Merge remote-tracking branch 'upstream/master'

dataset/__init__.py

@@ -18,12 +18,14 @@ def connect(url=None, schema=None, reflectMetadata=True, engine_kwargs=None):
     If *url* is not defined it will try to use *DATABASE_URL* from environment variable.
     Returns an instance of :py:class:`Database <dataset.Database>`. Set *reflectMetadata* to False if you
     don't want the entire database schema to be pre-loaded. This significantly speeds up
-    connecting to large databases with lots of tables.
+    connecting to large databases with lots of tables. Additionally, *engine_kwargs* will be directly passed to
+    SQLAlchemy, e.g. set *engine_kwargs={'pool_recycle': 3600}* will avoid `DB connection timeout`_.
     ::
 
         db = dataset.connect('sqlite:///factbook.db')
 
     .. _SQLAlchemy Engine URL: http://docs.sqlalchemy.org/en/latest/core/engines.html#sqlalchemy.create_engine
+    .. _DB connection timeout: http://docs.sqlalchemy.org/en/latest/core/pooling.html#setting-pool-recycle
     """
     if url is None:
         url = os.environ.get('DATABASE_URL', url)

dataset/persistence/database.py

@@ -80,7 +80,7 @@ class Database(object):
             self.local.must_release = True
 
     def _release_internal(self):
-        if not hasattr(self.local, 'must_release') and self.local.must_release:
+        if getattr(self.local, 'must_release', None):
             self.lock.release()
             self.local.must_release = False
 
@@ -141,6 +141,9 @@ class Database(object):
             set(self.metadata.tables.keys()) | set(self._tables.keys())
         )
 
+    def __contains__(self, member):
+        return member in self.tables
+
     def create_table(self, table_name, primary_id='id', primary_type='Integer'):
         """
         Creates a new table. The new table will automatically have an `id` column
@@ -253,7 +256,7 @@ class Database(object):
         """
         Run a statement on the database directly, allowing for the
         execution of arbitrary read/write queries. A query can either be
-        a plain text string, or a `SQLAlchemy expression <http://docs.sqlalchemy.org/ru/latest/core/tutorial.html#selecting>`_. The returned
+        a plain text string, or a `SQLAlchemy expression <http://docs.sqlalchemy.org/en/latest/core/tutorial.html#selecting>`_. The returned
         iterator will yield each result sequentially.
 
         Any keyword arguments will be passed into the query to perform

docs/_themes/kr/sidebarlogo.html

@@ -1,4 +1,4 @@
-<a style="border:0" href="index.html"><img src="_static/dataset-logo.png" alt="dataset" /></a>
+<a style="border:0" href="index.html"><img src="{{ pathto('_static/dataset-logo.png', 1) }}" alt="dataset" /></a>
 
 <p style="font-style:italic;font-size:0.9em; text-align:center; margin-bottom:1.5em">Because managing databases in Python should be as simple as reading and writing JSON files.</p>
 

docs/quickstart.rst

@@ -75,7 +75,7 @@ statement::
     with dataset.connect() as tx:
         tx['user'].insert(dict(name='John Doe', age=46, country='China'))
 
-You can get same functionality by invocing the methods :py:meth:`begin() <dataset.Table.begin>`,
+You can get same functionality by invoking the methods :py:meth:`begin() <dataset.Table.begin>`,
 :py:meth:`commit() <dataset.Table.commit>` and :py:meth:`rollback() <dataset.Table.rollback>`
 explicitly::
 
@@ -92,7 +92,7 @@ Nested transactions are supported too::
     db = dataset.connect()
     with db as tx1:
         tx1['user'].insert(dict(name='John Doe', age=46, country='China'))
-        with db sa tx2:
+        with db as tx2:
             tx2['user'].insert(dict(name='Jane Doe', age=37, country='France', gender='female'))
 
 

setup.py

@@ -8,7 +8,7 @@ if sys.version_info[:2] <= (2, 6):
 
 setup(
     name='dataset',
-    version='0.5.4',
+    version='0.5.5',
     description="Toolkit for Python-based data processing.",
     long_description="",
     classifiers=[

test/test_persistence.py

@@ -38,6 +38,9 @@ class DatabaseTestCase(unittest.TestCase):
     def test_tables(self):
         assert self.db.tables == ['weather'], self.db.tables
 
+    def test_contains(self):
+        assert 'weather' in self.db, self.db.tables
+
     def test_create_table(self):
         table = self.db['foo']
         assert table.table.exists()