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bin/ci: Ensure that all jobs have nodes in DAG

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Some automatic jobs, such as 'rustfmt' and 'clang-format', are skipped
during the graph sweep because their parents are already included in the
node set.

This commit ensures all visited jobs are in DAG and fixes iteration
modification using deepcopy.

Closes: https://gitlab.freedesktop.org/mesa/mesa/-/issues/9376

Signed-off-by: Guilherme Gallo <guilherme.gallo@collabora.com>
Acked-by: David Heidelberg <david.heidelberg@collabora.com>
Reviewed-by: Eric Engestrom <eric@engestrom.ch>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/24176>
This commit is contained in:
Guilherme Gallo
2023-07-17 01:30:59 -03:00
committed by Marge Bot
parent 5e4029bfe5
commit 701b035179
1 changed files with 15 additions and 10 deletions
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25
bin/ci/gitlab_gql.py
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@@ -3,6 +3,8 @@
import re
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
from collections import defaultdict
from copy import deepcopy
from dataclasses import dataclass, field
from os import getenv
from pathlib import Path
@@ -14,7 +16,7 @@ from gql import Client, gql
from gql.transport.aiohttp import AIOHTTPTransport
from graphql import DocumentNode
Dag = dict[str, list[str]]
Dag = dict[str, set[str]]
TOKEN_DIR = Path(getenv("XDG_CONFIG_HOME") or Path.home() / ".config")
@@ -85,7 +87,7 @@ def create_job_needs_dag(
) -> tuple[Dag, dict[str, dict[str, Any]]]:
result = gl_gql.query("pipeline_details.gql", params)
dag = {}
incomplete_dag = defaultdict(set)
jobs = {}
pipeline = result["project"]["pipeline"]
if not pipeline:
@@ -96,20 +98,23 @@ def create_job_needs_dag(
for job in stage_job["jobs"]["nodes"]:
needs = job.pop("needs")["nodes"]
jobs[job["name"]] = job
dag[job["name"]] = {node["name"] for node in needs}
incomplete_dag[job["name"]] = {node["name"] for node in needs}
# ensure that all needed nodes its in the graph
[incomplete_dag[node["name"]] for node in needs]
for job, needs in dag.items():
needs: set
final_dag: Dag = {}
for job, needs in incomplete_dag.items():
final_needs: set = deepcopy(needs)
partial = True
while partial:
next_depth = {n for dn in needs for n in dag[dn]}
partial = not needs.issuperset(next_depth)
needs = needs.union(next_depth)
next_depth = {n for dn in final_needs for n in incomplete_dag[dn]}
partial = not final_needs.issuperset(next_depth)
final_needs = final_needs.union(next_depth)
dag[job] = needs
final_dag[job] = final_needs
return dag, jobs
return final_dag, jobs
def filter_dag(dag: Dag, regex: Pattern) -> Dag: