Skip to main content

openGauss-sqlalchemy

适配SQLAlchemy框架的OpenGauss方言库。

项目已通过SQLAlchemy社区用例集。

运行依赖

注意:

使用不匹配的psycopg2会导致SQLAlchemy2.0部分autoescape相关测试用例不通过。

若需要使用autoescape相关功能,请保证环境中正确安装openGauss,并且通过修改变量LD_LIBRARY_PATH保证pg_config来自openGauss。

# 配置环境变量
$ export GAUSSHOME=/home/omm/openGauss-server/mppdb_temp_install
$ export LD_LIBRARY_PATH=$GAUSSHOME/lib:$LD_LIBRARY_PATH

$ which pg_config
# 预期结果
'/home/omm/openGauss-server/mppdb_temp_install/bin/pg_config'

# 删除psycopg2 for opengauss
$ pip install --force-reinstall psycopg2

# 若已经安装完成opengauss-sqlalchemy,重新安装
>>> python setup.py install

或者安装psycopg2-binary:

$ pip uninstall psycopg2
$ pip install psycopg2-binary

# 修改数据库实例下postgresql.conf文件中password_encryption_type = 1
$ vim /datanode/postgresql.conf

# 重启数据库
$ gs_ctl restart -D /datanode

修改密码
$ gsql -d postgres -p <port_num>
openGauss=# alter user <usrname> with password <yourpassword>;

安装

# 从pypi安装
>>> python -m pip install opengauss-sqlalchemy

# 从本地源码安装
>>> python setup.py install

使用方法

在OpenGauss中创建一个数据库。

>>> import sqlalchemy as sa
# 访问集中式模式DB
>>> sa.create_engine('opengauss://username:password@host:port/database_name')
# 或
>>> sa.create_engine('opengauss+psycopg2://username:password@host:port/database_name')
# 访问分布式模式DB
>>> sa.create_engine('opengauss+dc_psycopg2://username:password@host:port/database_name')
# 或
>>> sa.create_engine('opengauss+dc_psycopg2://username:password@/database_name?host=hostA:portA&host=hostB:portB')

2.4.0版本新增异步连接接口,由于asyncpg的特殊性,在使用asyncpg连接并且使用vector类型时需要注册该数据类型,代码示例如下:

from opengauss_sqlalchemy.register_async import register_vector
engine = create_async_engine("opengauss+asyncpg://username:password@host:port/database_name")

# 绑定事件监听器
@event.listens_for(engine.sync_engine, "connect")
def connect(dbapi_connection, connection_record):
    dbapi_connection.run_async(register_vector)

OpenGauss的数据库开发指南详见 OpenGauss DeveloperGuide。

OpenGauss特性的使用方式(集中式和分布式)

索引

  • Index with USING method
tbl = Table("testtbl", m, Column("data", String))
Index("test_idx1", tbl.c.data, opengauss_using="btree")
  • Index with column expression
tbl = Table(
    "testtbl",
    m,
    Column("data", String),
    Column("data2", Integer, key="d2"),
)

Index(
    "test_idx1",
    tbl.c.data,
    tbl.c.d2,
    opengauss_ops={"data": "text_pattern_ops", "d2": "int4_ops"},
)
  • Index with LOCAL, only available for index on a partitioned table
tbl = Table(
    "testtbl",
    m,
    Column("data", Integer),
    opengauss_partition_by="RANGE (data) ..."
)
Index("test_idx1", tbl.c.data, opengauss_local=[""])

Index(
    "test_idx2",
    tbl.c.data,
    opengauss_local=[
        "PARTITION data_index1",
        "PARTITION data_index2 TABLESPACE example3",
    ]
)
  • Index with WITH
tbl = Table("testtbl", m, Column("data", String))
Index("test_idx1", tbl.c.data, opengauss_with={"fillfactor": 50})
  • Index with TABLESPACE
tbl = Table("testtbl", m, Column("data", String))
Index("test_idx1", tbl.c.data, opengauss_tablespace="sometablespace")
  • Index with WHERE, unsupported for index on a partitioned table
tbl = Table("testtbl", m, Column("data", Integer))
Index(
    "test_idx1",
    tbl.c.data,
    opengauss_where=and_(tbl.c.data > 5, tbl.c.data < 10),
)

表

  • Table with WITH ({storage_parameter = value})
Table("some_table", ..., opengauss_with={"storage_parameter": "value"})
  • Table with ON COMMIT
Table("some_talbe", ..., prefixes=["TEMPORARY"], opengauss_on_commit="PRESERVE ROWS")
  • Table with COMPRESS
Table("some_talbe", ..., opengauss_with={"ORIENTATION": "COLUMN"}, opengauss_compress=True)
  • Table with TABLESPACE tablespace_name
Table("some_talbe", ..., opengauss_tablespace="tablespace_name")
  • Table with PARTITION BY
Table("some_talbe", ..., opengauss_partition_by="RANGE(column_name) "
        "(PARTITION P1 VALUES LESS THAN(10), "
        "PARTITION P2 VALUES LESS THAN(MAXVALUE))")
  • Table with ENABLE ROW MOVEMENT
Table("some_talbe", ..., opengauss_partition_by="RANGE(column_name) ...",
    opengauss_enable_row_movement=True)

向量数据类型

  • vector data type with select
tbl = Table(
    "test",
    m,
    Column("id", Integer),
    Column("bit_embedding", BIT(3)),
    Column("sparsevec_embedding", SPARSEVEC(3)),
    Column("vector_embedding", VECTOR(3))
)

select(tbl.c.id).order_by(tbl.c.bit_embedding.jaccard_distance('110'))

select(tbl.c.id).order_by(tbl.c.sparsevec_embedding.l2_distance(SparseVector([1, 2, 3])))

select(tbl.c.id).order_by(tbl.c.vector_embedding.l2_distance([1,2,3]))

OpenGauss特性的使用方式(集中式)

索引

  • Index with CONCURRENTLY
tbl = Table("testtbl", m, Column("data", Integer))
Index("test_idx1", tbl.c.data, opengauss_concurrently=True)

OpenGauss特性的使用方式(分布式)

表

  • Table with DISTRIBUTE BY
Table("some_table", ..., opengauss_distribute_by="HASH(column_name)")

NOTE: table without distributable columns will be set with "DISTRIBUTE BY REPLICATION"

  • Table with TO GROUP
Table("some_table", ..., opengauss_to="GROUP group_name")

发布指南

构建 python wheel格式

>>> python -m pip install wheel
>>> python setup.py bdist_wheel

本地测试

  1. 设置环境变量 export LD_LIBRARY_PATH= 和 export PYTHONPATH= 的值为测试环境中 psycopg2 包所在的目录.
  2. 安装OpenGauss并修改数据库配置, 具体步骤见 "安装并配置OpenGauss调测环境".
  3. 执行命令 tox -e py38.

安装并配置OpenGauss调测环境

  1. 添加OpenGauss的操作系统用户 >>> useradd omm -g dbgrp
  2. 修改OpenGauss目录的用户和用户组 >>> chown omm:dbgrp ${db_dir} -R
  3. 切换到新的系统用户 >>> su - omm
  4. 安装OpenGauss >>> sh install.sh -w ${db_password} -p 37200
  5. 启动OpenGauss >>> gs_ctl start -D ${db_dir}/data/single_node/
  6. 登录OpenGauss >>> gsql -d postgres -p 37200
  7. 创建数据库用户、测试数据库和测试模式
openGauss=# create user scott identified by 'Tiger123';
openGauss=# create database test with owner=scott encoding='utf8' template=template0;
openGauss=# GRANT ALL PRIVILEGES TO scott;
openGauss=# ALTER DATABASE test SET default_text_search_config = 'pg_catalog.english';
openGauss=# \c test
test=# create schema test_schema AUTHORIZATION scott;
test=# create schema test_schema_2 AUTHORIZATION scott;
test=# \q
  1. 修改OpenGauss配置
>>> gs_guc set -D ${db_dir}/data/single_node/ -c "ssl=off"
>>> gs_guc set -D ${db_dir}/data/single_node/ -c "max_prepared_transactions = 100"
>>> gs_guc reload -D ${db_dir}/data/single_node/ -h "local all scott sha256"
>>> gs_guc reload -D ${db_dir}/data/single_node/ -h "host all scott 127.0.0.1/32 sha256"
>>> gs_guc reload -D ${db_dir}/data/single_node/ -h "host all scott 0.0.0.0/0 sha256"
>>> gs_ctl stop -D ${db_dir}/data/single_node/
>>> gs_tl start -D ${db_dir}/data/single_node/
  1. 启用SQL日志记录(可选)
>>> gs_guc set -D ${db_dir}/data/single_node/ -c "log_min_error_statement = error"
>>> gs_guc set -D ${db_dir}/data/single_node/ -c "log_statement = 'all'"

Release files for opengauss-sqlalchemy 2.4.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for opengauss-sqlalchemy 2.4.0
File Interpreter ABI Platform
opengauss_sqlalchemy-2.4.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Release files / opengauss_sqlalchemy-2.4.0-py2.py3-none-any.whl

Download URL opengauss_sqlalchemy-2.4.0-py2.py3-none-any.whl
Size 27.9 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
bdaf3b40ebd8884e419f93bb274b100ff1367af07f075df833f500cdf09e87de
BLAKE2b-256 checksum
How to use checksums
bcf4cad1ddef7551f54a4a6e96f03c1af00bfefd821a2cec2df45180c1d67abf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.9

Release history Release notifications | RSS feed

This release

2.4.0 This release

1 release file

2.3.1

1 release file

2.2.0

1 release file

2.1.0

1 release file

2.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page