os-autoinst-distri-rocky/fifloader

#!/bin/python3

"""This is an openQA template loader/converter for FIF, the Fedora Intermediate Format. It reads
from one or more files expected to contain FIF JSON-formatted template data; read on for details
on this format as it compares to the upstream format. It produces data in the upstream format; it
can write this data to a JSON file and/or call the upstream loader on it directly, depending on
the command-line arguments specified.

The input data must contain definitions of Machines, Products, TestSuites, and Profiles. The input
data *may* contain JobTemplates, but does not have to and is expected to contain none or only a few
oddballs.

The format for Machines, Products and TestSuites is based on the upstream format but with various
quality-of-life improvements. Upstream, each of these is a list-of-dicts, each dict containing a
'name' key. This loader expects each to be a dict-of-dicts, with the names as keys (this is both
easier to read and easier to access). In the upstream format, each Machine, Product and TestSuite
dict can contain an entry with the key 'settings' which defines variables. The value (for some
reason...) is a list of dicts, each dict of the format {"key": keyname, "value": value}. This
loader expects a more obvious and simple format where the value of the 'settings' key is simply a
dict of keys and values.

The expected format of the Profiles dict is a dict-of-dicts. For each entry, the key is a unique
name, and the value is a dict with keys 'machine' and 'product', each value being a valid name from
the Machines or Products dict respectively. The name of each profile can be anything as long as
it's unique.

For TestSuites, this loader then expects an additional 'profiles' key in each dict, whose value is
a dict indicating the Profiles from which we should generate one or more job templates for that
test suite. For each entry in the dict, the key is a profile name from the Profiles dict, and the
value is the priority to give the generated job template.

This loader will generate JobTemplates from the combination of TestSuites and Profiles. It means
that, for instance, if you want to add a new test suite and run it on the same set of images and
arches as several other tests are already run, you do not need to do a large amount of copying and
pasting to create a bunch of JobTemplates that look a lot like other existing JobTemplates but with
a different test_suite value; you can just specify an appropriate profiles dict, which is much
shorter and easier and less error-prone. Thus specifying JobTemplates directly is not usually
needed and is expected to be used only for some oddball case which the generation system does not
handle.

The loader will automatically set the group_name for each job template based on Fedora-specific
logic which we previously followed manually when creating job templates (e.g. it is set to 'Fedora
PowerPC' for compose tests run on the PowerPC arch); thus this loader is not really generic but
specific to Fedora conventions. This could possibly be changed (e.g. by allowing the logic for
deciding group names to be configurable) if anyone else wants to use it.

Multiple input files will be combined. Mostly this involves simply updating dicts, but there is
special handling for TestSuites to allow multiple input files to each include entries for 'the
same' test suite, but with different profile dicts. So for instance one input file may contain a
complete TestSuite definition, with the value of its `profiles` key as `{'foo': 10}`. Another input
file may contain a TestSuite entry with the same key (name) as the complete definition in the other
file, and the value as a dict with only a `profiles` key (with the value `{'bar': 20}`). This
loader will combine those into a single complete TestSuite entry with the `profiles` value
`{'foo': 10, 'bar': 20}`.
"""

import argparse
import json
import subprocess
import sys

def merge_inputs(inputs):
    """Merge multiple input files. Expects JSON file names. Returns
    a 5-tuple of machines, products, profiles, testsuites and
    jobtemplates (the first four as dicts, the fifth as a list).
    """
    machines = {}
    products = {}
    profiles = {}
    testsuites = {}
    jobtemplates = []

    for input in inputs:
        try:
            with open(input, 'r') as inputfh:
                data = json.load(inputfh)
        except Exception as err:
            print("Reading input file {} failed!".format(input))
            sys.exit(str(err))

        # simple merges for all these
        for (datatype, tgt) in (
            ('Machines', machines),
            ('Products', products),
            ('Profiles', profiles),
            ('JobTemplates', jobtemplates),
        ):
            if datatype in data:
                if datatype == 'JobTemplates':
                    tgt.extend(data[datatype])
                else:
                    tgt.update(data[datatype])
        # special testsuite merging as described in the docstring
        if 'TestSuites' in data:
            for (name, newsuite) in data['TestSuites'].items():
                try:
                    existing = testsuites[name]
                    # combine and stash the profiles
                    existing['profiles'].update(newsuite['profiles'])
                    combinedprofiles = existing['profiles']
                    # now update the existing suite with the new one, this
                    # will overwrite the profiles
                    existing.update(newsuite)
                    # now restore the combined profiles
                    existing['profiles'] = combinedprofiles
                except KeyError:
                    testsuites[name] = newsuite

    return (machines, products, profiles, testsuites, jobtemplates)

def generate_job_templates(machines, products, profiles, testsuites):
    """Given machines, products, profiles and testsuites (after
    merging, but still in intermediate format), generates job
    templates and returns them as a list.
    """
    jobtemplates = []
    for (name, suite) in testsuites.items():
        if 'profiles' not in suite:
            print("Warning: no profiles for test suite {}".format(name))
            continue
        for (profile, prio) in suite['profiles'].items():
            jobtemplate = {'test_suite': {'name': name}, 'prio': prio}
            # x86_64 compose
            jobtemplate['group_name'] = 'fedora'
            jobtemplate['machine'] = {'name': profiles[profile]['machine']}
            product = products[profiles[profile]['product']]
            jobtemplate['product'] = {
                'arch': product['arch'],
                'flavor': product['flavor'],
                'distri': product['distri'],
                'version': product['version']
            }
            if jobtemplate['machine']['name'] == 'ppc64le':
                if 'updates' in product['flavor']:
                    jobtemplate['group_name'] = "Fedora PowerPC Updates"
                else:
                    jobtemplate['group_name'] = "Fedora PowerPC"
            elif jobtemplate['machine']['name'] == 'aarch64':
                if 'updates' in product['flavor']:
                    jobtemplate['group_name'] = "Fedora AArch64 Updates"
                else:
                    jobtemplate['group_name'] = "Fedora AArch64"
            elif 'updates' in product['flavor']:
                    # x86_64 updates
                    jobtemplate['group_name'] = "Fedora Updates"
            jobtemplates.append(jobtemplate)
    return jobtemplates

def reverse_qol(machines, products, testsuites):
    """Reverse all our quality-of-life improvements in Machines,
    Products and TestSuites. We don't do profiles as only this loader
    uses them, upstream loader does not. We don't do jobtemplates as
    we don't do any QOL stuff for that. Returns the same tuple it's
    passed.
    """
    # first, some nested convenience functions
    def to_list_of_dicts(datadict):
        """Convert our nice dicts to upstream's stupid list-of-dicts-with
        -name-keys.
        """
        converted = []
        for (name, item) in datadict.items():
            item['name'] = name
            converted.append(item)
        return converted

    def dumb_settings(settdict):
        """Convert our sensible settings dicts to upstream's weird-ass
        list-of-dicts format.
        """
        converted = []
        for (key, value) in settdict.items():
            converted.append({'key': key, 'value': value})
        return converted

    machines = to_list_of_dicts(machines)
    products = to_list_of_dicts(products)
    testsuites = to_list_of_dicts(testsuites)
    for datatype in (machines, products, testsuites):
        for item in datatype:
            item['settings'] = dumb_settings(item['settings'])
            if 'profiles' in item:
                # this is only part of the intermediate format, should
                # not be in the final output
                del item['profiles']

    return (machines, products, testsuites)

def parse_args():
    """Parse arguments with argparse."""
    parser = argparse.ArgumentParser(description=(
        "Alternative openQA template loader/generator, using a more "
        "convenient input format. See docstring for details. "))
    parser.add_argument(
        '-l', '--load', help="Load the generated templates into openQA.",
        action='store_true')
    parser.add_argument(
        '--loader', help="Loader to use with --load",
        default="/usr/share/openqa/script/load_templates")
    parser.add_argument(
        '-w', '--write', help="Write the generated templates in JSON "
        "format.", action='store_true')
    parser.add_argument(
        '--filename', help="Filename to write with --write",
        default="generated.json")
    parser.add_argument(
        '--host', help="If specified with --load, gives a host "
        "to load the templates to. Is passed unmodified to upstream "
        "loader.")
    parser.add_argument(
        '-c', '--clean', help="If specified with --load, passed to "
        "upstream loader and behaves as documented there.",
        action='store_true')
    parser.add_argument(
        '-u', '--update', help="If specified with --load, passed to "
        "upstream loader and behaves as documented there.",
        action='store_true')
    parser.add_argument(
        'files', help="Input JSON files", nargs='+')
    return parser.parse_args()

def run():
    """Read in arguments and run the appropriate steps."""
    args = parse_args()
    if not args.write and not args.load:
        sys.exit("Neither --write nor --load specified! Doing nothing.")
    (machines, products, profiles, testsuites, jobtemplates) = merge_inputs(args.files)
    jobtemplates.extend(generate_job_templates(machines, products, profiles, testsuites))
    (machines, products, testsuites) = reverse_qol(machines, products, testsuites)
    # now produce the output in upstream-compatible format
    out = {
        'JobTemplates': jobtemplates,
        'Machines': machines,
        'Products': products,
        'TestSuites': testsuites
    }
    if args.write:
        # write generated output to given filename
        with open(args.filename, 'w') as outfh:
            json.dump(out, outfh, indent=4)
    if args.load:
        # load generated output with given loader (defaults to
        # /usr/share/openqa/script/load_templates)
        loadargs = [args.loader]
        if args.host:
            loadargs.extend(['--host', args.host])
        if args.clean:
            loadargs.append('--clean')
        if args.update:
            loadargs.append('--update')
        loadargs.append('-')
        subprocess.run(loadargs, input=json.dumps(out), text=True)

def main():
    """Main loop."""
    try:
        run()
    except KeyboardInterrupt:
        sys.stderr.write("Interrupted, exiting...\n")
        sys.exit(1)

if __name__ == '__main__':
    main()

# vim: set textwidth=100 ts=8 et sw=4: