python内存数据库pydblite

create a database instance, passing it a path in the file system : db = Base(‘dummy‘)

for a new database, define the field names : db.create(‘name‘,‘age‘,‘size‘)
You don‘t have to define the field types. PyDbLite will accept any value that can be serialized by the cPickle module : strings, Unicode strings, integers, floats, dates and datetimes (instances of the date and datetime classes in the datetime module), user-defined classes, etc

if the base exists, open it : db.open()

you can pass a parameter "mode" to the create() method, to specify what you want to do if the base already exists in the file system

mode = "open" : db.create(‘name‘,‘age‘,‘size‘,mode="open") opens the database and ignores the field definition
mode = "override" : db.create(‘name‘,‘age‘,‘size‘,mode="override") erases the existing base and creates a new one with the field definition
if mode is not specified and the base already exists, an IOError is raised

insert a new record

by keywords : db.insert(name=‘homer‘,age=23,size=1.84)
If some fields are missing, they are initialized with the value None
by positional arguments : db.insert(‘homer‘,23,1.84)
The arguments must be provided in the same order as in the create() method

save the changes on disk : db.commit()
If you don‘t commit the changes, the insertion, deletion and update operations will not be saved on disk. To return to the previous version, just open() it again (this is equivalent to rollback in transactional databases)

besides the fields passed to the create() method, an internal field called __id__ is added. It is a integer which is guaranteed to be unique and unchanged for each record in the base, so that it can be used as the record identifier

another internal field called __version__ is also managed by the database engine. It is a integer which is set to 0 when the record is created, then incremented by 1 each time the record is updated. This is used to detect concurrency control, for instance in a web application where 2 users select the same record and want to update it at the same time

the selection of records uses Python list comprehension syntax :
recs = [ r for r in db if 30 > r[‘age‘] >= 18 and r[‘size‘] < 2 ]
returns the records in the base where the age is between 18 and 30, and size is below 2 meters. The record is a dictionary, where the key is the field name and value is the field value

Python generator expression syntax can also be used :
for r in (r for r in db if r[‘name‘] in (‘homer‘,‘marge‘) ):
do_something_with(r)
iterates on the records where the name is one of ‘homer‘ or ‘marge‘

to iterate on all the records :
for r in db:
do_something_with(r)

a record can be accessed by its identifier : record = db[rec_id] returns the record such that record[‘__id__‘] == rec_id

finally, a shortcut can be used for simple selections : db(key1=val1,key2=val2) returns the list of records where the keys take the given value. It is equivalent to [ r for r in db if r["key1"]==val1 and r["key2"]==val2], but much more concise

to speed up selections, an index can be created on a field : db.create_index(‘age‘)
When an index is created, the database instance has an attribute (here _age : note the heading underscore, to avoid name conflicts with internal names). This attribute is a dictionary-like object, where keys are the values taken by the field, and values are the records whose field values are egal to the key :
records = db._age[23] returns the list of records with age == 23
If no record has this value, lookup by this value returns an empty list
The index supports iteration on the field values, and the keys() method returns all existing values for the field

number of records in the base : len(db)

to delete a record : db.delete(record) or, if you know the record identifier : del db[rec_id]

to delete a list of records : db.delete(list_of_records)
list_of_records can be any iterable (list, tuple, set, etc) yielding records

to update a record : db.update(record,age=24)

to add a new field to an existing base and specify a default value : db.add_field(‘new_field‘[,default=v]). If no default is provided, the field value is None

to drop an existing field : db.drop_field(‘name‘)

to get the list of fields : db.fields

import pydblite
# 使用内存数据库
pydb = pydblite.Base("address")
# 创建a,b,c三个字段
pydb.create(‘a‘, ‘b‘, ‘c‘)
# 为字段a,b创建索引
pydb.create_index(‘a‘, ‘b‘)
# 插入一条数据

pydb.insert(a=0, b=0, c=1)
pydb.insert(a=1, b=0, c=1)
pydb.insert(a=1, b=0, c=1)
pydb.insert(a=1, b=0, c=1)
pydb.update(records=pydb[1],a=2,c="li")
pydb.delete(pydb[0])
# 查询符合特定要求的数据
results = pydb(a=2)
for i in  results:
    print results[i]

python内存数据库pydblite

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