Kraiem Taha Yassine
GitHub
parent
d573d5ad97
commit
f56ea86bd4
4 changed files with 18 additions and 151 deletions
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@ -457,9 +457,9 @@ def get_stages(stages, rows):
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drop = int(100 * (session_counts[i] - session_counts[i + 1]) / session_counts[i])
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stages_list.append(
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{"value": stage["value"],
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"type": stage["type"],
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"operator": stage["operator"],
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{"value": stage.value,
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"type": stage.type,
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"operator": stage.operator,
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"sessionsCount": session_counts[i + 1],
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"drop_pct": drop,
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"usersCount": users_counts[i + 1],
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@ -587,8 +587,8 @@ def get_top_insights(filter_d: schemas.CardSeriesFilterSchema, project_id):
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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total_drop_due_to_issues = get_issues(stages, rows,
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first_stage=filter_d.get("firstStage"),
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last_stage=filter_d.get("lastStage"),
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first_stage=1,
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last_stage=len(filter_d.events),
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drop_only=True)
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return stages_list, total_drop_due_to_issues
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@ -609,45 +609,3 @@ def get_issues_list(filter_d: schemas.CardSeriesFilterSchema, project_id, first_
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# output['critical_issues_count'] = n_critical_issues
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output = {**output, **issues_dict}
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return output
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def get_overview(filter_d, project_id, first_stage=None, last_stage=None):
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output = dict()
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stages = filter_d["events"]
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# TODO: handle 1 stage alone
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if len(stages) == 0:
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return {"stages": [],
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"criticalIssuesCount": 0}
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elif len(stages) == 1:
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# TODO: count sessions, and users for single stage
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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return output
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# The result of the multi-stage query
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rows = get_stages_and_events(filter_d=filter_d, project_id=project_id)
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if len(rows) == 0:
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# PS: not sure what to return if rows are empty
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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output['criticalIssuesCount'] = 0
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return output
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# Obtain the first part of the output
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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n_critical_issues, issues_dict, total_drop_due_to_issues = get_issues(stages, rows, first_stage=first_stage,
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last_stage=last_stage)
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output['stages'] = stages_list
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output['criticalIssuesCount'] = n_critical_issues
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return output
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@ -761,6 +761,9 @@ class SessionsSearchPayloadSchema(_TimedSchema, _PaginatedSchema):
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def merge_identical_filters(cls, values):
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i = 0
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while i < len(values):
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if values[i].is_event:
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i += 1
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continue
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j = i + 1
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while j < len(values):
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if values[i].type == values[j].type:
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@ -1024,16 +1027,6 @@ class CardSessionsSchema(_TimedSchema, _PaginatedSchema):
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v["isEvent"] = ProductAnalyticsSelectedEventType.has_value(v["type"])
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return values
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@model_validator(mode="before")
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def remove_wrong_filter_values(cls, values):
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for f in values.get("filters", []):
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vals = []
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for v in f.get("value", []):
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if v is not None:
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vals.append(v)
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f["value"] = vals
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return values
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@model_validator(mode="before")
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def __enforce_default(cls, values):
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if values.get("startTimestamp") is None:
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@ -463,9 +463,9 @@ def get_stages(stages, rows):
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drop = int(100 * (session_counts[i] - session_counts[i + 1]) / session_counts[i])
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stages_list.append(
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{"value": stage["value"],
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"type": stage["type"],
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"operator": stage["operator"],
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{"value": stage.value,
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"type": stage.type,
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"operator": stage.operator,
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"sessionsCount": session_counts[i + 1],
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"drop_pct": drop,
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"usersCount": users_counts[i + 1],
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@ -593,8 +593,8 @@ def get_top_insights(filter_d: schemas.CardSeriesFilterSchema, project_id):
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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total_drop_due_to_issues = get_issues(stages, rows,
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first_stage=filter_d.get("firstStage"),
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last_stage=filter_d.get("lastStage"),
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first_stage=1,
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last_stage=len(filter_d.events),
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drop_only=True)
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return stages_list, total_drop_due_to_issues
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@ -615,45 +615,3 @@ def get_issues_list(filter_d: schemas.CardSeriesFilterSchema, project_id, first_
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# output['critical_issues_count'] = n_critical_issues
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output = {**output, **issues_dict}
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return output
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def get_overview(filter_d, project_id, first_stage=None, last_stage=None):
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output = dict()
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stages = filter_d["events"]
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# TODO: handle 1 stage alone
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if len(stages) == 0:
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return {"stages": [],
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"criticalIssuesCount": 0}
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elif len(stages) == 1:
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# TODO: count sessions, and users for single stage
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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return output
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# The result of the multi-stage query
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rows = get_stages_and_events(filter_d=filter_d, project_id=project_id)
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if len(rows) == 0:
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# PS: not sure what to return if rows are empty
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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output['criticalIssuesCount'] = 0
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return output
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# Obtain the first part of the output
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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n_critical_issues, issues_dict, total_drop_due_to_issues = get_issues(stages, rows, first_stage=first_stage,
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last_stage=last_stage)
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output['stages'] = stages_list
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output['criticalIssuesCount'] = n_critical_issues
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return output
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@ -462,9 +462,9 @@ def get_stages(stages, rows):
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drop = int(100 * (session_counts[i] - session_counts[i + 1]) / session_counts[i])
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stages_list.append(
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{"value": stage["value"],
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"type": stage["type"],
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"operator": stage["operator"],
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{"value": stage.value,
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"type": stage.type,
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"operator": stage.operator,
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"sessionsCount": session_counts[i + 1],
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"drop_pct": drop,
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"usersCount": users_counts[i + 1],
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@ -592,8 +592,8 @@ def get_top_insights(filter_d: schemas.CardSeriesFilterSchema, project_id):
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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total_drop_due_to_issues = get_issues(stages, rows,
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first_stage=filter_d.get("firstStage"),
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last_stage=filter_d.get("lastStage"),
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first_stage=1,
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last_stage=len(filter_d.events),
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drop_only=True)
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return stages_list, total_drop_due_to_issues
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@ -614,45 +614,3 @@ def get_issues_list(filter_d: schemas.CardSeriesFilterSchema, project_id, first_
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# output['critical_issues_count'] = n_critical_issues
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output = {**output, **issues_dict}
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return output
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def get_overview(filter_d, project_id, first_stage=None, last_stage=None):
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output = dict()
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stages = filter_d["events"]
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# TODO: handle 1 stage alone
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if len(stages) == 0:
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return {"stages": [],
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"criticalIssuesCount": 0}
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elif len(stages) == 1:
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# TODO: count sessions, and users for single stage
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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return output
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# The result of the multi-stage query
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rows = get_stages_and_events(filter_d=filter_d, project_id=project_id)
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if len(rows) == 0:
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# PS: not sure what to return if rows are empty
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output["stages"] = [{
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"type": stages[0]["type"],
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"value": stages[0]["value"],
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"sessionsCount": None,
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"dropPercentage": None,
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"usersCount": None
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}]
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output['criticalIssuesCount'] = 0
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return output
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# Obtain the first part of the output
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stages_list = get_stages(stages, rows)
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# Obtain the second part of the output
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n_critical_issues, issues_dict, total_drop_due_to_issues = get_issues(stages, rows, first_stage=first_stage,
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last_stage=last_stage)
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output['stages'] = stages_list
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output['criticalIssuesCount'] = n_critical_issues
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return output
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