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Add first csv formatter test
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‎.gitignore‎

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@@ -133,3 +133,4 @@ dmypy.json
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.DS_Store
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robusta_lib
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.idea
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.vscode

‎robusta_krr/core/models/result.py‎

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@@ -17,8 +17,8 @@ class Recommendation(pd.BaseModel):
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class ResourceRecommendation(pd.BaseModel):
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requests: dict[ResourceType, RecommendationValue]
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limits: dict[ResourceType, RecommendationValue]
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requests: dict[ResourceType, RecommendationValue | Recommendation]
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limits: dict[ResourceType, RecommendationValue | Recommendation]
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info: dict[ResourceType, Optional[str]]
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@@ -40,6 +40,7 @@ def calculate(cls, object: K8sObjectData, recommendation: ResourceAllocations) -
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current_severity = Severity.calculate(current, recommended, resource_type)
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#TODO: consider... changing field after model created doesn't validate it.
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getattr(recommendation_processed, selector)[resource_type] = Recommendation(
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value=recommended, severity=current_severity
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)

‎tests/formatters/test_csv_formatter.py‎

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import json
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from typing import Any
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from robusta_krr.core.models.result import Result
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from robusta_krr.formatters.csv import csv_exporter
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import io
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import csv
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RESULT = """
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{
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"scans": [
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{
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"object": {
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"cluster": "mock-cluster",
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"name": "mock-object-1",
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"container": "mock-container-1",
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"pods": [
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{
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"name": "mock-pod-1",
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"deleted": false
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},
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{
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"name": "mock-pod-2",
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"deleted": false
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},
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{
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"name": "mock-pod-3",
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"deleted": true
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}
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],
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"hpa": null,
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"namespace": "default",
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"kind": "Deployment",
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"allocations": {
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"requests": {
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"cpu": 1.0,
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"memory": 1.0
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},
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"limits": {
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"cpu": 2.0,
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"memory": 2.0
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},
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"info": {}
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},
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"warnings": []
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},
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"recommended": {
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"requests": {
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"cpu": {
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"value": "?",
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"severity": "UNKNOWN"
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},
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"memory": {
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"value": "?",
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"severity": "UNKNOWN"
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}
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},
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"limits": {
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"cpu": {
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"value": "?",
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"severity": "UNKNOWN"
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},
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"memory": {
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"value": "?",
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"severity": "UNKNOWN"
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}
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},
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"info": {
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"cpu": "Not enough data",
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"memory": "Not enough data"
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}
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},
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"severity": "UNKNOWN"
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}
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],
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"score": 100,
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"resources": [
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"cpu",
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"memory"
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],
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"description": "tests data",
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"strategy": {
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"name": "simple",
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"settings": {
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"history_duration": 336.0,
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"timeframe_duration": 1.25,
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"cpu_percentile": 95.0,
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"memory_buffer_percentage": 15.0,
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"points_required": 100,
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"allow_hpa": false,
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"use_oomkill_data": false,
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"oom_memory_buffer_percentage": 25.0
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}
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},
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"errors": [],
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"clusterSummary": {},
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"config": {
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"quiet": false,
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"verbose": false,
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"clusters": [],
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"kubeconfig": null,
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"impersonate_user": null,
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"impersonate_group": null,
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"namespaces": "*",
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"resources": [],
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"selector": null,
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"cpu_min_value": 10,
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"memory_min_value": 100,
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"prometheus_url": null,
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"prometheus_auth_header": null,
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"prometheus_other_headers": {},
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"prometheus_ssl_enabled": false,
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"prometheus_cluster_label": null,
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"prometheus_label": null,
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"eks_managed_prom": false,
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"eks_managed_prom_profile_name": null,
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"eks_access_key": null,
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"eks_secret_key": null,
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"eks_service_name": "aps",
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"eks_managed_prom_region": null,
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"coralogix_token": null,
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"openshift": false,
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"max_workers": 10,
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"format": "csv",
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"show_cluster_name": false,
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"strategy": "simple",
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"log_to_stderr": false,
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"width": null,
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"file_output": null,
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"slack_output": null,
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"other_args": {
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"history_duration": "336",
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"timeframe_duration": "1.25",
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"cpu_percentile": "95",
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"memory_buffer_percentage": "15",
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"points_required": "100",
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"allow_hpa": false,
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"use_oomkill_data": false,
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"oom_memory_buffer_percentage": "25"
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},
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"inside_cluster": false,
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"file_output_dynamic": false,
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"bool": false
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}
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}
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"""
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def test_csv_headers() -> None:
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res_data = json.loads(RESULT)
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result = Result(**res_data)
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x = csv_exporter(result)
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reader = csv.DictReader(io.StringIO(x))
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expected_headers: list[str] = [
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"Namespace",
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"Name",
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"Pods",
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"Old Pods",
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"Type",
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"Container",
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"CPU Diff",
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"CPU Requests",
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"CPU Limits",
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"Memory Diff",
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"Memory Requests",
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"Memory Limits",
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]
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assert reader.fieldnames == expected_headers
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expected_first_row: dict[str, str] = {
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"Namespace": "default",
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"Name": "mock-object-1",
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"Pods": "2",
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"Old Pods": "1",
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"Type": "Deployment",
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"Container": "mock-container-1",
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"CPU Diff": "",
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"CPU Requests": "1.0 -> ?",
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"CPU Limits": "2.0 -> ?",
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"Memory Diff": "",
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"Memory Requests": "1.0 -> ?",
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"Memory Limits": "2.0 -> ?",
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}
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first_row: dict[str, Any] = next(reader)
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assert first_row == expected_first_row

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