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Description:

hypothesissqlalchemy 1.1.0

hypothesis_sqlalchemy

In what follows python is an alias for python3.7 or pypy3.7
or any later version (python3.8, pypy3.8 and so on).
Installation
Install the latest pip & setuptools packages versions
python -m pip install --upgrade pip setuptools

User
Download and install the latest stable version from PyPI repository
python -m pip install --upgrade hypothesis_sqlalchemy

Developer
Download the latest version from GitHub repository
git clone https://github.com/lycantropos/hypothesis_sqlalchemy.git
cd hypothesis_sqlalchemy

Install dependencies
python -m pip install -r requirements.txt

Install
python setup.py install

Usage
With setup
>>> import warnings
>>> from hypothesis.errors import NonInteractiveExampleWarning
>>> # ignore hypothesis warnings caused by `example` method call
... warnings.filterwarnings('ignore', category=NonInteractiveExampleWarning)

let's take a look at what can be generated and how.
Tables
We can write a strategy that produces tables
>>> from hypothesis_sqlalchemy import scheme
>>> from sqlalchemy.engine.default import DefaultDialect
>>> dialect = DefaultDialect()
>>> tables = scheme.tables(dialect,
... min_size=3,
... max_size=10)
>>> table = tables.example()
>>> from sqlalchemy.schema import Table
>>> isinstance(table, Table)
True
>>> from sqlalchemy.schema import Column
>>> all(isinstance(column, Column) for column in table.columns)
True
>>> 3 <= len(table.columns) <= 10
True

Records
Suppose we have a table
>>> from sqlalchemy.schema import (Column,
... MetaData,
... Table)
>>> from sqlalchemy.sql.sqltypes import (Integer,
... String)
>>> metadata = MetaData()
>>> user_table = Table('user', metadata,
... Column('user_id', Integer,
... primary_key=True),
... Column('user_name', String(16),
... nullable=False),
... Column('email_address', String(60)),
... Column('password', String(20),
... nullable=False))

and we can write strategy that

produces single records (as tuples)
>>> from hypothesis import strategies
>>> from hypothesis_sqlalchemy.sample import table_records
>>> records = table_records(user_table,
... email_address=strategies.emails())
>>> record = records.example()
>>> isinstance(record, tuple)
True
>>> len(record) == len(user_table.columns)
True
>>> all(column.nullable and value is None
... or isinstance(value, column.type.python_type)
... for value, column in zip(record, user_table.columns))
True

produces records lists (with configurable list size bounds)
>>> from hypothesis_sqlalchemy.sample import table_records_lists
>>> records_lists = table_records_lists(user_table,
... min_size=2,
... max_size=5,
... email_address=strategies.emails())
>>> records_list = records_lists.example()
>>> isinstance(records_list, list)
True
>>> 2 <= len(records_list) <= 5
True
>>> all(isinstance(record, tuple) for record in records_list)
True
>>> all(len(record) == len(user_table.columns) for record in records_list)
True

Development
Bumping version
Preparation
Install
bump2version.
Pre-release
Choose which version number category to bump following semver
specification.
Test bumping version
bump2version --dry-run --verbose $CATEGORY

where $CATEGORY is the target version number category name, possible
values are patch/minor/major.
Bump version
bump2version --verbose $CATEGORY

This will set version to major.minor.patch-alpha.
Release
Test bumping version
bump2version --dry-run --verbose release

Bump version
bump2version --verbose release

This will set version to major.minor.patch.
Running tests
Install dependencies
python -m pip install -r requirements-tests.txt

Plain
pytest

Inside Docker container:

with CPython
docker-compose --file docker-compose.cpython.yml up

with PyPy
docker-compose --file docker-compose.pypy.yml up

Bash script:

with CPython
./run-tests.sh

or
./run-tests.sh cpython

with PyPy
./run-tests.sh pypy

PowerShell script:

with CPython
.\run-tests.ps1

or
.\run-tests.ps1 cpython

with PyPy
.\run-tests.ps1 pypy