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duo-0.3.2
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مشاهده بیشترتوضیحات
A powerful, dynamic, pythonic interface to AWS DynamoDB.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | duo-0.3.2 |
| نام | duo |
| نسخه کتابخانه | 0.3.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | David Eyk |
| ایمیل نویسنده | deyk@crossway.org |
| آدرس صفحه اصلی | http://github.com/eykd/duo |
| آدرس اینترنتی | https://pypi.org/project/duo/ |
| مجوز | BSD |
Duo: A powerful, dynamic, pythonic interface to AWS DynamoDB
============================================================
.. image:: https://travis-ci.org/eykd/duo.svg?branch=master
:target: https://travis-ci.org/eykd/duo#
.. image:: https://coveralls.io/repos/github/eykd/duo/badge.svg?branch=master
:target: https://coveralls.io/github/eykd/duo?branch=master
Duo provides a few straightforward, Pythonic abstractions for working
with Amazon Web Services' DynamoDB. It's a very light wrapper around
`boto.dynamodb.layer2`, so you have full access to that excellent
library when you need it, but you don't have to sweat the details when
you don't.
Stern warning:
--------------
No seriously, it's a very light wrapper around
`boto.dynamodb.layer2`. If you stray much beyond the usage examples
below, you'd do best to be familiar with Boto's DynamoDB API. `The
docs`_ are excellent. Reading `duo's source`_ may also be helpful. It's
kept short for that reason.
.. _The docs: http://boto.readthedocs.org/en/latest/ref/dynamodb.html
.. _duo's source: https://github.com/eykd/duo/blob/master/duo.py
Usage:
------
`duo` is made up of one module::
>>> import duo
The module isn't very big (at the time of this writing, ~700
lines). If you want to know how something works, `you should read it`_.
.. _you should read it: https://github.com/eykd/duo/blob/master/duo.py
Pre-create your tables in the AWS console, then write simple classes
to access them. `duo.Table` Sub-classes are automatically registered
with the db::
>>> class MyHashKeyTable(duo.Table):
... table_name = 'my_hashkey_table'
... hash_key_name = 'slug'
... range_key_name = None # Implicit default
`duo.Item` is a thin wrapper around `boto.dynamodb.items.Item`, with
lots of syntactic sugar. `duo.Item` sub-classs are automatically
registered with the db::
>>> import datetime
>>> class MyHashKeyItem(duo.Item):
... table_name = 'my_hashkey_table'
... hash_key_name = 'slug'
...
... slug = duo.UnicodeField()
... my_field = duo.UnicodeField(default='foo')
... on_this_date = duo.DateField(default=lambda o: datetime.date.today())
Databases and Tables use dict-like access syntax::
>>> db = duo.DynamoDB(key='access_key', secret='secret_key')
>>> # The correct Table sub-class is matched by table name:
>>> table = duo.DynamoDB['my_hashkey_table']
>>> # The correct Item sub-class is matched by table name:
>>> item = table['new-item']
>>> # Items are actually dict subclasses, but that's not where the
>>> # fun is. They can only store unicode strings and integers:
>>> item['slug']
'new-item'
Specify a field on an Item sub-class to get useful data types::
>>> item.is_new
True
>>> # A field doesn't exist initially...
>>> item['my_field']
Traceback (most recent call last):
File "...", line 1, in <module>
item['my_field']
KeyError: 'my_field'
>>> # But we specified a default.
>>> item.my_field
'foo'
>>> # The default, once accessed, gets populated:
>>> item['my_field']
'foo'
>>> # Or we can set our own value...
>>> item.my_field = 'bar'
>>> item['my_field']
'bar'
>>> # Finally, we save it to DynamoDB.
>>> item.put()
>>> item.is_new
False
Caching:
--------
Duo integrates with any cache that implements a `python-memcached`\
-compatible interface, namely, the following::
import pylibmc
cache = pylibmc.Client(['127.0.0.1'])
cache.get(<keyname>)
cache.set(<keyname>, <duration-in-seconds>)
cache.delete(<keyname>)
Integrate caching by passing the cache to the db constructor::
>>> import duo
>>> db = duo.DynamoDB(key='access_key', secret='secret_key', cache=cache)
You can also specify a cache object on a per-table or per-item basis::
>>> class MyHashKeyTable(duo.Table):
... cache = pylibmc.Client(['127.0.0.1'])
...
... table_name = 'my_hashkey_table'
... hash_key_name = 'slug'
... range_key_name = None # Implicit default
Caching is turned off by default, but you can turn it on by specifying
a `cache_duration` as an integer (0 is forever)::
>>> class MyHashKeyItem(duo.Item):
... cache_duration = 30 # 30 seconds
...
... table_name = 'my_hashkey_table'
... hash_key_name = 'slug'
...
... slug = duo.UnicodeField()
... my_field = duo.UnicodeField(default='foo')
... on_this_date = duo.DateField(default=lambda o: datetime.date.today())
Cache keys are determined by hash key, range key, and a cache prefix
(set on the Table). By default, the cache prefix is the table name::
>>> table = duo.DynamoDB['my_hashkey_table']
>>> item = table['new-item']
>>> item.cache_prefix is None
True
>>>item._cache_key
'my_hashkey_table_new-item'
>>> MyHashKeyTable.cache_prefix = 'hello_world'
>>> item._get_cache_key()
'hello_world_new-item'
CHANGELOG
---------
0.3.1
^^^^^
Fixed bug whereby EnumMeta and subclasses were not comparing properly (re: at all) in Python 3.
0.3.0
^^^^^
Add Python 3 compatibility.
0.2.5
^^^^^
get_item() now writes to the cache, even though it doesn't read from the cache.
0.2.4
^^^^^
Added a custom get_item to Table, for specifying consistent reads,
etc. Used by __getitem__, for simpler code!
0.2.3
^^^^^
One more packaging fix, so pip won't explode. Thanks, cbrinker!
0.2.2
^^^^^
Table.scan() and .query() should return extended Items.
0.2.1
^^^^^
Corrections/improvements to setup.py. Packaging is HARD.
0.2
^^^
Initial public release.
نحوه نصب
نصب پکیج whl duo-0.3.2:
pip install duo-0.3.2.whl
نصب پکیج tar.gz duo-0.3.2:
pip install duo-0.3.2.tar.gz