Skip to main content

Python client for NebulaGraph V3.4

Project description

nebula-python

This repository holds the official Python API for NebulaGraph.

Before you start

Before you start, please read this section to choose the right branch for you. The compatibility between the API and NebulaGraph service can be found in How to choose nebula-python. The current master branch is compatible with NebulaGraph 3.3.

The directory structure

|--nebula-python
    |
    |-- nebula3                               // client code
    |   |-- fbthrift                          // the fbthrift lib code
    |   |-- common           
    |   |-- data           
    |   |-- graph           
    |   |-- meta           
    |   |-- net                               // the net code for graph client
    |   |-- storage           
    |   |-- Config.py                         // the pool config
    |   |__ Exception.py                      // the define exception
    |           
    |-- examples
    |   |-- GraphClientMultiThreadExample.py  // the multi thread example
    |   |-- GraphClientSimpleExample.py       // the simple example
    |   |__ ScanVertexEdgeExample.py                   
    |
    |-- tests                                 // the test code
    |                      
    |-- setup.py                              // used to install or package
    |                      
    |__ README.md                             // the introduction of nebula3-python

How to get nebula3-python

Option one: install with pip

# for v3.x
pip install nebula3-python==$version
# for v2.x
pip install nebula2-python==$version

Option two: install from the source code

  • Clone from GitHub
git clone https://github.com/vesoft-inc/nebula-python.git
cd nebula-python
  • Install
pip install .

Quick example to use graph-client to connect graphd

from nebula3.gclient.net import ConnectionPool
from nebula3.Config import Config

# define a config
config = Config()
config.max_connection_pool_size = 10
# init connection pool
connection_pool = ConnectionPool()
# if the given servers are ok, return true, else return false
ok = connection_pool.init([('127.0.0.1', 9669)], config)

# option 1 control the connection release yourself
# get session from the pool
session = connection_pool.get_session('root', 'nebula')

# select space
session.execute('USE nba')

# show tags
result = session.execute('SHOW TAGS')
print(result)

# release session
session.release()

# option 2 with session_context, session will be released automatically
with connection_pool.session_context('root', 'nebula') as session:
    session.execute('USE nba')
    result = session.execute('SHOW TAGS')
    print(result)

# close the pool
connection_pool.close()

Example of using session pool

There are some limitations while using the session pool:

1. There MUST be an existing space in the DB before initializing the session pool.
2. Each session pool is corresponding to a single USER and a single Space. This is to ensure that the user's access control is consistent. i.g. The same user may have different access privileges in different spaces. If you need to run queries in different spaces, you may have multiple session pools.
3. Every time when sessinPool.execute() is called, the session will execute the query in the space set in the session pool config.
4. Commands that alter passwords or drop users should NOT be executed via session pool.

see /example/SessinPoolExample.py

Quick example to fetch result to dataframe

from nebula3.gclient.net import ConnectionPool
from nebula3.Config import Config
import pandas as pd
from typing import Dict
from nebula3.data.ResultSet import ResultSet

def result_to_df(result: ResultSet) -> pd.DataFrame:
    """
    build list for each column, and transform to dataframe
    """
    assert result.is_succeeded()
    columns = result.keys()
    d: Dict[str, list] = {}
    for col_num in range(result.col_size()):
        col_name = columns[col_num]
        col_list = result.column_values(col_name)
        d[col_name] = [x.cast() for x in col_list]
    return pd.DataFrame.from_dict(d, columns=columns)

# define a config
config = Config()

# init connection pool
connection_pool = ConnectionPool()

# if the given servers are ok, return true, else return false
ok = connection_pool.init([('127.0.0.1', 9669)], config)

# option 2 with session_context, session will be released automatically
with connection_pool.session_context('root', 'nebula') as session:
    session.execute('USE <your graph space>')
    result = session.execute('<your query>')
    df = result_to_df(result)
    print(df)

# close the pool
connection_pool.close()

Quick example to use storage-client to scan vertex and edge

You should make sure the scan client can connect to the address of storage which see from SHOW HOSTS

from nebula3.mclient import MetaCache, HostAddr
from nebula3.sclient.GraphStorageClient import GraphStorageClient

# the metad servers's address
meta_cache = MetaCache([('172.28.1.1', 9559),
                        ('172.28.1.2', 9559),
                        ('172.28.1.3', 9559)],
                       50000)

# option 1 metad usually discover the storage address automatically
graph_storage_client = GraphStorageClient(meta_cache)

# option 2 manually specify the storage address
storage_addrs = [HostAddr(host='172.28.1.4', port=9779),
                 HostAddr(host='172.28.1.5', port=9779),
                 HostAddr(host='172.28.1.6', port=9779)]
graph_storage_client = GraphStorageClient(meta_cache, storage_addrs)

resp = graph_storage_client.scan_vertex(
        space_name='ScanSpace',
        tag_name='person')
while resp.has_next():
    result = resp.next()
    for vertex_data in result:
        print(vertex_data)
        
resp = graph_storage_client.scan_edge(
    space_name='ScanSpace',
    edge_name='friend')
while resp.has_next():
    result = resp.next()
    for edge_data in result:
        print(edge_data)

How to choose nebula-python

Nebula-Python Version NebulaGraph Version
1.0 1.x
2.0.0 2.0.0/2.0.1
2.5.0 2.5.0
2.6.0 2.6.0/2.6.1
3.0.0 3.0.0
3.1.0 3.1.0
3.3.0 3.3.0
master master

How to contribute to nebula-python

Fork this repo, then clone it locally (be sure to replace the {username} in the repo URL below with your GitHub username):

git clone https://github.com/{username}/nebula-python.git
cd nebula-python

Install the package in the editable mode, then install all the dev dependencies:

pip install -e .
pip install -r requirements/dev.txt

Make sure the Nebula server in running, then run the tests with pytest:

pytest

Using the default formatter with black.

Please run make fmt to format python code before submitting.

See How to contribute for the general process of contributing to Nebula projects.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nebula3-python-3.4.0.tar.gz (265.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

nebula3_python-3.4.0-py3-none-any.whl (312.4 kB view details)

Uploaded Python 3

File details

Details for the file nebula3-python-3.4.0.tar.gz.

File metadata

  • Download URL: nebula3-python-3.4.0.tar.gz
  • Upload date:
  • Size: 265.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.1

File hashes

Hashes for nebula3-python-3.4.0.tar.gz
Algorithm Hash digest
SHA256 47bd8b1b4bb2c2f0e5122bc147926cb50578a66841acf6a743cae4d0362c9eaa
MD5 c4d4d4c3b58cc4f1b8beaeee98a10549
BLAKE2b-256 9e2f3f942deb4a5da23c0cabeac954ec6a224ee6e21d0f8e35845164dce65b79

See more details on using hashes here.

File details

Details for the file nebula3_python-3.4.0-py3-none-any.whl.

File metadata

  • Download URL: nebula3_python-3.4.0-py3-none-any.whl
  • Upload date:
  • Size: 312.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.1

File hashes

Hashes for nebula3_python-3.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d9d94c6a41712875e6ec866907de0789057f860e64f547f87d9f199439759dd6
MD5 e125ed61e691fdfe570b04add2bff150
BLAKE2b-256 acbc23396a5d394801ec8a1cfb2eed6643ded878d77c9242fd097c4a4a5d3489

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page