This is an automated email from the ASF dual-hosted git repository. Gerrrr pushed a commit to branch pydantic-and-split-persistence-report-json in repository https://gitbox.apache.org/repos/asf/otava.git
commit 31886b03b0db9d37a8686996920901bdfda532fb Author: Alex Sorokoumov <[email protected]> AuthorDate: Tue Aug 18 19:52:58 2026 -0700 Split persistence and report JSON serialization Make domain to_json() methods return the precise persistence representation: ChangePoint and ChangePointGroup now emit numeric fields, include qhat, and no longer use rounded=True/False as a presentation switch. Move rounded JSON output into Report, alongside the other report renderers. ReportType.JSON now owns display-only fields such as backward_change_percent and formats human-facing values as strings. Add Pydantic v2 schema models for the persisted analyzed-series payload and validate AnalyzedSeries.to_json() against that schema before returning JSON-safe data. Update tests to pin the split: persistence JSON stays numeric and round-trippable, while report JSON keeps the existing rounded output shape. --- otava/change_point_divisive/base.py | 127 ++++++++++++++--------------- otava/report.py | 32 +++++++- otava/serialization.py | 68 ++++++++++++++++ otava/series.py | 27 +++++-- pyproject.toml | 1 + tests/change_point_classes_test.py | 38 ++++++--- tests/report_test.py | 88 ++++++++++++++------- tests/series_test.py | 31 ++++++++ uv.lock | 154 ++++++++++++++++++++++++++++++++++++ 9 files changed, 454 insertions(+), 112 deletions(-) diff --git a/otava/change_point_divisive/base.py b/otava/change_point_divisive/base.py index 1020c83..edc0f61 100644 --- a/otava/change_point_divisive/base.py +++ b/otava/change_point_divisive/base.py @@ -201,9 +201,8 @@ class ChangePoint(CandidateChangePoint, Generic[GenericStats]): data = {f.name: getattr(self, f.name) for f in fields(CandidateChangePoint)} return CandidateChangePoint(**data) - def to_json(self, rounded=True): - cps = ChangePointSerializer(self) - return cps.to_json(rounded) + def to_json(self): + return ChangePointSerializer(self).to_json() class ChangePointSerializer(ChangePoint): @@ -217,6 +216,7 @@ class ChangePointSerializer(ChangePoint): def __init__(self, cp: ChangePoint[GenericStats]): self.stats = cp.stats self.index = cp.index + self.qhat = cp.qhat self.metric = cp.metric def forward_change_percent(self) -> float: @@ -243,33 +243,19 @@ class ChangePointSerializer(ChangePoint): def pvalue(self): return self.stats.pvalue - def to_json(self, rounded=True): - if rounded: - return { - "metric": self.metric, - "index": int(self.index), - "forward_change_percent": f"{self.forward_change_percent():.0f}", - "backward_change_percent": f"{self.backward_change_percent():.0f}", - "magnitude": f"{self.magnitude():-0f}", - "mean_before": f"{self.mean_before():-0f}", - "stddev_before": f"{self.stddev_before():-0f}", - "mean_after": f"{self.mean_after():-0f}", - "stddev_after": f"{self.stddev_after():-0f}", - "pvalue": f"{self.pvalue():-0f}", - } - - else: - return { - "metric": self.metric, - "index": int(self.index), - "forward_change_percent": self.forward_change_percent(), - "magnitude": self.magnitude(), - "mean_before": self.mean_before(), - "stddev_before": self.stddev_before(), - "mean_after": self.mean_after(), - "stddev_after": self.stddev_after(), - "pvalue": self.pvalue(), - } + def to_json(self): + return { + "metric": self.metric, + "index": int(self.index), + "qhat": self.qhat, + "forward_change_percent": self.forward_change_percent(), + "magnitude": self.magnitude(), + "mean_before": self.mean_before(), + "stddev_before": self.stddev_before(), + "mean_after": self.mean_after(), + "stddev_after": self.stddev_after(), + "pvalue": self.pvalue(), + } @dataclass @@ -288,15 +274,16 @@ class ChangePointGroup: :param attributes: The attributes of the test result at this timestamp. Commit and test metadata. :param changes: For each metric that has a change point at this time(stamp), the ChangePoint object. """ + time: float attributes: Dict[str, str] # ChangePointGroup.changes.keys() stores the set of metrics that were used at this ChangePointGroup.time. changes: Dict[str, ChangePoint] - def to_json(self, rounded=False): + def to_json(self): changes = [] for metric, cp in self.changes.items(): - changes.append(cp.to_json(rounded=rounded)) + changes.append(cp.to_json()) return { "time": self.time, @@ -365,9 +352,7 @@ class ChangePoints: def from_list(cls, cps: list[ChangePointGroup]): """Build from a list of ChangePointGroup objects, ordered by time.""" if not isinstance(cps, list): - raise TypeError( - f"from_list() argument must be a list. Got {type(cps)}." - ) + raise TypeError(f"from_list() argument must be a list. Got {type(cps)}.") for cpg in cps: if not isinstance(cpg, ChangePointGroup): raise TypeError( @@ -396,12 +381,12 @@ class ChangePoints: for metric, cpglist in cps.items(): for cpg in cpglist: if not isinstance(cpg, ChangePointGroup): - raise TypeError( - "from_dict() takes a dict[str, list[ChangePointGroup]]." - ) + raise TypeError("from_dict() takes a dict[str, list[ChangePointGroup]].") for cp in cpg: if cp.metric and cp.metric != metric: - raise ValueError(f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}") + raise ValueError( + f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}" + ) # store each metric's groups sorted by timestamp obj._change_points[metric] = sorted(cpglist, key=lambda cpg: cpg.time) return obj @@ -506,7 +491,9 @@ class ChangePoints: for cpg in single_metric._change_points: for metric, cp in cpg.changes.items(): if cp.metric and cp.metric != metric: - raise ValueError(f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}") + raise ValueError( + f"metric field is not internally consistent. {cp.metric} != {metric} at {cpg.time}" + ) metric_change_points.append(cp) return metric_change_points @@ -520,7 +507,7 @@ class ChangePoints: def at_commit(self, sha: str): for row in self: - if row.attributes['commit'] == sha: + if row.attributes["commit"] == sha: return row raise LookupError(sha) @@ -539,17 +526,18 @@ class ChangePoints: class ChangePointsByTime(ChangePoints): """ - Implementation of ChangePoints class where the internal structure is ordered by time/commit. + Implementation of ChangePoints class where the internal structure is ordered by time/commit. - In fact, this is the default way, and therefore all of this class' implementation is already - in its parent class ChangePoints. However, you can still create instances from this class - to make it explicit that your code at that point explicitly wanted a collection of ChangePoints - ordered by time. + In fact, this is the default way, and therefore all of this class' implementation is already + in its parent class ChangePoints. However, you can still create instances from this class + to make it explicit that your code at that point explicitly wanted a collection of ChangePoints + ordered by time. - The pivot() method will return a new object (a copy) holding the same data, but ordered by metrics - as the primary and optimized axis. The method by_metric() can be used for the same purpose. Note - that the method by_time() is a no-op and returns self, it doesn't even do a copy. + The pivot() method will return a new object (a copy) holding the same data, but ordered by metrics + as the primary and optimized axis. The method by_metric() can be used for the same purpose. Note + that the method by_time() is a no-op and returns self, it doesn't even do a copy. """ + @classmethod def from_dict(cls, cps: dict): """ @@ -563,14 +551,14 @@ class ChangePointsByTime(ChangePoints): class ChangePointsByMetric(ChangePoints): """ - Provides same interface as ChangePointsByTime, but internally stores with metric first. + Provides same interface as ChangePointsByTime, but internally stores with metric first. - You can create empty instances of this class, or you can also use the factory method - `ChangePoints.from_dict()` to get an instance of this type. + You can create empty instances of this class, or you can also use the factory method + `ChangePoints.from_dict()` to get an instance of this type. - The pivot() method will return a new object (a copy) holding the same data, but ordered by time - as the primary and optimized axis. The method by_time() can be used for the same purpose. Note - that the method by_metric() is a no-op and returns self, it doesn't even do a copy. + The pivot() method will return a new object (a copy) holding the same data, but ordered by time + as the primary and optimized axis. The method by_time() can be used for the same purpose. Note + that the method by_metric() is a no-op and returns self, it doesn't even do a copy. """ def __init__(self): @@ -620,7 +608,9 @@ class ChangePointsByMetric(ChangePoints): self._change_points[metric] = [] for metric1, cp in cpg.changes.items(): if metric1 != cp.metric: - raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}") + raise ValueError( + f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}" + ) if (not self._change_points[metric]) or cpg.time > self._change_points[metric][-1].time: self._change_points[metric].append(cpg.select_metrics(metric)) else: @@ -637,10 +627,14 @@ class ChangePointsByMetric(ChangePoints): raise TypeError(errmsg) for metric1, cp in cpg.changes.items(): if metric1 != cp.metric: - raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}") + raise ValueError( + f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}" + ) if metric1 not in self._change_points: self._change_points[metric1] = [] - if (not self._change_points[metric1]) or cpg.time > self._change_points[metric1][-1].time: + if (not self._change_points[metric1]) or cpg.time > self._change_points[metric1][ + -1 + ].time: self._change_points[metric1].append(cpg) else: raise ValueError( @@ -706,7 +700,9 @@ class ChangePointsByMetric(ChangePoints): for cpg in cpglist: for metric2, cp in cpg.changes.items(): if metric1 != metric2 or cp.metric and metric1 != cp.metric: - raise ValueError(f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}") + raise ValueError( + f"metric field is not internally consistent. {metric1} != {cp.metric} at {cpg.time}" + ) metric_change_points.append(cp) return metric_change_points @@ -730,13 +726,18 @@ class SignificanceTester(Generic[GenericStats]): def __init__(self, max_pvalue: float): self.max_pvalue = max_pvalue - def compare(self, left: Sequence[SupportsFloat], right: Sequence[SupportsFloat], p: float = None) -> GenericStats: + def compare( + self, left: Sequence[SupportsFloat], right: Sequence[SupportsFloat], p: float = None + ) -> GenericStats: if len(left) == 0 or len(right) == 0: raise ValueError return BaseStats.calculate(left, right, p) def get_sides( - self, candidate: CandidateChangePoint, series: Sequence[SupportsFloat], intervals: List[slice] + self, + candidate: CandidateChangePoint, + series: Sequence[SupportsFloat], + intervals: List[slice], ) -> (Sequence, Sequence): """ Computes properties of the change point if the Candidate Change Point based on the provided intervals. @@ -757,7 +758,9 @@ class SignificanceTester(Generic[GenericStats]): left_interval = interval right_interval = intervals[i + 1] break - elif (interval.start is None or interval.start < candidate.index) and (interval.stop is None or candidate.index < interval.stop): + elif (interval.start is None or interval.start < candidate.index) and ( + interval.stop is None or candidate.index < interval.stop + ): # Split step # Note: handles slices with omitted indexes: # diff --git a/otava/report.py b/otava/report.py index 5431b82..e46db72 100644 --- a/otava/report.py +++ b/otava/report.py @@ -103,7 +103,37 @@ class Report: def __format_json(self, test_name: str) -> str: import json - return json.dumps({test_name: [cpg.to_json(rounded=True) for cpg in self.__change_points]}) + return json.dumps( + { + test_name: [ + self.__format_change_point_group_json(cpg) for cpg in self.__change_points + ] + } + ) + + @staticmethod + def __format_change_point_group_json(cpg): + return { + "time": cpg.time, + "attributes": cpg.attributes, + "changes": [Report.__format_change_point_json(cp) for cp in cpg.changes.values()], + } + + @staticmethod + def __format_change_point_json(cp): + cp = ChangePointSerializer(cp) + return { + "metric": cp.metric, + "index": int(cp.index), + "forward_change_percent": f"{cp.forward_change_percent():.0f}", + "backward_change_percent": f"{cp.backward_change_percent():.0f}", + "magnitude": f"{cp.magnitude():-0f}", + "mean_before": f"{cp.mean_before():-0f}", + "stddev_before": f"{cp.stddev_before():-0f}", + "mean_after": f"{cp.mean_after():-0f}", + "stddev_after": f"{cp.stddev_after():-0f}", + "pvalue": f"{cp.pvalue():-0f}", + } def __format_regressions_only(self, test_name: str) -> str: output = [] diff --git a/otava/serialization.py b/otava/serialization.py new file mode 100644 index 0000000..8ed4546 --- /dev/null +++ b/otava/serialization.py @@ -0,0 +1,68 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +from datetime import datetime +from typing import Dict, List, Optional + +from pydantic import BaseModel, ConfigDict + + +class AnalysisOptionsModel(BaseModel): + window_len: int + max_pvalue: float + min_magnitude: float + orig_edivisive: bool + + +class MetricModel(BaseModel): + direction: Optional[int] = None + scale: Optional[float] = None + unit: str = "" + + +class ChangePointModel(BaseModel): + metric: Optional[str] = None + index: int + qhat: float + forward_change_percent: float + magnitude: float + mean_before: float + stddev_before: float + mean_after: float + stddev_after: float + pvalue: float + + +class ChangePointGroupModel(BaseModel): + time: float + attributes: Dict[str, str] + changes: List[ChangePointModel] + + +class AnalyzedSeriesModel(BaseModel): + model_config = ConfigDict(arbitrary_types_allowed=False) + + test_name: str + time: List[int] + change_points_timestamp: datetime + branch_name: Optional[str] = None + options: AnalysisOptionsModel + metrics: Dict[str, MetricModel] + attributes: Dict[str, List[str]] + data: Dict[str, List[Optional[float]]] + change_points: Dict[str, List[ChangePointGroupModel]] + weak_change_points: Dict[str, List[ChangePointGroupModel]] diff --git a/otava/series.py b/otava/series.py index e3d9e82..dbc6822 100644 --- a/otava/series.py +++ b/otava/series.py @@ -32,6 +32,7 @@ from otava.change_point_divisive.base import ( ChangePointsByMetric, ChangePointsByTime, ) +from otava.serialization import AnalyzedSeriesModel @dataclass @@ -371,31 +372,36 @@ class AnalyzedSeries: for metric_name in self.change_points.metrics(): change_points_json[metric_name] = [] for cp in cpbm.select_metrics(metric_name): - change_points_json[metric_name].append(cp.to_json(rounded=False)) + change_points_json[metric_name].append(cp.to_json()) weak_change_points_json = {} wcpbm = self.weak_change_points.by_metric() for metric_name in self.weak_change_points.metrics(): weak_change_points_json[metric_name] = [] for cp in wcpbm.select_metrics(metric_name): - weak_change_points_json[metric_name].append(cp.to_json(rounded=False)) + weak_change_points_json[metric_name].append(cp.to_json()) data_json = {} for metric, datapoints in self.__series.data.items(): data_json[metric] = [float(d) if d is not None else None for d in datapoints] - return { + metrics_json = {} + for metric, unit in self.__series.metrics.items(): + metrics_json[metric] = unit.to_json() + + payload = { "test_name": self.test_name(), "time": self.time(), "change_points_timestamp": self.change_points_timestamp, "branch_name": self.branch_name(), "options": self.options.to_json(), - "metrics": self.__series.metrics, + "metrics": metrics_json, "attributes": self.__series.attributes, - "data": self.__series.data, + "data": data_json, "change_points": change_points_json, "weak_change_points": weak_change_points_json, } + return AnalyzedSeriesModel.model_validate(payload).model_dump(mode="python") @classmethod def from_json(cls, analyzed_json): @@ -445,8 +451,15 @@ class AnalyzedSeries: new_metrics = {} - for metric_name, unit in analyzed_json["metrics"].items(): - new_metrics[metric_name] = Metric(None, None, unit) + for metric_name, metric_json in analyzed_json["metrics"].items(): + if isinstance(metric_json, dict): + new_metrics[metric_name] = Metric( + metric_json.get("direction"), + metric_json.get("scale"), + metric_json.get("unit", ""), + ) + else: + new_metrics[metric_name] = Metric(None, None, metric_json) new_series = Series( analyzed_json["test_name"], diff --git a/pyproject.toml b/pyproject.toml index c243321..d882968 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,6 +54,7 @@ dependencies = [ "google-cloud-bigquery>=3.38.0", "pg8000>=1.31.5", "configargparse>=1.7.1", + "pydantic>=2,<3", # For Python 3.10: last series that supports it "scipy>=1.15,<1.16; python_version < '3.11'", diff --git a/tests/change_point_classes_test.py b/tests/change_point_classes_test.py index 5c30603..5b0e780 100644 --- a/tests/change_point_classes_test.py +++ b/tests/change_point_classes_test.py @@ -48,9 +48,7 @@ def make_stats(left=(1.0, 1.0), right=(5.0, 5.0), pvalue=0.01): def make_cp(metric="m", index=3, left=(1.0, 1.0), right=(5.0, 5.0), pvalue=0.01): - return ChangePoint( - index=index, qhat=1.0, stats=make_stats(left, right, pvalue), metric=metric - ) + return ChangePoint(index=index, qhat=1.0, stats=make_stats(left, right, pvalue), metric=metric) def make_group(time, metric="m", index=3, commit="sha"): @@ -181,20 +179,27 @@ def test_changepoint_copy_is_deep(): assert cp.stats.mean_1 != -1.0 -def test_changepoint_serializer_rounded_json(): +def test_changepoint_serializer_json_is_precise(): cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02) - j = ChangePointSerializer(cp).to_json(rounded=True) + j = ChangePointSerializer(cp).to_json() assert j["metric"] == "m" assert j["index"] == 3 - assert j["forward_change_percent"] == "100" - assert all(isinstance(j[k], str) for k in ("magnitude", "mean_before", "pvalue")) + assert j["qhat"] == 1.0 + assert j["forward_change_percent"] == 100.0 + assert j["magnitude"] == 1.0 + assert j["mean_before"] == 10.0 + assert j["mean_after"] == 20.0 + assert j["pvalue"] == 0.02 -def test_changepoint_serializer_unrounded_json(): +def test_changepoint_json_is_precise(): cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02) - j = ChangePointSerializer(cp).to_json(rounded=False) + j = cp.to_json() + assert j["metric"] == "m" assert j["index"] == 3 + assert j["qhat"] == 1.0 assert j["forward_change_percent"] == 100.0 + assert j["magnitude"] == 1.0 assert j["mean_before"] == 10.0 assert j["mean_after"] == 20.0 assert j["pvalue"] == 0.02 @@ -202,7 +207,7 @@ def test_changepoint_serializer_unrounded_json(): def test_changepoint_to_json_delegates_to_serializer(): cp = make_cp(metric="m", index=3, left=(10.0, 10.0), right=(20.0, 20.0), pvalue=0.02) - assert cp.to_json(rounded=False) == ChangePointSerializer(cp).to_json(rounded=False) + assert cp.to_json() == ChangePointSerializer(cp).to_json() # ChangePointGroup @@ -251,6 +256,9 @@ def test_group_to_json(): assert j["attributes"] == {"commit": "abc"} assert isinstance(j["changes"], list) and len(j["changes"]) == 1 assert j["changes"][0]["metric"] == "m" + assert j["changes"][0]["qhat"] == 1.0 + assert j["changes"][0]["forward_change_percent"] == 400.0 + assert isinstance(j["changes"][0]["mean_before"], float) def test_group_copy_is_deep(): @@ -380,7 +388,11 @@ def test_bytime_append_out_of_order(): def test_bytime_get_change_points_for_metric_sparse(): # 'a' appears at t=1 and t=3, 'b' only at t=2 -> sparse columns c = ChangePointsByTime.from_list( - [make_group(1.0, "a", index=1), make_group(2.0, "b", index=2), make_group(3.0, "a", index=3)] + [ + make_group(1.0, "a", index=1), + make_group(2.0, "b", index=2), + make_group(3.0, "a", index=3), + ] ) a_points = c.get_change_points_for_metric("a") assert [cp.index for cp in a_points] == [1, 3] @@ -437,7 +449,9 @@ def test_from_dict_is_metric_keyed_and_returns_by_metric(): def test_bymetric_list_constructor(): - bm = ChangePointsByMetric.from_list([make_group(1.0, "a"), make_group(2.0, "a"), make_group(2.0, "b")]) + bm = ChangePointsByMetric.from_list( + [make_group(1.0, "a"), make_group(2.0, "a"), make_group(2.0, "b")] + ) # from_list() returns the class it is called on (asymmetric with from_dict) assert isinstance(bm, ChangePointsByMetric) assert bm.metrics() == {"a", "b"} diff --git a/tests/report_test.py b/tests/report_test.py index 31263b0..d3d9e6f 100644 --- a/tests/report_test.py +++ b/tests/report_test.py @@ -70,30 +70,50 @@ def test_report(series, change_points): def test_json_report(report): output = report.produce_report("test_name_from_config", ReportType.JSON) obj = json.loads(output) - expected = {'test_name_from_config': [{'attributes': {}, - 'changes': [{'forward_change_percent': '-11', - 'backward_change_percent': '12', - 'index': 4, - 'magnitude': '0.124108', - 'mean_after': '1.801429', - 'mean_before': '2.025000', - 'metric': 'series2', - 'pvalue': '0.000000', - 'stddev_after': '0.026954', - 'stddev_before': '0.011180'}], - 'time': 4}, - {'attributes': {}, - 'changes': [{'forward_change_percent': '-49', - 'backward_change_percent': '98', - 'index': 6, - 'magnitude': '0.977513', - 'mean_after': '0.504000', - 'mean_before': '0.996667', - 'metric': 'series1', - 'pvalue': '0.000000', - 'stddev_after': '0.025768', - 'stddev_before': '0.067495'}], - 'time': 6}]} + first_change = obj["test_name_from_config"][0]["changes"][0] + assert first_change["forward_change_percent"] == "-11" + assert first_change["backward_change_percent"] == "12" + assert isinstance(first_change["mean_before"], str) + expected = { + "test_name_from_config": [ + { + "attributes": {}, + "changes": [ + { + "forward_change_percent": "-11", + "backward_change_percent": "12", + "index": 4, + "magnitude": "0.124108", + "mean_after": "1.801429", + "mean_before": "2.025000", + "metric": "series2", + "pvalue": "0.000000", + "stddev_after": "0.026954", + "stddev_before": "0.011180", + } + ], + "time": 4, + }, + { + "attributes": {}, + "changes": [ + { + "forward_change_percent": "-49", + "backward_change_percent": "98", + "index": 6, + "magnitude": "0.977513", + "mean_after": "0.504000", + "mean_before": "0.996667", + "metric": "series1", + "pvalue": "0.000000", + "stddev_after": "0.025768", + "stddev_before": "0.067495", + } + ], + "time": 6, + }, + ] + } assert isinstance(obj, dict) assert obj == expected @@ -104,12 +124,20 @@ def test_regression_only_report(report): def test_simplereport_regression_only(): - s = Series('t', None, list(range(11)), - {'a': Metric(1, 1.0), 'b': Metric(1, 1.0)}, - {'a': [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55], - 'b': [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78]}, - {}) - out = Report(s, s.analyze().change_points_by_time).produce_report('t', ReportType.REGRESSIONS_ONLY) + s = Series( + "t", + None, + list(range(11)), + {"a": Metric(1, 1.0), "b": Metric(1, 1.0)}, + { + "a": [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55], + "b": [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78], + }, + {}, + ) + out = Report(s, s.analyze().change_points_by_time).produce_report( + "t", ReportType.REGRESSIONS_ONLY + ) print(out) assert "Regressions" in out assert "-11.0" in out diff --git a/tests/series_test.py b/tests/series_test.py index cab900a..9d48370 100644 --- a/tests/series_test.py +++ b/tests/series_test.py @@ -21,6 +21,7 @@ from random import random import pytest from otava.change_point_divisive.base import ChangePointSerializer +from otava.serialization import AnalyzedSeriesModel from otava.series import AnalysisOptions, AnalyzedSeries, Metric, Series @@ -268,6 +269,36 @@ def test_analyzed_series_json_round_trip(): assert restored.to_json()["weak_change_points"] == payload["weak_change_points"] +def test_analyzed_series_json_uses_pydantic_model_shape(): + series_1 = [1.02, 0.95, 0.99, 1.00, 1.12, 0.90, 0.50, 0.51, 0.48, 0.48, 0.55] + series_2 = [2.02, 2.03, 2.01, 2.04, 1.82, 1.85, 1.79, 1.81, 1.80, 1.76, 1.78] + time = list(range(len(series_1))) + series = Series( + "test", + branch=None, + time=time, + metrics={"series1": Metric(1, 1.0), "series2": Metric(1, 1.0)}, + data={"series1": series_1, "series2": series_2}, + attributes={}, + ) + + analyzed_series = series.analyze() + analyzed_series.append( + time=[len(time)], new_data={"series1": [0.5], "series2": [1.97]}, attributes={} + ) + + payload = analyzed_series.to_json() + model = AnalyzedSeriesModel.model_validate(payload) + dumped = model.model_dump(mode="python") + + change = dumped["change_points"]["series2"][0]["changes"][0] + weak_change = 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