micropython/docs/library/btree.rst

:mod:`btree` -- simple BTree database
=====================================

.. module:: btree
   :synopsis: simple BTree database

The ``btree`` module implements a simple key-value database using external
storage (disk files, or in general case, a random-access stream). Keys are
stored sorted in the database, and besides efficient retrieval by a key
value, a database also supports efficient ordered range scans (retrieval
of values with the keys in a given range). On the application interface
side, BTree database work as close a possible to a way standard `dict`
type works, one notable difference is that both keys and values must
be `bytes` objects (so, if you want to store objects of other types, you
need to serialize them to `bytes` first).

The module is based on the well-known BerkelyDB library, version 1.xx.

Example::

    import btree

    # First, we need to open a stream which holds a database
    # This is usually a file, but can be in-memory database
    # using uio.BytesIO, a raw flash section, etc.
    # Oftentimes, you want to create a database file if it doesn't
    # exist and open if it exists. Idiom below takes care of this.
    # DO NOT open database with "a+b" access mode.
    try:
        f = open("mydb", "r+b")
    except OSError:
        f = open("mydb", "w+b")

    # Now open a database itself
    db = btree.open(f)

    # The keys you add will be sorted internally in the database
    db[b"3"] = b"three"
    db[b"1"] = b"one"
    db[b"2"] = b"two"

    # Assume that any changes are cached in memory unless
    # explicitly flushed (or database closed). Flush database
    # at the end of each "transaction".
    db.flush()

    # Prints b'two'
    print(db[b"2"])

    # Iterate over sorted keys in the database, starting from b"2"
    # until the end of the database, returning only values.
    # Mind that arguments passed to values() method are *key* values.
    # Prints:
    #   b'two'
    #   b'three'
    for word in db.values(b"2"):
        print(word)

    del db[b"2"]

    # No longer true, prints False
    print(b"2" in db)

    # Prints:
    #  b"1"
    #  b"3"
    for key in db:
        print(key)

    db.close()

    # Don't forget to close the underlying stream!
    f.close()


Functions
---------

.. function:: open(stream, \*, flags=0, cachesize=0, pagesize=0, minkeypage=0)

   Open a database from a random-access `stream` (like an open file). All
   other parameters are optional and keyword-only, and allow to tweak advanced
   parameters of the database operation (most users will not need them):

   * `flags` - Currently unused.
   * `cachesize` - Suggested maximum memory cache size in bytes. For a
     board with enough memory using larger values may improve performance.
     The value is only a recommendation, the module may use more memory if
     values set too low.
   * `pagesize` - Page size used for the nodes in BTree. Acceptable range
     is 512-65536. If 0, underlying I/O block size will be used (the best
     compromise between memory usage and performance).
   * `minkeypage` - Minimum number of keys to store per page. Default value
     of 0 equivalent to 2.

   Returns a `BTree` object, which implements a dictionary protocol (set
   of methods), and some additional methods described below.

Methods
-------

.. method:: btree.close()

   Close the database. It's mandatory to close the database at the end of
   processing, as some unwritten data may be still in the cache. Note that
   this does not close underlying streamw with which the database was opened,
   it should be closed separately (which is also mandatory to make sure that
   data flushed from buffer to the underlying storage).

.. method:: btree.flush()

   Flush any data in cache to the underlying stream.

.. method:: btree.__getitem__(key)
.. method:: btree.get(key, default=None)
.. method:: btree.__setitem__(key, val)
.. method:: btree.__detitem__(key)
.. method:: btree.__contains__(key)

   Standard dictionary methods.

.. method:: btree.__iter__()

   A BTree object can be iterated over directly (similar to a dictionary)
   to get access to all keys in order.

.. method:: btree.keys([start_key, [end_key, [flags]]])
.. method:: btree.values([start_key, [end_key, [flags]]])
.. method:: btree.items([start_key, [end_key, [flags]]])

   These methods are similar to standard dictionary methods, but also can
   take optional parameters to iterate over a key sub-range, instead of
   the entire database. Note that for all 3 methods, `start_key` and
   `end_key` arguments represent key values. For example, ``values()``
   method will iterate over values corresponding to they key range
   given. None values for `start_key` means "from the first key", no
   `end_key` or its value of None means "until the end of database".
   By default, range is inclusive of `start_key` and exclusive of
   `end_key`, you can include `end_key` in iteration by passing `flags`
   of `btree.INCL`. You can iterate in descending key direction
   by passing `flags` of `btree.DESC`. The flags values can be ORed
   together.

Constants
---------

.. data:: INCL

   A flag for `keys()`, `values()`, `items()` methods to specify that
   scanning should be inclusive of the end key.

.. data:: DESC

   A flag for `keys()`, `values()`, `items()` methods to specify that
   scanning should be in descending direction of keys.