # The option points to a table name. v = v.as_entity() elif isinstance(v, (list, tuple)): # Lists will be quoted and joined by commas. v = SQL("'%s'" % ','.join(map(str, v))) elif not isinstance(v, Node): v = SQL(v) option = Clause(SQL(k), v) option.glue = '=' columns_constraints.nodes.append(option) if getattr(model_class._meta, 'without_rowid', None): clause.nodes.append(SQL('WITHOUT ROWID')) return clause def clean_options(self, model_class, clause, extra_options): model_options = getattr(model_class._meta, 'extension_options', None) if model_options: options = model_class.clean_options(**model_options) else: options = {} if extra_options: options.update(model_class.clean_options(**extra_options)) return options def create_table(self, model_class, safe=False, options=None): return self.parse_node(self._create_table(model_class, safe, options)) @Node.extend(clone=False) def disqualify(self): # In the where clause, prevent the given node/expression from constraining # an index. return Clause('+', self, glue='') class SqliteExtDatabase(SqliteDatabase): """ Database class which provides additional Sqlite-specific functionality: * Register custom aggregates, collations and functions * Specify a row factory * Advanced transactions (specify isolation level) """ compiler_class = SqliteExtQueryCompiler def __init__(self, database, c_extensions=True, *args, **kwargs): super(SqliteExtDatabase, self).__init__(database, *args, **kwargs) self._aggregates = {} self._collations = {} self._functions = {} self._extensions = set([]) self._row_factory = None if _c_ext and c_extensions: self._using_c_extensions = True self.register_function(_c_ext.peewee_date_part, 'date_part', 2) self.register_function(_c_ext.peewee_date_trunc, 'date_trunc', 2) self.register_function(_c_ext.peewee_regexp, 'regexp', 2) self.register_function(_c_ext.peewee_rank, 'fts_rank', -1) self.register_function(_c_ext.peewee_lucene, 'fts_lucene', -1) self.register_function(_c_ext.peewee_bm25, 'fts_bm25', -1) self.register_function(_c_ext.peewee_murmurhash, 'murmurhash', 1) else: self._using_c_extensions = False self.register_function(_sqlite_date_part, 'date_part', 2) self.register_function(_sqlite_date_trunc, 'date_trunc', 2) self.register_function(_sqlite_regexp, 'regexp', 2) self.register_function(rank, 'fts_rank', -1) self.register_function(bm25, 'fts_bm25', -1) @property def using_c_extensions(self): return self._using_c_extensions def _add_conn_hooks(self, conn): self._set_pragmas(conn) self._load_aggregates(conn) self._load_collations(conn) self._load_functions(conn) if self._row_factory: conn.row_factory = self._row_factory if self._extensions: self._load_extensions(conn) def _load_aggregates(self, conn): for name, (klass, num_params) in self._aggregates.items(): conn.create_aggregate(name, num_params, klass) def _load_collations(self, conn): for name, fn in self._collations.items(): conn.create_collation(name, fn) def _load_functions(self, conn): for name, (fn, num_params) in self._functions.items(): conn.create_function(name, num_params, fn) def _load_extensions(self, conn): conn.enable_load_extension(True) for extension in self._extensions: conn.load_extension(extension) def register_aggregate(self, klass, name=None, num_params=-1): self._aggregates[name or klass.__name__.lower()] = (klass, num_params) if not self.is_closed(): self._load_aggregates(self.get_conn()) def aggregate(self, name=None, num_params=-1): def decorator(klass): self.register_aggregate(klass, name, num_params) return klass return decorator def register_collation(self, fn, name=None): name = name or fn.__name__ def _collation(*args): expressions = args + (SQL('collate %s' % name),) return Clause(*expressions) fn.collation = _collation self._collations[name] = fn if not self.is_closed(): self._load_collations(self.get_conn()) def collation(self, name=None): def decorator(fn): self.register_collation(fn, name) return fn return decorator def register_function(self, fn, name=None, num_params=-1): self._functions[name or fn.__name__] = (fn, num_params) if not self.is_closed(): self._load_functions(self.get_conn()) def func(self, name=None, num_params=-1): def decorator(fn): self.register_function(fn, name, num_params) return fn return decorator def load_extension(self, extension): self._extensions.add(extension) if not self.is_closed(): conn = self.get_conn() conn.enable_load_extension(True) conn.load_extension(extension) def unregister_aggregate(self, name): del(self._aggregates[name]) def unregister_collation(self, name): del(self._collations[name]) def unregister_function(self, name): del(self._functions[name]) def unload_extension(self, extension): self._extensions.remove(extension) def row_factory(self, fn): self._row_factory = fn def create_table(self, model_class, safe=False, options=None): sql, params = self.compiler().create_table(model_class, safe, options) return self.execute_sql(sql, params) def create_index(self, model_class, field_name, unique=False): if issubclass(model_class, FTSModel): return return super(SqliteExtDatabase, self).create_index( model_class, field_name, unique) def granular_transaction(self, lock_type='deferred'): assert lock_type.lower() in ('deferred', 'immediate', 'exclusive') return granular_transaction(self, lock_type) class granular_transaction(transaction): def __init__(self, db, lock_type='deferred'): self.db = db self.conn = self.db.get_conn() self.lock_type = lock_type def _begin(self): self.db.begin(self.lock_type) OP.MATCH = 'match' SqliteExtDatabase.register_ops({ OP.MATCH: 'MATCH', }) def match(lhs, rhs): return Expression(lhs, OP.MATCH, rhs) def _parse_match_info(buf): # See http://sqlite.org/fts3.html#matchinfo bufsize = len(buf) # Length in bytes. return [struct.unpack('@I', buf[i:i+4])[0] for i in range(0, bufsize, 4)] # Ranking implementation, which parse matchinfo. def rank(raw_match_info, *weights): # Handle match_info called w/default args 'pcx' - based on the example rank # function http://sqlite.org/fts3.html#appendix_a match_info = _parse_match_info(raw_match_info) score = 0.0 p, c = match_info[:2] if not weights: weights = [1] * c else: weights = [0] * c for i, weight in enumerate(weights): weights[i] = weight for phrase_num in range(p): phrase_info_idx = 2 + (phrase_num * c * 3) for col_num in range(c): weight = weights[col_num] if not weight: continue col_idx = phrase_info_idx + (col_num * 3) x1, x2 = match_info[col_idx:col_idx + 2] if x1 > 0: score += weight * (float(x1) / x2) return -score # Okapi BM25 ranking implementation (FTS4 only). def bm25(raw_match_info, *args): """ Usage: # Format string *must* be pcnalx # Second parameter to bm25 specifies the index of the column, on # the table being queries. bm25(matchinfo(document_tbl, 'pcnalx'), 1) AS rank """ match_info = _parse_match_info(raw_match_info) K = 1.2 B = 0.75 score = 0.0 P_O, C_O, N_O, A_O = range(4) term_count = match_info[P_O] col_count = match_info[C_O] total_docs = match_info[N_O] L_O = A_O + col_count X_O = L_O + col_count if not args: weights = [1] * col_count else: weights = [0] * col_count for i, weight in enumerate(args): weights[i] = args[i] for i in range(term_count): for j in range(col_count): weight = weights[j] if weight == 0: continue avg_length = float(match_info[A_O + j]) doc_length = float(match_info[L_O + j]) if avg_length == 0: D = 0 else: D = 1 - B + (B * (doc_length / avg_length)) x = X_O + (3 * j * (i + 1)) term_frequency = float(match_info[x]) docs_with_term = float(match_info[x + 2]) idf = max( math.log( (total_docs - docs_with_term + 0.5) / (docs_with_term + 0.5)), 0) denom = term_frequency + (K * D) if denom == 0: rhs = 0 else: rhs = (term_frequency * (K + 1)) / denom score += (idf * rhs) * weight return -score