def load_and_merge(yaml_file: str) -> Transformer:
    """Load and merge sources defined in the config YAML.

    Args:
        yaml_file: A string pointing to a KGX compatible config YAML.

    Returns:
        kgx.Transformer: The merged transformer that contains the merged graph.

    """
    config = parse_load_config(yaml_file)
    transformers: List = []

    # read all the sources defined in the YAML
    for key in config['target']:
        target = config['target'][key]
        logging.info("Loading {}".format(key))
        if target['type'] in get_file_types():
            # loading from a file
            transformer = get_transformer(target['type'])()
            for f in target['filename']:
                transformer.parse(f, input_format='tsv')
            transformers.append(transformer)
        elif target['type'] == 'neo4j':
            transformer = NeoTransformer(None, target['uri'],
                                         target['username'],
                                         target['password'])
            transformer.load()
            transformers.append(transformer)
        else:
            logging.error("type {} not yet supported".format(target['type']))

    # merge all subgraphs into a single graph
    merged_transformer = Transformer()
    merged_transformer.merge_graphs([x.graph for x in transformers])
    merged_transformer.report()

    # write the merged graph
    if 'destination' in config:
        destination = config['destination']
        if destination['type'] in ['csv', 'tsv', 'ttl', 'json', 'tar']:
            destination_transformer = get_transformer(destination['type'])(
                merged_transformer.graph)
            destination_transformer.save(destination['filename'],
                                         extension=destination['type'])
        elif destination['type'] == 'neo4j':
            destination_transformer = NeoTransformer(
                merged_transformer.graph,
                uri=destination['uri'],
                username=destination['username'],
                password=destination['password'])
            destination_transformer.save_with_unwind()
        else:
            logging.error(
                "type {} not yet supported for KGX load-and-merge operation.".
                format(destination['type']))

    return merged_transformer
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def test_neo_to_graph_upload():
    """ loads a neo4j graph from a json file
    """
    jt = JsonTransformer()
    jt.parse('resources/robodb2.json')

    nt = NeoTransformer(jt.graph, host='localhost', port='7474', username='******', password='******')
    nt.save_with_unwind()
    nt.neo4j_report()
Exemple #3
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def test_csv_to_neo_load():
    """
    load csv to neo4j test
    """
    pt = PandasTransformer()
    pt.parse(os.path.join(resource_dir, "cm_nodes.csv"))
    pt.parse(os.path.join(resource_dir, "cm_edges.csv"))
    nt = NeoTransformer(pt.graph, host='localhost', port='7474', username='******', password='******')
    nt.save_with_unwind()
    nt.neo4j_report()
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def test_csv_to_neo_load():
    """
    load csv to neo4j test
    """
    pt = PandasTransformer()
    pt.parse("resources/x1n.csv")
    pt.parse("resources/x1e.csv")
    nt = NeoTransformer(pt.graph,
                        host='http://localhost',
                        port='7474',
                        username='******',
                        password='******')
    nt.save_with_unwind()
    nt.neo4j_report()
Exemple #5
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def test_csv_to_neo_load():
    """
    load csv to neo4j test
    """
    return

    pt = PandasTransformer()
    pt.parse("resources/nodes.csv")
    pt.parse("resources/edges.csv")
    nt = NeoTransformer(pt.graph,
                        host='localhost',
                        port='7474',
                        username='',
                        password='')
    nt.save_with_unwind()
    nt.neo4j_report()
Exemple #6
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                    default='7474')
parser.add_argument('--username',
                    help='username (default: neo4j)',
                    default='neo4j')
parser.add_argument('--password',
                    help='password (default: demo)',
                    default='demo')
args = parser.parse_args()

if args.nodes is None or args.edges is None:
    usage()
    exit()

print(args)
# Initialize PandasTransformer
t = PandasTransformer()

# Load nodes and edges into graph
t.parse(args.nodes, error_bad_lines=False)
t.parse(args.edges, error_bad_lines=False)

# Initialize NeoTransformer
# TODO: eliminate bolt
n = NeoTransformer(t.graph, args.host, {'http': args.http_port}, args.username,
                   args.password)

# Save graph into Neo4j
n.save_with_unwind()

n.neo4j_report()
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def load_and_merge(yaml_file: str) -> nx.MultiDiGraph:
    """Load and merge sources defined in the config YAML.

    Args:
        yaml_file: A string pointing to a KGX compatible config YAML.

    Returns:
        networkx.MultiDiGraph: The merged graph.

    """
    gm = GraphMerge()
    config = parse_load_config(yaml_file)
    transformers: List = []

    # make sure all files exist before we start load
    for key in config['target']:
        target = config['target'][key]
        logging.info("Checking that file exist for {}".format(key))
        if target['type'] in get_file_types():
            for f in target['filename']:
                if not os.path.exists(f) or not os.path.isfile(f):
                    raise FileNotFoundError(
                        "File {} for transform {}  in yaml file {} "
                        "doesn't exist! Dying.", f, key, yaml_file)

    # read all the sources defined in the YAML
    for key in config['target']:
        target = config['target'][key]
        logging.info("Loading {}".format(key))
        if target['type'] in get_file_types():
            # loading from a file
            transformer = get_transformer(target['type'])()
            for f in target['filename']:
                transformer.parse(f, input_format='tsv')
                transformer.graph.name = key
            transformers.append(transformer)
        elif target['type'] == 'neo4j':
            transformer = NeoTransformer(None, target['uri'],
                                         target['username'],
                                         target['password'])
            transformer.load()
            transformers.append(transformer)
            transformer.graph.name = key
        else:
            logging.error("type {} not yet supported".format(target['type']))
        stats_filename = f"{key}_stats.yaml"
        generate_graph_stats(transformer.graph, key, stats_filename)

    # merge all subgraphs into a single graph
    merged_graph = gm.merge_all_graphs([x.graph for x in transformers])
    merged_graph.name = 'merged_graph'
    generate_graph_stats(merged_graph, merged_graph.name,
                         f"merged_graph_stats.yaml")

    # write the merged graph
    if 'destination' in config:
        for _, destination in config['destination'].items():
            if destination['type'] == 'neo4j':
                destination_transformer = NeoTransformer(
                    merged_graph,
                    uri=destination['uri'],
                    username=destination['username'],
                    password=destination['password'])
                destination_transformer.save_with_unwind()
            elif destination['type'] in get_file_types():
                destination_transformer = get_transformer(
                    destination['type'])(merged_graph)
                destination_transformer.save(destination['filename'],
                                             extension=destination['type'])
            else:
                logging.error(
                    "type {} not yet supported for KGX load-and-merge operation."
                    .format(destination['type']))

    return merged_graph