lycantropos/hypothesis_sqlalchemy
hypothesis strategies for generating SQLAlchemy objects
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 setuptoolsUser
Download and install the latest stable version from PyPI repository
python -m pip install --upgrade hypothesis_sqlalchemyDeveloper
Download the latest version from GitHub repository
git clone https://github.com/lycantropos/hypothesis_sqlalchemy.git
cd hypothesis_sqlalchemyInstall dependencies
python -m pip install -r requirements.txtInstall
python setup.py installUsage
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
TrueRecords
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 configurablelistsize 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 $CATEGORYwhere $CATEGORY is the target version number category name, possible
values are patch/minor/major.
Bump version
bump2version --verbose $CATEGORYThis will set version to major.minor.patch-alpha.
Release
Test bumping version
bump2version --dry-run --verbose releaseBump version
bump2version --verbose releaseThis will set version to major.minor.patch.
Running tests
Install dependencies
python -m pip install -r requirements-tests.txtPlain
pytestInside Docker container:
- with
CPythondocker-compose --file docker-compose.cpython.yml up
- with
PyPydocker-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
CPythonor.\run-tests.ps1.\run-tests.ps1 cpython - with
PyPy.\run-tests.ps1 pypy