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import json import math import re import struct import sys from peewee import * from peewee import ColumnBase from peewee import EnclosedNodeList from peewee import Entity from peewee import Expression from peewee import Insert from peewee import Node from peewee import NodeList from peewee import OP from peewee import VirtualField from peewee import merge_dict from peewee import sqlite3 try: from playhouse._sqlite_ext import ( backup, backup_to_file, Blob, ConnectionHelper, register_bloomfilter, register_hash_functions, register_rank_functions, sqlite_get_db_status, sqlite_get_status, TableFunction, ZeroBlob, ) CYTHON_SQLITE_EXTENSIONS = True except ImportError: CYTHON_SQLITE_EXTENSIONS = False if sys.version_info[0] == 3: basestring = str FTS3_MATCHINFO = 'pcx' FTS4_MATCHINFO = 'pcnalx' if sqlite3 is not None: FTS_VERSION = 4 if sqlite3.sqlite_version_info[:3] >= (3, 7, 4) else 3 else: FTS_VERSION = 3 FTS5_MIN_SQLITE_VERSION = (3, 9, 0) class RowIDField(AutoField): auto_increment = True column_name = name = required_name = 'rowid' def bind(self, model, name, *args): if name != self.required_name: raise ValueError('%s must be named "%s".' % (type(self), self.required_name)) super(RowIDField, self).bind(model, name, *args) class DocIDField(RowIDField): column_name = name = required_name = 'docid' class AutoIncrementField(AutoField): def ddl(self, ctx): node_list = super(AutoIncrementField, self).ddl(ctx) return NodeList((node_list, SQL('AUTOINCREMENT'))) class TDecimalField(DecimalField): field_type = 'TEXT' def get_modifiers(self): pass class JSONPath(ColumnBase): def __init__(self, field, path=None): super(JSONPath, self).__init__() self._field = field self._path = path or () @property def path(self): return Value('$%s' % ''.join(self._path)) def __getitem__(self, idx): if isinstance(idx, int) or idx == '#': item = '[%s]' % idx else: item = '.%s' % idx return JSONPath(self._field, self._path + (item,)) def append(self, value, as_json=None): if as_json or isinstance(value, (list, dict)): value = fn.json(self._field._json_dumps(value)) return fn.json_set(self._field, self['#'].path, value) def _json_operation(self, func, value, as_json=None): if as_json or isinstance(value, (list, dict)): value = fn.json(self._field._json_dumps(value)) return func(self._field, self.path, value) def insert(self, value, as_json=None): return self._json_operation(fn.json_insert, value, as_json) def set(self, value, as_json=None): return self._json_operation(fn.json_set, value, as_json) def replace(self, value, as_json=None): return self._json_operation(fn.json_replace, value, as_json) def update(self, value): return self.set(fn.json_patch(self, self._field._json_dumps(value))) def remove(self): return fn.json_remove(self._field, self.path) def json_type(self): return fn.json_type(self._field, self.path) def length(self): return fn.json_array_length(self._field, self.path) def children(self): return fn.json_each(self._field, self.path) def tree(self): return fn.json_tree(self._field, self.path) def __sql__(self, ctx): return ctx.sql(fn.json_extract(self._field, self.path) if self._path else self._field) class JSONField(TextField): field_type = 'JSON' unpack = False def __init__(self, json_dumps=None, json_loads=None, **kwargs): self._json_dumps = json_dumps or json.dumps self._json_loads = json_loads or json.loads super(JSONField, self).__init__(**kwargs) def python_value(self, value): if value is not None: try: return self._json_loads(value) except (TypeError, ValueError): return value def db_value(self, value): if value is not None: if not isinstance(value, Node): value = fn.json(self._json_dumps(value)) return value def _e(op): def inner(self, rhs): if isinstance(rhs, (list, dict)): rhs = Value(rhs, converter=self.db_value, unpack=False) return Expression(self, op, rhs) return inner __eq__ = _e(OP.EQ) __ne__ = _e(OP.NE) __gt__ = _e(OP.GT) __ge__ = _e(OP.GTE) __lt__ = _e(OP.LT) __le__ = _e(OP.LTE) __hash__ = Field.__hash__ def __getitem__(self, item): return JSONPath(self)[item] def extract(self, *paths): paths = [Value(p, converter=False) for p in paths] return fn.json_extract(self, *paths) def extract_json(self, path): return Expression(self, '->', Value(path, converter=False)) def extract_text(self, path): return Expression(self, '->>', Value(path, converter=False)) def append(self, value, as_json=None): return JSONPath(self).append(value, as_json) def insert(self, value, as_json=None): return JSONPath(self).insert(value, as_json) def set(self, value, as_json=None): return JSONPath(self).set(value, as_json) def replace(self, value, as_json=None): return JSONPath(self).replace(value, as_json) def update(self, data): return JSONPath(self).update(data) def remove(self, *paths): if not paths: return JSONPath(self).remove() return fn.json_remove(self, *paths) def json_type(self): return fn.json_type(self) def length(self, path=None): args = (self, path) if path else (self,) return fn.json_array_length(*args) def children(self): """ 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) """ return fn.json_each(self) def tree(self): return fn.json_tree(self) class SearchField(Field): def __init__(self, unindexed=False, column_name=None, **k): if k: raise ValueError('SearchField does not accept these keyword ' 'arguments: %s.' % sorted(k)) super(SearchField, self).__init__(unindexed=unindexed, column_name=column_name, null=True) def match(self, term): return match(self, term) @property def fts_column_index(self): if not hasattr(self, '_fts_column_index'): search_fields = [f.name for f in self.model._meta.sorted_fields if isinstance(f, SearchField)] self._fts_column_index = search_fields.index(self.name) return self._fts_column_index def highlight(self, left, right): column_idx = self.fts_column_index return fn.highlight(self.model._meta.entity, column_idx, left, right) def snippet(self, left, right, over_length='...', max_tokens=16): if not (0 < max_tokens < 65): raise ValueError('max_tokens must be between 1 and 64 (inclusive)') column_idx = self.fts_column_index return fn.snippet(self.model._meta.entity, column_idx, left, right, over_length, max_tokens) class VirtualTableSchemaManager(SchemaManager): def _create_virtual_table(self, safe=True, **options): options = self.model.clean_options( merge_dict(self.model._meta.options, options)) # Structure: # CREATE VIRTUAL TABLE <model> # USING <extension_module> # ([prefix_arguments, ...] fields, ... [arguments, ...], [options...]) ctx = self._create_context() ctx.literal('CREATE VIRTUAL TABLE ') if safe: ctx.literal('IF NOT EXISTS ') (ctx .sql(self.model) .literal(' USING ')) ext_module = self.model._meta.extension_module if isinstance(ext_module, Node): return ctx.sql(ext_module) ctx.sql(SQL(ext_module)).literal(' ') arguments = [] meta = self.model._meta if meta.prefix_arguments: arguments.extend([SQL(a) for a in meta.prefix_arguments]) # Constraints, data-types, foreign and primary keys are all omitted. for field in meta.sorted_fields: if isinstance(field, (RowIDField)) or field._hidden: continue field_def = [Entity(field.column_name)] if field.unindexed: field_def.append(SQL('UNINDEXED')) arguments.append(NodeList(field_def)) if meta.arguments: arguments.extend([SQL(a) for a in meta.arguments]) if options: arguments.extend(self._create_table_option_sql(options)) return ctx.sql(EnclosedNodeList(arguments)) def _create_table(self, safe=True, **options): if issubclass(self.model, VirtualModel): return self._create_virtual_table(safe, **options) return super(VirtualTableSchemaManager, self)._create_table( safe, **options) class VirtualModel(Model): class Meta: arguments = None extension_module = None prefix_arguments = None primary_key = False schema_manager_class = VirtualTableSchemaManager @classmethod def clean_options(cls, options): return options class BaseFTSModel(VirtualModel): @classmethod def clean_options(cls, options): content = options.get('content') prefix = options.get('prefix') tokenize = options.get('tokenize') if isinstance(content, basestring) and content == '': # Special-case content-less full-text search tables. options['content'] = "''" elif isinstance(content, Field): # Special-case to ensure fields are fully-qualified. options['content'] = Entity(content.model._meta.table_name, content.column_name) if prefix: if isinstance(prefix, (list, tuple)): prefix = ','.join([str(i) for i in prefix]) options['prefix'] = "'%s'" % prefix.strip("' ") if tokenize and cls._meta.extension_module.lower() == 'fts5': # Tokenizers need to be in quoted string for FTS5, but not for FTS3 # or FTS4. options['tokenize'] = '"%s"' % tokenize 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. """ # FTS3/4 uses "docid" in the same way a normal table uses "rowid". docid = DocIDField() class Meta: extension_module = 'FTS%s' % FTS_VERSION @classmethod def _fts_cmd(cls, cmd): tbl = cls._meta.table_name 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._meta.entity, term) @classmethod def rank(cls, *weights): matchinfo = fn.matchinfo(cls._meta.entity, FTS3_MATCHINFO) return fn.fts_rank(matchinfo, *weights) @classmethod def bm25(cls, *weights): match_info = fn.matchinfo(cls._meta.entity, FTS4_MATCHINFO) return fn.fts_bm25(match_info, *weights) @classmethod def bm25f(cls, *weights): match_info = fn.matchinfo(cls._meta.entity, FTS4_MATCHINFO) return fn.fts_bm25f(match_info, *weights) @classmethod def lucene(cls, *weights): match_info = fn.matchinfo(cls._meta.entity, FTS4_MATCHINFO) 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.sorted_fields: # Attempt to get the specified weight of the field by looking # it up using it's field instance followed by name. field_weight = weights.get(field, weights.get(field.name, 1.0)) weight_args.append(field_weight) 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_bm25f(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.bm25f, 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 ,"(){}*:_+0123456789') | set(_alphabet) | set(_alphabet.upper()) | set((chr(26),))) _invalid_ascii = set(chr(p) for p in range(128) if chr(p) not in _alphanum) del _alphabet del _alphanum _quote_re = re.compile(r'(?:[^\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_SQLITE_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: tmp_db.enable_load_extension(True) tmp_db.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._meta.entity, term) @classmethod def rank(cls, *args): return cls.bm25(*args) if args else SQL('rank') @classmethod def bm25(cls, *weights): return fn.bm25(cls._meta.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.sorted_fields: if isinstance(field, SearchField) and not field.unindexed: weight_args.append( weights.get(field, weights.get(field.name, 1.0))) rank = fn.bm25(cls._meta.entity, *weight_args) else: rank = fn.bm25(cls._meta.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_sql(cls, cmd, **extra_params): tbl = cls._meta.entity columns = [tbl] values = [cmd] for key, value in extra_params.items(): columns.append(Entity(key)) values.append(value) return NodeList(( SQL('INSERT INTO'), cls._meta.entity, EnclosedNodeList(columns), SQL('VALUES'), EnclosedNodeList(values))) @classmethod def _fts_cmd(cls, cmd, **extra_params): query = cls._fts_cmd_sql(cmd, **extra_params) return cls._meta.database.execute(query) @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 optimize(cls): return cls._fts_cmd('optimize') @classmethod def rebuild(cls): return cls._fts_cmd('rebuild') @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 integrity_check(cls, rank=0): return cls._fts_cmd('integrity-check', rank=rank) @classmethod def VocabModel(cls, table_type='row', table=None): if table_type not in ('row', 'col', 'instance'): raise ValueError('table_type must be either "row", "col" or ' '"instance".') attr = '_vocab_model_%s' % table_type if not hasattr(cls, attr): class Meta: database = cls._meta.database table_name = table or cls._meta.table_name + '_v' extension_module = fn.fts5vocab( cls._meta.entity, SQL(table_type)) attrs = { 'term': VirtualField(TextField), 'doc': IntegerField(), 'cnt': IntegerField(), 'rowid': RowIDField(), 'Meta': Meta, } if table_type == 'col': attrs['col'] = VirtualField(TextField) elif table_type == 'instance': attrs['offset'] = VirtualField(IntegerField) class_name = '%sVocab' % cls.__name__ setattr(cls, attr, type(class_name, (VirtualModel,), attrs)) return getattr(cls, attr) def ClosureTable(model_class, foreign_key=None, referencing_class=None, referencing_key=None): """Model factory for the transitive closure extension.""" if referencing_class is None: referencing_class = model_class if foreign_key is None: for field_obj in model_class._meta.refs: if field_obj.rel_model is model_class: foreign_key = field_obj break else: raise ValueError('Unable to find self-referential foreign key.') source_key = model_class._meta.primary_key if referencing_key is None: referencing_key = source_key class BaseClosureTable(VirtualModel): depth = VirtualField(IntegerField) id = VirtualField(IntegerField) idcolumn = VirtualField(TextField) parentcolumn = VirtualField(TextField) root = VirtualField(IntegerField) tablename = VirtualField(TextField) 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=(source_key == cls.id)) .where(cls.root == node) .objects()) 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=(source_key == cls.root)) .where(cls.id == node) .objects()) 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): if referencing_class is model_class: # self-join fk_value = node.__data__.get(foreign_key.name) query = model_class.select().where(foreign_key == fk_value) else: # siblings as given in reference_class siblings = (referencing_class .select(referencing_key) .join(cls, on=(foreign_key == cls.root)) .where((cls.id == node) & (cls.depth == 1))) # the according models query = (model_class .select() .where(source_key << siblings) .objects()) if not include_node: query = query.where(source_key != node) return query class Meta: database = referencing_class._meta.database options = { 'tablename': referencing_class._meta.table_name, 'idcolumn': referencing_key.column_name, 'parentcolumn': foreign_key.column_name} primary_key = False name = '%sClosure' % model_class.__name__ return type(name, (BaseClosureTable,), {'Meta': Meta}) class LSMTable(VirtualModel): class Meta: extension_module = 'lsm1' filename = None @classmethod def clean_options(cls, options): filename = cls._meta.filename if not filename: raise ValueError('LSM1 extension requires that you specify a ' 'filename for the LSM database.') else: if len(filename) >= 2 and filename[0] != '"': filename = '"%s"' % filename if not cls._meta.primary_key: raise ValueError('LSM1 models must specify a primary-key field.') key = cls._meta.primary_key if isinstance(key, AutoField): raise ValueError('LSM1 models must explicitly declare a primary ' 'key field.') if not isinstance(key, (TextField, BlobField, IntegerField)): raise ValueError('LSM1 key must be a TextField, BlobField, or ' 'IntegerField.') key._hidden = True if isinstance(key, IntegerField): data_type = 'UINT' elif isinstance(key, BlobField): data_type = 'BLOB' else: data_type = 'TEXT' cls._meta.prefix_arguments = [filename, '"%s"' % key.name, data_type] # Does the key map to a scalar value, or a tuple of values? if len(cls._meta.sorted_fields) == 2: cls._meta._value_field = cls._meta.sorted_fields[1] else: cls._meta._value_field = None return options @classmethod def load_extension(cls, path='lsm.so'): cls._meta.database.load_extension(path) @staticmethod def slice_to_expr(key, idx): if idx.start is not None and idx.stop is not None: return key.between(idx.start, idx.stop) elif idx.start is not None: return key >= idx.start elif idx.stop is not None: return key <= idx.stop @staticmethod def _apply_lookup_to_query(query, key, lookup): if isinstance(lookup, slice): expr = LSMTable.slice_to_expr(key, lookup) if expr is not None: query = query.where(expr) return query, False elif isinstance(lookup, Expression): return query.where(lookup), False else: return query.where(key == lookup), True @classmethod def get_by_id(cls, pk): query, is_single = cls._apply_lookup_to_query( cls.select().namedtuples(), cls._meta.primary_key, pk) if is_single: row = query.get() return row[1] if cls._meta._value_field is not None else row else: return query @classmethod def set_by_id(cls, key, value): if cls._meta._value_field is not None: data = {cls._meta._value_field: value} elif isinstance(value, tuple): data = {} for field, fval in zip(cls._meta.sorted_fields[1:], value): data[field] = fval elif isinstance(value, dict): data = value elif isinstance(value, cls): data = value.__dict__ data[cls._meta.primary_key] = key cls.replace(data).execute() @classmethod def delete_by_id(cls, pk): query, is_single = cls._apply_lookup_to_query( cls.delete(), cls._meta.primary_key, pk) return query.execute() OP.MATCH = 'MATCH' def _sqlite_regexp(regex, value): return re.search(regex, value) is not None class SqliteExtDatabase(SqliteDatabase): def __init__(self, database, c_extensions=None, rank_functions=True, hash_functions=False, regexp_function=False, bloomfilter=False, json_contains=False, *args, **kwargs): super(SqliteExtDatabase, self).__init__(database, *args, **kwargs) self._row_factory = None if c_extensions and not CYTHON_SQLITE_EXTENSIONS: raise ImproperlyConfigured('SqliteExtDatabase initialized with ' 'C extensions, but shared library was ' 'not found!') prefer_c = CYTHON_SQLITE_EXTENSIONS and (c_extensions is not False) if rank_functions: if prefer_c: register_rank_functions(self) else: self.register_function(bm25, 'fts_bm25') self.register_function(rank, 'fts_rank') self.register_function(bm25, 'fts_bm25f') # Fall back to bm25. self.register_function(bm25, 'fts_lucene') if hash_functions: if not prefer_c: raise ValueError('C extension required to register hash ' 'functions.') register_hash_functions(self) if regexp_function: self.register_function(_sqlite_regexp, 'regexp', 2) if bloomfilter: if not prefer_c: raise ValueError('C extension required to use bloomfilter.') register_bloomfilter(self) if json_contains: self.register_function(_json_contains, 'json_contains') self._c_extensions = prefer_c def _add_conn_hooks(self, conn): super(SqliteExtDatabase, self)._add_conn_hooks(conn) if self._row_factory: conn.row_factory = self._row_factory def row_factory(self, fn): self._row_factory = fn if CYTHON_SQLITE_EXTENSIONS: SQLITE_STATUS_MEMORY_USED = 0 SQLITE_STATUS_PAGECACHE_USED = 1 SQLITE_STATUS_PAGECACHE_OVERFLOW = 2 SQLITE_STATUS_SCRATCH_USED = 3 SQLITE_STATUS_SCRATCH_OVERFLOW = 4 SQLITE_STATUS_MALLOC_SIZE = 5 SQLITE_STATUS_PARSER_STACK = 6 SQLITE_STATUS_PAGECACHE_SIZE = 7 SQLITE_STATUS_SCRATCH_SIZE = 8 SQLITE_STATUS_MALLOC_COUNT = 9 SQLITE_DBSTATUS_LOOKASIDE_USED = 0 SQLITE_DBSTATUS_CACHE_USED = 1 SQLITE_DBSTATUS_SCHEMA_USED = 2 SQLITE_DBSTATUS_STMT_USED = 3 SQLITE_DBSTATUS_LOOKASIDE_HIT = 4 SQLITE_DBSTATUS_LOOKASIDE_MISS_SIZE = 5 SQLITE_DBSTATUS_LOOKASIDE_MISS_FULL = 6 SQLITE_DBSTATUS_CACHE_HIT = 7 SQLITE_DBSTATUS_CACHE_MISS = 8 SQLITE_DBSTATUS_CACHE_WRITE = 9 SQLITE_DBSTATUS_DEFERRED_FKS = 10 #SQLITE_DBSTATUS_CACHE_USED_SHARED = 11 def __status__(flag, return_highwater=False): """ Expose a sqlite3_status() call for a particular flag as a property of the Database object. """ def getter(self): result = sqlite_get_status(flag) return result[1] if return_highwater else result return property(getter) def __dbstatus__(flag, return_highwater=False, return_current=False): """ Expose a sqlite3_dbstatus() call for a particular flag as a property of the Database instance. Unlike sqlite3_status(), the dbstatus properties pertain to the current connection. """ def getter(self): if self._state.conn is None: raise ImproperlyConfigured('database connection not opened.') result = sqlite_get_db_status(self._state.conn, flag) if return_current: return result[0] return result[1] if return_highwater else result return property(getter) class CSqliteExtDatabase(SqliteExtDatabase): def __init__(self, *args, **kwargs): self._conn_helper = None self._commit_hook = self._rollback_hook = self._update_hook = None self._replace_busy_handler = False super(CSqliteExtDatabase, self).__init__(*args, **kwargs) def init(self, database, replace_busy_handler=False, **kwargs): super(CSqliteExtDatabase, self).init(database, **kwargs) self._replace_busy_handler = replace_busy_handler def _close(self, conn): if self._commit_hook: self._conn_helper.set_commit_hook(None) if self._rollback_hook: self._conn_helper.set_rollback_hook(None) if self._update_hook: self._conn_helper.set_update_hook(None) return super(CSqliteExtDatabase, self)._close(conn) def _add_conn_hooks(self, conn): super(CSqliteExtDatabase, self)._add_conn_hooks(conn) self._conn_helper = ConnectionHelper(conn) if self._commit_hook is not None: self._conn_helper.set_commit_hook(self._commit_hook) if self._rollback_hook is not None: self._conn_helper.set_rollback_hook(self._rollback_hook) if self._update_hook is not None: self._conn_helper.set_update_hook(self._update_hook) if self._replace_busy_handler: timeout = self._timeout or 5 self._conn_helper.set_busy_handler(timeout * 1000) def on_commit(self, fn): self._commit_hook = fn if not self.is_closed(): self._conn_helper.set_commit_hook(fn) return fn def on_rollback(self, fn): self._rollback_hook = fn if not self.is_closed(): self._conn_helper.set_rollback_hook(fn) return fn def on_update(self, fn): self._update_hook = fn if not self.is_closed(): self._conn_helper.set_update_hook(fn) return fn def changes(self): return self._conn_helper.changes() @property def last_insert_rowid(self): return self._conn_helper.last_insert_rowid() @property def autocommit(self): return self._conn_helper.autocommit() def backup(self, destination, pages=None, name=None, progress=None): return backup(self.connection(), destination.connection(), pages=pages, name=name, progress=progress) def backup_to_file(self, filename, pages=None, name=None, progress=None): return backup_to_file(self.connection(), filename, pages=pages, name=name, progress=progress) def blob_open(self, table, column, rowid, read_only=False): return Blob(self, table, column, rowid, read_only) # Status properties. memory_used = __status__(SQLITE_STATUS_MEMORY_USED) malloc_size = __status__(SQLITE_STATUS_MALLOC_SIZE, True) malloc_count = __status__(SQLITE_STATUS_MALLOC_COUNT) pagecache_used = __status__(SQLITE_STATUS_PAGECACHE_USED) pagecache_overflow = __status__(SQLITE_STATUS_PAGECACHE_OVERFLOW) pagecache_size = __status__(SQLITE_STATUS_PAGECACHE_SIZE, True) scratch_used = __status__(SQLITE_STATUS_SCRATCH_USED) scratch_overflow = __status__(SQLITE_STATUS_SCRATCH_OVERFLOW) scratch_size = __status__(SQLITE_STATUS_SCRATCH_SIZE, True) # Connection status properties. lookaside_used = __dbstatus__(SQLITE_DBSTATUS_LOOKASIDE_USED) lookaside_hit = __dbstatus__(SQLITE_DBSTATUS_LOOKASIDE_HIT, True) lookaside_miss = __dbstatus__(SQLITE_DBSTATUS_LOOKASIDE_MISS_SIZE, True) lookaside_miss_full = __dbstatus__(SQLITE_DBSTATUS_LOOKASIDE_MISS_FULL, True) cache_used = __dbstatus__(SQLITE_DBSTATUS_CACHE_USED, False, True) #cache_used_shared = __dbstatus__(SQLITE_DBSTATUS_CACHE_USED_SHARED, # False, True) schema_used = __dbstatus__(SQLITE_DBSTATUS_SCHEMA_USED, False, True) statement_used = __dbstatus__(SQLITE_DBSTATUS_STMT_USED, False, True) cache_hit = __dbstatus__(SQLITE_DBSTATUS_CACHE_HIT, False, True) cache_miss = __dbstatus__(SQLITE_DBSTATUS_CACHE_MISS, False, True) cache_write = __dbstatus__(SQLITE_DBSTATUS_CACHE_WRITE, False, True) 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)] def get_weights(ncol, raw_weights): if not raw_weights: return [1] * ncol else: weights = [0] * ncol for i, weight in enumerate(raw_weights): weights[i] = weight return weights # Ranking implementation, which parse matchinfo. def rank(raw_match_info, *raw_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] weights = get_weights(c, raw_weights) # matchinfo X value corresponds to, for each phrase in the search query, a # list of 3 values for each column in the search table. # So if we have a two-phrase search query and three columns of data, the # following would be the layout: # p0 : c0=[0, 1, 2], c1=[3, 4, 5], c2=[6, 7, 8] # p1 : c0=[9, 10, 11], c1=[12, 13, 14], c2=[15, 16, 17] 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) # The idea is that we count the number of times the phrase appears # in this column of the current row, compared to how many times it # appears in this column across all rows. The ratio of these values # provides a rough way to score based on "high value" terms. row_hits = match_info[col_idx] all_rows_hits = match_info[col_idx + 1] if row_hits > 0: score += weight * (float(row_hits) / all_rows_hits) 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) # Offsets into the matchinfo buffer. term_count = match_info[P_O] # n col_count = match_info[C_O] total_docs = match_info[N_O] # N L_O = A_O + col_count X_O = L_O + col_count # Worked example of pcnalx for two columns and two phrases, 100 docs total. # { # p = 2 # c = 2 # n = 100 # a0 = 4 -- avg number of tokens for col0, e.g. title # a1 = 40 -- avg number of tokens for col1, e.g. body # l0 = 5 -- curr doc has 5 tokens in col0 # l1 = 30 -- curr doc has 30 tokens in col1 # # x000 -- hits this row for phrase0, col0 # x001 -- hits all rows for phrase0, col0 # x002 -- rows with phrase0 in col0 at least once # # x010 -- hits this row for phrase0, col1 # x011 -- hits all rows for phrase0, col1 # x012 -- rows with phrase0 in col1 at least once # # x100 -- hits this row for phrase1, col0 # x101 -- hits all rows for phrase1, col0 # x102 -- rows with phrase1 in col0 at least once # # x110 -- hits this row for phrase1, col1 # x111 -- hits all rows for phrase1, col1 # x112 -- rows with phrase1 in col1 at least once # } weights = get_weights(col_count, args) for i in range(term_count): for j in range(col_count): weight = weights[j] if weight == 0: continue x = X_O + (3 * (j + i * col_count)) term_frequency = float(match_info[x]) # f(qi, D) docs_with_term = float(match_info[x + 2]) # n(qi) # log( (N - n(qi) + 0.5) / (n(qi) + 0.5) ) idf = math.log( (total_docs - docs_with_term + 0.5) / (docs_with_term + 0.5)) if idf <= 0.0: idf = 1e-6 doc_length = float(match_info[L_O + j]) # |D| avg_length = float(match_info[A_O + j]) or 1. # avgdl ratio = doc_length / avg_length num = term_frequency * (K + 1.0) b_part = 1.0 - B + (B * ratio) denom = term_frequency + (K * b_part) pc_score = idf * (num / denom) score += (pc_score * weight) return -score def _json_contains(src_json, obj_json): stack = [] try: stack.append((json.loads(obj_json), json.loads(src_json))) except: # Invalid JSON! return False while stack: obj, src = stack.pop() if isinstance(src, dict): if isinstance(obj, dict): for key in obj: if key not in src: return False stack.append((obj[key], src[key])) elif isinstance(obj, list): for item in obj: if item not in src: return False elif obj not in src: return False elif isinstance(src, list): if isinstance(obj, dict): return False elif isinstance(obj, list): try: for i in range(len(obj)): stack.append((obj[i], src[i])) except IndexError: return False elif obj not in src: return False elif obj != src: return False return True