astro py:docs

- Index
- Modules

### Navigation

- next »
- « previous |
- Astropy v0.3 »
- Coding Guidelines

# Coding Guidelines

This section describes requirements and guidelines that should be followed both for the core package and for affiliated packages.

Note

Affiliated packages will only be considered for integration as a module in the core package once these guidelines have been followed.

## Interface and Dependencies

- All code must be compatible with Python 2.6, 2.7, as well as 3.1 and later. The use of six for writing code that is portable between Python 2.x and 3.x is encouraged going forward. However, much of our legacy code still uses `2to3` to process Python 2.x files to be compatible with Python 3.x.

  Packages that use `six` must include the following in their `setup_package.py` file:

      def requires_2to3():
          return False

  Code that uses `six` should use the following preamble:

      from __future__ import (absolute_import, division, print_function,
                              unicode_literals)

  Code that uses `2to3` may limit the `__future__` statement to only the following, if necessary (though using all 4 is still preferred):

      from __future__ import print_function, division

  Additional information on writing code using `six` that is compatible with both Python 2.x and 3.x is in the section Writing portable code for Python 2 and 3.

- The new Python 3 formatting style should be used (i.e. `"{0:s}".format("spam")` instead of `"%s" % "spam"`), although when using positional arguments, the position should always be specified (i.e. `"{:s}"` is not compatible with Python 2.6).

- The core package and affiliated packages should be importable with no dependencies other than components already in the Astropy core, the Python Standard Library, and NumPy 1.5.0 or later.

- The package should be importable from the source tree at build time. This means that, for example, if the package relies on C extensions that have yet to be built, the Python code is still importable, even if none of its functionality will work. One way to ensure this is to import the functions in the C extensions only within the functions/methods that require them (see next bullet point).

- Additional dependencies - such as SciPy, Matplotlib, or other third-party packages - are allowed for sub-modules or in function calls, but they must be noted in the package documentation and should only affect the relevant component.

- General utilities necessary for but not specific to the package or sub-package should be placed in the `packagename.utils`. These utilities will be moved to the `astropy.utils` module when the package is integrated into the core package. If a utility is already present in `astropy.utils`, the package should always use that utility instead of re-implementing it in `packagename.utils`.

## Documentation and Testing

- Docstrings must be present for all public classes/methods/functions, and must follow the form outlined in the Writing Documentation document.
- Write usage examples in the docstrings of all classes and functions whenever possible. These examples should be short and simple to reproduce–users should be able to copy them verbatim and run them. These examples should, whenever possible, be in the doctest format and will be executed as part of the test suite.
- Unit tests should be provided for as many public methods and functions as possible, and should adhere to the standards set in the Testing Guidelines document.

## Data and Configuration

- Packages can include data in a directory named `data` inside a subpackage source directory as long as it is less than about 100 kb. These data should always be accessed via the `astropy.utils.data.get_pkg_data_fileobj()` or `astropy.utils.data.get_pkg_data_filename()` functions. If the data exceeds this size, it should be hosted outside the source code repository, either at a third-party location on the internet or the astropy data server. In either case, it should always be downloaded using the `astropy.utils.data.get_pkg_data_fileobj()` or `astropy.utils.data.get_pkg_data_filename()` functions. If a specific version of a data file is needed, the hash mechanism described in `astropy.utils.data` should be used.
- All persistent configuration should use the `astropy.config.ConfigurationItem` mechanism. Such configuration items should be placed at the top of the module or package that makes use of them, and supply a description sufficient for users to understand what the setting changes.

## Standard output, warnings, and errors

The built-in `print(...)` function should only be used for output that is explicitly requested by the user, for example `print_header(...)` or `list_catalogs(...)`. Any other standard output, warnings, and errors should follow these rules:

- For errors/exceptions, one should always use `raise` with one of the built-in exception classes, or a custom exception class. The nondescript `Exception` class should be avoided as much as possible, in favor of more specific exceptions (`IOError`, `ValueError`, etc.).
- For warnings, one should always use `warnings.warn(message, warning_class)`. These get redirected to `log.warn` by default, but one can still use the standard warning-catching mechanism and custom warning classes. The warning class should be either `AstropyUserWarning` or inherit from it.
- For informational and debugging messages, one should always use `log.info(message)` and `log.debug(message)`.

The logging system uses the built-in Python logging module. The logger can be imported using:

    from astropy import log

## Coding Style/Conventions

- The code will follow the standard PEP8 Style Guide for Python Code. In particular, this includes using only 4 spaces for indentation, and never tabs.

- One exception is to be made from the PEP8 style: new style relative imports of the form `from . import modname` are allowed and required for Astropy, as opposed to absolute (as PEP8 suggets) or the simpler `import modname` syntax. This is primarily due to improved relative import support since PEP8 was developed, and to simplify the process of moving modules.

  Note

  There are multiple options for testing PEP8 compliance of code, see Testing Guidelines for more information. See Emacs setup for following coding guidelines for some configuration options for Emacs that helps in ensuring conformance to PEP8.

- Astropy source code should contain a comment at the beginning of the file (or immediately after the `#!/usr/bin env python` command, if relevant) pointing to the license for the Astropy source code. This line should say:

      # Licensed under a 3-clause BSD style license - see LICENSE.rst

- The `import numpy as np`, `import matplotlib as mpl`, and `import matplotlib.pyplot as plt` naming conventions should be used wherever relevant. `from packagename import *` should never be used, except as a tool to flatten the namespace of a module. An example of the allowed usage is given in Acceptable use of from module import *.

- Classes should either use direct variable access, or python’s property mechanism for setting object instance variables. `get_value`/`set_value` style methods should be used only when getting and setting the values requires a computationally-expensive operation. Properties vs. get_/set_ below illustrates this guideline.

- All new classes should be new-style classes inheriting from `object` (in Python 3 this is a non-issue as all classes are new-style by default). The one exception to this rule is older classes in third-party libraries such the Python standard library or numpy.

- Classes should use the builtin `super()` function when making calls to methods in their super-class(es) unless there are specific reasons not to. `super()` should be used consistently in all subclasses since it does not work otherwise. super() vs. Direct Calling illustrates why this is important.

- Multiple inheritance should be avoided in general without good reason. Multiple inheritance is complicated to implement well, which is why many object-oriented languages, like Java, do not allow it at all. Python does enable multiple inheritance through use of the C3 Linearization algorithm, which provides a consistent method resolution ordering. Non-trivial multiple-inheritance schemes should not be attempted without good justification, or without understanding how C3 is used to determine method resolution order. However, trivial multiple inheritance using orthogonal base classes, known as the ‘mixin’ pattern, may be used.

- `__init__.py` files for modules should not contain any significant implementation code. `__init__.py` can contain docstrings and code for organizing the module layout, however (e.g. `from submodule import *` in accord with the guideline above). If a module is small enough that it fits in one file, it should simple be a single file, rather than a directory with an `__init__.py` file.

- When `try...except` blocks are used to catch exceptions, the `as` syntax should always be used, because this is available in all supported versions of python and is less ambiguous syntax (see try...except block “as” syntax).

- Command-line scripts should follow the form outlined in the Writing Command-Line Scripts document.

## Unicode guidelines

For maximum compatibility, we need to assume that writing non-ascii characters to the console or to files will not work. However, for those that have a correctly configured Unicode environment, we should allow them to opt-in to take advantage of Unicode output when appropriate. Therefore, there is a global configuration option, `astropy.UNICODE_OUTPUT` to enable Unicode output of values, set to `False` by default.

The following conventions should be used for classes that define the standard string conversion methods (`__str__`, `__repr__`, `__unicode__`, `__bytes__`, and `__format__`). In the bullets below, the phrase “unicode instance” is used to refer to `unicode` on Python 2 and `str` on Python 3. The phrase “bytes instance” is used to refer to `str` on Python 2 and `bytes` on Python 3.

- `__repr__`: Return a “unicode instance” (for historical reasons, could also be a “bytes instance” on Python 2, though not preferred) containing only 7-bit characters.
- `__str__` on Python 2 / `__bytes__` on Python 3: Return a “bytes instance” containing only 7-bit characters.
- `__unicode__` on Python 2 / `__str__` on Python 3: Return a “unicode instance”. If `astropy.UNICODE_OUTPUT` is `False`, it must contain only 7-bit characters. If `astropy.UNICODE_OUTPUT` is `True`, it may contain non-ascii characters when applicable.
- `__format__`: Return a “unicode instance”. If `astropy.UNICODE_OUTPUT` is `False`, it must contain only 7-bit characters. If `astropy.UNICODE_OUTPUT` is `True`, it may contain non-ascii characters when applicable.

For classes that are expected to roundtrip through strings (unicode or bytes), the parser must accept either the output of `__str__` or `__unicode__` unambiguously. Additionally, `__repr__` should roundtrip when that makes sense.

This design generally follows Postel’s Law: “Be liberal in what you accept, and conservative in what you send”.

The following example class shows a way to implement this (using six for Python 2 and 3 cross-version compatibility:

    # -*- coding: utf-8 -*-

    from __future__ import unicode_literals

    from astropy.extern import six
    from astropy import UNICODE_OUTPUT

    class FloatList(object):
        def __init__(self, init):
            if isinstance(init, six.text_type):
                init = init.split('‖')
            elif isinstance(init, bytes):
                init = init.split(b'|')
            self.x = [float(x) for x in init]

        def __repr__(self):
            # Return unicode object containing no non-ascii characters
            return '<FloatList [{0}]>'.format(', '.join(
                six.text_type(x) for x in self.x))

        def __bytes__(self):
            return b'|'.join(bytes(x) for x in self.x)
        if six.PY2:
            __str__ = __bytes__

        def __unicode__(self):
            if astropy.UNICODE_OUTPUT():
                return '‖'.join(six.text_type(x) for x in self.x)
            else:
                return self.__bytes__().decode('ascii')
        if six.PY3:
            __str__ = __unicode__

Additionally, there is a test helper, `astropy.test.helper.assert_follows_unicode_guidelines` to ensure that a class follows the Unicode guidelines outlined above. The following example test will test that our example class above is compliant:

    def test_unicode_guidelines():
        from astropy.test.helper import assert_follows_unicode_guidelines
        assert_follows_unicode_guidelines(FloatList(b'5|4|3|2'), roundtrip=True)

## Including C Code

- C extensions are only allowed when they provide a significant performance enhancement over pure python, or a robust C library already exists to provided the needed functionality. When C extensions are used, the Python interface must meet the aforementioned python interface guidelines.
- The use of Cython is strongly recommended for C extensions, as per the example in the template package. Cython extensions should store `.pyx` files in the source code repository, but they should be compiled to `.c` files that are updated in the repository when important changes are made to the `.pyx` file.
- If a C extension has a dependency on an external C library, the source code for the library should be bundled with the Astropy core, provided the license for the C library is compatible with the Astropy license. Additionally, the package must be compatible with using a system-installed library in place of the library included in Astropy.
- In cases where C extensions are needed but Cython cannot be used, the PEP 7 Style Guide for C Code is recommended.
- C extensions (Cython or otherwise) should provide the necessary information for building the extension via the mechanisms described in C or Cython Extensions.

## Writing portable code for Python 2 and 3

As of astropy 0.3, the six library is included to allow supporting Python 2 and 3 from a single code base. The use of the `2to3` tool is being phased out in favor of using `six`.

To start using `six` instead of `2to3` in a package, you first need to put the following in the package’s `setup_package.py` file:

    def requires_2to3():
        return False

This section is mainly about moving existing code that works with `2to3` to using `six`. It is not a complete guide to Python 2 and 3 compatibility.

### Welcome to the `__future__`

The top of every `py` file should include the following:

    from __future__ import (absolute_import, division, print_function,
                            unicode_literals)

This will make the Python 2 interpreter behave as close to Python 3 as possible.

All files should also import `six`, whether they are using it or not, just to make moving code between modules easier, as `six` gets used a lot:

    from ..extern import six

(where `extern` refers to `astropy.extern`). Do not import `six` from the top-level: only import the copy of `six` included with astropy.

### Finding places to use six

Unfortunately, the only way to be certain that code works on both Python 2 and 3 is to make sure it is covered by unit tests.

However, the `2to3` commandline tool can also be used to locate places that require special handling with `six`. Starting from Python 2 code, or code that is known to work on both Python 2 and 3 by processing it with the `2to3` tool (which is most of the existing code in astropy), simply run `2to3` on the file to display the changes it would make in diff format. This diff can be used to highlight places that need to be updated to use `six`.

For example, most things that have been renamed between Python 2 and 3 are in the `six.moves` namespace, so given this Python 2 code:

    import cPickle

it can be replaced with:

    from ..extern.six.moves import cPickle

Note

The modernize tool aims to convert Python 2 code to portable code that uses `six`, but at the time of this writing, it is not feature complete and misses many important transformations.

The six documentation serves as a good reference for the sorts of things that need to be updated.

### Not so fast on that Unicode thing

By importing `unicode_literals` from `__future__`, many things that were once byte strings on Python 2 will now by unicode strings. This is mostly a good thing, as the behavior of the code will be more consistent between Python 2 and 3. However, certain third-party libraries still assume certain values will be byte strings on Python 2.

For example, when specifying Numpy structured dtypes, all strings must be byte strings on Python 2 and unicode strings on Python 3. The easiest way to handle this is to force cast them using `str()`, for example:

    x = np.array([1.0, 2.0, 3.0], dtype=[(str('name'), '>f8')])

The same is true of structure specifiers in the built-in `struct` module on Python 2.6.

`pytest.mark.skipif` also requires a “native” string, i.e.:

    @pytest.mark.skipif(str('CONDITIONAL'))

### Iteration

The behavior of the methods for iterating over the items, values and keys of a dictionary has changed in Python 3. Additionally, other built-in functions such as `zip`, `range` and `map` have changed to return iterators rather than temporary lists.

In many cases, the performance implications of iterating vs. creating a temporary list won’t matter, so it’s tempting to use the form that is simplest to read. However, that results in code that behaves differently on Python 2 and 3, leading to subtle bugs that may not be detected by the regression tests. Therefore, unless the loop in question is provably simple and doesn’t call into other code, the `six` versions that ensure the same behavior on both Python 2 and 3 should be used. The following table shows the mapping of equivalent semantics between Python 2, 3 and six for `dict.items()`:

Python 2 | Python 3 | six
--- | --- | ---
`d.items()` | `list(d.items())` | `list(six.iteritems(d))`
`d.iteritems()` | `d.items()` | `six.iteritems(d)`

The above table holds true, analogously, for `values`, `keys`, `zip`, `range` and `map`.

### Issues with `\u` escapes

When `from __future__ import unicode_literals` is used, all string literals (not preceded with a `b`) will become unicode literals.

Normally, one would use “raw” string literals to encode strings that contain a lot of slashes that we don’t want Python to interpret as special characters. Unfortunately, on Python 2, there is no way to represent `u` in a raw unicode string literal, since it will always be interpreted as the start of a unicode character escape, such as `u20af`. The only solution is to use a regular (non-raw) string literal and repeat all slashes, e.g. `"\\usepackage{foo}"`.

The following shows the problem on Python 2:

    >>> ur'\u'
      File "<stdin>", line 1
    SyntaxError: (unicode error) 'rawunicodeescape' codec can't decode bytes in
    position 0-1: truncated \uXXXX
    >>> ur'\\u'
    u'\\\\u'
    >>> u'\u'
      File "<stdin>", line 1
    SyntaxError: (unicode error) 'unicodeescape' codec can't decode bytes in
    position 0-1: truncated \uXXXX escape
    >>> u'\\u'
    u'\\u'

This bug has been fixed in Python 3, however, we can’t take advantage of that and still support Python 2:

    >>> r'\u'
    '\\u'
    >>> r'\\u'
    '\\\\u'
    >>> '\u'
      File "<stdin>", line 1
    SyntaxError: (unicode error) 'unicodeescape' codec can't decode bytes in
    position 0-1: truncated \uXXXX escape
    >>> '\\u'
    '\\u'

## Requirements Specific to Affiliated Packages

- Affiliated packages implementing many classes/functions not relevant to the affiliated package itself (for example leftover code from a previous package) will not be accepted - the package should only include the required functionality and relevant extensions.
- Affiliated packages are required to follow the layout and documentation form of the template package included in the core package source distribution.
- Affiliated packages must be registered on the Python Package Index, with proper metadata for downloading and installing the source package.
- The `astropy` root package name should not be used by affiliated packages - it is reserved for use by the core package. Recommended naming conventions for an affiliated package are either simply `packagename` or `awastropy.packagename` (“affiliated with Astropy”).

## Examples

This section shows a few examples (not all of which are correct!) to illustrate points from the guidelines. These will be moved into the template project once it has been written.

### Properties vs. get_/set_

This example shows a sample class illustrating the guideline regarding the use of properties as opposed to getter/setter methods.

Let’s assuming you’ve defined a `Star` class and create an instance like this:

    >>> s = Star(B=5.48, V=4.83)

You should always use attribute syntax like this:

    >>> s.color = 0.4
    >>> print(s.color)
    0.4

Rather than like this:

    >>> s.set_color(0.4)  #Bad form!
    >>> print(s.get_color())  #Bad form!
    0.4

Using python properties, attribute syntax can still do anything possible with a get/set method. For lengthy or complex calculations, however, use a method:

    >>> print(s.compute_color(5800, age=5e9))
    0.4

### super() vs. Direct Calling

This example shows why the use of `super()` leads to a more consistent method resolution order than manually calling methods of the super classes in a multiple inheritance case:

    # This is dangerous and bug-prone!

    class A(object):
        def method(self):
            print('Doing A')

    class B(A):
        def method(self):
            print('Doing B')
            A.method(self)

    class C(A):
        def method(self):
            print('Doing C')
            A.method(self)

    class D(C, B):
        def method(self):
            print('Doing D')
            C.method(self)
            B.method(self)

if you then do:

    >>> b = B()
    >>> b.method()

you will see:

    Doing B
    Doing A

which is what you expect, and similarly for C. However, if you do:

    >>> d = D()
    >>> d.method()

you might expect to see the methods called in the order D, B, C, A but instead you see:

    Doing D
    Doing C
    Doing A
    Doing B
    Doing A

because both `B.method()` and `C.method()` call `A.method()` unaware of the fact that they’re being called as part of a chain in a hierarchy. When `C.method()` is called it is unaware that it’s being called from a subclass that inherits from both `B` and `C`, and that `B.method()` should be called next. By calling `super()` the entire method resolution order for `D` is precomputed, enabling each superclass to cooperatively determine which class should be handed control in the next `super()` call:

    # This is safer

    class A(object):
        def method(self):
            print('Doing A')

    class B(A):
        def method(self):
            print('Doing B')
            super(B, self).method()

    class C(A):
        def method(self):
            print('Doing C')
            super(C, self).method()

    class D(C, B):
        def method(self):
            print('Doing D')
            super(D, self).method()

    >>> d = D()
    >>> d.method()
    Doing D
    Doing C
    Doing B
    Doing A

As you can see, each superclass’s method is entered only once. For this to work it is very important that each method in a class that calls its superclass’s version of that method use `super()` instead of calling the method directly. In the most common case of single-inheritance, using `super()` is functionally equivalent to calling the superclass’s method directly. But as soon as a class is used in a multiple-inheritance hierarchy it must use `super()` in order to cooperate with other classes in the hierarchy.

Note

For more info on the pros and cons of using super, see http://rhettinger.wordpress.com/2011/05/26/super-considered-super/ or http://keithdevens.com/weblog/archive/2011/Mar/16/Python.super)

### Acceptable use of `from module import *`

`from module import *` is discouraged in a module that contains implementation code, as it impedes clarity and often imports unused variables. It can, however, be used for a package that is laid out in the following manner:

    packagename
    packagename/__init__.py
    packagename/submodule1.py
    packagename/submodule2.py

In this case, `packagename/__init__.py` may be:

    """
    A docstring describing the package goes here
    """
    from submodule1 import *
    from submodule2 import *

This allows functions or classes in the submodules to be used directly as `packagename.foo` rather than `packagename.submodule1.foo`. If this is used, it is strongly recommended that the submodules make use of the __all__ variable to specify which modules should be imported. Thus, submodule2.py might read:

    from numpy import array,linspace

    __all__ = ('foo', 'AClass')

    def foo(bar):
        #the function would be defined here
        pass

    class AClass(object):
        #the class is defined here
        pass

This ensures that `from submodule import *` only imports `foo()` and `AClass`, but not `numpy.array` or `numpy.linspace()`.

### try...except block “as” syntax

Catching of exceptions should always use this syntax:

    try:
        ... some code that might produce a variety of exceptions ...
    except ImportError as e:
        if 'somemodule' in e.args[0]"
            #for whatever reason, failed import of somemodule is ok
            pass
        else:
            raise
    except ValueError, TypeError as e:
        msg = 'Hit an input problem, which is ok,'
        msg2 = 'but we're printing it here just so you know:'
        print msg, msg2, e

This avoids the old style syntax of `except ImportError, e` or `except (ValueError,TypeError), e`, which is dangerous because it’s easy to instead accidentally do something like `except ValueError,TypeError`, which won’t catch `TypeError`.

## Additional Resources

Further tips and hints relating to the coding guidelines are included below.

- Emacs setup for following coding guidelines