diff options
Diffstat (limited to 'csit.infra.dash/app/pal/utils')
| -rw-r--r-- | csit.infra.dash/app/pal/utils/__init__.py | 12 | ||||
| -rw-r--r-- | csit.infra.dash/app/pal/utils/constants.py | 315 | ||||
| -rw-r--r-- | csit.infra.dash/app/pal/utils/tooltips.yaml | 42 | ||||
| -rw-r--r-- | csit.infra.dash/app/pal/utils/url_processing.py | 99 | ||||
| -rw-r--r-- | csit.infra.dash/app/pal/utils/utils.py | 344 |
5 files changed, 812 insertions, 0 deletions
diff --git a/csit.infra.dash/app/pal/utils/__init__.py b/csit.infra.dash/app/pal/utils/__init__.py new file mode 100644 index 0000000000..5692432123 --- /dev/null +++ b/csit.infra.dash/app/pal/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/pal/utils/constants.py b/csit.infra.dash/app/pal/utils/constants.py new file mode 100644 index 0000000000..8f39fc8991 --- /dev/null +++ b/csit.infra.dash/app/pal/utils/constants.py @@ -0,0 +1,315 @@ +# 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 +import dash_bootstrap_components as dbc + +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" + + # The application description. + DESCRIPTION = "Performance Dashboard" + + # 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 = ["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" + + # 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 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/csit.infra.dash/app/pal/utils/tooltips.yaml b/csit.infra.dash/app/pal/utils/tooltips.yaml new file mode 100644 index 0000000000..476882076c --- /dev/null +++ b/csit.infra.dash/app/pal/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/pal/utils/url_processing.py b/csit.infra.dash/app/pal/utils/url_processing.py new file mode 100644 index 0000000000..9307015d0d --- /dev/null +++ b/csit.infra.dash/app/pal/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/pal/utils/utils.py b/csit.infra.dash/app/pal/utils/utils.py new file mode 100644 index 0000000000..9e4eeeb892 --- /dev/null +++ b/csit.infra.dash/app/pal/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])) + } |