Merge branch 'dev-tests' into dev-tests-plat-143-modernpy

LNX-docker-compose.yml

@@ -45,7 +45,7 @@ services:
       interval: 15s
   fakeservices.datajoint.io:
     <<: *net
-    image: datajoint/nginx:v0.2.7
+    image: datajoint/nginx:v0.2.8
     environment:
       - ADD_db_TYPE=DATABASE
       - ADD_db_ENDPOINT=db:3306

docs/src/develop.md

@@ -39,24 +39,16 @@ The following will verify there are no regression errors by running our test sui
 
 - Entire test suite:
   ```
-  nosetests -vw tests_old
+  pytest -sv --cov-report term-missing --cov=datajoint tests
   ```
-  > Note: We are in the process of upgrading to `pytest` tests. To run those, use:
-  > ```
-  > pytest -sv --cov-report term-missing --cov=datajoint tests
-  > ```
 
 - A single functional test:
   ```
-  nosetests -vs --tests=tests_old.test_external_class:test_insert_and_fetch
+  pytest -sv tests/test_connection.py::test_dj_conn
   ```
-  > Note: We are in the process of upgrading to `pytest` tests. To run those, use:
-  > ```
-  > pytest -sv tests/test_connection.py::test_dj_conn
-  > ```
 - A single class test:
   ```
-  nosetests -vs --tests=tests_old.test_fetch:TestFetch.test_getattribute_for_fetch1
+  pytest -sv tests/test_aggr_regressions.py::TestIssue558
   ```
 
 ### Style Tests

tests/test_blob.py

@@ -1,3 +1,4 @@
+import pytest
 import datajoint as dj
 import timeit
 import numpy as np
@@ -10,6 +11,13 @@
 from .schema import Longblob
 
 
+@pytest.fixture
+def enable_feature_32bit_dims():
+    dj.blob.use_32bit_dims = True
+    yield
+    dj.blob.use_32bit_dims = False
+
+
 def test_pack():
     for x in (
         32,
@@ -180,6 +188,8 @@ def test_insert_longblob(schema_any):
     assert (Longblob & "id=1").fetch1()["data"].all() == query_mym_blob["data"].all()
     (Longblob & "id=1").delete()
 
+
+def test_insert_longblob_32bit(schema_any, enable_feature_32bit_dims):
     query_32_blob = (
         "INSERT INTO djtest_test1.longblob (id, data) VALUES (1, "
         "X'6D596D00530200000001000000010000000400000068697473007369646573007461736B73007374"
@@ -190,7 +200,6 @@ def test_insert_longblob(schema_any):
         "00000041020000000100000008000000040000000000000053007400610067006500200031003000')"
     )
     dj.conn().query(query_32_blob).fetchall()
-    dj.blob.use_32bit_dims = True
     fetched = (Longblob & "id=1").fetch1()
     expected = {
         "id": 1,
@@ -211,25 +220,31 @@ def test_insert_longblob(schema_any):
     assert fetched["id"] == expected["id"]
     assert np.array_equal(fetched["data"], expected["data"])
     (Longblob & "id=1").delete()
-    dj.blob.use_32bit_dims = False
 
 
 def test_datetime_serialization_speed():
     # If this fails that means for some reason deserializing/serializing
     # np arrays of np.datetime64 types is now slower than regular arrays of datetime
+    assert not dj.blob.use_32bit_dims, "32 bit dims should be off for this test"
+    context = dict(
+        np=np,
+        datetime=datetime,
+        pack=pack,
+        unpack=unpack,
+    )
 
     optimized_exe_time = timeit.timeit(
         setup="myarr=pack(np.array([np.datetime64('2022-10-13 03:03:13') for _ in range(0, 10000)]))",
         stmt="unpack(myarr)",
         number=10,
-        globals=globals(),
+        globals=context,
     )
     print(f"np time {optimized_exe_time}")
     baseline_exe_time = timeit.timeit(
         setup="myarr2=pack(np.array([datetime(2022,10,13,3,3,13) for _ in range (0, 10000)]))",
         stmt="unpack(myarr2)",
         number=10,
-        globals=globals(),
+        globals=context,
     )
     print(f"python time {baseline_exe_time}")