path: root/_doc/api.ryd

version: 0.2
text: rst
fix_inline_single_backquotes: true
pdf: true
--- !python-pre |
import sys
from io import StringIO
import ruamel.yaml
from ruamel.yaml import YAML
yaml=YAML()
ostream = s = StringIO()
istream = stream = doc = "a: 1"
data = dict(a=1)
from pathlib import Path  # or: from ruamel.std.pathlib import Path
--- |
+++++++++++++++++++++++++++
Departure from previous API
+++++++++++++++++++++++++++

With version 0.15.0 ``ruamel.yaml`` starts to depart from the previous (PyYAML) way
of loading and dumping.  During a transition period the original
``load()`` and ``dump()`` in its various formats will still be supported,
but this is not guaranteed to be so with the transition to 1.0.

At the latest with 1.0, but possible earlier transition error and
warning messages will be issued, so any packages depending on
ruamel.yaml should pin the version with which they are testing.


Up to 0.15.0, the loaders (``load()``, ``safe_load()``,
``round_trip_load()``, ``load_all``, etc.) took, apart from the input
stream, a ``version`` argument to allow downgrading to YAML 1.1,
sometimes needed for
documents without directive. When round-tripping, there was an option to
preserve quotes.

Up to 0.15.0, the dumpers (``dump()``, ``safe_dump``,
``round_trip_dump()``, ``dump_all()``, etc.) had a plethora of
arguments, some inherited from ``PyYAML``, some added in
``ruamel.yaml``. The only required argument is the ``data`` to be
dumped. If the stream argument is not provided to the dumper, then a
string representation is build up in memory and returned to the
caller.

Starting with 0.15.0 ``load()`` and ``dump()`` are methods on a
``YAML`` instance and only take the stream,
resp. the data and stream argument. All other parameters are set on the instance
of ``YAML`` before calling ``load()`` or ``dump()``

Before 0.15.0 you could do:

.. code:: python

    from pathlib import Path
    from ruamel import yaml

    data = yaml.safe_load("abc: 1")
    out = Path('/tmp/out.yaml')
    with out.open('w') as fp:
        yaml.safe_dump(data, fp, default_flow_style=False)

after:
--- !python |
from pathlib import Path
from ruamel.yaml import YAML

yaml = YAML(typ='safe')
yaml.default_flow_style = False
data = yaml.load("abc: 1")
out = Path('/tmp/out.yaml')
yaml.dump(data, out)
--- |
If you previously used a keyword argument ``explicit_start=True`` you
now do ``yaml.explicit_start = True`` before calling ``dump()``. The
``Loader`` and ``Dumper`` keyword arguments are not supported that
way. You can provide the ``typ`` keyword to ``rt``  (default),
``safe``, ``unsafe`` or ``base`` (for round-trip load/dump, safe_load/dump,
load/dump resp. using the BaseLoader / BaseDumper. More fine-control
is possible by setting the attributes ``.Parser``, ``.Constructor``,
``.Emitter``, etc., to the class of the type to create for that stage
(typically a subclass of an existing class implementing that).

The default loader (``typ='rt'``) is a direct derivative of the safe loader, without the
methods to construct arbitrary Python objects that make the ``unsafe`` loader
unsafe, but with the changes needed for round-trip preservation of comments,
etc.. For trusted Python classes a constructor can of course be added to the round-trip
or safe-loader, but this has to be done explicitly (``add_constructor``).

All data is dumped (not just for round-trip-mode) with ``.allow_unicode
= True``

You can of course have multiple YAML instances active at the same
time, with different load and/or dump behaviour.

Initially only the typical operations are supported, but in principle
all functionality of the old interface will be available via
``YAML`` instances (if you are using something that isn't let me know).

If a parse or dump fails, and throws and exception, the state of the
``YAML()`` instance is not guaranteed to be able to handle further
processing. You should, at that point to recreate the YAML instance before
proceeding.


Loading
+++++++

Duplicate keys
^^^^^^^^^^^^^^

In JSON mapping keys should be unique, in YAML they must be unique.
PyYAML never enforced this although the YAML 1.1 specification already
required this.

In the new API (starting 0.15.1) duplicate keys in mappings are no longer allowed by
default. To allow duplicate keys in mappings:

--- !python |
yaml = ruamel.yaml.YAML()
yaml.allow_duplicate_keys = True
yaml.load(stream)
--- |
In the old API this is a warning starting with 0.15.2 and an error in
0.16.0.

When a duplicate key is found it and its value are discarded, as should be done
according to the `YAML 1.1 specification <http://yaml.org/spec/1.1/#id932806>`__.

Dumping a multi-documents YAML stream
+++++++++++++++++++++++++++++++++++++

The "normal" ``dump_all`` expected as first element a list of documents, or 
something else the internals of the method can iterate over. To read
and write a multi-document you would either make a ``list``::

--- !code |
   yaml = YAML()
   data = list(yaml.load_all(in_path))
   # do something on data[0], data[1], etc.
   yaml.dump_all(data, out_path)
--- |

or create some function/object that would yield the ``data`` values.

What you now can do is create ``YAML()`` as an context manager. This
works for output (dumping) only, requires you to specify the output
(file, buffer, ``Path``) at creation time, and doesn't support
``transform`` (yet).

::

--- !code |
    with YAML(output=sys.stdout) as yaml:
            yaml.explicit_start = True
            for data in yaml.load_all(Path(multi_document_filename)):
                # do something on data
                yaml.dump(data)
--- |

Within the context manager, you cannot use the ``dump()`` with a
second (stream) argument, nor can you use ``dump_all()``. The
``dump()`` within the context of the ``YAML()`` automatically creates
multi-document if called more than once.

To combine multiple YAML documents from multiple files:

::

--- !code |
    list_of_filenames = ['x.yaml', 'y.yaml', ]
    with YAML(output=sys.stdout) as yaml:
            yaml.explicit_start = True
            for path in list_of_filename:
                with open(path) as fp:
                    yaml.dump(yaml.load(fp))
--- |

The output will be a valid, uniformly indented YAML file. Doing
``cat {x,y}.yaml`` might result in a single document if there is not
document start marker at the beginning of ``y.yaml``




Dumping
+++++++

Controls
^^^^^^^^

On your ``YAML()`` instance you can set attributes e.g with::

  yaml = YAML(typ='safe', pure=True)
  yaml.allow_unicode = False

available attributes include:

``unicode_supplementary``
   Defaults to ``True`` if Python's Unicode size is larger than 2 bytes. Set to ``False`` to
   enforce output of the form ``\U0001f601`` (ignored if ``allow_unicode`` is ``False``)

Transparent usage of new and old API
++++++++++++++++++++++++++++++++++++

If you have multiple packages depending on ``ruamel.yaml``, or install
your utility together with other packages not under your control, then
fixing your ``install_requires`` might not be so easy.

Depending on your usage you might be able to "version" your usage to
be compatible with both the old and the new. The following are some
examples all assuming ``from ruamel import yaml`` somewhere at the top
of your file and some ``istream`` and ``ostream`` apropriately opened
for reading resp.  writing.


Loading and dumping using the ``SafeLoader``::

    if ruamel.yaml.version_info < (0, 15):
        data = yaml.safe_load(istream)
        yaml.safe_dump(data, ostream)
    else:
        yml = ruamel.yaml.YAML(typ='safe', pure=True)  # 'safe' load and dump
        data = yml.load(istream)
        yml.dump(data, ostream)

Loading with the ``CSafeLoader``, dumping with
``RoundTripLoader``. You need two ``YAML`` instances, but each of them
can be re-used:
--- !python |
if ruamel.yaml.version_info < (0, 15):
    data = yaml.load(istream, Loader=yaml.CSafeLoader)
    yaml.round_trip_dump(data, ostream, width=1000, explicit_start=True)
else:
    yml = ruamel.yaml.YAML(typ='safe')
    data = yml.load(istream)
    ymlo = ruamel.yaml.YAML()   # or yaml.YAML(typ='rt')
    ymlo.width = 1000
    ymlo.explicit_start = True
    ymlo.dump(data, ostream)
--- |
Loading and dumping from  ``pathlib.Path`` instances using the
round-trip-loader::

--- !code |
# in myyaml.py
if ruamel.yaml.version_info < (0, 15):
    class MyYAML(yaml.YAML):
        def __init__(self):
            yaml.YAML.__init__(self)
            self.preserve_quotes = True
            self.indent(mapping=4, sequence=4, offset=2)
# in your code
try:
    from myyaml import MyYAML
except (ModuleNotFoundError, ImportError):
    if ruamel.yaml.version_info >= (0, 15):
        raise

# some pathlib.Path
from pathlib import Path
inf = Path('/tmp/in.yaml')
outf = Path('/tmp/out.yaml')

if ruamel.yaml.version_info < (0, 15):
    with inf.open() as ifp:
         data = yaml.round_trip_load(ifp, preserve_quotes=True)
    with outf.open('w') as ofp:
         yaml.round_trip_dump(data, ofp, indent=4, block_seq_indent=2)
else:
    yml = MyYAML()
    # no need for with statement when using pathlib.Path instances
    data = yml.load(inf)
    yml.dump(data, outf)
--- |
+++++++++++++++++++++
Reason for API change
+++++++++++++++++++++

``ruamel.yaml`` inherited the way of doing things from ``PyYAML``. In
particular when calling the function ``load()`` or ``dump()``
temporary instances of  ``Loader()`` resp. ``Dumper()``  were
created that were discarded on termination of the function.

This way of doing things leads to several problems:

- it is virtually impossible to return information to the caller apart from the
  constructed data structure. E.g. if you would get a YAML document
  version number from a directive, there is no way to let the caller
  know apart from handing back special data structures. The same
  problem exists when trying to do on the fly
  analysis of a document for indentation width.

- these instances were composites of the various load/dump steps and
  if you wanted to enhance one of the steps, you needed e.g. subclass
  the emitter and make a new composite (dumper) as well, providing all
  of the parameters (i.e. copy paste)

  Alternatives, like making a class that returned a ``Dumper`` when
  called and sets attributes before doing so, is cumbersome for
  day-to-day use.

- many routines (like ``add_representer()``) have a direct global
  impact on all of the following calls to ``dump()`` and those are
  difficult if not impossible to turn back. This forces the need to
  subclass ``Loaders`` and ``Dumpers``, a long time problem in PyYAML
  as some attributes were not ``deep_copied`` although a bug-report
  (and fix) had been available a long time.

- If you want to set an attribute, e.g. to control whether literal
  block style scalars are allowed to have trailing spaces on a line
  instead of being dumped as double quoted scalars, you have to change
  the ``dump()`` family of routines, all of the ``Dumpers()`` as well
  as the actual functionality change in ``emitter.Emitter()``. The
  functionality change takes changing 4 (four!) lines in one file, and being able
  to enable that another 50+ line changes (non-contiguous) in 3 more files resulting
  in diff that is far over 200 lines long.

- replacing libyaml with something that doesn't both support ``0o52``
  and ``052`` for the integer ``42`` (instead of ``52`` as per YAML 1.2)
  is difficult


With ``ruamel.yaml>=0.15.0`` the various steps "know" about the
``YAML`` instance and can pick up setting, as well as report back
information via that instance. Representers, etc., are added to a
reusable instance and different YAML instances can co-exists.

This change eases development and helps prevent regressions.