fix(cdash): Rename

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

5 files changed, 0 insertions, 831 deletions

diff --git a/csit.infra.dash/app/pal/utils/__init__.py b/csit.infra.dash/app/pal/utils/__init__.py
deleted file mode 100644
index 5692432123..0000000000
--- a/csit.infra.dash/app/pal/utils/__init__.py
+++ /dev/null
@@ -1,12 +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.
diff --git a/csit.infra.dash/app/pal/utils/constants.py b/csit.infra.dash/app/pal/utils/constants.py
deleted file mode 100644
index 8807fec6ca..0000000000
--- a/csit.infra.dash/app/pal/utils/constants.py
+++ /dev/null
@@ -1,334 +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.
-
-"""Constants used in Dash PAL.
-
-"Constant" means a value that keeps its value since initialization. The value
-does not need to be hard coded here, but can be read from environment variables.
-"""
-
-import logging
-
-from dash import html
-
-
-class Constants:
-    """Constants used in Dash PAL.
-    """
-
-    ############################################################################
-    # General, application wide constants.
-
-    # Logging settings.
-    LOG_LEVEL = logging.INFO
-    LOG_FORMAT = "%(asctime)s: %(levelname)s: %(message)s"
-    LOG_DATE_FORMAT = "%Y/%m/%d %H:%M:%S"
-
-    # The application title.
-    TITLE = "FD.io CSIT"
-    BRAND = "CSIT-Dash"
-
-    # The application description.
-    DESCRIPTION = 'Performance Dashboard "CSIT-Dash"'
-
-    # Copyright statement.
-    COPYRIGHT = (
-        'Copyright © 2016-2022 '
-        '<a href="https://fd.io" class="text-white">The Fast Data Project</a>, '
-        'a series of LF Projects, LLC.'
-    )
-
-    # External stylesheets.
-    EXTERNAL_STYLESHEETS = ["/static/dist/css/bootstrap.css", ]
-
-    # Top level template for all pages.
-    TEMPLATE = "d-flex h-100 text-center text-white bg-dark"
-
-    # Path and name of the file specifying the HTML layout of the dash
-    # application.
-    MAIN_HTML_LAYOUT_FILE = "index_layout.jinja2"
-
-    # Application root.
-    APPLICATIN_ROOT = "/"
-
-    # Data to be downloaded from the parquets specification file.
-    DATA_SPEC_FILE = "pal/data/data.yaml"
-
-    # The file with tooltips.
-    TOOLTIP_FILE = "pal/utils/tooltips.yaml"
-
-    # Maximal value of TIME_PERIOD for data read from the parquets in days.
-    # Do not change without a good reason.
-    MAX_TIME_PERIOD = 180
-
-    # It defines the time period for data read from the parquets in days from
-    # now back to the past.
-    # TIME_PERIOD = None - means all data (max MAX_TIME_PERIOD days) is read.
-    # TIME_PERIOD = MAX_TIME_PERIOD - is the default value
-    TIME_PERIOD = MAX_TIME_PERIOD  # [days]
-
-    # List of releases used for iterative data processing.
-    # The releases MUST be in the order from the current (newest) to the last
-    # (oldest).
-    RELEASES = ["csit2210", "csit2206", "csit2202", ]
-
-    ############################################################################
-    # General, application wide, layout affecting constants.
-
-    # If True, clear all inputs in control panel when button "ADD SELECTED" is
-    # pressed.
-    CLEAR_ALL_INPUTS = False
-
-    # The element is disabled.
-    STYLE_DISABLED = {"display": "none"}
-
-    # The element is enabled and visible.
-    STYLE_ENABLED = {"display": "inherit"}
-
-    # Checklist "All" is disabled.
-    CL_ALL_DISABLED = [
-        {
-            "label": "All",
-            "value": "all",
-            "disabled": True
-        }
-    ]
-
-    # Checklist "All" is enable, visible and unchecked.
-    CL_ALL_ENABLED = [
-        {
-            "label": "All",
-            "value": "all",
-            "disabled": False
-        }
-    ]
-
-    # Placeholder for any element in the layout.
-    PLACEHOLDER = html.Nobr("")
-
-    # List of drivers used in CSIT.
-    DRIVERS = ("avf", "af-xdp", "rdma", "dpdk")
-
-    # Labels for input elements (dropdowns, ...).
-    LABELS = {
-        "dpdk": "DPDK",
-        "container_memif": "LXC/DRC Container Memif",
-        "crypto": "IPSec IPv4 Routing",
-        "ip4": "IPv4 Routing",
-        "ip6": "IPv6 Routing",
-        "ip4_tunnels": "IPv4 Tunnels",
-        "l2": "L2 Ethernet Switching",
-        "srv6": "SRv6 Routing",
-        "vm_vhost": "VMs vhost-user",
-        "nfv_density-dcr_memif-chain_ipsec": "CNF Service Chains Routing IPSec",
-        "nfv_density-vm_vhost-chain_dot1qip4vxlan":"VNF Service Chains Tunnels",
-        "nfv_density-vm_vhost-chain": "VNF Service Chains Routing",
-        "nfv_density-dcr_memif-pipeline": "CNF Service Pipelines Routing",
-        "nfv_density-dcr_memif-chain": "CNF Service Chains Routing",
-    }
-
-    # URL style.
-    URL_STYLE = {
-        "background-color": "#d2ebf5",
-        "border-color": "#bce1f1",
-        "color": "#135d7c"
-    }
-
-    ############################################################################
-    # General, normalization constants.
-
-    NORM_FREQUENCY = 2.0  # [GHz]
-    FREQUENCY = {  # [GHz]
-        "2n-aws": 1.000,
-        "2n-dnv": 2.000,
-        "2n-clx": 2.300,
-        "2n-icx": 2.600,
-        "2n-skx": 2.500,
-        "2n-tx2": 2.500,
-        "2n-zn2": 2.900,
-        "3n-alt": 3.000,
-        "3n-aws": 1.000,
-        "3n-dnv": 2.000,
-        "3n-icx": 2.600,
-        "3n-skx": 2.500,
-        "3n-tsh": 2.200
-    }
-
-    ############################################################################
-    # General, plots constants.
-
-    PLOT_COLORS = (
-        "#1A1110", "#DA2647", "#214FC6", "#01786F", "#BD8260", "#FFD12A",
-        "#A6E7FF", "#738276", "#C95A49", "#FC5A8D", "#CEC8EF", "#391285",
-        "#6F2DA8", "#FF878D", "#45A27D", "#FFD0B9", "#FD5240", "#DB91EF",
-        "#44D7A8", "#4F86F7", "#84DE02", "#FFCFF1", "#614051"
-    )
-
-    # Trending, anomalies.
-    ANOMALY_COLOR = {
-        "regression": 0.0,
-        "normal": 0.5,
-        "progression": 1.0
-    }
-
-    COLORSCALE_TPUT = [
-        [0.00, "red"],
-        [0.33, "red"],
-        [0.33, "white"],
-        [0.66, "white"],
-        [0.66, "green"],
-        [1.00, "green"]
-    ]
-
-    TICK_TEXT_TPUT = ["Regression", "Normal", "Progression"]
-
-    COLORSCALE_LAT = [
-        [0.00, "green"],
-        [0.33, "green"],
-        [0.33, "white"],
-        [0.66, "white"],
-        [0.66, "red"],
-        [1.00, "red"]
-    ]
-
-    TICK_TEXT_LAT = ["Progression", "Normal", "Regression"]
-
-    # Access to the results.
-    VALUE = {
-        "mrr": "result_receive_rate_rate_avg",
-        "ndr": "result_ndr_lower_rate_value",
-        "pdr": "result_pdr_lower_rate_value",
-        "pdr-lat": "result_latency_forward_pdr_50_avg"
-    }
-
-    VALUE_ITER = {
-        "mrr": "result_receive_rate_rate_values",
-        "ndr": "result_ndr_lower_rate_value",
-        "pdr": "result_pdr_lower_rate_value",
-        "pdr-lat": "result_latency_forward_pdr_50_avg"
-    }
-
-    UNIT = {
-        "mrr": "result_receive_rate_rate_unit",
-        "ndr": "result_ndr_lower_rate_unit",
-        "pdr": "result_pdr_lower_rate_unit",
-        "pdr-lat": "result_latency_forward_pdr_50_unit"
-    }
-
-    # Latencies.
-    LAT_HDRH = (  # Do not change the order
-        "result_latency_forward_pdr_0_hdrh",
-        "result_latency_reverse_pdr_0_hdrh",
-        "result_latency_forward_pdr_10_hdrh",
-        "result_latency_reverse_pdr_10_hdrh",
-        "result_latency_forward_pdr_50_hdrh",
-        "result_latency_reverse_pdr_50_hdrh",
-        "result_latency_forward_pdr_90_hdrh",
-        "result_latency_reverse_pdr_90_hdrh",
-    )
-
-    # This value depends on latency stream rate (9001 pps) and duration (5s).
-    # Keep it slightly higher to ensure rounding errors to not remove tick mark.
-    PERCENTILE_MAX = 99.999501
-
-    GRAPH_LAT_HDRH_DESC = {
-        "result_latency_forward_pdr_0_hdrh": "No-load.",
-        "result_latency_reverse_pdr_0_hdrh": "No-load.",
-        "result_latency_forward_pdr_10_hdrh": "Low-load, 10% PDR.",
-        "result_latency_reverse_pdr_10_hdrh": "Low-load, 10% PDR.",
-        "result_latency_forward_pdr_50_hdrh": "Mid-load, 50% PDR.",
-        "result_latency_reverse_pdr_50_hdrh": "Mid-load, 50% PDR.",
-        "result_latency_forward_pdr_90_hdrh": "High-load, 90% PDR.",
-        "result_latency_reverse_pdr_90_hdrh": "High-load, 90% PDR."
-    }
-
-    ############################################################################
-    # News.
-
-    # The title.
-    NEWS_TITLE = "CI TEST FAILURE AND ANOMALY STATISTICS"
-
-    # The pathname prefix for the application.
-    NEWS_ROUTES_PATHNAME_PREFIX = "/news/"
-
-    # Path and name of the file specifying the HTML layout of the dash
-    # application.
-    NEWS_HTML_LAYOUT_FILE = "pal/templates/news_layout.jinja2"
-
-    # Time period for regressions and progressions.
-    NEWS_TIME_PERIOD = TIME_PERIOD  # [days]
-
-    # Time periods for summary tables.
-    NEWS_LAST = 1  # [days]
-    NEWS_SHORT = 7  # [days]
-    NEWS_LONG = NEWS_TIME_PERIOD  # [days]
-
-    ############################################################################
-    # Report.
-
-    # The title.
-    REPORT_TITLE = "PER RELEASE PERFORMANCE RESULTS"
-
-    # The pathname prefix for the application.
-    REPORT_ROUTES_PATHNAME_PREFIX = "/report/"
-
-    # Path and name of the file specifying the HTML layout of the dash
-    # application.
-    REPORT_HTML_LAYOUT_FILE = "pal/templates/report_layout.jinja2"
-
-    # Layout of plot.ly graphs.
-    REPORT_GRAPH_LAYOUT_FILE = "pal/report/layout.yaml"
-
-    # Default name of downloaded file with selected data.
-    REPORT_DOWNLOAD_FILE_NAME = "iterative_data.csv"
-
-    ############################################################################
-    # Statistics.
-
-    # The title.
-    STATS_TITLE = "CI JOB EXECUTION STATISTICS"
-
-    # The pathname prefix for the application.
-    STATS_ROUTES_PATHNAME_PREFIX = "/stats/"
-
-    # Path and name of the file specifying the HTML layout of the dash
-    # application.
-    STATS_HTML_LAYOUT_FILE = "pal/templates/stats_layout.jinja2"
-
-    # Layout of plot.ly graphs.
-    STATS_GRAPH_LAYOUT_FILE = "pal/stats/layout.yaml"
-
-    # The default job displayed when the page is loaded first time.
-    STATS_DEFAULT_JOB = "csit-vpp-perf-mrr-daily-master-2n-icx"
-
-    # Default name of downloaded file with selected data.
-    STATS_DOWNLOAD_FILE_NAME = "stats.csv"
-
-    ############################################################################
-    # Trending.
-
-    # The title.
-    TREND_TITLE = "PERFORMANCE TRENDING (DAILY, WEEKLY)"
-
-    # The pathname prefix for the application.
-    TREND_ROUTES_PATHNAME_PREFIX = "/trending/"
-
-    # Path and name of the file specifying the HTML layout of the dash
-    # application.
-    TREND_HTML_LAYOUT_FILE = "pal/templates/trending_layout.jinja2"
-
-    # Layout of plot.ly graphs.
-    TREND_GRAPH_LAYOUT_FILE = "pal/trending/layout.yaml"
-
-    # Default name of downloaded file with selected data.
-    TREND_DOWNLOAD_FILE_NAME = "trending_data.csv"
diff --git a/csit.infra.dash/app/pal/utils/tooltips.yaml b/csit.infra.dash/app/pal/utils/tooltips.yaml
deleted file mode 100644
index 476882076c..0000000000
--- a/csit.infra.dash/app/pal/utils/tooltips.yaml
+++ /dev/null
@@ -1,42 +0,0 @@
-help-area:
-  The area defines a VPP packet path and lookup type.
-help-cadence:
-  The cadence of the Jenkins job which runs the tests.
-help-cores:
-  Number of cores the DUT uses during the test.
-help-download:
-  Download the selected data as a csv file.
-help-dut:
-  Device Under Test (DUT) - In software networking, “device” denotes a specific
-  piece of software tasked with packet processing. Such device is surrounded
-  with other software components (such as operating system kernel).
-help-dut-ver:
-  The version of the Device under Test.
-help-framesize:
-  Frame size - size of an Ethernet Layer-2 frame on the wire, including any VLAN
-  tags (dot1q, dot1ad) and Ethernet FCS, but excluding Ethernet preamble and
-  inter-frame gap. Measured in Bytes.
-help-infra:
-  Infrastructure is defined by the toplology (number of nodes), processor
-  architecture, NIC and driver.
-help-normalize:
-  Normalize the results to CPU frequency 2GHz. The results from AWS environment
-  are not normalized as we do not know the exact value of CPU frequency.
-help-release:
-  The CSIT release.
-help-summary-period:
-  Choose the number of runs for summary tables.
-help-tbed:
-  The test bed is defined by toplology (number of nodes) and processor
-  architecture.
-help-test:
-  The test specification consists of packet encapsulation, VPP packet processing
-  (packet forwarding mode and packet processing function(s)) and packet
-  forwarding path.
-help-time-period:
-  Choose a time period for selected tests.
-help-ttype:
-  Main measured variable.
-help-url:
-  URL with current configuration. If there is no "Copy URL" button, use triple
-  click.
diff --git a/csit.infra.dash/app/pal/utils/url_processing.py b/csit.infra.dash/app/pal/utils/url_processing.py
deleted file mode 100644
index 9307015d0d..0000000000
--- a/csit.infra.dash/app/pal/utils/url_processing.py
+++ /dev/null
@@ -1,99 +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.
-
-"""URL decoding and parsing and URL encoding.
-"""
-
-import logging
-
-from base64 import urlsafe_b64encode, urlsafe_b64decode
-from urllib.parse import urlencode, urlunparse, urlparse, parse_qs
-from zlib import compress, decompress
-from zlib import error as ZlibErr
-from binascii import Error as BinasciiErr
-
-
-def url_encode(params: dict) -> str:
-    """Encode the URL parameters and zip them and create the whole URL using
-    given data.
-
-    :param params: All data necessary to create the URL:
-        - scheme,
-        - network location,
-        - path,
-        - query,
-        - parameters.
-    :type params: dict
-    :returns: Encoded URL.
-    :rtype: str
-    """
-
-    url_params = params.get("params", None)
-    if url_params:
-        encoded_params = urlsafe_b64encode(
-            compress(urlencode(url_params).encode("utf-8"), level=9)
-        ).rstrip(b"=").decode("utf-8")
-    else:
-        encoded_params = str()
-
-    return urlunparse((
-        params.get("scheme", "http"),
-        params.get("netloc", str()),
-        params.get("path", str()),
-        str(),  # params
-        params.get("query", str()),
-        encoded_params
-    ))
-
-
-def url_decode(url: str) -> dict:
-    """Parse the given URL and decode the parameters.
-
-    :param url: URL to be parsed and decoded.
-    :type url: str
-    :returns: Paresed URL.
-    :rtype: dict
-    """
-
-    try:
-        parsed_url = urlparse(url)
-    except ValueError as err:
-        logging.warning(f"\nThe url {url} is not valid, ignoring.\n{repr(err)}")
-        return None
-
-    if parsed_url.fragment:
-        try:
-            padding = b"=" * (4 - (len(parsed_url.fragment) % 4))
-            params = parse_qs(decompress(
-                urlsafe_b64decode(
-                    (parsed_url.fragment.encode("utf-8") + padding)
-                )).decode("utf-8")
-            )
-        except (BinasciiErr, UnicodeDecodeError, ZlibErr) as err:
-            logging.warning(
-                f"\nNot possible to decode the parameters from url: {url}"
-                f"\nEncoded parameters: '{parsed_url.fragment}'"
-                f"\n{repr(err)}"
-            )
-            return None
-    else:
-        params = None
-
-    return {
-        "scheme": parsed_url.scheme,
-        "netloc": parsed_url.netloc,
-        "path":  parsed_url.path,
-        "query":  parsed_url.query,
-        "fragment":  parsed_url.fragment,
-        "params": params
-    }
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]))
-    }