Skip to main content

Databases Connection and Queries

Project description

Databases Connection and Queries

Donate License PyPi PyPI Downloads Code style: black Build Status Python

Install All databases dependencies

pip install ddcDatabases[all]

Install MSSQL

pip install ddcDatabases[mssql]

Install PostgreSQL

pip install ddcDatabases[pgsql]

Databases

  • Parameters for all classes are declared as OPTIONAL falling back to .env file variables
  • All examples are using db_utils.py
  • By default, the MSSQL class will open a session to the database, but the engine can be available at session.bind
  • SYNC sessions defaults:
    • autoflush is True
    • expire_on_commit is True
    • echo is False
  • ASYNC sessions defaults:
    • autoflush is True
    • expire_on_commit is False
    • echo is False

SQLITE

class Sqlite(
    filepath: Optional[str] = None,
    echo: Optional[bool] = None,
    autoflush: Optional[bool] = None,
    expire_on_commit: Optional[bool] = None,
    extra_engine_args: Optional[dict] = None,
)

Session

import sqlalchemy as sa
from ddcDatabases import DBUtils, Sqlite
with Sqlite() as session:
    utils = DBUtils(session)
    stmt = sa.select(TableModel).where(TableModel.id == 1)
    results = utils.fetchall(stmt)
    for row in results:
        print(row)

Sync Engine

from ddcDatabases import Sqlite
with Sqlite() as session:
    engine = session.bind
    ...

MSSQL

class MSSQL(        
    host: Optional[str] = None,
    port: Optional[int] = None,
    user: Optional[str] = None,
    password: Optional[str] = None,
    database: Optional[str] = None,
    schema: Optional[str] = None,
    echo: Optional[bool] = None,
    pool_size: Optional[int] = None,
    max_overflow: Optional[int] = None,
    autoflush: Optional[bool] = None,
    expire_on_commit: Optional[bool] = None,
    extra_engine_args: Optional[dict] = None,
)

Sync Example

import sqlalchemy as sa
from ddcDatabases import DBUtils, MSSQL
with MSSQL() as session:
    stmt = sa.select(TableModel).where(TableModel.id == 1)
    db_utils = DBUtils(session)
    results = db_utils.fetchall(stmt)
    for row in results:
        print(row)

Async Example

import sqlalchemy as sa
from ddcDatabases import DBUtilsAsync, MSSQL
async with MSSQL() as session:
    stmt = sa.select(TableModel).where(TableModel.id == 1)
    db_utils = DBUtilsAsync(session)
    results = await db_utils.fetchall(stmt)
    for row in results:
        print(row)

Sync Engine

from ddcDatabases import MSSQL
with MSSQL() as session:
    engine = session.bind
    ...

Async Engine

from ddcDatabases import MSSQL
async with MSSQL() as session:
    engine = await session.bind
    ...

PostgreSQL

class DBPostgres(
    host: Optional[str] = None,
    port: Optional[int] = None,
    user: Optional[str] = None,
    password: Optional[str] = None,
    database: Optional[str] = None,
    echo: Optional[bool] = None,
    autoflush: Optional[bool] = None,
    expire_on_commit: Optional[bool] = None,
    engine_args: Optional[dict] = None,
)

Sync Example

import sqlalchemy as sa
from ddcDatabases import DBUtils, PostgreSQL
with PostgreSQL() as session:
    stmt = sa.select(TableModel).where(TableModel.id == 1)
    db_utils = DBUtils(session)
    results = db_utils.fetchall(stmt)
    for row in results:
        print(row)

Async Example

import sqlalchemy as sa
from ddcDatabases import DBUtilsAsync, PostgreSQL
async with PostgreSQL() as session:
    stmt = sa.select(TableModel).where(TableModel.id == 1)
    db_utils = DBUtilsAsync(session)
    results = await db_utils.fetchall(stmt)
    for row in results:
        print(row)

Sync Engine

from ddcDatabases import PostgreSQL
with PostgreSQL() as session:
    engine = session.bind
    ...

Async Engine

from ddcDatabases import PostgreSQL
async with PostgreSQL() as session:
    engine = await session.bind
    ...

DBUtils and DBUtilsAsync

  • Take an open session as parameter
  • Can use SQLAlchemy statements
  • Execute function can be used to update, insert or any SQLAlchemy.text
from ddcDatabases import DBUtils
db_utils = DBUtils(session)
db_utils.fetchall(stmt)                     # returns a list of RowMapping
db_utils.fetchvalue(stmt)                   # fetch a single value, returning as string
db_utils.insert(stmt)                       # insert into model table
db_utils.deleteall(model)                   # delete all records from model
db_utils.insertbulk(model, list[dict])      # insert records into model from a list of dicts
db_utils.execute(stmt)                      # this is the actual execute from session

Source Code

Build

poetry build -f wheel

Run Tests and Get Coverage Report using Poe

poetry update --with test
poe tests

License

Released under the MIT License

Buy me a cup of coffee

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

ddcdatabases-1.0.18.tar.gz (8.9 kB view details)

Uploaded Source

Built Distribution

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

ddcdatabases-1.0.18-py3-none-any.whl (10.4 kB view details)

Uploaded Python 3

File details

Details for the file ddcdatabases-1.0.18.tar.gz.

File metadata

  • Download URL: ddcdatabases-1.0.18.tar.gz
  • Upload date:
  • Size: 8.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for ddcdatabases-1.0.18.tar.gz
Algorithm Hash digest
SHA256 8ed18c1532af27778ba66ebe4d7f2181d67f02d833d7f5e314fcbb6c482e32fe
MD5 9071b7e41703f207fabfb5cdc0cac589
BLAKE2b-256 38cdabaacb7efaa80dfaa291f6c08e8396810b8bfb79650496569d164f64ce32

See more details on using hashes here.

Provenance

The following attestation bundles were made for ddcdatabases-1.0.18.tar.gz:

Publisher: workflow.yml on ddc/ddcDatabases

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file ddcdatabases-1.0.18-py3-none-any.whl.

File metadata

  • Download URL: ddcdatabases-1.0.18-py3-none-any.whl
  • Upload date:
  • Size: 10.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for ddcdatabases-1.0.18-py3-none-any.whl
Algorithm Hash digest
SHA256 f1156dfbccad8ae4597b4e390355a89e4b6d61ccc0b907a8750afd9a4b35362d
MD5 b5466871afefd3119415b6149122a673
BLAKE2b-256 4a3ca1091567bad7615e48af9941ce366ff6154789087df4528965ec8334ef54

See more details on using hashes here.

Provenance

The following attestation bundles were made for ddcdatabases-1.0.18-py3-none-any.whl:

Publisher: workflow.yml on ddc/ddcDatabases

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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