.. _serialization: Serialization ============= In order to dump a **Quantity** to disk, store it in a database or transmit it over the wire you need to be able to serialize and then deserialize the object. The easiest way to do this is by converting the quantity to a string: .. testsetup:: * import pint .. doctest:: >>> import pint >>> ureg = pint.UnitRegistry() >>> duration = 24.2 * ureg.years >>> duration >>> serialized = str(duration) >>> print(serialized) 24.2 year Remember that you can easily control the number of digits in the representation as shown in `String formatting`_. You dump/store/transmit the content of serialized ('24.2 year'). When you want to recover it in another process/machine, you just: .. doctest:: >>> import pint >>> ureg = pint.UnitRegistry() >>> duration = ureg('24.2 year') >>> print(duration) 24.2 year Notice that the serialized quantity is likely to be parsed in **another** registry as shown in this example. Pint Quantities do not exist on their own but they are always related to a **UnitRegistry**. Everything will work as expected if both registries, are compatible (e.g. they were created using the same definition file). However, things could go wrong if the registries are incompatible. For example, **year** could not be defined in the target registry. Or what is even worse, it could be defined in a different way. Always have to keep in mind that the interpretation and conversion of Quantities are UnitRegistry dependent. In certain cases, you want a binary representation of the data. Python's standard algorithm for serialization is called Pickle_. Pint quantities implement the magic `__reduce__` method and therefore can be *Pickled* and *Unpickled*. However, you have to bear in mind, that the **DEFAULT_REGISTRY** is used for unpickling and this might be different from the one that was used during pickling. If you want to have control over the deserialization, the best way is to create a tuple with the magnitude and the units: .. doctest:: >>> to_serialize = duration.to_tuple() >>> print(to_serialize) (24.2, (('year', 1.0),)) And then you can just pickle that: >>> import pickle >>> serialized = pickle.dumps(to_serialize, -1) To unpickle, just >>> loaded = pickle.loads(serialized) >>> ureg.Quantity.from_tuple(loaded) (To pickle to and from a file just use the dump and load method as described in _Pickle) You can use the same mechanism with any serialization protocol, not only with binary ones. (In fact, version 0 of the Pickle protocol is ASCII). Other common serialization protocols/packages are json_, yaml_, shelve_, hdf5_ (or via PyTables_) and dill_. Notice that not all of these packages will serialize properly the magnitude (which can be any numerical type such as `numpy.ndarray`). Using the serialize_ package you can load and read from multiple formats: >>> from serialize import dump, load, register_class >>> register_class(ureg.Quantity, ureg.Quantity.to_tuple, ureg.Quantity.from_tuple) >>> dump(duration, 'output.yaml') >>> r = load('output.yaml') (Check out the serialize_ docs for more information) .. _serialize: https://github.com/hgrecco/serialize .. _Pickle: http://docs.python.org/3/library/pickle.html .. _json: http://docs.python.org/3/library/json.html .. _yaml: http://pyyaml.org/ .. _shelve: http://docs.python.org/3.4/library/shelve.html .. _hdf5: http://www.h5py.org/ .. _PyTables: http://www.pytables.org .. _dill: https://pypi.python.org/pypi/dill