fix(cdash): Rename

Signed-off-by: pmikus <peter.mikus@protonmail.ch>
Change-Id: Ia6dff2674a28b42ebfbe91230587f1e175ae1137

1 files changed, 0 insertions, 344 deletions

diff --git a/csit.infra.dash/app/pal/utils/utils.py b/csit.infra.dash/app/pal/utils/utils.py
deleted file mode 100644
index 9e4eeeb892..0000000000
--- a/csit.infra.dash/app/pal/utils/utils.py
+++ /dev/null
@@ -1,344 +0,0 @@
-# Copyright (c) 2022 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.
-
-"""Function used by Dash applications.
-"""
-
-import pandas as pd
-import dash_bootstrap_components as dbc
-
-from numpy import isnan
-from dash import dcc
-from datetime import datetime
-
-from ..jumpavg import classify
-from ..utils.constants import Constants as C
-from ..utils.url_processing import url_encode
-
-
-def classify_anomalies(data):
-    """Process the data and return anomalies and trending values.
-
-    Gather data into groups with average as trend value.
-    Decorate values within groups to be normal,
-    the first value of changed average as a regression, or a progression.
-
-    :param data: Full data set with unavailable samples replaced by nan.
-    :type data: OrderedDict
-    :returns: Classification and trend values
-    :rtype: 3-tuple, list of strings, list of floats and list of floats
-    """
-    # NaN means something went wrong.
-    # Use 0.0 to cause that being reported as a severe regression.
-    bare_data = [0.0 if isnan(sample) else sample for sample in data.values()]
-    # TODO: Make BitCountingGroupList a subclass of list again?
-    group_list = classify(bare_data).group_list
-    group_list.reverse()  # Just to use .pop() for FIFO.
-    classification = list()
-    avgs = list()
-    stdevs = list()
-    active_group = None
-    values_left = 0
-    avg = 0.0
-    stdv = 0.0
-    for sample in data.values():
-        if isnan(sample):
-            classification.append("outlier")
-            avgs.append(sample)
-            stdevs.append(sample)
-            continue
-        if values_left < 1 or active_group is None:
-            values_left = 0
-            while values_left < 1:  # Ignore empty groups (should not happen).
-                active_group = group_list.pop()
-                values_left = len(active_group.run_list)
-            avg = active_group.stats.avg
-            stdv = active_group.stats.stdev
-            classification.append(active_group.comment)
-            avgs.append(avg)
-            stdevs.append(stdv)
-            values_left -= 1
-            continue
-        classification.append("normal")
-        avgs.append(avg)
-        stdevs.append(stdv)
-        values_left -= 1
-    return classification, avgs, stdevs
-
-
-def get_color(idx: int) -> str:
-    """Returns a color from the list defined in Constants.PLOT_COLORS defined by
-    its index.
-
-    :param idx: Index of the color.
-    :type idx: int
-    :returns: Color defined by hex code.
-    :trype: str
-    """
-    return C.PLOT_COLORS[idx % len(C.PLOT_COLORS)]
-
-
-def show_tooltip(tooltips:dict, id: str, title: str,
-        clipboard_id: str=None) -> list:
-    """Generate list of elements to display a text (e.g. a title) with a
-    tooltip and optionaly with Copy&Paste icon and the clipboard
-    functionality enabled.
-
-    :param tooltips: Dictionary with tooltips.
-    :param id: Tooltip ID.
-    :param title: A text for which the tooltip will be displayed.
-    :param clipboard_id: If defined, a Copy&Paste icon is displayed and the
-        clipboard functionality is enabled.
-    :type tooltips: dict
-    :type id: str
-    :type title: str
-    :type clipboard_id: str
-    :returns: List of elements to display a text with a tooltip and
-        optionaly with Copy&Paste icon.
-    :rtype: list
-    """
-
-    return [
-        dcc.Clipboard(target_id=clipboard_id, title="Copy URL") \
-            if clipboard_id else str(),
-        f"{title} ",
-        dbc.Badge(
-            id=id,
-            children="?",
-            pill=True,
-            color="white",
-            text_color="info",
-            class_name="border ms-1",
-        ),
-        dbc.Tooltip(
-            children=tooltips.get(id, str()),
-            target=id,
-            placement="auto"
-        )
-    ]
-
-
-def label(key: str) -> str:
-    """Returns a label for input elements (dropdowns, ...).
-
-    If the label is not defined, the function returns the provided key.
-
-    :param key: The key to the label defined in Constants.LABELS.
-    :type key: str
-    :returns: Label.
-    :rtype: str
-    """
-    return C.LABELS.get(key, key)
-
-
-def sync_checklists(options: list, sel: list, all: list, id: str) -> tuple:
-    """Synchronize a checklist with defined "options" with its "All" checklist.
-
-    :param options: List of options for the cheklist.
-    :param sel: List of selected options.
-    :param all: List of selected option from "All" checklist.
-    :param id: ID of a checklist to be used for synchronization.
-    :returns: Tuple of lists with otions for both checklists.
-    :rtype: tuple of lists
-    """
-    opts = {v["value"] for v in options}
-    if id =="all":
-        sel = list(opts) if all else list()
-    else:
-        all = ["all", ] if set(sel) == opts else list()
-    return sel, all
-
-
-def list_tests(selection: dict) -> list:
-    """Transform list of tests to a list of dictionaries usable by checkboxes.
-
-    :param selection: List of tests to be displayed in "Selected tests" window.
-    :type selection: list
-    :returns: List of dictionaries with "label", "value" pairs for a checkbox.
-    :rtype: list
-    """
-    if selection:
-        return [{"label": v["id"], "value": v["id"]} for v in selection]
-    else:
-        return list()
-
-
-def get_date(s_date: str) -> datetime:
-    """Transform string reprezentation of date to datetime.datetime data type.
-
-    :param s_date: String reprezentation of date.
-    :type s_date: str
-    :returns: Date as datetime.datetime.
-    :rtype: datetime.datetime
-    """
-    return datetime(int(s_date[0:4]), int(s_date[5:7]), int(s_date[8:10]))
-
-
-def gen_new_url(url_components: dict, params: dict) -> str:
-    """Generate a new URL with encoded parameters.
-
-    :param url_components: Dictionary with URL elements. It should contain
-        "scheme", "netloc" and "path".
-    :param url_components: URL parameters to be encoded to the URL.
-    :type parsed_url: dict
-    :type params: dict
-    :returns Encoded URL with parameters.
-    :rtype: str
-    """
-
-    if url_components:
-        return url_encode(
-            {
-                "scheme": url_components.get("scheme", ""),
-                "netloc": url_components.get("netloc", ""),
-                "path": url_components.get("path", ""),
-                "params": params
-            }
-        )
-    else:
-        return str()
-
-
-def get_duts(df: pd.DataFrame) -> list:
-    """Get the list of DUTs from the pre-processed information about jobs.
-
-    :param df: DataFrame with information about jobs.
-    :type df: pandas.DataFrame
-    :returns: Alphabeticaly sorted list of DUTs.
-    :rtype: list
-    """
-    return sorted(list(df["dut"].unique()))
-
-
-def get_ttypes(df: pd.DataFrame, dut: str) -> list:
-    """Get the list of test types from the pre-processed information about
-    jobs.
-
-    :param df: DataFrame with information about jobs.
-    :param dut: The DUT for which the list of test types will be populated.
-    :type df: pandas.DataFrame
-    :type dut: str
-    :returns: Alphabeticaly sorted list of test types.
-    :rtype: list
-    """
-    return sorted(list(df.loc[(df["dut"] == dut)]["ttype"].unique()))
-
-
-def get_cadences(df: pd.DataFrame, dut: str, ttype: str) -> list:
-    """Get the list of cadences from the pre-processed information about
-    jobs.
-
-    :param df: DataFrame with information about jobs.
-    :param dut: The DUT for which the list of cadences will be populated.
-    :param ttype: The test type for which the list of cadences will be
-        populated.
-    :type df: pandas.DataFrame
-    :type dut: str
-    :type ttype: str
-    :returns: Alphabeticaly sorted list of cadences.
-    :rtype: list
-    """
-    return sorted(list(df.loc[(
-        (df["dut"] == dut) &
-        (df["ttype"] == ttype)
-    )]["cadence"].unique()))
-
-
-def get_test_beds(df: pd.DataFrame, dut: str, ttype: str, cadence: str) -> list:
-    """Get the list of test beds from the pre-processed information about
-    jobs.
-
-    :param df: DataFrame with information about jobs.
-    :param dut: The DUT for which the list of test beds will be populated.
-    :param ttype: The test type for which the list of test beds will be
-        populated.
-    :param cadence: The cadence for which the list of test beds will be
-        populated.
-    :type df: pandas.DataFrame
-    :type dut: str
-    :type ttype: str
-    :type cadence: str
-    :returns: Alphabeticaly sorted list of test beds.
-    :rtype: list
-    """
-    return sorted(list(df.loc[(
-        (df["dut"] == dut) &
-        (df["ttype"] == ttype) &
-        (df["cadence"] == cadence)
-    )]["tbed"].unique()))
-
-
-def get_job(df: pd.DataFrame, dut, ttype, cadence, testbed):
-    """Get the name of a job defined by dut, ttype, cadence, test bed.
-    Input information comes from the control panel.
-
-    :param df: DataFrame with information about jobs.
-    :param dut: The DUT for which the job name will be created.
-    :param ttype: The test type for which the job name will be created.
-    :param cadence: The cadence for which the job name will be created.
-    :param testbed: The test bed for which the job name will be created.
-    :type df: pandas.DataFrame
-    :type dut: str
-    :type ttype: str
-    :type cadence: str
-    :type testbed: str
-    :returns: Job name.
-    :rtype: str
-    """
-    return df.loc[(
-        (df["dut"] == dut) &
-        (df["ttype"] == ttype) &
-        (df["cadence"] == cadence) &
-        (df["tbed"] == testbed)
-    )]["job"].item()
-
-
-def generate_options(opts: list) -> list:
-    """Return list of options for radio items in control panel. The items in
-    the list are dictionaries with keys "label" and "value".
-
-    :params opts: List of options (str) to be used for the generated list.
-    :type opts: list
-    :returns: List of options (dict).
-    :rtype: list
-    """
-    return [{"label": i, "value": i} for i in opts]
-
-
-def set_job_params(df: pd.DataFrame, job: str) -> dict:
-    """Create a dictionary with all options and values for (and from) the
-    given job.
-
-    :param df: DataFrame with information about jobs.
-    :params job: The name of job for and from which the dictionary will be
-        created.
-    :type df: pandas.DataFrame
-    :type job: str
-    :returns: Dictionary with all options and values for (and from) the
-        given job.
-    :rtype: dict
-    """
-
-    l_job = job.split("-")
-    return {
-        "job": job,
-        "dut": l_job[1],
-        "ttype": l_job[3],
-        "cadence": l_job[4],
-        "tbed": "-".join(l_job[-2:]),
-        "duts": generate_options(get_duts(df)),
-        "ttypes": generate_options(get_ttypes(df, l_job[1])),
-        "cadences": generate_options(get_cadences(df, l_job[1], l_job[3])),
-        "tbeds": generate_options(
-            get_test_beds(df, l_job[1], l_job[3], l_job[4]))
-    }