Skip to main content

Easy-to-use ORM for database operations with lazy table reflection

Project description

kepler-atlas

基于sqlalchemy的python数据库orm包,加入对交互式编程的支持,更简易的API。

注意

自动补全功能在ipython>7.1.1的版本下会出现卡顿现象,如果需要,请回滚至该本版或以下。

安装

pip install kepler-atlas

使用方法

建表

from kepler.atlas import DataBase
from sqlalchemy import create_engine

engine = create_engine('mysql://....')
# or
engine = 'mysql://....'

# 实例化
db = DataBase(engine, schema=None)

from sqlalchemy import Column, Integer, String

# 构建User类
class User(db.Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String(20))
    fullname = Column(String(20))
    password = Column(String(20))

    def __repr__(self):
        return "<User(name='%s', fullname='%s', password='%s')>" % (
            self.name, self.fullname, self.password)

# 建表
db.create_all()

更多api用法可参考python对Mysql操作和使用ORM框架(SQLAlchemy)

# database下以TABLE_NAME为表名的Table类
# TABLE_NAME为任意该database下存在主键的表
table = db.TABLE_NAME

# 表TABLE_NAME下以COLUMN为列名的Column类
table.COLUMN

# 继承了sqlalchemy的Query,支持同样方法
# 返回实例化对象序列
db.query(table).filter(table.COLUMN==....).all() 

# 返回DataFrame
db.query(table).filter(...).to_df()

增/改 (适用于逐条增改)

# 增
t_obj_add = table(c1=xxx, c2=xxx, c3=xxx)
db.update(t_obj_add)
db.commit()

# 改
t_obj_update = db.query(table).filter(...).all()
for t in t_obj_update:
    t.c1 = xxx
db.update(t_obj_update)
db.commit()

# 或者一起搞
# 构建一个iterable对象
t_change = [t_obj_add] + t_obj_update
db.update(t_change)
db.commit()

# 或者另外一种模式
db.query(table).filter(...).update({table.c1: "hello"}, synchronize_session=False)
db.commit()

批量插入

import pandas as pd
df = pd.DataFrame(...)
# 批量插入支持DataFrame格式 或 list of dicts [{'xx': ...}, ..., {}]
# ignore默认为True,如果存在唯一性索引,会忽略重复键错误
# 解决了pandas中 if_exist='append'中重复插入报错的问题
db.insert(table, df, ignore=True)
db.commit()

# 删
t_obj_delete = db.query(table).filter(...).first()
db.delete(t_obj_delete)
db.commit()

# 或者另外一种模式
db.query(table).filter(...).delete()
db.commit()

ipython or jupyter-notebook

实例化Database类后,kepler-atlas会自动为该实例添加以表名命名的属性,这点在交互式编程中十分方便。

需要注意的是,该属性为懒加载,并不会一次性将database下的所有表映射成Table类,只有在单独调用时才会映射对应的表,解决了性能问题。

tables

columns

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

kepler_atlas-0.1.3.tar.gz (29.8 kB view details)

Uploaded Source

Built Distribution

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

kepler_atlas-0.1.3-py3-none-any.whl (30.0 kB view details)

Uploaded Python 3

File details

Details for the file kepler_atlas-0.1.3.tar.gz.

File metadata

  • Download URL: kepler_atlas-0.1.3.tar.gz
  • Upload date:
  • Size: 29.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.7

File hashes

Hashes for kepler_atlas-0.1.3.tar.gz
Algorithm Hash digest
SHA256 2947e696010c45ef9b2da66cfa8c7366a452722e46f8107b06e4588239e52c50
MD5 e066a4be47b31a947c892036b801f99b
BLAKE2b-256 b0d92ef6b120fcffebd8dddbec8a9d7957de467f98962dbba664618e37c85d6b

See more details on using hashes here.

File details

Details for the file kepler_atlas-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: kepler_atlas-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 30.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.7

File hashes

Hashes for kepler_atlas-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 c619f2fe2f7b024069f0d41f3cc16b0b6627dcc56beec5ca9ff989ce8847a278
MD5 0db91ec98e30c66864e00f3a8014dcdc
BLAKE2b-256 4701036558853ca30e641696bddf3c955a92efe779923658ed8ed6f7fa4ea7f5

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