``hypothesis`` strategies for ``SQLAlchemy`` objects and data from them.
Project description
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
tuple
s)>>> 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
list
s (with configurablelist
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
Project details
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