systex_phase2/file_loader/gsheet2neo4j.py

import pandas as pd

from py2neo import Graph
from py2neo import NodeMatcher, RelationshipMatcher
from py2neo import Node, Relationship
from py2neo.matching import NodeMatcher

# Neo4j connection settings
NEO4J_URL = "bolt://cmm.ai:7687"
NEO4J_USERNAME = "neo4j"
NEO4J_PASSWORD = "chuz8310xsystex"

# Initialize the Neo4j graph database connection
graph = Graph(NEO4J_URL, auth=(NEO4J_USERNAME, NEO4J_PASSWORD))

import pandas as pd
sheet_id ="1ltqF8KfHYin90SFfLnaTATZyLVqjJgbEJmszyV6_2JE"
gid = "1280923991"
df = pd.read_csv(f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv&gid={gid}")

import pandas as pd
sheet_id ="1ltqF8KfHYin90SFfLnaTATZyLVqjJgbEJmszyV6_2JE"
gid = "168214340"
df = pd.read_csv(f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv&gid={gid}")

def get_property_text(row):
    # df_property = df.iloc[:, 3:]
    properties = {k: v for k, v in row[3:].items() if pd.notna(v)}
    properties["id"] = row['Node']

    property_list = []
    for k, v in properties.items():
        property_list.append(f"{k.strip().replace(' ', '_')}: '{v}'")
    property_text = f"{{{', '.join(property_list)}}}"

    # records = df_property.apply(lambda row: {k: v for k, v in row.items() if pd.notna(v)}, axis=1).tolist()
    # df['properties'] = properties

    return property_text

def get_label_text(row):
    if pd.notna(row['label list']):
        labels = ":__Entity__:" + row['label list'].replace(" ","").replace(",", ":")
    else:
        labels = ":__Entity__"
    return labels

def create_query_for_each_row(row):
    # (`溫室氣體`:定義 {id: "溫室氣體"}),
    node = row['Node']
    labels = get_label_text(row)
    property = get_property_text(row)

    query = f'(`{node}`{labels} {property})'

    return query
    # print("The Node is %s" % row["Node"])
    
def bulk_create_query():
    sheet_id ="1ltqF8KfHYin90SFfLnaTATZyLVqjJgbEJmszyV6_2JE"
    gid = "1280923991"
    df = pd.read_csv(f"https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv&gid={gid}")

    query = df.apply(create_query_for_each_row, axis = 1).to_list()
    create_query = "CREATE\n" + ',\n'.join(query)

    return create_query

def create_node():
    query = bulk_create_query()
    graph.run(query)