# Departure from previous API

With version 0.15.0 `ruyaml` 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 ruyaml 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 `ruyaml`. 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:

    from pathlib import Path
    import ruyaml

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

after:

    from pathlib import Path
    from ruyaml 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:

    yaml = ruyaml.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.

## 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`:

    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).

    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:

    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 `ruyaml`, 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 `import ruyaml` somewhere at the top of your file and some `istream` and `ostream` apropriately opened for reading resp. writing.

Loading and dumping using the `SafeLoader`:

    yml = ruyaml.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:

    yml = ruyaml.YAML(typ='safe')
    data = yml.load(istream)
    ymlo = ruyaml.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:

    # in myyaml.py
    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
    from myyaml import MyYAML

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

    yml = MyYAML()
    # no need for with statement when using pathlib.Path instances
    data = yml.load(inf)
    yml.dump(data, outf)

# Reason for API change

`ruyaml` 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 `ruyaml>=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.