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Configuration and monitoring of database connections

Project description

Mara DB

Build Status PyPI - License PyPI version Slack Status

Mini package for configuring and accessing multiple databases in a single project. Decouples the use of databases and their configuration by using "aliases" for databases.

The file mara_db/dbs.py contains abstract database configurations for PostgreSQL, Mysql, SQL Server, Oracle and SQLite. The database connections of a project are configured by overwriting the databases function in mara_db/config.py:

import mara_db.config
import mara_db.dbs

## configure database connections for different aliases
mara_db.config.databases = lambda: {
    'mara': mara_db.dbs.PostgreSQLDB(host='localhost', user='root', database='mara'),
    'dwh': mara_db.dbs.PostgreSQLDB(database='dwh'),
    'source-1': mara_db.dbs.MysqlDB(host='some-localhost', database='my_app', user='dwh'),
    'source-2': mara_db.dbs.SQLServerDB(user='dwh_read', password='123abc', database='db1', host='some-sql-server')
}

## access individual database configurations with `dbs.db`:
print(mara_db.dbs.db('mara'))
# -> <PostgreSQLDB: host=localhost, database=mara>

 

Visualization of (PostgreSQL) database schemas

mara_db/views.py contains a schema visualization for all configured databases using graphviz (currently PostgreSQL only). It basically show tables of selected schemas together with the foreign key relations between them.

Schema visualization

For finding missing foreign key constraints, columns that follow a specific naming pattern (configurable via config.schema_ui_foreign_key_column_regex, default *_fk) and that are not part of foreign key constraints are drawn in pink.

 

Fast batch processing: Accessing databases with shell commands

The file mara_db/shell.py contains functions that create commands for accessing databases via their command line clients.

For example, the query_command function creates a shell command that can receive an SQL query from stdin and execute it:

import mara_db.shell

print(mara_db.shell.query_command('source-1'))
# -> mysql --default-character-set=utf8mb4 --user=dwh --host=some-localhost my_app

print(mara_db.shell.query_command('dwh', timezone='Europe/Lisbon', echo_queries=False))
# -> PGTZ=Europe/Lisbon PGOPTIONS=--client-min-messages=warning psql  --no-psqlrc --set ON_ERROR_STOP=on dwh

The function copy_to_stdout_command creates a shell command that receives a query on stdin and writes the result to stdout in tabular form:

print(mara_db.shell.copy_to_stdout_command('source-1'))
# -> mysql --default-character-set=utf8mb4 --user=dwh --host=some-localhost my_app --skip-column-names

Similarly, copy_from_stdin_command creates a client command that receives tabular data from stdin and and writes it to a target table:

print(mara_db.shell.copy_from_stdin_command('dwh', target_table='some_table', delimiter_char=';'))
# -> PGTZ=Europe/Berlin PGOPTIONS=--client-min-messages=warning psql --echo-all --no-psqlrc --set ON_ERROR_STOP=on dwh \
#      --command="COPY some_table FROM STDIN WITH DELIMITER AS ';'"

Finally, copy_command creates a shell command that receives a sql query from stdin, executes the query in source_db and then writes the result of to target_table in target_db:

print(mara_db.shell.copy_command('source-2', 'dwh', target_table='some_table'))
# -> sed 's/\\\\$/\$/g;s/\$/\\\\$/g' \
#   | sqsh  -U dwh_read -P 123abc -S some-sql-server -D db1 -m csv \
#   | PGTZ=Europe/Berlin PGOPTIONS=--client-min-messages=warning psql --echo-all --no-psqlrc --set ON_ERROR_STOP=on dwh \
#         --command = "COPY some_table FROM STDIN WITH CSV HEADER"

 

The following command line clients are used to access the various databases:

Database Client binary Comments
Postgresql psql Included in standard distributions.
MariaDB / Mysql mysql Included in standard distributions.
SQL Server sqsh From https://sourceforge.net/projects/sqsh/, usually messy to get working. On ubuntu, use http://ppa.launchpad.net/jasc/sqsh/ubuntu/ backport. On Mac, try the homebrew version or install from source.
Oracle sqlplus64 See the Oracle Instant Client homepage for details. On Mac, follow these instructions. Then sudo ln -s /usr/local/bin/sqlplus /usr/local/bin/sqlplus64 to make the binary accessible as sqlplus64.
SQLite sqlite3 Available in standard distributions. Version >3.20.x required (not the case on Ubuntu 14.04).

 

Make it so! Auto-migration of SQLAlchemy models

Alembic has a feature that can create a diff between the state of a database and the ORM models of an application. This feature is used in mara_db/auto_migrate.py to automatically perform all necessary database transformations, without intermediate migration files:

# define a model / table
class MyTable(sqlalchemy.ext.declarative.declarative_base()):
    __tablename__ = 'my_table'
    my_table_id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
    column_1 = sqlalchemy.Column(sqlalchemy.TEXT, nullable=False, index=True)


db = mara_db.dbs.SQLiteDB(file_name='/tmp/test.sqlite')

# create database and table 
mara_db.auto_migration.auto_migrate(engine=mara_db.auto_migration.engine(db), models=[MyTable])
# ->
# Created database "sqlite:////tmp/test.sqlite"
#
# CREATE TABLE my_table (
#     my_table_id SERIAL NOT NULL,
#     column_1 TEXT NOT NULL,
#     PRIMARY KEY (my_table_id)
# );
#
# CREATE INDEX ix_my_table_column_1 ON my_table (column_1);

When the model is changed later, then auto_migrate creates a diff against the existing database and applies it:

# remove index and add another column
class MyTable(sqlalchemy.ext.declarative.declarative_base()):
    __tablename__ = 'my_table'
    my_table_id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
    column_1 = sqlalchemy.Column(sqlalchemy.TEXT, nullable=False)
    column_2 = sqlalchemy.Column(sqlalchemy.Integer)

auto_migrate(engine=engine(db), models=[MyTable])
# ->
# ALTER TABLE my_table ADD COLUMN column_2 INTEGER;
#
# DROP INDEX ix_my_table_text_column_1;

Use with care! The are lot of changes that alembic auto-generate can not detect. We recommend testing each aut-migration on a staging system first before deploying to production. Sometimes manual migration scripts will be necessary.

Installation

pip install mara-db

or

pip install git+https://github.com/mara/mara-db.git

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