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体验新版 GitCode,发现更多精彩内容 >>
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d53b232a
编写于
6月 29, 2021
作者:
T
ThreadDao
提交者:
GitHub
6月 29, 2021
浏览文件
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电子邮件补丁
差异文件
update cases (#6179)
Signed-off-by:
N
ThreadDao
<
yufen.zong@zilliz.com
>
上级
3a202cad
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
44 addition
and
38 deletion
+44
-38
tests20/python_client/check/func_check.py
tests20/python_client/check/func_check.py
+1
-1
tests20/python_client/testcases/test_collection.py
tests20/python_client/testcases/test_collection.py
+37
-29
tests20/python_client/testcases/test_insert.py
tests20/python_client/testcases/test_insert.py
+4
-4
tests20/python_client/testcases/test_query.py
tests20/python_client/testcases/test_query.py
+2
-4
未找到文件。
tests20/python_client/check/func_check.py
浏览文件 @
d53b232a
...
...
@@ -61,7 +61,7 @@ class ResponseChecker:
assert
len
(
error_dict
)
>
0
if
isinstance
(
res
,
Error
):
error_code
=
error_dict
[
ct
.
err_code
]
assert
res
.
code
==
error_code
and
error_dict
[
ct
.
err_msg
]
in
res
.
message
assert
res
.
code
==
error_code
or
error_dict
[
ct
.
err_msg
]
in
res
.
message
else
:
log
.
error
(
"[CheckFunc] Response of API is not an error: %s"
%
str
(
res
))
assert
False
...
...
tests20/python_client/testcases/test_collection.py
浏览文件 @
d53b232a
...
...
@@ -42,7 +42,7 @@ class TestCollectionParams(TestcaseBase):
@
pytest
.
fixture
(
scope
=
"function"
,
params
=
ct
.
get_invalid_strs
)
def
get_invalid_dim
(
self
,
request
):
if
request
.
param
==
1
:
pytest
.
skip
(
"
i
is valid dim"
)
pytest
.
skip
(
"
1
is valid dim"
)
yield
request
.
param
@
pytest
.
mark
.
tags
(
CaseLabel
.
L0
)
...
...
@@ -61,6 +61,7 @@ class TestCollectionParams(TestcaseBase):
assert
c_name
,
_
in
self
.
utility_wrap
.
list_collections
()
@
pytest
.
mark
.
tags
(
CaseLabel
.
L0
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_empty_name
(
self
):
"""
target: test collection with empty name
...
...
@@ -69,11 +70,12 @@ class TestCollectionParams(TestcaseBase):
"""
self
.
_connect
()
c_name
=
""
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"value is illegal"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
f
'`collection_name` value is illegal'
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
default_schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
@
pytest
.
mark
.
parametrize
(
"name"
,
[[],
1
,
[
1
,
"2"
,
3
],
(
1
,),
{
1
:
1
},
None
])
def
test_collection_illegal_name
(
self
,
name
):
"""
...
...
@@ -148,8 +150,8 @@ class TestCollectionParams(TestcaseBase):
check_items
=
{
exp_name
:
c_name
,
exp_schema
:
default_schema
})
fields
=
[
cf
.
gen_int64_field
(
is_primary
=
True
)]
schema
=
cf
.
gen_collection_schema
(
fields
=
fields
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema isnot the same as the "
"schema passed in"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema is
not the same as the "
"schema passed in
.
"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -171,8 +173,8 @@ class TestCollectionParams(TestcaseBase):
check_items
=
{
exp_name
:
c_name
,
exp_schema
:
schema
,
exp_primary
:
int_field_one
.
name
})
new_schema
=
cf
.
gen_collection_schema
(
fields
,
primary_field
=
int_field_two
.
name
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema isnot the same as the "
"schema passed in"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema is
not the same as the "
"schema passed in
.
"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
new_schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
assert
collection_w
.
primary_field
.
name
==
int_field_one
.
name
...
...
@@ -192,7 +194,7 @@ class TestCollectionParams(TestcaseBase):
schema
=
cf
.
gen_default_collection_schema
()
new_fields
=
cf
.
gen_float_vec_field
(
dim
=
new_dim
)
schema
.
fields
[
-
1
]
=
new_fields
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema isnot the same as the "
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The collection already exist, but the schema is
not the same as the "
"schema passed in."
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
dim
=
collection_w
.
schema
.
fields
[
-
1
].
params
[
'dim'
]
...
...
@@ -266,7 +268,7 @@ class TestCollectionParams(TestcaseBase):
"""
self
.
_connect
()
fields
=
get_invalid_type_fields
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"The fields of schema must be type list"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"The fields of schema must be type list"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
=
fields
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -278,11 +280,12 @@ class TestCollectionParams(TestcaseBase):
expected: raise exception
"""
self
.
_connect
()
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field
type not support <DataType.UNKNOWN: 999
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field
dtype must be of DataType
"
}
self
.
field_schema_wrap
.
init_field_schema
(
name
=
"unknown"
,
dtype
=
DataType
.
UNKNOWN
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
@
pytest
.
mark
.
parametrize
(
"name"
,
[[],
1
,
(
1
,),
{
1
:
1
},
"12-s"
])
def
test_collection_invalid_type_field
(
self
,
name
):
"""
...
...
@@ -315,6 +318,7 @@ class TestCollectionParams(TestcaseBase):
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_none_field_name
(
self
):
"""
target: test field schema with None name
...
...
@@ -337,11 +341,12 @@ class TestCollectionParams(TestcaseBase):
expected: raise exception
"""
self
.
_connect
()
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field type must be of DataType"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field
d
type must be of DataType"
}
self
.
field_schema_wrap
.
init_field_schema
(
name
=
"test"
,
dtype
=
dtype
,
is_primary
=
True
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L2
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_field_dtype_float_value
(
self
):
"""
target: test collection with float type
...
...
@@ -353,7 +358,7 @@ class TestCollectionParams(TestcaseBase):
field
,
_
=
self
.
field_schema_wrap
.
init_field_schema
(
name
=
ct
.
default_int64_field_name
,
dtype
=
5.0
,
is_primary
=
True
)
schema
=
cf
.
gen_collection_schema
(
fields
=
[
field
,
cf
.
gen_float_vec_field
()])
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field type must be of DataType"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Field type must be of DataType
!
"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L0
)
...
...
@@ -364,7 +369,7 @@ class TestCollectionParams(TestcaseBase):
expected: exception
"""
self
.
_connect
()
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
=
[],
primary_field
=
ct
.
default_int64_field_name
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -434,7 +439,7 @@ class TestCollectionParams(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
schema
=
cf
.
gen_collection_schema
([
cf
.
gen_int64_field
(
is_primary
=
True
)])
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
The schema must have vector column
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
No vector field is found.
"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -448,7 +453,7 @@ class TestCollectionParams(TestcaseBase):
int_fields
,
_
=
self
.
field_schema_wrap
.
init_field_schema
(
name
=
ct
.
default_int64_field_name
,
dtype
=
DataType
.
INT64
)
vec_fields
,
_
=
self
.
field_schema_wrap
.
init_field_schema
(
name
=
ct
.
default_float_vec_field_name
,
dtype
=
DataType
.
FLOAT_VECTOR
,
dim
=
ct
.
default_dim
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
([
int_fields
,
vec_fields
],
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -462,7 +467,7 @@ class TestCollectionParams(TestcaseBase):
self
.
_connect
()
fields
=
[
cf
.
gen_int64_field
(
is_primary
=
False
),
cf
.
gen_float_field
(
is_primary
=
False
),
cf
.
gen_float_vec_field
(
is_primary
=
False
)]
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -489,7 +494,7 @@ class TestCollectionParams(TestcaseBase):
"""
self
.
_connect
()
fields
=
[
cf
.
gen_int64_field
(),
cf
.
gen_float_vec_field
()]
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
=
fields
,
primary_field
=
primary_field
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -503,7 +508,7 @@ class TestCollectionParams(TestcaseBase):
"""
self
.
_connect
()
fields
=
[
cf
.
gen_int64_field
(),
cf
.
gen_float_vec_field
()]
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
,
primary_field
=
primary_field
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -517,7 +522,7 @@ class TestCollectionParams(TestcaseBase):
self
.
_connect
()
fake_field
=
cf
.
gen_unique_str
()
fields
=
[
cf
.
gen_int64_field
(),
cf
.
gen_float_vec_field
()]
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_schema_wrap
.
init_collection_schema
(
fields
,
primary_field
=
fake_field
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -549,6 +554,7 @@ class TestCollectionParams(TestcaseBase):
assert
self
.
collection_wrap
.
primary_field
.
name
==
ct
.
default_int64_field_name
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_unsupported_primary_field
(
self
,
get_unsupported_primary_field
):
"""
target: test collection with unsupported primary field type
...
...
@@ -753,10 +759,11 @@ class TestCollectionParams(TestcaseBase):
c_name
=
cf
.
gen_unique_str
(
prefix
)
float_vec_field
,
_
=
self
.
field_schema_wrap
.
init_field_schema
(
name
=
"vec"
,
dtype
=
dtype
)
schema
=
cf
.
gen_collection_schema
(
fields
=
[
cf
.
gen_int64_field
(
is_primary
=
True
),
float_vec_field
])
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"dimension is not defined in field type params"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"dimension is not defined in field type params"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_vector_invalid_dim
(
self
,
get_invalid_dim
):
"""
target: test collection with invalid dimension
...
...
@@ -767,7 +774,7 @@ class TestCollectionParams(TestcaseBase):
c_name
=
cf
.
gen_unique_str
(
prefix
)
float_vec_field
=
cf
.
gen_float_vec_field
(
dim
=
get_invalid_dim
)
schema
=
cf
.
gen_collection_schema
(
fields
=
[
cf
.
gen_int64_field
(
is_primary
=
True
),
float_vec_field
])
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
f
'invalid dim:
{
get_invalid_dim
}
'
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
f
'invalid dim:
{
get_invalid_dim
}
'
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -782,7 +789,7 @@ class TestCollectionParams(TestcaseBase):
c_name
=
cf
.
gen_unique_str
(
prefix
)
float_vec_field
=
cf
.
gen_float_vec_field
(
dim
=
dim
)
schema
=
cf
.
gen_collection_schema
(
fields
=
[
cf
.
gen_int64_field
(
is_primary
=
True
),
float_vec_field
])
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"invalid dimension: {}. should be in range 1 ~ 32768"
.
format
(
dim
)}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"invalid dimension: {}. should be in range 1 ~ 32768"
.
format
(
dim
)}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -815,6 +822,7 @@ class TestCollectionParams(TestcaseBase):
check_items
=
{
exp_name
:
c_name
,
exp_schema
:
schema
})
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"exception not MilvusException"
)
def
test_collection_none_desc
(
self
):
"""
target: test collection with none description
...
...
@@ -824,7 +832,7 @@ class TestCollectionParams(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
schema
=
cf
.
gen_default_collection_schema
(
description
=
None
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
expected one of: bytes, unicode"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"None has type NoneType, but
expected one of: bytes, unicode"
}
self
.
collection_wrap
.
init_collection
(
c_name
,
schema
=
schema
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -918,7 +926,7 @@ class TestCollectionOperation(TestcaseBase):
check_items
=
{
exp_name
:
c_name
,
exp_schema
:
default_schema
})
self
.
collection_wrap
.
drop
()
assert
not
self
.
utility_wrap
.
has_collection
(
c_name
)[
0
]
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"can't find collection"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
f
'HasPartition failed: can
\'
t find collection:
{
c_name
}
'
}
collection_w
.
has_partition
(
"p"
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -991,7 +999,7 @@ class TestCollectionDataframe(TestcaseBase):
"""
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Dataframe can not be None
!
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Dataframe can not be None
.
"
}
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
None
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -1033,7 +1041,7 @@ class TestCollectionDataframe(TestcaseBase):
"""
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Data type must be pandas.DataFrame
!
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Data type must be pandas.DataFrame
.
"
}
df
=
get_non_df
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
df
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -1047,7 +1055,7 @@ class TestCollectionDataframe(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
df
=
pd
.
DataFrame
({
"date"
:
pd
.
date_range
(
'20210101'
,
periods
=
3
),
ct
.
default_int64_field_name
:
[
1
,
2
,
3
]})
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Cannot infer schema from
dataframe
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Cannot infer schema from
empty dataframe.
"
}
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
df
,
primary_field
=
ct
.
default_int64_field_name
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -1075,7 +1083,7 @@ class TestCollectionDataframe(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
df
=
cf
.
gen_default_dataframe_data
(
ct
.
default_nb
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Schema must have a primary key field
!
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Schema must have a primary key field
.
"
}
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
df
,
primary_field
=
None
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -1089,7 +1097,7 @@ class TestCollectionDataframe(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
df
=
cf
.
gen_default_dataframe_data
(
ct
.
default_nb
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Must be have a primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"
Primary field must in dataframe.
"
}
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
df
,
primary_field
=
c_name
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
@@ -1117,7 +1125,7 @@ class TestCollectionDataframe(TestcaseBase):
self
.
_connect
()
c_name
=
cf
.
gen_unique_str
(
prefix
)
df
=
cf
.
gen_default_dataframe_data
(
nb
=
100
)
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Auto_id is True,
but get the data of primary key field
"
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
"Auto_id is True,
primary field should not have data.
"
}
self
.
collection_wrap
.
construct_from_dataframe
(
c_name
,
df
,
primary_field
=
ct
.
default_int64_field_name
,
auto_id
=
True
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
tests20/python_client/testcases/test_insert.py
浏览文件 @
d53b232a
...
...
@@ -289,7 +289,7 @@ class TestInsertParams(TestcaseBase):
float_values
=
[
np
.
float32
(
i
)
for
i
in
range
(
nb
)]
float_vec_values
=
cf
.
gen_vectors
(
nb
,
ct
.
default_dim
)
data
=
[
int_values
,
float_values
,
float_vec_values
]
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
'arrays must all be same length
'
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
'Arrays must all be same length.
'
}
collection_w
.
insert
(
data
=
data
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -306,7 +306,7 @@ class TestInsertParams(TestcaseBase):
float_values
=
[
np
.
float32
(
i
)
for
i
in
range
(
nb
)]
float_vec_values
=
cf
.
gen_vectors
(
nb
-
1
,
ct
.
default_dim
)
data
=
[
int_values
,
float_values
,
float_vec_values
]
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
'arrays must all be same length
'
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
'Arrays must all be same length.
'
}
collection_w
.
insert
(
data
=
data
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -321,7 +321,7 @@ class TestInsertParams(TestcaseBase):
df
=
cf
.
gen_default_dataframe_data
(
ct
.
default_nb
)
new_values
=
[
i
for
i
in
range
(
ct
.
default_nb
)]
df
.
insert
(
3
,
'new'
,
new_values
)
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
'Column cnt not match with schema
'
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
'The data fields number is not match with schema.
'
}
collection_w
.
insert
(
data
=
df
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -335,7 +335,7 @@ class TestInsertParams(TestcaseBase):
collection_w
=
self
.
init_collection_wrap
(
name
=
c_name
)
df
=
cf
.
gen_default_dataframe_data
(
ct
.
default_nb
)
df
.
drop
(
ct
.
default_float_vec_field_name
,
axis
=
1
,
inplace
=
True
)
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
'Column cnt not match with schema
'
}
error
=
{
ct
.
err_code
:
0
,
ct
.
err_msg
:
'The data fields number is not match with schema.
'
}
collection_w
.
insert
(
data
=
df
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
tests20/python_client/testcases/test_query.py
浏览文件 @
d53b232a
...
...
@@ -109,7 +109,6 @@ class TestQueryBase(TestcaseBase):
collection_w
.
query
(
expr
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"#6046"
)
@
pytest
.
mark
.
parametrize
(
"expr"
,
[
"12-s"
,
"中文"
,
"a"
,
" "
])
def
test_query_expr_invalid_string
(
self
,
expr
):
"""
...
...
@@ -118,7 +117,7 @@ class TestQueryBase(TestcaseBase):
expected: raise exception
"""
collection_w
,
vectors
,
_
,
=
self
.
init_collection_general
(
prefix
,
insert_data
=
True
)
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"
invalid expr
"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"
Invalid expression!
"
}
collection_w
.
query
(
expr
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
...
...
@@ -298,7 +297,6 @@ class TestQueryBase(TestcaseBase):
assert
set
(
res_1
[
0
].
keys
())
==
set
(
fields
)
@
pytest
.
mark
.
tags
(
CaseLabel
.
L1
)
@
pytest
.
mark
.
xfail
(
reason
=
"issue #6143"
)
@
pytest
.
mark
.
parametrize
(
"output_fields"
,
[[
ct
.
default_float_vec_field_name
],
[
ct
.
default_int64_field_name
,
ct
.
default_float_vec_field_name
]])
def
test_query_output_vec_field
(
self
,
output_fields
):
...
...
@@ -308,7 +306,7 @@ class TestQueryBase(TestcaseBase):
expected: raise exception
"""
collection_w
,
vectors
,
_
,
=
self
.
init_collection_general
(
prefix
,
insert_data
=
True
)
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"
unsupported leaf node
"
}
error
=
{
ct
.
err_code
:
1
,
ct
.
err_msg
:
"
Query does not support vector field currently
"
}
collection_w
.
query
(
default_term_expr
,
output_fields
=
output_fields
,
check_task
=
CheckTasks
.
err_res
,
check_items
=
error
)
...
...
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