# SQLObject Developer Guide

Contents

- SQLObject Developer Guide

  - Development Installation

  - Architecture

    - Columns, validators and converters

  - Branch workflow

  - Style Guide

  - Testing

  - Documentation

These are some notes on developing SQLObject.

## Development Installation

First install FormEncode:

    $ git clone git://github.com/formencode/formencode.git
    $ cd formencode
    $ sudo python setup.py develop

Then do the same for SQLObject:

    $ git clone git clone git://github.com/sqlobject/sqlobject.git
    $ cd sqlobject
    $ sudo python setup.py develop

Or rather fork it and clone your fork. To develop a feature or a bugfix create a separate branch, push it to your fork and create a pull request to the original repo. That way CI will be triggered to test your code.

Voila! The packages are globally installed, but the files from the checkout were not copied into `site-packages`. See setuptools for more.

## Architecture

There are three main kinds of objects in SQLObject: tables, columns and connections.

Tables-related objects are in sqlobject/main.py module. There are two main classes: `SQLObject` and `sqlmeta`; the latter is not a metaclass but a parent class for `sqlmeta` attribute in every class - the authors tried to move there all attributes and methods not directly related to columns to avoid cluttering table namespace.

Connections are instances of `DBConnection` class (from sqlobject/dbconnection.py) and its concrete descendants. `DBConnection` contains generic code for generating SQL, working with transactions and so on. Concrete connection classes (like `PostgresConnection` and `SQLiteConnection`) provide backend-specific functionality.

### Columns, validators and converters

Columns are instances of classes from sqlobject/col.py. There are two classes for every column: one is for user to include into an instance of SQLObject, an instance of the other is automatically created by SQLObject’s metaclass. The two classes are usually named `Col` and `SOCol`; for example, `BoolCol` and `SOBoolCol`. User-visible classes, descendants of `Col`, seldom contain any code; the main code for a column is in `SOCol` descendants and in validators.

Every column has a list of validators. Validators validate input data and convert input data to python data and back. Every validator must have methods `from_python` and `to_python`. The former converts data from python to internal representation that will be converted by converters to SQL strings. The latter converts data from SQL data to python. Also please bear in mind that validators can receive `None` (for SQL `NULL`) and `SQLExpression` (an object that represents SQLObject expressions); both objects must be passed unchanged by validators.

Converters from sqlobject/converters.py aren’t visible to users. They are used behind the scene to convert objects returned by validators to backend-specific SQL strings. The most elaborated converter is `StringLikeConverter`. Yes, it converts strings to strings. It converts python strings to SQL strings using backend-specific quoting rules.

Let look into `BoolCol` as an example. The very `BoolCol` doesn’t have any code. `SOBoolCol` has a method to create `BoolValidator` and methods to create backend-specific column type. `BoolValidator` has identical methods `from_python` and `to_python`; the method passes `None`, `SQLExpression` and bool values unchanged; int and objects that have method `__nonzero__` (`__bool__` in Python 3) are converted to bool; other objects trigger validation error. Bool values that are returned by call to `from_python` will be converted to SQL strings by `BoolConverter`; bool values from `to_python` (is is supposed they are originated from the backend via DB API driver) are passed to the application.

Objects that are returned from `from_python` must be registered with converters. Another approach for `from_python` is to return an object that has `__sqlrepr__` method. Such objects convert to SQL strings themselves, converters are not used.

## Branch workflow

Initially `SQLObject` was being developed using `Subversion`. Even after switching to git development process somewhat preserves the old workflow.

The `trunk`, called `master` in git, is the most advanced and the most unstable branch. It is where new features are applied. Bug fixes are applied to `oldstable` and `stable` branches and are merged upward – from `oldstable` to `stable` and from `stable` to `master`.

## Style Guide

Generally you should follow the recommendations in PEP 8, the Python Style Guide. Some things to take particular note of:

- With a few exceptions sources must be flake8-clean (and hence pep8-clean). Please consider using pre-commit hook installed by running `flake8 --install-hook`.

- No tabs. Not anywhere. Always indent with 4 spaces.

- We don’t stress too much on line length. But try to break lines up by grouping with parenthesis instead of with backslashes (if you can). Do asserts like:

      assert some_condition(a, b), (
          "Some condition failed, %r isn't right!" % a)

- But if you are having problems with line length, maybe you should just break the expression up into multiple statements.

- Blank lines between methods, unless they are very small and closely bound to each other.

- Never use the form `condition and trueValue or falseValue`. Break it out and use a variable.

- Careful of namespace pollution. SQLObject does allow for `from sqlobject import *` so names should be fairly distinct, or they shouldn’t be exported in `sqlobject.__init__`.

- We’re very picky about whitespace. There’s one and only one right way to do it. Good examples:

      short = 3
      longerVar = 4

      if x == 4:
          do stuff

      func(arg1='a', arg2='b')
      func((a + b)*10)

  Bad examples:

      short    =3
      longerVar=4

      if x==4: do stuff

      func(arg1 = 'a', arg2 = 'b')
      func(a,b)
      func( a, b )
      [ 1, 2, 3 ]

  To us, the poor use of whitespace seems lazy. We’ll think less of your code (justified or not) for this very trivial reason. We will fix all your code for you if you don’t do it yourself, because we can’t bear to look at sloppy whitespace.

- Use `@@` to mark something that is suboptimal, or where you have a concern that it’s not right. Try to also date it and put your username there.

- Docstrings are good. They should look like:

      class AClass(object):
          """
          doc string...
          """

  Don’t use single quotes (‘’’). Don’t bother trying make the string less vertically compact.

- Comments go right before the thing they are commenting on.

- Methods never, ever, ever start with capital letters. Generally only classes are capitalized. But definitely never methods.

- mixedCase is preferred.

- Use `cls` to refer to a class. Use `meta` to refer to a metaclass (which also happens to be a class, but calling a metaclass `cls` will be confusing).

- Use `isinstance` instead of comparing types. E.g.:

      if isinstance(var, str): ...
      # Bad:
      if type(var) is StringType: ...

- Never, ever use two leading underscores. This is annoyingly private. If name clashes are a concern, use name mangling instead (e.g., `_SO_blahblah`). This is essentially the same thing as double-underscore, only it’s transparent where double underscore obscures.

- Module names should be unique in the package. Subpackages shouldn’t share module names with sibling or parent packages. Sadly this isn’t possible for `__init__`, but it’s otherwise easy enough.

- Module names should be all lower case, and probably have no underscores (smushedwords).

## Testing

Tests are important. Tests keep everything from falling apart. All new additions should have tests.

Testing uses pytest, an alternative to `unittest`. It is available at http://pytest.org/ and https://pypi.org/project/pytest/. Read its getting started document for more.

To actually run the test, you have to give it a database to connect to. You do so with the option `-D`. You can either give a complete URI or one of several shortcuts like `mysql` (these shortcuts are defined in the top of `tests/dbtest.py`).

All the tests are modules in `sqlobject/tests`. Each module tests one kind of feature, more or less. If you are testing a module, call the test module `tests/test_modulename.py` – only modules that start with `test_` will be picked up by pytest.

The “framework” for testing is in `tests/dbtest`. There’s a couple of important functions:

`setupClass(soClass)` creates the tables for the class. It tries to avoid recreating tables if not necessary.

`supports(featureName)` checks if the database backend supports the named feature. What backends support what is defined at the top of `dbtest`.

If you `import *` you’ll also get pytest’s version of raises, an `inserts` function that can create instances for you, and a couple miscellaneous functions.

If you submit a patch or implement a feature without a test, we’ll be forced to write the test. That’s no fun for us, to just be writing tests. So please, write tests; everything at least needs to be exercised, even if the tests are absolutely complete.

We now use Travis CI and AppVeyor to run tests.

Visit Travis CI status <<https://travis-ci.org/sqlobject/sqlobject> or Appveyor CI status <https://https://ci.appveyor.com/project/phdru/sqlobject> to see the current status.

To avoid triggering unnecessary test run at CI services add text [skip ci] or `[ci skip]` anywhere in your commit messages for commits that don’t change code (documentation updates and such).

We use coverage.py to measures code coverage by tests and upload the result for analyzis to Coveralls and Codecov.

Visit Coveralls status <https://coveralls.io/github/sqlobject/sqlobject?branch=master> or Codecov status <https://codecov.io/gh/sqlobject/sqlobject> to see the current status.

## Documentation

Please write documentation. Documentation should live in the docs/ directory in reStructuredText format. We use Sphinx to convert docs to HTML.