=========================== Writing custom model fields =========================== .. currentmodule:: django.db.models Introduction ============ The :doc:`model reference ` documentation explains how to use Django's standard field classes -- :class:`~django.db.models.CharField`, :class:`~django.db.models.DateField`, etc. For many purposes, those classes are all you'll need. Sometimes, though, the Django version won't meet your precise requirements, or you'll want to use a field that is entirely different from those shipped with Django. Django's built-in field types don't cover every possible database column type -- only the common types, such as ``VARCHAR`` and ``INTEGER``. For more obscure column types, such as geographic polygons or even user-created types such as `PostgreSQL custom types`_, you can define your own Django ``Field`` subclasses. .. _PostgreSQL custom types: http://www.postgresql.org/docs/8.2/interactive/sql-createtype.html Alternatively, you may have a complex Python object that can somehow be serialized to fit into a standard database column type. This is another case where a ``Field`` subclass will help you use your object with your models. Our example object ------------------ Creating custom fields requires a bit of attention to detail. To make things easier to follow, we'll use a consistent example throughout this document: wrapping a Python object representing the deal of cards in a hand of Bridge_. Don't worry, you don't have know how to play Bridge to follow this example. You only need to know that 52 cards are dealt out equally to four players, who are traditionally called *north*, *east*, *south* and *west*. Our class looks something like this:: class Hand(object): """A hand of cards (bridge style)""" def __init__(self, north, east, south, west): # Input parameters are lists of cards ('Ah', '9s', etc) self.north = north self.east = east self.south = south self.west = west # ... (other possibly useful methods omitted) ... .. _Bridge: http://en.wikipedia.org/wiki/Contract_bridge This is just an ordinary Python class, with nothing Django-specific about it. We'd like to be able to do things like this in our models (we assume the ``hand`` attribute on the model is an instance of ``Hand``):: example = MyModel.objects.get(pk=1) print example.hand.north new_hand = Hand(north, east, south, west) example.hand = new_hand example.save() We assign to and retrieve from the ``hand`` attribute in our model just like any other Python class. The trick is to tell Django how to handle saving and loading such an object. In order to use the ``Hand`` class in our models, we **do not** have to change this class at all. This is ideal, because it means you can easily write model support for existing classes where you cannot change the source code. .. note:: You might only be wanting to take advantage of custom database column types and deal with the data as standard Python types in your models; strings, or floats, for example. This case is similar to our ``Hand`` example and we'll note any differences as we go along. Background theory ================= Database storage ---------------- The simplest way to think of a model field is that it provides a way to take a normal Python object -- string, boolean, ``datetime``, or something more complex like ``Hand`` -- and convert it to and from a format that is useful when dealing with the database (and serialization, but, as we'll see later, that falls out fairly naturally once you have the database side under control). Fields in a model must somehow be converted to fit into an existing database column type. Different databases provide different sets of valid column types, but the rule is still the same: those are the only types you have to work with. Anything you want to store in the database must fit into one of those types. Normally, you're either writing a Django field to match a particular database column type, or there's a fairly straightforward way to convert your data to, say, a string. For our ``Hand`` example, we could convert the card data to a string of 104 characters by concatenating all the cards together in a pre-determined order -- say, all the *north* cards first, then the *east*, *south* and *west* cards. So ``Hand`` objects can be saved to text or character columns in the database. What does a field class do? --------------------------- .. class:: Field All of Django's fields (and when we say *fields* in this document, we always mean model fields and not :doc:`form fields `) are subclasses of :class:`django.db.models.Field`. Most of the information that Django records about a field is common to all fields -- name, help text, uniqueness and so forth. Storing all that information is handled by ``Field``. We'll get into the precise details of what ``Field`` can do later on; for now, suffice it to say that everything descends from ``Field`` and then customizes key pieces of the class behavior. It's important to realize that a Django field class is not what is stored in your model attributes. The model attributes contain normal Python objects. The field classes you define in a model are actually stored in the ``Meta`` class when the model class is created (the precise details of how this is done are unimportant here). This is because the field classes aren't necessary when you're just creating and modifying attributes. Instead, they provide the machinery for converting between the attribute value and what is stored in the database or sent to the :doc:`serializer `. Keep this in mind when creating your own custom fields. The Django ``Field`` subclass you write provides the machinery for converting between your Python instances and the database/serializer values in various ways (there are differences between storing a value and using a value for lookups, for example). If this sounds a bit tricky, don't worry -- it will become clearer in the examples below. Just remember that you will often end up creating two classes when you want a custom field: * The first class is the Python object that your users will manipulate. They will assign it to the model attribute, they will read from it for displaying purposes, things like that. This is the ``Hand`` class in our example. * The second class is the ``Field`` subclass. This is the class that knows how to convert your first class back and forth between its permanent storage form and the Python form. Writing a field subclass ======================== When planning your :class:`~django.db.models.Field` subclass, first give some thought to which existing :class:`~django.db.models.Field` class your new field is most similar to. Can you subclass an existing Django field and save yourself some work? If not, you should subclass the :class:`~django.db.models.Field` class, from which everything is descended. Initializing your new field is a matter of separating out any arguments that are specific to your case from the common arguments and passing the latter to the :meth:`~django.db.models.Field.__init__` method of :class:`~django.db.models.Field` (or your parent class). In our example, we'll call our field ``HandField``. (It's a good idea to call your :class:`~django.db.models.Field` subclass ``Field``, so it's easily identifiable as a :class:`~django.db.models.Field` subclass.) It doesn't behave like any existing field, so we'll subclass directly from :class:`~django.db.models.Field`:: from django.db import models class HandField(models.Field): description = "A hand of cards (bridge style)" def __init__(self, *args, **kwargs): kwargs['max_length'] = 104 super(HandField, self).__init__(*args, **kwargs) Our ``HandField`` accepts most of the standard field options (see the list below), but we ensure it has a fixed length, since it only needs to hold 52 card values plus their suits; 104 characters in total. .. note:: Many of Django's model fields accept options that they don't do anything with. For example, you can pass both :attr:`~django.db.models.Field.editable` and :attr:`~django.db.models.Field.auto_now` to a :class:`django.db.models.DateField` and it will simply ignore the :attr:`~django.db.models.Field.editable` parameter (:attr:`~django.db.models.Field.auto_now` being set implies ``editable=False``). No error is raised in this case. This behavior simplifies the field classes, because they don't need to check for options that aren't necessary. They just pass all the options to the parent class and then don't use them later on. It's up to you whether you want your fields to be more strict about the options they select, or to use the simpler, more permissive behavior of the current fields. .. method:: Field.__init__ The :meth:`~django.db.models.Field.__init__` method takes the following parameters: * :attr:`~django.db.models.Field.verbose_name` * :attr:`~django.db.models.Field.name` * :attr:`~django.db.models.Field.primary_key` * :attr:`~django.db.models.Field.max_length` * :attr:`~django.db.models.Field.unique` * :attr:`~django.db.models.Field.blank` * :attr:`~django.db.models.Field.null` * :attr:`~django.db.models.Field.db_index` * :attr:`~django.db.models.Field.rel`: Used for related fields (like :class:`ForeignKey`). For advanced use only. * :attr:`~django.db.models.Field.default` * :attr:`~django.db.models.Field.editable` * :attr:`~django.db.models.Field.serialize`: If ``False``, the field will not be serialized when the model is passed to Django's :doc:`serializers `. Defaults to ``True``. * :attr:`~django.db.models.Field.unique_for_date` * :attr:`~django.db.models.Field.unique_for_month` * :attr:`~django.db.models.Field.unique_for_year` * :attr:`~django.db.models.Field.choices` * :attr:`~django.db.models.Field.help_text` * :attr:`~django.db.models.Field.db_column` * :attr:`~django.db.models.Field.db_tablespace`: Only for index creation, if the backend supports :doc:`tablespaces `. You can usually ignore this option. * :attr:`~django.db.models.Field.auto_created`: True if the field was automatically created, as for the `OneToOneField` used by model inheritance. For advanced use only. All of the options without an explanation in the above list have the same meaning they do for normal Django fields. See the :doc:`field documentation ` for examples and details. The ``SubfieldBase`` metaclass ------------------------------ .. class:: django.db.models.SubfieldBase As we indicated in the introduction_, field subclasses are often needed for two reasons: either to take advantage of a custom database column type, or to handle complex Python types. Obviously, a combination of the two is also possible. If you're only working with custom database column types and your model fields appear in Python as standard Python types direct from the database backend, you don't need to worry about this section. If you're handling custom Python types, such as our ``Hand`` class, we need to make sure that when Django initializes an instance of our model and assigns a database value to our custom field attribute, we convert that value into the appropriate Python object. The details of how this happens internally are a little complex, but the code you need to write in your ``Field`` class is simple: make sure your field subclass uses a special metaclass: For example:: class HandField(models.Field): description = "A hand of cards (bridge style)" __metaclass__ = models.SubfieldBase def __init__(self, *args, **kwargs): # ... This ensures that the :meth:`.to_python` method, documented below, will always be called when the attribute is initialized. ModelForms and custom fields ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If you use :class:`~django.db.models.SubfieldBase`, :meth:`.to_python` will be called every time an instance of the field is assigned a value. This means that whenever a value may be assigned to the field, you need to ensure that it will be of the correct datatype, or that you handle any exceptions. This is especially important if you use :doc:`ModelForms `. When saving a ModelForm, Django will use form values to instantiate model instances. However, if the cleaned form data can't be used as valid input to the field, the normal form validation process will break. Therefore, you must ensure that the form field used to represent your custom field performs whatever input validation and data cleaning is necessary to convert user-provided form input into a `to_python()`-compatible model field value. This may require writing a custom form field, and/or implementing the :meth:`.formfield` method on your field to return a form field class whose `to_python()` returns the correct datatype. Documenting your custom field ----------------------------- .. attribute:: Field.description As always, you should document your field type, so users will know what it is. In addition to providing a docstring for it, which is useful for developers, you can also allow users of the admin app to see a short description of the field type via the :doc:`django.contrib.admindocs ` application. To do this simply provide descriptive text in a ``description`` class attribute of your custom field. In the above example, the description displayed by the ``admindocs`` application for a ``HandField`` will be 'A hand of cards (bridge style)'. Useful methods -------------- Once you've created your :class:`~django.db.models.Field` subclass and set up the ``__metaclass__``, you might consider overriding a few standard methods, depending on your field's behavior. The list of methods below is in approximately decreasing order of importance, so start from the top. Custom database types ~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.db_type(self, connection) .. versionadded:: 1.2 The ``connection`` argument was added to support multiple databases. Returns the database column data type for the :class:`~django.db.models.Field`, taking into account the connection object, and the settings associated with it. Say you've created a PostgreSQL custom type called ``mytype``. You can use this field with Django by subclassing ``Field`` and implementing the :meth:`.db_type` method, like so:: from django.db import models class MytypeField(models.Field): def db_type(self, connection): return 'mytype' Once you have ``MytypeField``, you can use it in any model, just like any other ``Field`` type:: class Person(models.Model): name = models.CharField(max_length=80) gender = models.CharField(max_length=1) something_else = MytypeField() If you aim to build a database-agnostic application, you should account for differences in database column types. For example, the date/time column type in PostgreSQL is called ``timestamp``, while the same column in MySQL is called ``datetime``. The simplest way to handle this in a :meth:`.db_type` method is to check the ``connection.settings_dict['ENGINE']`` attribute. For example:: class MyDateField(models.Field): def db_type(self, connection): if connection.settings_dict['ENGINE'] == 'django.db.backends.mysql': return 'datetime' else: return 'timestamp' The :meth:`.db_type` method is only called by Django when the framework constructs the ``CREATE TABLE`` statements for your application -- that is, when you first create your tables. It's not called at any other time, so it can afford to execute slightly complex code, such as the ``connection.settings_dict`` check in the above example. Some database column types accept parameters, such as ``CHAR(25)``, where the parameter ``25`` represents the maximum column length. In cases like these, it's more flexible if the parameter is specified in the model rather than being hard-coded in the ``db_type()`` method. For example, it wouldn't make much sense to have a ``CharMaxlength25Field``, shown here:: # This is a silly example of hard-coded parameters. class CharMaxlength25Field(models.Field): def db_type(self, connection): return 'char(25)' # In the model: class MyModel(models.Model): # ... my_field = CharMaxlength25Field() The better way of doing this would be to make the parameter specifiable at run time -- i.e., when the class is instantiated. To do that, just implement :meth:`django.db.models.Field.__init__`, like so:: # This is a much more flexible example. class BetterCharField(models.Field): def __init__(self, max_length, *args, **kwargs): self.max_length = max_length super(BetterCharField, self).__init__(*args, **kwargs) def db_type(self, connection): return 'char(%s)' % self.max_length # In the model: class MyModel(models.Model): # ... my_field = BetterCharField(25) Finally, if your column requires truly complex SQL setup, return ``None`` from :meth:`.db_type`. This will cause Django's SQL creation code to skip over this field. You are then responsible for creating the column in the right table in some other way, of course, but this gives you a way to tell Django to get out of the way. Converting database values to Python objects ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.to_python(self, value) Converts a value as returned by your database (or a serializer) to a Python object. The default implementation simply returns ``value``, for the common case in which the database backend already returns data in the correct format (as a Python string, for example). If your custom :class:`~django.db.models.Field` class deals with data structures that are more complex than strings, dates, integers or floats, then you'll need to override this method. As a general rule, the method should deal gracefully with any of the following arguments: * An instance of the correct type (e.g., ``Hand`` in our ongoing example). * A string (e.g., from a deserializer). * Whatever the database returns for the column type you're using. In our ``HandField`` class, we're storing the data as a VARCHAR field in the database, so we need to be able to process strings and ``Hand`` instances in :meth:`.to_python`:: import re class HandField(models.Field): # ... def to_python(self, value): if isinstance(value, Hand): return value # The string case. p1 = re.compile('.{26}') p2 = re.compile('..') args = [p2.findall(x) for x in p1.findall(value)] return Hand(*args) Notice that we always return a ``Hand`` instance from this method. That's the Python object type we want to store in the model's attribute. **Remember:** If your custom field needs the :meth:`to_python` method to be called when it is created, you should be using `The SubfieldBase metaclass`_ mentioned earlier. Otherwise :meth:`.to_python` won't be called automatically. Converting Python objects to query values ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.get_prep_value(self, value) .. versionadded:: 1.2 This method was factored out of ``get_db_prep_value()`` This is the reverse of :meth:`.to_python` when working with the database backends (as opposed to serialization). The ``value`` parameter is the current value of the model's attribute (a field has no reference to its containing model, so it cannot retrieve the value itself), and the method should return data in a format that has been prepared for use as a parameter in a query. This conversion should *not* include any database-specific conversions. If database-specific conversions are required, they should be made in the call to :meth:`.get_db_prep_value`. For example:: class HandField(models.Field): # ... def get_prep_value(self, value): return ''.join([''.join(l) for l in (value.north, value.east, value.south, value.west)]) Converting query values to database values ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.get_db_prep_value(self, value, connection, prepared=False) .. versionadded:: 1.2 The ``connection`` and ``prepared`` arguments were added to support multiple databases. Some data types (for example, dates) need to be in a specific format before they can be used by a database backend. :meth:`.get_db_prep_value` is the method where those conversions should be made. The specific connection that will be used for the query is passed as the ``connection`` parameter. This allows you to use backend-specific conversion logic if it is required. The ``prepared`` argument describes whether or not the value has already been passed through :meth:`.get_prep_value` conversions. When ``prepared`` is False, the default implementation of :meth:`.get_db_prep_value` will call :meth:`.get_prep_value` to do initial data conversions before performing any database-specific processing. .. method:: Field.get_db_prep_save(self, value, connection) .. versionadded:: 1.2 The ``connection`` argument was added to support multiple databases. Same as the above, but called when the Field value must be *saved* to the database. As the default implementation just calls :meth:`.get_db_prep_value`, you shouldn't need to implement this method unless your custom field needs a special conversion when being saved that is not the same as the conversion used for normal query parameters (which is implemented by :meth:`.get_db_prep_value`). Preprocessing values before saving ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.pre_save(self, model_instance, add) This method is called just prior to :meth:`.get_db_prep_save` and should return the value of the appropriate attribute from ``model_instance`` for this field. The attribute name is in ``self.attname`` (this is set up by :class:`~django.db.models.Field`). If the model is being saved to the database for the first time, the ``add`` parameter will be ``True``, otherwise it will be ``False``. You only need to override this method if you want to preprocess the value somehow, just before saving. For example, Django's :class:`~django.db.models.DateTimeField` uses this method to set the attribute correctly in the case of :attr:`~django.db.models.Field.auto_now` or :attr:`~django.db.models.Field.auto_now_add`. If you do override this method, you must return the value of the attribute at the end. You should also update the model's attribute if you make any changes to the value so that code holding references to the model will always see the correct value. Preparing values for use in database lookups ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ As with value conversions, preparing a value for database lookups is a two phase process. .. method:: Field.get_prep_lookup(self, lookup_type, value) .. versionadded:: 1.2 This method was factored out of ``get_db_prep_lookup()`` :meth:`.get_prep_lookup` performs the first phase of lookup preparation, performing generic data validity checks Prepares the ``value`` for passing to the database when used in a lookup (a ``WHERE`` constraint in SQL). The ``lookup_type`` will be one of the valid Django filter lookups: ``exact``, ``iexact``, ``contains``, ``icontains``, ``gt``, ``gte``, ``lt``, ``lte``, ``in``, ``startswith``, ``istartswith``, ``endswith``, ``iendswith``, ``range``, ``year``, ``month``, ``day``, ``isnull``, ``search``, ``regex``, and ``iregex``. Your method must be prepared to handle all of these ``lookup_type`` values and should raise either a ``ValueError`` if the ``value`` is of the wrong sort (a list when you were expecting an object, for example) or a ``TypeError`` if your field does not support that type of lookup. For many fields, you can get by with handling the lookup types that need special handling for your field and pass the rest to the :meth:`.get_db_prep_lookup` method of the parent class. If you needed to implement ``get_db_prep_save()``, you will usually need to implement ``get_prep_lookup()``. If you don't, ``get_prep_value`` will be called by the default implementation, to manage ``exact``, ``gt``, ``gte``, ``lt``, ``lte``, ``in`` and ``range`` lookups. You may also want to implement this method to limit the lookup types that could be used with your custom field type. Note that, for ``range`` and ``in`` lookups, ``get_prep_lookup`` will receive a list of objects (presumably of the right type) and will need to convert them to a list of things of the right type for passing to the database. Most of the time, you can reuse ``get_prep_value()``, or at least factor out some common pieces. For example, the following code implements ``get_prep_lookup`` to limit the accepted lookup types to ``exact`` and ``in``:: class HandField(models.Field): # ... def get_prep_lookup(self, lookup_type, value): # We only handle 'exact' and 'in'. All others are errors. if lookup_type == 'exact': return self.get_prep_value(value) elif lookup_type == 'in': return [self.get_prep_value(v) for v in value] else: raise TypeError('Lookup type %r not supported.' % lookup_type) .. method:: Field.get_db_prep_lookup(self, lookup_type, value, connection, prepared=False) .. versionadded:: 1.2 The ``connection`` and ``prepared`` arguments were added to support multiple databases. Performs any database-specific data conversions required by a lookup. As with :meth:`.get_db_prep_value`, the specific connection that will be used for the query is passed as the ``connection`` parameter. The ``prepared`` argument describes whether the value has already been prepared with :meth:`.get_prep_lookup`. Specifying the form field for a model field ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.formfield(self, form_class=forms.CharField, **kwargs) Returns the default form field to use when this field is displayed in a model. This method is called by the :class:`~django.forms.ModelForm` helper. All of the ``kwargs`` dictionary is passed directly to the form field's :meth:`~django.forms.Field__init__` method. Normally, all you need to do is set up a good default for the ``form_class`` argument and then delegate further handling to the parent class. This might require you to write a custom form field (and even a form widget). See the :doc:`forms documentation ` for information about this, and take a look at the code in :mod:`django.contrib.localflavor` for some examples of custom widgets. Continuing our ongoing example, we can write the :meth:`.formfield` method as:: class HandField(models.Field): # ... def formfield(self, **kwargs): # This is a fairly standard way to set up some defaults # while letting the caller override them. defaults = {'form_class': MyFormField} defaults.update(kwargs) return super(HandField, self).formfield(**defaults) This assumes we've imported a ``MyFormField`` field class (which has its own default widget). This document doesn't cover the details of writing custom form fields. .. _helper functions: ../forms/#generating-forms-for-models .. _forms documentation: ../forms/ Emulating built-in field types ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.get_internal_type(self) Returns a string giving the name of the :class:`~django.db.models.Field` subclass we are emulating at the database level. This is used to determine the type of database column for simple cases. If you have created a :meth:`.db_type` method, you don't need to worry about :meth:`.get_internal_type` -- it won't be used much. Sometimes, though, your database storage is similar in type to some other field, so you can use that other field's logic to create the right column. For example:: class HandField(models.Field): # ... def get_internal_type(self): return 'CharField' No matter which database backend we are using, this will mean that ``syncdb`` and other SQL commands create the right column type for storing a string. If :meth:`.get_internal_type` returns a string that is not known to Django for the database backend you are using -- that is, it doesn't appear in ``django.db.backends..creation.DATA_TYPES`` -- the string will still be used by the serializer, but the default :meth:`.db_type` method will return ``None``. See the documentation of :meth:`.db_type` for reasons why this might be useful. Putting a descriptive string in as the type of the field for the serializer is a useful idea if you're ever going to be using the serializer output in some other place, outside of Django. Converting field data for serialization ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. method:: Field.value_to_string(self, obj) This method is used by the serializers to convert the field into a string for output. Calling :meth:`Field._get_val_from_obj(obj)` is the best way to get the value to serialize. For example, since our ``HandField`` uses strings for its data storage anyway, we can reuse some existing conversion code:: class HandField(models.Field): # ... def value_to_string(self, obj): value = self._get_val_from_obj(obj) return self.get_db_prep_value(value) Some general advice -------------------- Writing a custom field can be a tricky process, particularly if you're doing complex conversions between your Python types and your database and serialization formats. Here are a couple of tips to make things go more smoothly: 1. Look at the existing Django fields (in :file:`django/db/models/fields/__init__.py`) for inspiration. Try to find a field that's similar to what you want and extend it a little bit, instead of creating an entirely new field from scratch. 2. Put a :meth:`__str__` or :meth:`__unicode__` method on the class you're wrapping up as a field. There are a lot of places where the default behavior of the field code is to call :func:`~django.utils.encoding.force_unicode` on the value. (In our examples in this document, ``value`` would be a ``Hand`` instance, not a ``HandField``). So if your :meth:`__unicode__` method automatically converts to the string form of your Python object, you can save yourself a lot of work. Writing a ``FileField`` subclass ================================= In addition to the above methods, fields that deal with files have a few other special requirements which must be taken into account. The majority of the mechanics provided by ``FileField``, such as controlling database storage and retrieval, can remain unchanged, leaving subclasses to deal with the challenge of supporting a particular type of file. Django provides a ``File`` class, which is used as a proxy to the file's contents and operations. This can be subclassed to customize how the file is accessed, and what methods are available. It lives at ``django.db.models.fields.files``, and its default behavior is explained in the :doc:`file documentation `. Once a subclass of ``File`` is created, the new ``FileField`` subclass must be told to use it. To do so, simply assign the new ``File`` subclass to the special ``attr_class`` attribute of the ``FileField`` subclass. A few suggestions ------------------ In addition to the above details, there are a few guidelines which can greatly improve the efficiency and readability of the field's code. 1. The source for Django's own ``ImageField`` (in ``django/db/models/fields/files.py``) is a great example of how to subclass ``FileField`` to support a particular type of file, as it incorporates all of the techniques described above. 2. Cache file attributes wherever possible. Since files may be stored in remote storage systems, retrieving them may cost extra time, or even money, that isn't always necessary. Once a file is retrieved to obtain some data about its content, cache as much of that data as possible to reduce the number of times the file must be retrieved on subsequent calls for that information.