src/vnet/dhcp/dhcp_api.c

# Copyright (c) 2017 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.

"""Algorithms to generate tables.
"""


import logging
import csv
import prettytable

from string import replace

from errors import PresentationError
from utils import mean, stdev, relative_change


def generate_tables(spec, data):
    """Generate all tables specified in the specification file.

    :param spec: Specification read from the specification file.
    :param data: Data to process.
    :type spec: Specification
    :type data: InputData
    """

    logging.info("Generating the tables ...")
    for table in spec.tables:
        try:
            eval(table["algorithm"])(table, data)
        except NameError:
            logging.error("The algorithm '{0}' is not defined.".
                          format(table["algorithm"]))
    logging.info("Done.")


def table_details(table, input_data):
    """Generate the table(s) with algorithm: table_detailed_test_results
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    data = input_data.filter_data(table)

    # Prepare the header of the tables
    header = list()
    for column in table["columns"]:
        header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))

    # Generate the data for the table according to the model in the table
    # specification
    job = table["data"].keys()[0]
    build = str(table["data"][job][0])
    try:
        suites = input_data.suites(job, build)
    except KeyError:
        logging.error("    No data available. The table will not be generated.")
        return

    for suite_longname, suite in suites.iteritems():
        # Generate data
        suite_name = suite["name"]
        table_lst = list()
        for test in data[job][build].keys():
            if data[job][build][test]["parent"] in suite_name:
                row_lst = list()
                for column in table["columns"]:
                    try:
                        col_data = str(data[job][build][test][column["data"].
                                       split(" ")[1]]).replace('"', '""')
                        if column["data"].split(" ")[1] in ("vat-history",
                                                            "show-run"):
                            col_data = replace(col_data, " |br| ", "",
                                               maxreplace=1)
                            col_data = " |prein| {0} |preout| ".\
                                format(col_data[:-5])
                        row_lst.append('"{0}"'.format(col_data))
                    except KeyError:
                        row_lst.append("No data")
                table_lst.append(row_lst)

        # Write the data to file
        if table_lst:
            file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
                                            table["output-file-ext"])
            logging.info("      Writing file: '{}'".format(file_name))
            with open(file_name, "w") as file_handler:
                file_handler.write(",".join(header) + "\n")
                for item in table_lst:
                    file_handler.write(",".join(item) + "\n")

    logging.info("  Done.")


def table_merged_details(table, input_data):
    """Generate the table(s) with algorithm: table_merged_details
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    data = input_data.filter_data(table)
    data = input_data.merge_data(data)
    data.sort_index(inplace=True)

    suites = input_data.filter_data(table, data_set="suites")
    suites = input_data.merge_data(suites)

    # Prepare the header of the tables
    header = list()
    for column in table["columns"]:
        header.append('"{0}"'.format(str(column["title"]).replace('"', '""')))

    for _, suite in suites.iteritems():
        # Generate data
        suite_name = suite["name"]
        table_lst = list()
        for test in data.keys():
            if data[test]["parent"] in suite_name:
                row_lst = list()
                for column in table["columns"]:
                    try:
                        col_data = str(data[test][column["data"].
                                       split(" ")[1]]).replace('"', '""')
                        if column["data"].split(" ")[1] in ("vat-history",
                                                            "show-run"):
                            col_data = replace(col_data, " |br| ", "",
                                               maxreplace=1)
                            col_data = " |prein| {0} |preout| ".\
                                format(col_data[:-5])
                        row_lst.append('"{0}"'.format(col_data))
                    except KeyError:
                        row_lst.append("No data")
                table_lst.append(row_lst)

        # Write the data to file
        if table_lst:
            file_name = "{0}_{1}{2}".format(table["output-file"], suite_name,
                                            table["output-file-ext"])
            logging.info("      Writing file: '{}'".format(file_name))
            with open(file_name, "w") as file_handler:
                file_handler.write(",".join(header) + "\n")
                for item in table_lst:
                    file_handler.write(",".join(item) + "\n")

    logging.info("  Done.")


def table_performance_improvements(table, input_data):
    """Generate the table(s) with algorithm: table_performance_improvements
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    def _write_line_to_file(file_handler, data):
        """Write a line to the .csv file.

        :param file_handler: File handler for the csv file. It must be open for
         writing text.
        :param data: Item to be written to the file.
        :type file_handler: BinaryIO
        :type data: list
        """

        line_lst = list()
        for item in data:
            if isinstance(item["data"], str):
                # Remove -?drdisc from the end
                if item["data"].endswith("drdisc"):
                    item["data"] = item["data"][:-8]
                line_lst.append(item["data"])
            elif isinstance(item["data"], float):
                line_lst.append("{:.1f}".format(item["data"]))
            elif item["data"] is None:
                line_lst.append("")
        file_handler.write(",".join(line_lst) + "\n")

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Read the template
    file_name = table.get("template", None)
    if file_name:
        try:
            tmpl = _read_csv_template(file_name)
        except PresentationError:
            logging.error("  The template '{0}' does not exist. Skipping the "
                          "table.".format(file_name))
            return None
    else:
        logging.error("The template is not defined. Skipping the table.")
        return None

    # Transform the data
    data = input_data.filter_data(table)

    # Prepare the header of the tables
    header = list()
    for column in table["columns"]:
        header.append(column["title"])

    # Generate the data for the table according to the model in the table
    # specification
    tbl_lst = list()
    for tmpl_item in tmpl:
        tbl_item = list()
        for column in table["columns"]:
            cmd = column["data"].split(" ")[0]
            args = column["data"].split(" ")[1:]
            if cmd == "template":
                try:
                    val = float(tmpl_item[int(args[0])])
                except ValueError:
                    val = tmpl_item[int(args[0])]
                tbl_item.append({"data": val})
            elif cmd == "data":
                jobs = args[0:-1]
                operation = args[-1]
                data_lst = list()
                for job in jobs:
                    for build in data[job]:
                        try:
                            data_lst.append(float(build[tmpl_item[0]]
                                                  ["throughput"]["value"]))
                        except (KeyError, TypeError):
                            # No data, ignore
                            continue
                if data_lst:
                    tbl_item.append({"data": (eval(operation)(data_lst)) /
                                             1000000})
                else:
                    tbl_item.append({"data": None})
            elif cmd == "operation":
                operation = args[0]
                try:
                    nr1 = float(tbl_item[int(args[1])]["data"])
                    nr2 = float(tbl_item[int(args[2])]["data"])
                    if nr1 and nr2:
                        tbl_item.append({"data": eval(operation)(nr1, nr2)})
                    else:
                        tbl_item.append({"data": None})
                except (IndexError, ValueError, TypeError):
                    logging.error("No data for {0}".format(tbl_item[0]["data"]))
                    tbl_item.append({"data": None})
                    continue
            else:
                logging.error("Not supported command {0}. Skipping the table.".
                              format(cmd))
                return None
        tbl_lst.append(tbl_item)

    # Sort the table according to the relative change
    tbl_lst.sort(key=lambda rel: rel[-1]["data"], reverse=True)

    # Create the tables and write them to the files
    file_names = [
        "{0}_ndr_top{1}".format(table["output-file"], table["output-file-ext"]),
        "{0}_pdr_top{1}".format(table["output-file"], table["output-file-ext"]),
        "{0}_ndr_low{1}".format(table["output-file"], table["output-file-ext"]),
        "{0}_pdr_low{1}".format(table["output-file"], table["output-file-ext"])
    ]

    for file_name in file_names:
        logging.info("    Writing the file '{0}'".format(file_name))
        with open(file_name, "w") as file_handler:
            file_handler.write(",".join(header) + "\n")
            for item in tbl_lst:
                if isinstance(item[-1]["data"], float):
                    rel_change = round(item[-1]["data"], 1)
                else:
                    rel_change = item[-1]["data"]
                if "ndr_top" in file_name \
                        and "ndr" in item[0]["data"] \
                        and rel_change >= 10.0:
                    _write_line_to_file(file_handler, item)
                elif "pdr_top" in file_name \
                        and "pdr" in item[0]["data"] \
                        and rel_change >= 10.0:
                    _write_line_to_file(file_handler, item)
                elif "ndr_low" in file_name \
                        and "ndr" in item[0]["data"] \
                        and rel_change < 10.0:
                    _write_line_to_file(file_handler, item)
                elif "pdr_low" in file_name \
                        and "pdr" in item[0]["data"] \
                        and rel_change < 10.0:
                    _write_line_to_file(file_handler, item)

    logging.info("  Done.")


def _read_csv_template(file_name):
    """Read the template from a .csv file.

    :param file_name: Name / full path / relative path of the file to read.
    :type file_name: str
    :returns: Data from the template as list (lines) of lists (items on line).
    :rtype: list
    :raises: PresentationError if it is not possible to read the file.
    """

    try:
        with open(file_name, 'r') as csv_file:
            tmpl_data = list()
            for line in csv_file:
                tmpl_data.append(line[:-1].split(","))
        return tmpl_data
    except IOError as err:
        raise PresentationError(str(err), level="ERROR")


def table_performance_comparison(table, input_data):
    """Generate the table(s) with algorithm: table_performance_comparison
    specified in the specification file.

    :param table: Table to generate.
    :param input_data: Data to process.
    :type table: pandas.Series
    :type input_data: InputData
    """

    logging.info("  Generating the table {0} ...".
                 format(table.get("title", "")))

    # Transform the data
    data = input_data.filter_data(table)

    # Prepare the header of the tables
    try:
        header = ["Test case",
                  "{0} Throughput [Mpps]".format(table["reference"]["title"]),
                  "{0} stdev [Mpps]".format(table["reference"]["title"]),
                  "{0} Throughput [Mpps]".format(table["compare"]["title"]),
                  "{0} stdev [Mpps]".format(table["compare"]["title"]),
                  "Change [%]"]
        header_str = ",".join(header) + "\n"
    except (AttributeError, KeyError) as err:
        logging.error("The model is invalid, missing parameter: {0}".
                      format(err))
        return

    # Prepare data to the table:
    tbl_dict = dict()
    for job, builds in table["reference"]["data"].items():
        for build in builds:
            for tst_name, tst_data in data[job][str(build)].iteritems():
                if tbl_dict.get(tst_name, None) is None:
                    name = "{0}-{1}".format(tst_data["parent"].split("-")[0],
                                            "-".join(tst_data["name"].
                                                     split("-")[1:]))
                    tbl_dict[tst_name] = {"name": name,
                                          "ref-data": list(),
                                          "cmp-data": list()}
                try:
                    tbl_dict[tst_name]["ref-data"].\
                        append(tst_data["throughput"]["value"])
                except TypeError:
                    pass  # No data in output.xml for this test

    for job, builds in table["compare"]["data"].items():
        for build in builds:
            for tst_name, tst_data in data[job][str(build)].iteritems():
                try:
                    tbl_dict[tst_name]["cmp-data"].\
                        append(tst_data["throughput"]["value"])
                except KeyError:
                    pass
                except TypeError:
                    tbl_dict.pop(tst_name, None)

    tbl_lst = list()
    for tst_name in tbl_dict.keys():
        item = [tbl_dict[tst_name]["name"], ]
        if tbl_dict[tst_name]["ref-data"]:
            item.append(round(mean(tbl_dict[tst_name]["ref-data"]) / 1000000,
                              2))
            item.append(round(stdev(tbl_dict[tst_name]["ref-data"]) / 1000000,
                              2))
        else:
            item.extend([None, None])
        if tbl_dict[tst_name]["cmp-data"]:
            item.append(round(mean(tbl_dict[tst_name]["cmp-data"]) / 1000000,
                              2))
            item.append(round(stdev(tbl_dict[tst_name]["cmp-data"]) / 1000000,
                              2))
        else:
            item.extend([None, None])
        if item[1] is not None and item[3] is not None:
            item.append(int(relative_change(float(item[1]), float(item[3]))))
        if len(item) == 6:
            tbl_lst.append(item)

    # Sort the table according to the relative change
    tbl_lst.sort(key=lambda rel: rel[-1], reverse=True)

    # Generate tables:
    # All tests in csv:
    tbl_names = ["{0}-ndr-1t1c-full{1}".format(table["output-file"],
                                               table["output-file-ext"]),
                 "{0}-ndr-2t2c-full{1}".format(table["output-file"],
                                               table["output-file-ext"]),
                 "{0}-ndr-4t4c-full{1}".format(table["output-file"],
                                               table["output-file-ext"]),
                 "{0}-pdr-1t1c-full{1}".format(table["output-file"],
                                               table["output-file-ext"]),
                 "{0}-pdr-2t2c-full{1}".format(table["output-file"],
                                               table["output-file-ext"]),
                 "{0}-pdr-4t4c-full{1}".format(table["output-file"],
                                               table["output-file-ext"])
                 ]
    for file_name in tbl_names:
        logging.info("      Writing file: '{}'".format(file_name))
        with open(file_name, "w") as file_handler:
            file_handler.write(header_str)
            for test in tbl_lst:
                if (file_name.split("-")[-3] in test[0] and    # NDR vs PDR
                        file_name.split("-")[-2] in test[0]):  # cores
                    test[0] = "-".join(test[0].split("-")[:-1])
                    file_handler.write(",".join([str(item) for item in test]) +
                                       "\n")

    # All tests in txt:
    tbl_names_txt = ["{0}-ndr-1t1c-full.txt".format(table["output-file"]),
                     "{0}-ndr-2t2c-full.txt".format(table["output-file"]),
                     "{0}-ndr-4t4c-full.txt".format(table["output-file"]),
                     "{0}-pdr-1t1c-full.txt".format(table["output-file"]),
                     "{0}-pdr-2t2c-full.txt".format(table["output-file"]),
                     "{0}-pdr-4t4c-full.txt".format(table["output-file"])
                     ]

    for i, txt_name in enumerate(tbl_names_txt):
        txt_table = None
        logging.info("      Writing file: '{}'".format(txt_name))
        with open(tbl_names[i], 'rb') as csv_file:
            csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
            for row in csv_content:
                if txt_table is None:
                    txt_table = prettytable.PrettyTable(row)
                else:
                    txt_table.add_row(row)
        with open(txt_name, "w") as txt_file:
            txt_file.write(str(txt_table))

    # Selected tests in csv:
    input_file = "{0}-ndr-1t1c-full{1}".format(table["output-file"],
                                               table["output-file-ext"])
    with open(input_file, "r") as in_file:
        lines = list()
        for line in in_file:
            lines.append(line)

    output_file = "{0}-ndr-1t1c-top{1}".format(table["output-file"],
                                               table["output-file-ext"])
    logging.info("      Writing file: '{}'".format(output_file))
    with open(output_file, "w") as out_file:
        out_file.write(header_str)
        for i, line in enumerate(lines[1:]):
            if i == table["nr-of-tests-shown"]:
                break
            out_file.write(line)

    output_file = "{0}-ndr-1t1c-bottom{1}".format(table["output-file"],
                                                  table["output-file-ext"])
    logging.info("      Writing file: '{}'".format(output_file))
    with open(output_file, "w") as out_file:
        out_file.write(header_str)
        for i, line in enumerate(lines[-1:0:-1]):
            if i == table["nr-of-tests-shown"]:
                break
            out_file.write(line)

    input_file = "{0}-pdr-1t1c-full{1}".format(table["output-file"],
                                               table["output-file-ext"])
    with open(input_file, "r") as in_file:
        lines = list()
        for line in in_file:
            lines.append(line)

    output_file = "{0}-pdr-1t1c-top{1}".format(table["output-file"],
                                               table["output-file-ext"])
    logging.info("      Writing file: '{}'".format(output_file))
    with open(output_file, "w") as out_file:
        out_file.write(header_str)
        for i, line in enumerate(lines[1:]):
            if i == table["nr-of-tests-shown"]:
                break
            out_file.write(line)

    output_file = "{0}-pdr-1t1c-bottom{1}".format(table["output-file"],
                                                  table["output-file-ext"])
    logging.info("      Writing file: '{}'".format(output_file))
    with open(output_file, "w") as out_file:
        out_file.write(header_str)
        for i, line in enumerate(lines[-1:0:-1]):
            if i == table["nr-of-tests-shown"]:
                break
            out_file.write(line)
Age	Commit message (Expand)	Author	Files	Lines
2018-01-23	For DHCP client configuration control the setting of the broadcast flag in the	Neale Ranns	1	-1/+1
2018-01-11	api: remove transport specific code from handlers	Florin Coras	1	-11/+11
2018-01-09	api: refactor vlibmemory	Florin Coras	1	-3/+3
2017-11-16	Add Support of DHCP VSS Type 0 where VPN-ID is ASCII	John Lo	1	-9/+27
2017-07-18	DHCP client option 61 "client_id"	Neale Ranns	1	-1/+2
2017-07-06	DHCP complete event sends mask length	Neale Ranns	1	-2/+3
2017-04-28	Fix hostname fencepost error in dhcp_compl_event_callback.	Jon Loeliger	1	-2/+4
2017-03-07	DHCP Multiple Servers (VPP-602, VPP-605)	Neale Ranns	1	-19/+47
2017-03-02	Clean up binary api message handler registration issues	Dave Barach	1	-8/+0
2017-02-16	Consolidate DHCP v4 and V6 implementation. No functional change intended	Neale Ranns	1	-51/+44
2017-02-21	dhcp: multiple additions	Neale Ranns	1	-46/+66
2017-01-26	API refactoring : dhcp	Pavel Kotucek	1	-0/+253