In what follows
python
is an alias forpython3.5
or any later version (python3.6
and so on),pypy
is an alias forpypy3.5
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
tuple
s)>>> 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
list
s (with configurablelist
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
or.\run-tests.ps1
.\run-tests.ps1 cpython
- with
PyPy
.\run-tests.ps1 pypy