Importer un fichier de données hiérarchiques CSV vers Neo4j.py

Question

Je me demande s'il existe un script Python pour importer le fichier de données hiérarchiques csv dans neo4j.py.

J'ai fait le script python ci-dessous, mais j'ai besoin d'un meilleur moyen de vérifier si un noeud est déjà créé avant de le créer.

graphdb = neo4j.GraphDatabase(lparam_database_path, classpath=lparam_kernel_class_path, jvm=lparam_jvm_path, heap_size=ls_jvm_heap_size) 

with graphdb.transaction: 
    sectornode = Subreference.Node.SECTOR_ROOT(graphdb, label="Sectors", level=1) 
    categorynode = graphdb.node(label="Categories", level=2) 
    productnode = graphdb.node(label="Products", level=3) 
    brandnode = graphdb.node(label="Brands", level=4) 
    subbrandnode = graphdb.node(label="Subbrands", level=5) 

    relationship1 = sectornode.CATEGORY_ROOT(categorynode) 
    relationship2 = categorynode.PRODUCT_ROOT(productnode) 
    relationship3 = productnode.BRAND_ROOT(brandnode) 
    relationship4 = brandnode.SUBBRAND_ROOT(subbrandnode) 

    li_index = 0 
    ls_last_sector = "" 
    ls_last_category = "" 
    ls_last_product = "" 
    ls_last_brand = "" 
    ls_last_subbrand = "" 
    for data in data_list: 
     li_index = li_index + 1 
     print "importing row " + str(li_index) + " of " + str(li_total_rows) 

     if data[0] != ls_last_sector: 
      tempsectornode = graphdb.node(label=data[0]) 
      lastsectornode = tempsectornode 
     if data[1] != ls_last_category or data[0] != ls_last_sector: 
      tempcategorynode = graphdb.node(label=data[1]) 
      lastcategorynode = tempcategorynode 
     if data[2] != ls_last_product or data[1] != ls_last_category or data[0] != ls_last_sector: 
      tempproductnode = graphdb.node(label=data[2]) 
      lastproductnode = tempproductnode 
     if data[3] != ls_last_brand or data[2] != ls_last_product or data[1] != ls_last_category or data[0] != ls_last_sector: 
      tempbrandnode = graphdb.node(label=data[3]) 
      lastbrandnode = tempbrandnode 
     if data[4] != ls_last_subbrand or data[3] != ls_last_brand or data[2] != ls_last_product or data[1] != ls_last_category or data[0] != ls_last_sector: 
      tempsubbrandnode = graphdb.node(label=data[4]) 
      lastsubbrandnode = tempsubbrandnode 

     temprelationship1 = tempsectornode.OFTYPE(sectornode) 
     temprelationship2 = tempcategorynode.OFTYPE(categorynode) 
     temprelationship3 = tempproductnode.OFTYPE(productnode) 
     temprelationship4 = tempbrandnode.OFTYPE(brandnode) 
     temprelationship5 = tempsubbrandnode.OFTYPE(subbrandnode) 

     temprelationship6 = tempcategorynode.MEMBEROF(tempsectornode) 
     temprelationship7 = tempproductnode.MEMBEROF(tempcategorynode) 
     temprelationship8 = tempbrandnode.MEMBEROF(tempproductnode) 
     temprelationship9 = tempsubbrandnode.MEMBEROF(tempbrandnode) 

     ls_last_sector = data[0] 
     ls_last_category = data[1] 
     ls_last_product = data[2] 
     ls_last_brand = data[3] 
     ls_last_subbrand = data[4] 

graphdb.shutdown() 

Answer 1

Vous devriez être en mesure d'indexer le noeud après sa création, puis vérifier via l'API d'index s'il existe déjà. Je n'ai pas l'API neo4j.py à portée de main mais elle devrait exposer cette fonctionnalité. approche principe

(en Java) est:

graphDatabase.index().forNodes("index-name"); 
index.add(node, "key","value"); 

Node node=index.get("key","value").getSingle();