Skip to main content

Databases Connection and Queries

Project description

Databases Connection and Queries

License Python PyPi PyPI Downloads Code style: black Build Status

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
  • 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().engine() as engine:
    ...

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().engine() as engine:
    ...

Async Engine

from ddcDatabases import MSSQL
async with MSSQL().async_engine() as engine:
    ...

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().engine() as engine:
    ...

Async Engine

from ddcDatabases import PostgreSQL
async with PostgreSQL().async_engine() as engine:
    ...

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-1.0.17.tar.gz (8.8 kB view details)

Uploaded Source

Built Distribution

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

ddcdatabases-1.0.17-py3-none-any.whl (10.4 kB view details)

Uploaded Python 3

File details

Details for the file ddcdatabases-1.0.17.tar.gz.

File metadata

  • Download URL: ddcdatabases-1.0.17.tar.gz
  • Upload date:
  • Size: 8.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for ddcdatabases-1.0.17.tar.gz
Algorithm Hash digest
SHA256 4658cc3c36ac79bdb350a321d6e53b5f7710a1fe733662d88ea5e1f3992cfb86
MD5 53c300d9fa28eb536e6f94499fd0db94
BLAKE2b-256 1a8c14053ea318452fa041feb3a3c8b069e67304b5b0b3518b6cf17ebf7f9146

See more details on using hashes here.

Provenance

The following attestation bundles were made for ddcdatabases-1.0.17.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-1.0.17-py3-none-any.whl.

File metadata

  • Download URL: ddcdatabases-1.0.17-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-1.0.17-py3-none-any.whl
Algorithm Hash digest
SHA256 9a441aefd8b815a0b20d80512e442a00b4858f83cd298142952f576ed787999f
MD5 892af9c46ba153885fddbb2fc4f4fc6a
BLAKE2b-256 9a0bd7d87cc0e0c2f594c1ea9cb173f1354c22e2d87d205133c1f1a615f06a98

See more details on using hashes here.

Provenance

The following attestation bundles were made for ddcdatabases-1.0.17-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