Merge pull request #661 from dimitri-yatsenko/dev

Fix issue #656 - typo in SQL UNIQUE INDEX declaration caused error

Author: guzman-raphael

CHANGELOG.md

@@ -1,7 +1,7 @@
 ## Release notes
 
-### 0.12.0 -- Aug 23, 2019
-* Support TLS/SSL connections PR620
+### 0.12.0 -- October 1, 2019
+* Support secure connections with TLS (aka SSL) PR #620
 * Convert numpy array from python object to appropriate data type if all elements are of the same type (#587) PR #608
 * Remove expression requirement to have additional attributes (#604) PR #604
 * Support for filepath datatype (#481) PR #603
@@ -19,7 +19,7 @@
 * Support for pandas and order by "KEY" (#459, #537, #538, #541) PR #534
 * Support file attachment datatype and configurable blob storage (#467, #475, #480, #497) PR #532
 * Increase default display rows (#523) PR #526
-* Bugfixes (#521, #205, #279, #477, #570, #581, #597, #596, #618, #633, #643, #644, #647)
+* Bugfixes (#521, #205, #279, #477, #570, #581, #597, #596, #618, #633, #643, #644, #647, #656)
 
 ### 0.11.3 -- Jul 26, 2019
 * Fix incompatibility with pyparsing 2.4.1 (#629) PR #631

README.md

@@ -6,11 +6,12 @@
 [![Join the chat at https://gitter.im/datajoint/datajoint-python](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/datajoint/datajoint-python?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 
 # Welcome to DataJoint for Python!
-DataJoint for Python is a high-level programming interface for relational databases designed to support data processing chains in science labs. DataJoint is built on the foundation of the relational data model and prescribes a consistent method for organizing, populating, and querying data.
+DataJoint for Python is a framework for scientific workflow management based on relational principles. DataJoint is built on the foundation of the relational data model and prescribes a consistent method for organizing, populating, computing, and querying data.
 
 DataJoint was initially developed in 2009 by Dimitri Yatsenko in Andreas Tolias' Lab for the distributed processing and management of large volumes of data streaming from regular experiments. Starting in 2011, DataJoint has been available as an open-source project adopted by other labs and improved through contributions from several developers.
 
 Vathes LLC supports DataJoint for Python as an open-source project and everyone is welcome to contribute.
+Its DataJoint Neuro (https://djneuro.io) business provides support to neuroscience labs for developing and executing custom data pipelines.
 
 ## Installation
 ```

datajoint/declare.py

@@ -220,7 +220,7 @@ def compile_foreign_key(line, context, attributes, primary_key, attr_sql, foreig
 
     # declare unique index
     if is_unique:
-        index_sql.append('UNIQUE INDEX ({attrs})'.format(attrs='`,`'.join(ref.primary_key)))
+        index_sql.append('UNIQUE INDEX ({attrs})'.format(attrs=','.join("`%s`" % attr for attr in ref.primary_key)))
 
 
 def prepare_declare(definition, context):

tests/schema.py

@@ -296,4 +296,29 @@ class IndexRich(dj.Manual):
     index (first_date, value)
     """
 
+#  Schema for issue 656
+@schema
+class ThingA(dj.Manual):
+    definition = """
+    a: int
+    """
+
+
+@schema
+class ThingB(dj.Manual):
+    definition = """
+    b1: int
+    b2: int
+    ---
+    b3: int
+    """
+
+
+@schema
+class ThingC(dj.Manual):
+    definition = """
+    -> ThingA
+    ---
+    -> [unique, nullable] ThingB
+    """
 

tests/test_connection.py

@@ -14,7 +14,7 @@ def test_dj_conn():
     Should be able to establish a connection
     """
     c = dj.conn(**CONN_INFO)
-    assert c.is_connected
+    assert_true(c.is_connected)
 
 
 def test_persistent_dj_conn():
@@ -33,8 +33,6 @@ def test_persistent_dj_conn():
     assert_true(c4 is c5)
 
 
-
-
 def test_repr():
     c1 = dj.conn(**CONN_INFO)
     assert_true('disconnected' not in repr(c1) and 'connected' in repr(c1))

tests/test_declare.py

@@ -40,6 +40,16 @@ def test_describe_indexes():
         s2 = declare(rel.full_table_name, rel.describe(), context)
         assert_equal(s1, s2)
 
+    @staticmethod
+    def test_describe_dependencies():
+        """real_definition should match original definition"""
+        rel = ThingC()
+        context = inspect.currentframe().f_globals
+        s1 = declare(rel.full_table_name, rel.definition, context)
+        s2 = declare(rel.full_table_name, rel.describe(), context)
+        assert_equal(s1, s2)
+
+
     @staticmethod
     def test_part():
         # Lookup and part with the same name.  See issue #365

tests/test_dependencies.py

@@ -0,0 +1,56 @@
+from nose.tools import assert_true, assert_false, assert_equal, assert_list_equal, raises
+from .schema import *
+
+
+def test_nullable_dependency():
+    """test nullable unique foreign key"""
+
+    # Thing C has a nullable dependency on B whose primary key is composite
+    a = ThingA()
+    b = ThingB()
+    c = ThingC()
+
+    # clear previous contents if any.
+    c.delete_quick()
+    b.delete_quick()
+    a.delete_quick()
+
+    a.insert(dict(a=a) for a in range(7))
+
+    b.insert1(dict(b1=1, b2=1, b3=100))
+    b.insert1(dict(b1=1, b2=2, b3=100))
+
+    # missing foreign key attributes = ok
+    c.insert1(dict(a=0))
+    c.insert1(dict(a=1, b1=33))
+    c.insert1(dict(a=2, b2=77))
+
+    # unique foreign key attributes = ok
+    c.insert1(dict(a=3, b1=1, b2=1))
+    c.insert1(dict(a=4, b1=1, b2=2))
+
+    assert_true(len(c) == len(c.fetch()) == 5)
+
+
+@raises(dj.errors.DuplicateError)
+def test_unique_dependency():
+    """test nullable unique foreign key"""
+
+    # Thing C has a nullable dependency on B whose primary key is composite
+    a = ThingA()
+    b = ThingB()
+    c = ThingC()
+
+    # clear previous contents if any.
+    c.delete_quick()
+    b.delete_quick()
+    a.delete_quick()
+
+    a.insert(dict(a=a) for a in range(7))
+
+    b.insert1(dict(b1=1, b2=1, b3=100))
+    b.insert1(dict(b1=1, b2=2, b3=100))
+
+    c.insert1(dict(a=0, b1=1, b2=1))
+    # duplicate foreign key attributes = not ok
+    c.insert1(dict(a=1, b1=1, b2=1))