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ceb147200a
Again looking at the upstream template loader, we don't need to pass a 'machine' hash with a 'name' key (we can just pass a 'machine_name' string), or a 'test_suite' hash with a 'name' key (we can just pass 'test_suite_name' string), and we don't need to pass a 'product' hash, we can just pass the product keys directly in the job template hash. In fact the upstream loader transforms 'machine' and 'test_suite' hash 'name' keys into the strings and moves 'product' hash keys up into the top level hash before POSTing to the API anyway. Signed-off-by: Adam Williamson <awilliam@redhat.com>
264 lines
12 KiB
Python
Executable File
264 lines
12 KiB
Python
Executable File
#!/bin/python3
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"""This is an openQA template loader/converter for FIF, the Fedora Intermediate Format. It reads
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from one or more files expected to contain FIF JSON-formatted template data; read on for details
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on this format as it compares to the upstream format. It produces data in the upstream format; it
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can write this data to a JSON file and/or call the upstream loader on it directly, depending on
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the command-line arguments specified.
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The input data must contain definitions of Machines, Products, TestSuites, and Profiles. The input
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data *may* contain JobTemplates, but does not have to and is expected to contain none or only a few
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oddballs.
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The format for Machines, Products and TestSuites is based on the upstream format but with various
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quality-of-life improvements. Upstream, each of these is a list-of-dicts, each dict containing a
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'name' key. This loader expects each to be a dict-of-dicts, with the names as keys (this is both
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easier to read and easier to access). In the upstream format, each Machine, Product and TestSuite
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dict can contain an entry with the key 'settings' which defines variables. The value (for some
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reason...) is a list of dicts, each dict of the format {"key": keyname, "value": value}. This
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loader expects a more obvious and simple format where the value of the 'settings' key is simply a
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dict of keys and values.
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The expected format of the Profiles dict is a dict-of-dicts. For each entry, the key is a unique
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name, and the value is a dict with keys 'machine' and 'product', each value being a valid name from
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the Machines or Products dict respectively. The name of each profile can be anything as long as
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it's unique.
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For TestSuites, this loader then expects an additional 'profiles' key in each dict, whose value is
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a dict indicating the Profiles from which we should generate one or more job templates for that
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test suite. For each entry in the dict, the key is a profile name from the Profiles dict, and the
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value is the priority to give the generated job template.
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This loader will generate JobTemplates from the combination of TestSuites and Profiles. It means
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that, for instance, if you want to add a new test suite and run it on the same set of images and
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arches as several other tests are already run, you do not need to do a large amount of copying and
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pasting to create a bunch of JobTemplates that look a lot like other existing JobTemplates but with
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a different test_suite value; you can just specify an appropriate profiles dict, which is much
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shorter and easier and less error-prone. Thus specifying JobTemplates directly is not usually
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needed and is expected to be used only for some oddball case which the generation system does not
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handle.
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The loader will automatically set the group_name for each job template based on Fedora-specific
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logic which we previously followed manually when creating job templates (e.g. it is set to 'Fedora
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PowerPC' for compose tests run on the PowerPC arch); thus this loader is not really generic but
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specific to Fedora conventions. This could possibly be changed (e.g. by allowing the logic for
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deciding group names to be configurable) if anyone else wants to use it.
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Multiple input files will be combined. Mostly this involves simply updating dicts, but there is
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special handling for TestSuites to allow multiple input files to each include entries for 'the
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same' test suite, but with different profile dicts. So for instance one input file may contain a
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complete TestSuite definition, with the value of its `profiles` key as `{'foo': 10}`. Another input
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file may contain a TestSuite entry with the same key (name) as the complete definition in the other
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file, and the value as a dict with only a `profiles` key (with the value `{'bar': 20}`). This
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loader will combine those into a single complete TestSuite entry with the `profiles` value
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`{'foo': 10, 'bar': 20}`.
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"""
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import argparse
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import json
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import subprocess
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import sys
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def merge_inputs(inputs):
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"""Merge multiple input files. Expects JSON file names. Returns
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a 5-tuple of machines, products, profiles, testsuites and
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jobtemplates (the first four as dicts, the fifth as a list).
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"""
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machines = {}
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products = {}
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profiles = {}
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testsuites = {}
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jobtemplates = []
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for input in inputs:
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try:
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with open(input, 'r') as inputfh:
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data = json.load(inputfh)
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except Exception as err:
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print("Reading input file {} failed!".format(input))
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sys.exit(str(err))
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# simple merges for all these
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for (datatype, tgt) in (
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('Machines', machines),
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('Products', products),
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('Profiles', profiles),
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('JobTemplates', jobtemplates),
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):
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if datatype in data:
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if datatype == 'JobTemplates':
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tgt.extend(data[datatype])
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else:
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tgt.update(data[datatype])
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# special testsuite merging as described in the docstring
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if 'TestSuites' in data:
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for (name, newsuite) in data['TestSuites'].items():
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try:
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existing = testsuites[name]
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# combine and stash the profiles
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existing['profiles'].update(newsuite['profiles'])
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combinedprofiles = existing['profiles']
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# now update the existing suite with the new one, this
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# will overwrite the profiles
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existing.update(newsuite)
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# now restore the combined profiles
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existing['profiles'] = combinedprofiles
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except KeyError:
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testsuites[name] = newsuite
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return (machines, products, profiles, testsuites, jobtemplates)
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def generate_job_templates(machines, products, profiles, testsuites):
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"""Given machines, products, profiles and testsuites (after
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merging, but still in intermediate format), generates job
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templates and returns them as a list.
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"""
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jobtemplates = []
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for (name, suite) in testsuites.items():
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if 'profiles' not in suite:
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print("Warning: no profiles for test suite {}".format(name))
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continue
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for (profile, prio) in suite['profiles'].items():
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jobtemplate = {'test_suite_name': name, 'prio': prio}
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# x86_64 compose
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jobtemplate['group_name'] = 'fedora'
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jobtemplate['machine_name'] = profiles[profile]['machine']
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product = products[profiles[profile]['product']]
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jobtemplate['arch'] = product['arch']
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jobtemplate['flavor'] = product['flavor']
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jobtemplate['distri'] = product['distri']
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jobtemplate['version']= product['version']
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if jobtemplate['machine_name'] == 'ppc64le':
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if 'updates' in product['flavor']:
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jobtemplate['group_name'] = "Fedora PowerPC Updates"
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else:
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jobtemplate['group_name'] = "Fedora PowerPC"
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elif jobtemplate['machine_name'] == 'aarch64':
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if 'updates' in product['flavor']:
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jobtemplate['group_name'] = "Fedora AArch64 Updates"
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else:
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jobtemplate['group_name'] = "Fedora AArch64"
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elif 'updates' in product['flavor']:
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# x86_64 updates
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jobtemplate['group_name'] = "Fedora Updates"
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jobtemplates.append(jobtemplate)
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return jobtemplates
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def reverse_qol(machines, products, testsuites):
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"""Reverse all our quality-of-life improvements in Machines,
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Products and TestSuites. We don't do profiles as only this loader
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uses them, upstream loader does not. We don't do jobtemplates as
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we don't do any QOL stuff for that. Returns the same tuple it's
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passed.
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"""
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# first, some nested convenience functions
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def to_list_of_dicts(datadict):
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"""Convert our nice dicts to upstream's stupid list-of-dicts-with
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-name-keys.
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"""
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converted = []
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for (name, item) in datadict.items():
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item['name'] = name
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converted.append(item)
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return converted
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def dumb_settings(settdict):
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"""Convert our sensible settings dicts to upstream's weird-ass
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list-of-dicts format.
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"""
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converted = []
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for (key, value) in settdict.items():
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converted.append({'key': key, 'value': value})
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return converted
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machines = to_list_of_dicts(machines)
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products = to_list_of_dicts(products)
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testsuites = to_list_of_dicts(testsuites)
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for datatype in (machines, products, testsuites):
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for item in datatype:
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item['settings'] = dumb_settings(item['settings'])
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if 'profiles' in item:
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# this is only part of the intermediate format, should
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# not be in the final output
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del item['profiles']
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return (machines, products, testsuites)
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def parse_args():
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"""Parse arguments with argparse."""
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parser = argparse.ArgumentParser(description=(
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"Alternative openQA template loader/generator, using a more "
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"convenient input format. See docstring for details. "))
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parser.add_argument(
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'-l', '--load', help="Load the generated templates into openQA.",
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action='store_true')
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parser.add_argument(
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'--loader', help="Loader to use with --load",
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default="/usr/share/openqa/script/load_templates")
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parser.add_argument(
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'-w', '--write', help="Write the generated templates in JSON "
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"format.", action='store_true')
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parser.add_argument(
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'--filename', help="Filename to write with --write",
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default="generated.json")
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parser.add_argument(
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'--host', help="If specified with --load, gives a host "
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"to load the templates to. Is passed unmodified to upstream "
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"loader.")
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parser.add_argument(
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'-c', '--clean', help="If specified with --load, passed to "
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"upstream loader and behaves as documented there.",
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action='store_true')
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parser.add_argument(
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'-u', '--update', help="If specified with --load, passed to "
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"upstream loader and behaves as documented there.",
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action='store_true')
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parser.add_argument(
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'files', help="Input JSON files", nargs='+')
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return parser.parse_args()
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def run():
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"""Read in arguments and run the appropriate steps."""
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args = parse_args()
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if not args.write and not args.load:
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sys.exit("Neither --write nor --load specified! Doing nothing.")
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(machines, products, profiles, testsuites, jobtemplates) = merge_inputs(args.files)
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jobtemplates.extend(generate_job_templates(machines, products, profiles, testsuites))
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(machines, products, testsuites) = reverse_qol(machines, products, testsuites)
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# now produce the output in upstream-compatible format
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out = {
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'JobTemplates': jobtemplates,
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'Machines': machines,
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'Products': products,
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'TestSuites': testsuites
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}
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if args.write:
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# write generated output to given filename
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with open(args.filename, 'w') as outfh:
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json.dump(out, outfh, indent=4)
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if args.load:
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# load generated output with given loader (defaults to
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# /usr/share/openqa/script/load_templates)
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loadargs = [args.loader]
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if args.host:
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loadargs.extend(['--host', args.host])
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if args.clean:
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loadargs.append('--clean')
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if args.update:
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loadargs.append('--update')
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loadargs.append('-')
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subprocess.run(loadargs, input=json.dumps(out), text=True)
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def main():
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"""Main loop."""
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try:
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run()
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except KeyboardInterrupt:
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sys.stderr.write("Interrupted, exiting...\n")
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sys.exit(1)
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if __name__ == '__main__':
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main()
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# vim: set textwidth=100 ts=8 et sw=4:
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