# -*- coding: utf-8 -*- import re import warnings import bson from bson.son import SON from collections import OrderedDict import pymongo from pymongo.errors import BulkWriteError import urllib from lodel import logger from .utils import object_collection_name, connect, \ MONGODB_SORT_OPERATORS_MAP, connection_string class MongoDbDataSourceError(Exception): pass class MongoDbDatasource(object): ##@brief Stores existing connections # #The key of this dict is a hash of the connection string + ro parameter. #The value is a dict with 2 keys : # - conn_count : the number of instanciated datasource that use this #connection # - db : the pymongo database object instance _connections = dict() ##@brief Mapping from lodel2 operators to mongodb operator lodel2mongo_op_map = { '=':'$eq', '<=':'$lte', '>=':'$gte', '!=':'$ne', '<':'$lt', '>':'$gt', 'in':'$in', 'not in':'$nin' } ##@brief List of mongodb operators that expect re as value mongo_op_re = ['$in', '$nin'] wildcard_re = re.compile('[^\\\\]\*') ##@brief instanciates a database object given a connection name #@param host str : hostname or IP #@param port int : mongodb listening port #@param db_name str #@param username str #@param password str #@param ro bool : If True the Datasource is for read only, else the #Datasource is write only ! def __init__(self, host, port, db_name, username, password, read_only = False): ##@brief Connections infos that can be kept securly self.__db_infos = {'host': host, 'port': port, 'db_name': db_name} ##@brief Is the instance read only ? (if not it's write only) self.__read_only = bool(read_only) ##@brief Uniq ID for mongodb connection self.__conn_hash= None ##@brief Stores the connection to MongoDB self.database = self.__connect(username, password) ##@brief Destructor that attempt to close connection to DB # #Decrease the conn_count of associated MongoDbDatasource::_connections #item. If it reach 0 close the connection to the db #@see MongoDbDatasource::__connect() def __del__(self): self._connections[self.__conn_hash]['conn_count'] -= 1 if self._connections[self.__conn_hash]['conn_count'] <= 0: self._connections[self.__conn_hash]['db'].close() del(self._connections[self.__conn_hash]) ##@brief returns a selection of documents from the datasource #@param target Emclass #@param field_list list #@param filters list : List of filters #@param rel_filters list : List of relational filters #@param order list : List of column to order. ex: order = [('title', 'ASC'),] #@param group list : List of tupple representing the column used as "group by" fields. ex: group = [('title', 'ASC'),] #@param limit int : Number of records to be returned #@param offset int: used with limit to choose the start record #@param instanciate bool : If true, the records are returned as instances, else they are returned as dict #@return list #@todo Implement the relations def select(self, target, field_list, filters, rel_filters=None, order=None, group=None, limit=None, offset=0): collection_name = object_collection_name(target) collection = self.database[collection_name] query_filters = self.__process_filters( target, filters, relational_filters) query_result_ordering = None if order is not None: query_result_ordering = parse_query_order(order) results_field_list = None if len(field_list) == 0 else field_list limit = limit if limit is not None else 0 if group is None: cursor = collection.find( filter=query_filters, projection=results_field_list, skip=offset, limit=limit, sort=query_result_ordering) else: pipeline = list() unwinding_list = list() grouping_dict = OrderedDict() sorting_list = list() for group_param in group: field_name = group_param[0] field_sort_option = group_param[1] sort_option = MONGODB_SORT_OPERATORS_MAP[field_sort_option] unwinding_list.append({'$unwind': '$%s' % field_name}) grouping_dict[field_name] = '$%s' % field_name sorting_list.append((field_name, sort_option)) sorting_list.extends(query_result_ordering) pipeline.append({'$match': query_filters}) if results_field_list is not None: pipeline.append({ '$project': SON([{field_name: 1} for field_name in field_list])}) pipeline.extend(unwinding_list) pipeline.append({'$group': grouping_dict}) pipeline.extend({'$sort': SON(sorting_list)}) if offset > 0: pipeline.append({'$skip': offset}) if limit is not None: pipeline.append({'$limit': limit}) results = list() for document in cursor: results.append(document) return results ##@brief Deletes records according to given filters #@param target Emclass : class of the record to delete #@param filters list : List of filters #@param relational_filters list : List of relational filters #@return int : number of deleted records def delete(self, target, filters, relational_filters): mongo_filters = self.__process_filters( target, filters, relational_filters) res = self.__collection(target).delete_many(mongo_filters) return res.deleted_count ## @brief updates records according to given filters #@param target Emclass : class of the object to insert #@param filters list : List of filters #@param rel_filters list : List of relational filters #@param upd_datas dict : datas to update (new values) #@return int : Number of updated records def update(self, target, filters, relational_filters, upd_datas): mongo_filters = self.__process_filters( target, filters, relational_filters) res = self.__collection(target).update_many(mongo_filters, upd_datas) return res.modified_count() ## @brief Inserts a record in a given collection # @param target Emclass : class of the object to insert # @param new_datas dict : datas to insert # @return the inserted uid def insert(self, target, new_datas): res = self.__collection(target).insert_one(new_datas) return res.inserted_id ## @brief Inserts a list of records in a given collection # @param target Emclass : class of the objects inserted # @param datas_list list : list of dict # @return list : list of the inserted records' ids def insert_multi(self, target, datas_list): res = self.__collection.insert_many(datas_list) return list(result.inserted_ids) ##@brief Connect to database #@not this method avoid opening two times the same connection using #MongoDbDatasource::_connections static attribute #@param host str : hostname or IP #@param port int : mongodb listening port #@param db_name str #@param username str #@param password str #@param ro bool : If True the Datasource is for read only, else the def __connect(self, username, password, ro): conn_string = connection_string( username = username, password = password, **self.__db_infos) conn_string += "__ReadOnly__:"+self.__read_only self.__conf_hash = conn_h = hash(conn_string) if conn_h in self._connections: self._connections[conn_h]['conn_count'] += 1 return self._connections[conn_h]['db'] ##@brief Return a pymongo collection given a LeObject child class #@param leobject LeObject child class (no instance) #return a pymongo.collection instance def __collection(self, leobject): return self.database[object_collection_name(leobject)] ##@brief Perform subqueries implies by relational filters and append the # result to existing filters # #The processing is divided in multiple steps : # - determine (for each relational field of the target) every collection #that are involved # - generate subqueries for relational_filters that concerns a different #collection than target collection #filters # - execute subqueries # - transform subqueries results in filters # - merge subqueries generated filters with existing filters # #@param target LeObject subclass (no instance) : Target class #@param filters list : List of tuple(FIELDNAME, OP, VALUE) #@param relational_filters : same composition thant filters except that # FIELD is represented by a tuple(FIELDNAME, {CLASS1:RFIELD1, # CLASS2:RFIELD2}) #@return a list of pymongo filters ( dict {FIELD:{OPERATOR:VALUE}} ) def __process_filters(self,target, filters, relational_filters): # Simple filters lodel2 -> pymongo converting res = [convert_filter(filt) for filt in filters] rfilters = self.__prepare_relational_filters(relational_filters) #Now that everything is well organized, begin to forge subquerie #filters subq_filters = self.__subqueries_from_relational_filters( target, rfilters) # Executing subqueries, creating filters from result, and injecting # them in original filters of the query if len(subq_filters) > 0: logger.debug("Begining subquery execution") for fname in subq_filters: if fname not in res: res[fname] = dict() subq_results = set() for leobject, sq_filters in subq_filters[fname].items(): uid_fname = mongo_fieldname(leobject._uid) log_msg = "Subquery running on collection {coll} with filters \ '{filters}'" logger.debug(log_msg.format( coll=object_collection_name(leobject), filters=sq_filters)) cursor = self.__collection(leobject).find( filter=sq_filters, projection=uid_fname) subq_results |= set(doc[uid_fname] for doc in cursor) #generating new filter from result if '$in' in res[fname]: #WARNING we allready have a IN on this field, doing dedup #from result deduped = set(res[fname]['$in']) & subq if len(deduped) == 0: del(res[fname]['$in']) else: res[fname]['$in'] = list(deduped) else: res[fname]['$in'] = list(subq_results) if len(subq_filters) > 0: logger.debug("End of subquery execution") return res ##@brief Generate subqueries from rfilters tree # #Returned struct organization : # - 1st level keys : relational field name of target # - 2nd level keys : referenced leobject # - 3th level values : pymongo filters (dict) # #@note The only caller of this method is __process_filters #@warning No return value, the rfilters arguement is modified by #reference # #@param target LeObject subclass (no instance) : Target class #@param rfilters dict : A struct as returned by #MongoDbDatasource.__prepare_relational_filters() #@return None, the rfilters argument is modified by reference def __subqueries_from_relational_filters(self, target, rfilters): for fname in rfilters: for leobject in rfilters[fname]: for rfield in rfilters[fname][leobject]: #This way of doing is not optimized but allows to trigger #warnings in some case (2 different values for a same op #on a same field on a same collection) mongofilters = self.__op_value_listconv( rfilters[fname][leobject][rfield]) rfilters[fname][leobject][rfield] = mongofilters ##@brief Generate a tree from relational_filters # #The generated struct is a dict with : # - 1st level keys : relational field name of target # - 2nd level keys : referenced leobject # - 3th level keys : referenced field in referenced class # - 4th level values : list of tuple(op, value) # #@note The only caller of this method is __process_filters #@warning An assertion is done : if two leobject are stored in the same #collection they share the same uid # #@param target LeObject subclass (no instance) : Target class #@param relational_filters : same composition thant filters except that #@return a struct as described above def __prepare_relational_filters(self, target, relational_filters): # We are going to regroup relationnal filters by reference field # then by collection rfilters = dict() for (fname, rfields), op, value in relational_filters: if fname not in rfilters: rfilters[fname] = dict() rfilters[fname] = dict() # Stores the representative leobject for associated to a collection # name leo_collname = dict() # WARNING ! Here we assert that all leobject that are stored # in a same collection are identified by the same field for leobject, rfield in rfields.items(): #here we are filling a dict with leobject as index but #we are doing a UNIQ on collection name cur_collname = object_collection_name(leobject) if cur_collname not in collnames: leo_collname[cur_collame] = leobject rfilters[fname][leobject] = dict() #Fecthing the collection's representative leobject repr_leo = leo_collname[cur_collname] if rfield not in rfilters[fname][repr_leo]: rfilters[fname][repr_leo][rfield] = list() rfilters[fname][repr_leo][rfield].append((op, value)) return rfilters ##@brief Convert lodel2 operator and value to pymongo struct # #Convertion is done using MongoDbDatasource::lodel2mongo_op_map #@param op str : take value in LeFilteredQuery::_query_operators #@param value mixed : the value #@return a tuple(mongo_op, mongo_value) def __op_value_conv(self, op, value): if op not in self.lodel2mongo_op_map: msg = "Invalid operator '%s' found" % op raise MongoDbDataSourceError(msg) mongop = self.lodel2mongo_op_map[op] mongoval = value #Converting lodel2 wildcarded string into a case insensitive #mongodb re if mongop in self.mon_op_re: #unescaping \ mongoval = value.replace('\\\\','\\') if not mongoval.startswith('*'): mongoval = '^'+mongoval #For the end of the string it's harder to detect escaped * if not (mongoval[-1] == '*' and mongoval[-2] != '\\'): mongoval += '$' #Replacing every other unescaped wildcard char mongoval = self.wildcard_re.sub('.*', mongoval) mongoval = {'$regex': mongoval, '$options': 'i'} return (op, mongoval) ##@brief Convert a list of tuple(OP, VALUE) into a pymongo filter dict #@return a dict with mongo op as key and value as value... def __op_value_listconv(self, op_value_list): result = dict() for op, value in op_value_list: mongop, mongoval = self.__op_value_conv(op, value) if mongop in result: warnings.warn("Duplicated value given for a single \ field/operator couple in a query. We will keep only the first one") else: result[mongop] = mongoval return result