diff options
Diffstat (limited to 'resources/tools/dash/app/pal/utils')
| -rw-r--r-- | resources/tools/dash/app/pal/utils/__init__.py | 12 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/utils/constants.py | 312 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/utils/tooltips.yaml | 40 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/utils/url_processing.py | 99 | ||||
| -rw-r--r-- | resources/tools/dash/app/pal/utils/utils.py | 344 |
5 files changed, 0 insertions, 807 deletions
diff --git a/resources/tools/dash/app/pal/utils/__init__.py b/resources/tools/dash/app/pal/utils/__init__.py deleted file mode 100644 index 5692432123..0000000000 --- a/resources/tools/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/resources/tools/dash/app/pal/utils/constants.py b/resources/tools/dash/app/pal/utils/constants.py deleted file mode 100644 index cc4a9e0f23..0000000000 --- a/resources/tools/dash/app/pal/utils/constants.py +++ /dev/null @@ -1,312 +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 dash_bootstrap_components as dbc - -from dash import html - - -class Constants: - """Constants used in Dash PAL. - """ - - ############################################################################ - # General, application wide constants. - - # The application title. - TITLE = "FD.io CSIT" - - # The application description. - DESCRIPTION = "Performance Dashboard" - - # External stylesheets. - EXTERNAL_STYLESHEETS = [dbc.themes.LUX, ] - - # 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 = ["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 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" - - # The default job displayed when the page is loaded first time. - NEWS_DEFAULT_JOB = "csit-vpp-perf-mrr-daily-master-2n-icx" - - # Time period for regressions and progressions. Be CAREFULL with this - # number. Setting it too high causes long processing time during the - # application start-up. - # If NEWS_TIME_PERIOD = 180, it takes approx. 35 minutes to calculate - # annomalies for all tests. - NEWS_TIME_PERIOD = 21 # [days] - - ############################################################################ - # Report. - - # 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 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 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/resources/tools/dash/app/pal/utils/tooltips.yaml b/resources/tools/dash/app/pal/utils/tooltips.yaml deleted file mode 100644 index 2086b575a9..0000000000 --- a/resources/tools/dash/app/pal/utils/tooltips.yaml +++ /dev/null @@ -1,40 +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-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/resources/tools/dash/app/pal/utils/url_processing.py b/resources/tools/dash/app/pal/utils/url_processing.py deleted file mode 100644 index 9307015d0d..0000000000 --- a/resources/tools/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/resources/tools/dash/app/pal/utils/utils.py b/resources/tools/dash/app/pal/utils/utils.py deleted file mode 100644 index 9e4eeeb892..0000000000 --- a/resources/tools/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])) - } |