In what follows

• python is an alias for python3.5 or any later version (python3.6 and so on),
• pypy is an alias for pypy3.5 or any later version (pypy3.6 and so on).

Install the latest pip & setuptools packages versions:

• with CPython

  python -m pip install --upgrade pip setuptools

• with PyPy

  pypy -m pip install --upgrade pip setuptools

Download and install the latest stable version from PyPI repository:

• with CPython

  python -m pip install --upgrade hypothesis_sqlalchemy

• with PyPy

  pypy -m pip install --upgrade hypothesis_sqlalchemy

Download the latest version from GitHub repository

git clone https://github.com/lycantropos/hypothesis_sqlalchemy.git
cd hypothesis_sqlalchemy

Install dependencies:

• with CPython

  python -m pip install -r requirements.txt

• with PyPy

  pypy -m pip install -r requirements.txt

Install:

• with CPython

  python setup.py install

• with PyPy

  pypy setup.py install

Let's take a look at what can be generated and how.

We can write a strategy that produces tables

>>> from hypothesis import strategies
>>> from hypothesis_sqlalchemy import tabular
>>> from sqlalchemy.schema import MetaData
>>> tables = tabular.factory(metadatas=strategies.builds(MetaData),
...                          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

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 import tabular
  >>> records = tabular.records.factory(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 import tabular
  >>> records_lists = tabular.records.lists_factory(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

Install bump2version.

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.

Test bumping version

bump2version --dry-run --verbose release

Bump version

bump2version --verbose release

This will set version to major.minor.patch.

Install dependencies:

• with CPython

  python -m pip install -r requirements-tests.txt

• with PyPy

  pypy -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 (e.g. can be used in Git hooks):

• with CPython

  ./run-tests.sh

  or

  ./run-tests.sh cpython

• with PyPy

  ./run-tests.sh pypy

PowerShell script (e.g. can be used in Git hooks):

• with CPython

  .\run-tests.ps1

  or

  .\run-tests.ps1 cpython

• with PyPy

  .\run-tests.ps1 pypy