Integrate correlation API

- add new api for gn2-gn3 sample r integration
- delete map for sample list to values
- add db util file
- add python msql-client dependency
- add db for fetching lit correlation results
- add unittests for db utils
- add tests for db_utils
- modify api for fetching lit correlation results
- refactor Mock Database Connector and unittests
- add sql url parser
- add SQL URI env variable
- refactor code for db utils
- modify return data for lit correlation
- refactor tissue correlation endpoint
- replace db_instance with conn

1 files changed, 97 insertions, 34 deletions

diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py
index 84b9330..52d1f60 100644
--- a/tests/unit/computations/test_correlation.py
+++ b/tests/unit/computations/test_correlation.py
@@ -18,6 +18,8 @@ from gn3.computations.correlations import query_formatter
 from gn3.computations.correlations import map_to_mouse_gene_id
 from gn3.computations.correlations import compute_all_lit_correlation
 from gn3.computations.correlations import compute_all_tissue_correlation
+from gn3.computations.correlations import map_shared_keys_to_values
+from gn3.computations.correlations import process_trait_symbol_dict
 
 
 class QueryableMixin:
@@ -27,6 +29,10 @@ class QueryableMixin:
         """base method for execute"""
         raise NotImplementedError()
 
+    def cursor(self):
+        """method for creating db cursor"""
+        raise NotImplementedError()
+
     def fetchone(self):
         """base method for fetching one iten"""
         raise NotImplementedError()
@@ -46,37 +52,39 @@ class IllegalOperationError(Exception):
 class DataBase(QueryableMixin):
     """Class for creating db object"""
 
-    def __init__(self):
+    def __init__(self, expected_results=None, password="1234", db_name=None):
+        """expects the expectede results value to be an array"""
+        self.password = password
+        self.db_name = db_name
         self.__query_options = None
-        self.__results = None
+        self.results_generator(expected_results)
 
     def execute(self, query_options):
         """method to execute an sql query"""
         self.__query_options = query_options
-        self.results_generator()
+        return 1
+
+    def cursor(self):
+        """method for creating db cursor"""
         return self
 
     def fetchone(self):
         """method to fetch single item from the db query"""
         if self.__results is None:
-            raise IllegalOperationError()
+            return None
 
         return self.__results[0]
 
     def fetchall(self):
         """method for fetching all items from db query"""
         if self.__results is None:
-            raise IllegalOperationError()
+            return None
         return self.__results
 
-    def results_generator(self, expected_results=None):
+    def results_generator(self, expected_results):
         """private method  for generating mock results"""
 
-        if expected_results is None:
-            self.__results = [namedtuple("lit_coeff", "val")(x*0.1)
-                              for x in range(1, 4)]
-        else:
-            self.__results = expected_results
+        self.__results = expected_results
 
 
 class TestCorrelation(TestCase):
@@ -236,21 +244,23 @@ class TestCorrelation(TestCase):
         """fetch results from  db call for lit correlation given a trait list\
         after doing correlation"""
 
-        target_trait_lists = [{"gene_id": 15},
-                              {"gene_id": 17},
-                              {"gene_id": 11}]
+        target_trait_lists = [("1426679_at", 15),
+                              ("1426702_at", 17),
+                              ("1426682_at", 11)]
         mock_mouse_gene_id.side_effect = [12, 11, 18, 16, 20]
 
-        database_instance = namedtuple("database", "execute")("fetchone")
+        conn = DataBase()
 
         fetch_lit_data.side_effect = [(15, 9), (17, 8), (11, 12)]
 
         lit_results = lit_correlation_for_trait_list(
-            database=database_instance, target_trait_lists=target_trait_lists,
+            conn=conn, target_trait_lists=target_trait_lists,
             species="rat", trait_gene_id="12")
 
-        expected_results = [{"gene_id": 15, "lit_corr": 9}, {
-            "gene_id": 17, "lit_corr": 8}, {"gene_id": 11, "lit_corr": 12}]
+        expected_results = [{"1426679_at": {"gene_id": 15, "lit_corr": 9}},
+                            {"1426702_at": {
+                                "gene_id": 17, "lit_corr": 8}},
+                            {"1426682_at": {"gene_id": 11, "lit_corr": 12}}]
 
         self.assertEqual(lit_results, expected_results)
 
@@ -258,8 +268,8 @@ class TestCorrelation(TestCase):
         """test for fetching lit correlation data from\
         the database where the input and mouse geneid are none"""
 
-        database_instance = DataBase()
-        results = fetch_lit_correlation_data(database=database_instance,
+        conn = DataBase()
+        results = fetch_lit_correlation_data(conn=conn,
                                              gene_id="1",
                                              input_mouse_gene_id=None,
                                              mouse_gene_id=None)
@@ -270,10 +280,12 @@ class TestCorrelation(TestCase):
         """test for fetching lit corr coefficent givent the input\
          input trait mouse gene id and mouse gene id"""
 
-        database_instance = DataBase()
+        expected_db_results = [namedtuple("lit_coeff", "val")(x*0.1)
+                               for x in range(1, 4)]
+        database_instance = DataBase(expected_results=expected_db_results)
         expected_results = ("1", 0.1)
 
-        lit_results = fetch_lit_correlation_data(database=database_instance,
+        lit_results = fetch_lit_correlation_data(conn=database_instance,
                                                  gene_id="1",
                                                  input_mouse_gene_id="20",
                                                  mouse_gene_id="15")
@@ -283,10 +295,8 @@ class TestCorrelation(TestCase):
     def test_query_lit_correlation_for_db_empty(self):
         """test that corr coeffient returned is 0 given the\
         db value if corr coefficient is empty"""
-        database_instance = mock.Mock()
-        database_instance.execute.return_value.fetchone.return_value = None
-
-        lit_results = fetch_lit_correlation_data(database=database_instance,
+        database_instance = DataBase()
+        lit_results = fetch_lit_correlation_data(conn=database_instance,
                                                  input_mouse_gene_id="12",
                                                  gene_id="16",
                                                  mouse_gene_id="12")
@@ -336,13 +346,15 @@ class TestCorrelation(TestCase):
         database_results = [namedtuple("mouse_id", "mouse")(val)
                             for val in range(12, 20)]
         results = []
-
-        database_instance.execute.return_value.fetchone.side_effect = database_results
+        cursor = mock.Mock()
+        cursor.execute.return_value = 1
+        cursor.fetchone.side_effect = database_results
+        database_instance.cursor.return_value = cursor
         expected_results = [12, None, 13, 14]
         for (species, gene_id) in test_data:
 
             mouse_gene_id_results = map_to_mouse_gene_id(
-                database=database_instance, species=species, gene_id=gene_id)
+                conn=database_instance, species=species, gene_id=gene_id)
             results.append(mouse_gene_id_results)
 
         self.assertEqual(results, expected_results)
@@ -361,7 +373,7 @@ class TestCorrelation(TestCase):
         mock_lit_corr.side_effect = expected_mocked_lit_results
 
         lit_correlation_results = compute_all_lit_correlation(
-            database_instance=database, trait_lists=[{"gene_id": 11}],
+            conn=database, trait_lists=[{"gene_id": 11}],
             species="rat", gene_id=12)
 
         expected_results = {
@@ -371,15 +383,26 @@ class TestCorrelation(TestCase):
         self.assertEqual(lit_correlation_results, expected_results)
 
     @mock.patch("gn3.computations.correlations.tissue_correlation_for_trait_list")
-    def test_compute_all_tissue_correlation(self, mock_tissue_corr):
+    @mock.patch("gn3.computations.correlations.process_trait_symbol_dict")
+    def test_compute_all_tissue_correlation(self, process_trait_symbol, mock_tissue_corr):
         """test for compute all tissue corelation which abstracts
         api calling the tissue_correlation for trait_list"""
 
         primary_tissue_dict = {"trait_id": "1419792_at",
                                "tissue_values": [1, 2, 3, 4, 5]}
 
-        target_tissue_dict = [{"trait_id": "1418702_a_at", "tissue_values": [1, 2, 3]},
-                              {"trait_id": "1412_at", "tissue_values": [1, 2, 3]}]
+        target_tissue_dict = [{"trait_id": "1418702_a_at",
+                               "symbol": "zf", "tissue_values": [1, 2, 3]},
+                              {"trait_id": "1412_at",
+                               "symbol": "prkce", "tissue_values": [1, 2, 3]}]
+
+        process_trait_symbol.return_value = target_tissue_dict
+
+        target_trait_symbol = {"1418702_a_at": "Zf", "1412_at": "Prkce"}
+        target_symbol_tissue_vals = {"zf": [1, 2, 3], "prkce": [1, 2, 3]}
+
+        target_tissue_data = {"trait_symbol_dict": target_trait_symbol,
+                              "symbol_tissue_vals_dict": target_symbol_tissue_vals}
 
         mock_tissue_corr.side_effect = [{"tissue_corr": -0.5, "p_value": 0.9, "tissue_number": 3},
                                         {"tissue_corr": 1.11, "p_value": 0.2, "tissue_number": 3}]
@@ -391,9 +414,49 @@ class TestCorrelation(TestCase):
 
         results = compute_all_tissue_correlation(
             primary_tissue_dict=primary_tissue_dict,
-            target_tissues_dict_list=target_tissue_dict,
+            target_tissues_data=target_tissue_data,
             corr_method="pearson")
+        process_trait_symbol.assert_called_once_with(
+            target_trait_symbol, target_symbol_tissue_vals)
 
         self.assertEqual(mock_tissue_corr.call_count, 2)
 
         self.assertEqual(results, expected_results)
+
+    def test_map_shared_keys_to_values(self):
+        """test helper function needed to integrate with genenenetwork2\
+        given a a samplelist containing dataset sampelist keys\
+        map that to given sample values """
+
+        dataset_sample_keys = ["BXD1", "BXD2", "BXD5"]
+
+        target_dataset_data = {"HCMA:_AT": [4.1, 5.6, 3.2],
+                               "TXD_AT": [6.2, 5.7, 3.6, ]}
+
+        expected_results = [{"trait_id": "HCMA:_AT",
+                             "trait_sample_data": {"BXD1": 4.1, "BXD2": 5.6, "BXD5": 3.2}},
+                            {"trait_id": "TXD_AT",
+                             "trait_sample_data": {"BXD1": 6.2, "BXD2": 5.7, "BXD5": 3.6}}]
+
+        results = map_shared_keys_to_values(
+            dataset_sample_keys, target_dataset_data)
+
+        self.assertEqual(results, expected_results)
+
+    def test_process_trait_symbol_dict(self):
+        """test for processing trait symbol dict\
+        and fetch tissue values from tissue value dict\
+        """
+        trait_symbol_dict = {"1452864_at": "Igsf10"}
+        tissue_values_dict = {"igsf10": [8.9615, 10.6375, 9.2795, 8.6605]}
+
+        expected_results = {
+            "trait_id": "1452864_at",
+            "symbol": "igsf10",
+            "tissue_values": [8.9615, 10.6375, 9.2795, 8.6605]
+        }
+
+        results = process_trait_symbol_dict(
+            trait_symbol_dict, tissue_values_dict)
+
+        self.assertEqual(results, [expected_results])