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    "info": {
        "author": "Alberto Planas",
        "author_email": "aplanas@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Other Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Topic :: Database",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "Tokyo Cabinet (http://1978th.net/tokyocabinet/) is a modern\nimplementation of DBM database. Mikio Hirabayashi (the author of Tokyo\nCabinet) describe the project as::\n\n  Tokyo Cabinet is a library of routines for managing a database. The\n  database is a simple data file containing records, each is a pair of\n  a key and a value. Every key and value is serial bytes with variable\n  length. Both binary data and character string can be used as a key\n  and a value. There is neither concept of data tables nor data\n  types. Records are organized in hash table, B+ tree, or fixed-length\n  array.\n\nThe py-tcdb project is an interface to the library using the ctypes\nPython module and provides a two-level access to TC functions: a low\nlevel and a high level.\n\nLow Level API\n-------------\n\nWe can interface with TC library using directly the tc module. This\nmodule declare all functions and data types. For example, if we want\nto create a HDB (hash database object) we can write::\n\n  from tcdb import tc\n  from tcdb import hdb\n\n  db = tc.hdb_new()\n\n  if not tc.hdb_open(db, 'example.tch', hdb.OWRITER|hdb.OCREAT):\n      print tc.hdb_errmsg(tc.hdb_ecode(db))\n\n  if not tc.hdb_put2(db, 'key', 'value'):\n      print tc.hdb_errmsg(tc.hdb_ecode(db))\n\n  v = tc.hdb_get2(db, 'key')\n\n  print 'VALUE:', v.value\n\n  tc.hdb_close(db)\n  tc.hdb_del(db)\n\nThe low level API works with ctypes types (like c_char_p or c_int).\n\nHigh Level API\n--------------\n\nFor each kind of database type allowed in TC, we have a Python class\nthat encapsulate all the functionality. For every class we try to\nemulate the bsddb Python module interface. This interface is quite\nsimilar to a dict data type with persistence.\n\nAlso, for HDB, DBD and FDB databases we have a simple version,\ndesigned to work only with strings. This version is faster than\nno-simple ones: it avoids serialization, data conversions (in Python\narena) and use a different way for call C functions. Use the 'simple'\nclass if you want speed and only need string management.\n\nWe also try to improve this API. For example, we can work with\ntransactions using the with Python keyword.\n\nHash Database\n~~~~~~~~~~~~~\n\nWe can use the HDB class to create and manage TC hash databases. This\nclass behaves like a dictionary object, but we can use put and get\nmethods in order to have more control over the stored data. In a hash\ndatabase we can store serialized Python objects as a key or as a\nvalue, or raw data (that can be retrieved from the database using C,\nLua, Perl or Java).\n\n::\n\n  from tcdb import hdb\n\n  # The open method can change other params like cache or\n  # auto defragmentation steep.\n  db = hdb.HDB()\n  db.open('example.tch')\n\n  # Store pickled object in the database\n  db['key'] = 10\n  assert type(db['key']) == int\n\n  db['key'] = 1+1j\n  assert type(db['key']) == complex\n\n  db[1+1j] = 'text'\n  assert type(db[1+1j]) == str\n\n  # If we use put/get, we can store raw data\n  # Equiv. to use db.put_int('key', 10, as_raw=True)\n  db.put('key', 10, raw_key=True, raw_value=True)\n  # Equiv. to use db.get_int('key', as_raw=True)\n  assert db.get('key', raw_key=True, value_type=int) == 10\n\n  # We can remove records using 'del' keyword\n  # or out methods\n  db.out('key', as_raw=True)\n\n  # We can iterate over the records.\n  for key, value in db.iteritems():\n      print key, ':', value\n\n  # The 'with' keywork works as expected\n  with db:\n      db[10] = 'ten'\n      assert db[10] == 'ten'\n      raise Exception\n\n  # Because we abort the transaction, we don't\n  # have the new record\n  try:\n      db[10]\n  except KeyError:\n      pass\n\n\nB+ Tree Database\n~~~~~~~~~~~~~~~~\n\nWe can use the class BDB to create and manage B+ tree TC\ndatabases. The API is quite similar to the HDB one. One thing that we\ncan do with BDB class is that we can access using a Cursor. With range\nwe can access to a set of ordered keys in a efficient way, and with\nCursor object we can navigate over the database.\n\nFixed-length Database\n~~~~~~~~~~~~~~~~~~~~~\n\nFDB class can create and manage a fixed-length array database. In this\nkind of database we can only use int keys, like in a dynamic array.\n\nTable Database\n~~~~~~~~~~~~~~\n\nTokyo Cabinet can use a variation of a hash database to store\ntable-like object. In Python we can use a dict object to represent a\nsingle table. With THD we can store these tables and make queries\nusing Query object.\n\n::\n\n  from tcdb import tdb\n\n  # The open method can change other params like cache or\n  # auto defragmentation steep.\n  db = tdb.TDB()\n  db.open('example.tct')\n\n  # Store directly a new table\n  alice = {'user': 'alice', 'name': 'Alice', 'age': 23}\n  db['pk'] = alice\n  assert db['pk'] == alice\n  assert type(db['pk']['age']) == int\n\n  # If we use put/get, we can store raw data\n  db.put('pk', alice, raw_key=True, raw_cols=True)\n  # Equiv. to use db.get_col_int('pk', 'age', raw_key=True)\n  schema = {'user': str, 'name': str, 'age': int}\n  assert db.get('pk', raw_key=True, schema=schema)['age'] == 23\n\n  # We can remove records using 'del' keyword\n  # or out methods\n  del db['pk']\n\nAbstract Database\n~~~~~~~~~~~~~~~~~\n\nFor completeness, we include the ADB abstract interface for accessing\nhash, B+ tree, fixed-length and table database objects.",
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        "keywords": "tokyo cabinet,ctypes,database",
        "license": "LGPL",
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        "summary": "A Python wrapper for Tokyo Cabinet database using ctypes.",
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