fix(cdash): Rename

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

5 files changed, 820 insertions, 0 deletions

diff --git a/csit.infra.dash/app/cdash/utils/__init__.py b/csit.infra.dash/app/cdash/utils/__init__.py
new file mode 100644
index 0000000000..5692432123
--- /dev/null
+++ b/csit.infra.dash/app/cdash/utils/__init__.py
@@ -0,0 +1,12 @@
+# 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/cdash/utils/constants.py b/csit.infra.dash/app/cdash/utils/constants.py
new file mode 100644
index 0000000000..75cd68a3a5
--- /dev/null
+++ b/csit.infra.dash/app/cdash/utils/constants.py
@@ -0,0 +1,323 @@
+# 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 CDash.
+
+"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 CDash.
+    """
+
+    ############################################################################
+    # 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"'
+
+    # 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"
+
+    # Path and name of the file specifying the HTML layout of the dash
+    # application.
+    HTML_LAYOUT_FILE = "cdash/templates/dash_layout.jinja2"
+
+    # Application root.
+    APPLICATIN_ROOT = "/"
+
+    # Data to be downloaded from the parquets specification file.
+    DATA_SPEC_FILE = "cdash/data/data.yaml"
+
+    # The file with tooltips.
+    TOOLTIP_FILE = "cdash/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/"
+
+    # 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/"
+
+    # Layout of plot.ly graphs.
+    REPORT_GRAPH_LAYOUT_FILE = "cdash/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 = "cdash/templates/stats_layout.jinja2"
+
+    # Layout of plot.ly graphs.
+    STATS_GRAPH_LAYOUT_FILE = "cdash/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 = "cdash/templates/trending_layout.jinja2"
+
+    # Layout of plot.ly graphs.
+    TREND_GRAPH_LAYOUT_FILE = "cdash/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/cdash/utils/tooltips.yaml b/csit.infra.dash/app/cdash/utils/tooltips.yaml
new file mode 100644
index 0000000000..476882076c
--- /dev/null
+++ b/csit.infra.dash/app/cdash/utils/tooltips.yaml
@@ -0,0 +1,42 @@
+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/cdash/utils/url_processing.py b/csit.infra.dash/app/cdash/utils/url_processing.py
new file mode 100644
index 0000000000..9307015d0d
--- /dev/null
+++ b/csit.infra.dash/app/cdash/utils/url_processing.py
@@ -0,0 +1,99 @@
+# 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/cdash/utils/utils.py b/csit.infra.dash/app/cdash/utils/utils.py
new file mode 100644
index 0000000000..9e4eeeb892
--- /dev/null
+++ b/csit.infra.dash/app/cdash/utils/utils.py
@@ -0,0 +1,344 @@
+# 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]))
+    }