-# Copyright (c) 2018 Cisco and/or its affiliates.
+# Copyright (c) 2020 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:
"""Algorithms to generate files.
"""
+from os.path import isfile
+from collections import OrderedDict
import logging
"""
generator = {
+ u"file_details_split": file_details_split,
+ u"file_details_split_html": file_details_split_html,
u"file_test_results": file_test_results,
u"file_test_results_html": file_test_results_html
}
return False
+def file_details_split(file_spec, input_data, frmt=u"rst"):
+ """Generate the file(s) with algorithms
+ - file_details_split
+ specified in the specification file.
+
+ :param file_spec: File to generate.
+ :param input_data: Data to process.
+ :param frmt: Format can be: rst or html
+ :type file_spec: pandas.Series
+ :type input_data: InputData
+ :type frmt: str
+ """
+
+ fileset_file_name = f"{file_spec[u'output-file']}"
+ rst_header = (
+ u"\n"
+ u".. |br| raw:: html\n\n <br />\n\n\n"
+ u".. |prein| raw:: html\n\n <pre>\n\n\n"
+ u".. |preout| raw:: html\n\n </pre>\n\n"
+ )
+ start_lvl = file_spec.get(u"data-start-level", 4)
+
+ logging.info(f" Generating the file set {fileset_file_name} ...")
+
+ data_sets = file_spec.get(u"data", None)
+ if not data_sets:
+ logging.error(
+ f" No data sets specified for {file_spec[u'output-file']}, exit."
+ )
+ return
+
+ table_sets = file_spec.get(u"dir-tables", None)
+ if not table_sets:
+ logging.error(
+ f" No table sets specified for {file_spec[u'output-file']}, exit."
+ )
+ return
+
+ if len(data_sets) != len(table_sets):
+ logging.error(
+ f" The number of data sets and the number of table sets for "
+ f"{file_spec[u'output-file']} are not equal, exit."
+ )
+ return
+
+ chapters = OrderedDict()
+ for data_set, table_set in zip(data_sets, table_sets):
+
+ logging.info(f" Processing the table set {table_set}...")
+
+ table_lst = None
+ if frmt == u"html":
+ table_lst = get_files(table_set, u".rst", full_path=True)
+ elif frmt == u"rst":
+ table_lst = get_files(table_set, u".csv", full_path=True)
+
+ if not table_lst:
+ logging.error(
+ f" No tables to include in {table_set}. Skipping."
+ )
+ return
+
+ logging.info(u" Creating the test data set...")
+ tests = input_data.filter_data(
+ element=file_spec,
+ params=[u"name", u"parent", u"doc", u"type", u"level"],
+ data=data_set,
+ data_set=u"tests",
+ continue_on_error=True
+ )
+ if tests.empty:
+ return
+ tests = input_data.merge_data(tests)
+
+ logging.info(u" Creating the suite data set...")
+ suites = input_data.filter_data(
+ element=file_spec,
+ data=data_set,
+ continue_on_error=True,
+ data_set=u"suites"
+ )
+ if suites.empty:
+ return
+ suites = input_data.merge_data(suites)
+ suites.sort_index(inplace=True)
+
+ logging.info(u" Generating files...")
+
+ file_name = u""
+ sub_chapter = u"-".join(table_set.split(u"_")[-2:])
+ for suite_longname, suite in suites.items():
+
+ suite_lvl = len(suite_longname.split(u"."))
+ if suite_lvl < start_lvl:
+ # Not interested in this suite
+ continue
+
+ if suite_lvl == start_lvl:
+ # Our top-level suite
+ chapter = suite_longname.split(u'.')[-1]
+ file_name = f"{table_set}/{chapter}.rst"
+ logging.info(f" Writing file {file_name}")
+ with open(file_name, u"a") as file_handler:
+ file_handler.write(rst_header)
+ if chapters.get(chapter, None) is None:
+ chapters[chapter] = OrderedDict()
+ chapters[chapter][sub_chapter] = file_name
+
+ title_line = get_rst_title_char(suite[u"level"] - start_lvl + 2) * \
+ len(sub_chapter)
+ with open(file_name, u"a") as file_handler:
+ if not (u"-ndrpdr" in suite[u"name"] or
+ u"-mrr" in suite[u"name"] or
+ u"-dev" in suite[u"name"]):
+ file_handler.write(f"\n{sub_chapter}\n{title_line}\n")
+
+ if _tests_in_suite(suite[u"name"], tests):
+ for tbl_file in table_lst:
+ if suite[u"name"] in tbl_file:
+ file_handler.write(
+ f"\n{suite[u'name']}\n{title_line}\n"
+ )
+ file_handler.write(
+ f"\n{suite[u'doc']}\n".
+ replace(u'|br|', u'\n\n -')
+ )
+ if frmt == u"html":
+ file_handler.write(
+ f"\n.. include:: {tbl_file.split(u'/')[-1]}"
+ f"\n"
+ )
+ elif frmt == u"rst":
+ file_handler.write(
+ RST_INCLUDE_TABLE.format(
+ file_latex=tbl_file,
+ file_html=tbl_file.split(u"/")[-1])
+ )
+ break
+ titles = {
+ # VPP Perf, MRR
+ u"container_memif": u"LXC/DRC Container Memif",
+ u"crypto": u"IPsec IPv4 Routing",
+ u"hoststack": u"Hoststack Testing",
+ u"ip4": u"IPv4 Routing",
+ u"ip4_tunnels": u"IPv4 Tunnels",
+ u"ip6": u"IPv6 Routing",
+ u"ip6_tunnels": u"IPv6 Tunnels",
+ u"l2": u"L2 Ethernet Switching",
+ u"lb": u"Link Bonding",
+ u"nfv_density": u"NFV Service Density",
+ u"srv6": u"SRv6 Routing",
+ u"vm_vhost": u"KVM VMs vhost-user",
+ u"vts": u"Virtual Topology System",
+ # VPP Device
+ u"interfaces": u"Interfaces",
+ u"l2bd": u"L2 Bridge-domain",
+ u"l2patch": u"L2 Patch",
+ u"l2xc": u"L2 Cross-connect",
+ }
+
+ order_chapters = file_spec.get(u"order-chapters", None)
+ if not order_chapters:
+ order_chapters = chapters.keys()
+
+ order_sub_chapters = file_spec.get(u"order-sub-chapters", None)
+
+ for chapter in order_chapters:
+ sub_chapters = chapters.get(chapter, None)
+ if not sub_chapters:
+ continue
+ with open(f"{fileset_file_name}/index.rst", u"a") as file_handler:
+ file_handler.write(f" {chapter}\n")
+ chapter_file_name = f"{fileset_file_name}/{chapter}.rst"
+ if not isfile(chapter_file_name):
+ with open(chapter_file_name, u"a") as file_handler:
+ title = titles.get(chapter, chapter)
+ file_handler.write(
+ f"{title}\n"
+ f"{get_rst_title_char(2) * len(title)}\n\n"
+ f".. toctree::\n\n"
+ )
+
+ if not order_sub_chapters:
+ order_sub_chapters = sub_chapters.keys()
+ for sub_chapter in order_sub_chapters:
+ testbed = sub_chapters.get(sub_chapter, None)
+ if not testbed:
+ continue
+ with open(chapter_file_name, u"a") as file_handler:
+ file_handler.write(
+ f" ../{u'/'.join(testbed.split(u'/')[-2:])}\n"
+ )
+
+
+def file_details_split_html(file_spec, input_data):
+ """Generate the file(s) with algorithms
+ - file_details_split_html
+ specified in the specification file.
+
+ :param file_spec: File to generate.
+ :param input_data: Data to process.
+ :type file_spec: pandas.Series
+ :type input_data: InputData
+ """
+ file_details_split(file_spec, input_data, frmt=u"html")
+
+
def file_test_results(file_spec, input_data, frmt=u"rst"):
"""Generate the file(s) with algorithms
- file_test_results
Code Review / csit.git / blobdiff