C-Dash: Add search in testsoper-240304

Change-Id: Ia250c4b4e299d48bc68cf01e65fe37a281047060
Signed-off-by: Tibor Frank <tifrank@cisco.com>

1 files changed, 123 insertions, 0 deletions

diff --git a/csit.infra.dash/app/cdash/search/tables.py b/csit.infra.dash/app/cdash/search/tables.py
new file mode 100644
index 0000000000..a5ffd76d3d
--- /dev/null
+++ b/csit.infra.dash/app/cdash/search/tables.py
@@ -0,0 +1,123 @@
+# Copyright (c) 2024 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""The search data tables.
+"""
+
+
+import pandas as pd
+
+from ..utils.constants import Constants as C
+
+
+def select_search_data(data: pd.DataFrame, selection: list) -> pd.DataFrame:
+    """Return the searched data based on the user's "selection".
+
+    :param data: Input data to be searched through.
+    :param selection: User selection.
+    :type data: pandas.DataFrame
+    :type selection: list[dict]
+    :returns: A dataframe with selected tests.
+    :trype: pandas.DataFrame
+    """
+
+    sel_data = data[selection["datatype"]]
+
+    if selection["datatype"] == "trending":
+        df = pd.DataFrame(sel_data.loc[
+            sel_data["dut_type"] == selection["dut"]
+        ])
+    else:
+        df = pd.DataFrame(sel_data.loc[(
+            (sel_data["dut_type"] == selection["dut"]) &
+            (sel_data["release"] == selection["release"])
+        )])
+    try:
+        df = df[
+            df.full_id.str.contains(
+                selection["regexp"].replace(" ", ".*"),
+                regex=True
+            )
+        ]
+    except Exception:
+        return pd.DataFrame()
+
+    return df
+
+
+def search_table(data: pd.DataFrame, selection: list) -> pd.DataFrame:
+    """Generate a table listing tests based on user's selection.
+
+    :param data: Input data (all tests).
+    :param selection: User selection.
+    :type data: pandas.DataFrame
+    :type selection: list[dict]
+    :returns: A dataframe with selected tests/
+    :rtype: pandas.DataFrame
+    """
+
+    sel = select_search_data(data, selection)
+    if sel.empty:
+        return pd.DataFrame()
+
+    l_tb, l_nic, l_drv, l_test, = list(), list(), list(), list()
+    if selection["datatype"] == "trending":
+        cols = ["job", "test_id"]
+    else:
+        l_dutver = list()
+        cols = ["job", "test_id", "dut_version"]
+    for _, row in sel[cols].drop_duplicates().iterrows():
+        l_id = row["test_id"].split(".")
+        suite = l_id[-2].replace("2n1l-", "").replace("1n1l-", "").\
+            replace("2n-", "")
+        l_tb.append("-".join(row["job"].split("-")[-2:]))
+        l_nic.append(suite.split("-")[0])
+        if selection["datatype"] != "trending":
+            l_dutver.append(row["dut_version"])
+        for driver in C.DRIVERS:
+            if driver in suite:
+                l_drv.append(driver)
+                break
+        else:
+            l_drv.append("dpdk")
+        l_test.append(l_id[-1])
+
+    if selection["datatype"] == "trending":
+        selected = pd.DataFrame.from_dict({
+            "Test Bed": l_tb,
+            "NIC": l_nic,
+            "Driver": l_drv,
+            "Test": l_test
+        })
+
+        selected.sort_values(
+            by=["Test Bed", "NIC", "Driver", "Test"],
+            ascending=True,
+            inplace=True
+        )
+    else:
+        selected = pd.DataFrame.from_dict({
+            "DUT Version": l_dutver,
+            "Test Bed": l_tb,
+            "NIC": l_nic,
+            "Driver": l_drv,
+            "Test": l_test
+        })
+
+        selected.sort_values(
+            by=["DUT Version", "Test Bed", "NIC", "Driver", "Test"],
+            ascending=True,
+            inplace=True
+        )
+
+    return selected