Add saved analysis workspace and live dashboard statistics
This commit is contained in:
Peter Stockings
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"""Presentation and matched-cohort baseline clauses for the analysis language."""
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import ast
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import json
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import re
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from .stats_dsl import QueryError
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CHARTS = {"auto", "line", "bar", "area", "histogram", "box", "heatmap", "stacked", "none"}
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def summary_parts(source):
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parts, start, quoted, escaped = [], 0, False, False
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for index, char in enumerate(source):
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if escaped:
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escaped = False
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elif char == "\\" and quoted:
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escaped = True
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elif char == '"':
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quoted = not quoted
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elif char == "," and not quoted:
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parts.append(source[start:index])
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start = index + 1
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parts.append(source[start:])
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return parts
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def extract(text):
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options = {
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"display": "separate",
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"baseline": None,
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"flag": None,
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"color": None,
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"size": None,
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"labels": {},
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"reference": None,
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"source": "runs",
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"cohorts": [],
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"comparison": "period",
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}
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seen, lines = set(), text.splitlines()
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def once(key, line):
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if key in seen:
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raise QueryError(f"Repeated {key} clause.", line)
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seen.add(key)
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for index, source in enumerate(lines):
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line, number = source.strip(), index + 1
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if line in {"runs", "laps", "segments"}:
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once("source", number)
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options["source"] = line
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lines[index] = "runs"
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continue
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elif line == "compare previous year":
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options["comparison"] = "year"
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lines[index] = "compare previous period"
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continue
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elif match := re.fullmatch(r'cohort ("(?:[^"\\]|\\.)*") where (.+)', line):
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name = json.loads(match[1])
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if (
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not 1 <= len(name) <= 60
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or len(options["cohorts"]) >= 4
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or name in {c["name"] for c in options["cohorts"]}
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):
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raise QueryError(
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"Choose up to four different cohort names of 1–60 characters.", number
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)
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options["cohorts"].append({"name": name, "source": match[2]})
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elif match := re.fullmatch(r"display (overlay|separate)", line):
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once("display", number)
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options["display"] = match[1]
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elif match := re.fullmatch(r"baseline previous (\d+) days", line):
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once("baseline", number)
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days = int(match[1])
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if not 7 <= days <= 732:
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raise QueryError("Use a baseline of 7–732 days.", number)
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options["baseline"] = days
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elif match := re.fullmatch(
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r"flag (above|below|outside) baseline (\S+) sd min (\d+) runs sustained (\d+) buckets",
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line,
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):
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once("flag", number)
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try:
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sd = float(match[2])
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minimum, sustained = int(match[3]), int(match[4])
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if not 0.5 <= sd <= 5 or not 2 <= minimum <= 1000 or not 1 <= sustained <= 12:
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raise ValueError
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except ValueError:
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raise QueryError(
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"Use 0.5–5 sd, 2–1,000 runs and 1–12 consecutive buckets.", number
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) from None
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options["flag"] = {
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"direction": match[1],
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"sd": sd,
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"minimum": minimum,
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"sustained": sustained,
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}
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elif match := re.fullmatch(r"(color|size) by (\w+)", line):
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once(match[1], number)
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options[match[1]] = match[2]
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elif match := re.fullmatch(r"reference (\w+) = (\S+) (\S+)", line):
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once("reference", number)
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options["reference"] = {"field": match[1], "raw": match[2], "unit": match[3]}
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elif line.startswith("summarize "):
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parts = []
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for part in summary_parts(line[10:]):
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if match := re.fullmatch(r'\s*(.+?)\s+as\s+("(?:[^"\\]|\\.)*")\s*', part):
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key, encoded_label = match.groups()
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key = re.sub(r"\s+", "", key)
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try:
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label = json.loads(encoded_label)
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if not 1 <= len(label.strip()) <= 80:
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raise ValueError
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except ValueError:
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raise QueryError(
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"Use a summary label of 1–80 characters in double quotes.", number
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) from None
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if key in options["labels"]:
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raise QueryError("Choose different summary expressions.", number)
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options["labels"][key] = label
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part = key
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parts.append(part.strip())
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lines[index] = "summarize " + ", ".join(parts)
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continue
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elif match := re.fullmatch(r"chart (\w+)", line):
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if match[1] not in CHARTS:
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raise QueryError(
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"Choose auto, line, bar, area, histogram, box, heatmap, stacked or none.",
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number,
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)
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once("chart", number)
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options["chart"] = match[1]
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else:
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continue
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lines[index] = ""
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return "\n".join(lines), options
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def validate(q, catalog):
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if q["plot"] and q["chart"] == "none":
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raise QueryError("A scatter plot conflicts with chart none.")
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if q["cohorts"] and (
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q["chart"] != "stacked"
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or q["secondary"] != "none"
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or q["extra_metrics"]
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or q["trend"]
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or q["baseline"]
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):
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raise QueryError(
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"Cohorts require chart stacked, one summary metric and no trend or baseline."
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)
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if q["chart"] == "stacked" and not q["cohorts"]:
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raise QueryError('Add named cohorts, e.g. cohort "Easy" where heart_rate <= 145 bpm.')
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if q["cohorts"]:
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key = q["metric"]
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aggregate = q["aggregates"].get(key, {})
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if aggregate.get("function") not in {"sum", "count"} and key not in {
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"distance",
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"duration",
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"elevation",
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"count",
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"calories",
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}:
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raise QueryError(
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"Stack additive metrics: sum, count, distance, duration, elevation or calories."
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)
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if q["compare"]:
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raise QueryError("Stacked cohorts show the current period; use compare none.")
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if q["source"] != "runs":
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temporal = {
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"gap_since_previous_run",
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"distance_change",
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"pace_change",
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"heart_rate_change",
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"rolling_7d_distance",
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"rolling_28d_distance",
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"rolling_7d_count",
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"rolling_28d_count",
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"run_day_streak",
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}
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fields = {
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q["metric"],
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q["secondary"],
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*q["extra_metrics"],
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q["sort"][0],
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q["color"],
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q["size"],
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*(q["plot"] or []),
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}
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fields.update(spec["field"] for spec in q["aggregates"].values())
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for conditions in [
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q["filters"],
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*q["filter_groups"],
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*(cohort["conditions"] for cohort in q["cohorts"]),
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]:
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fields.update(condition["field"] for condition in conditions)
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if q["bin"]:
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fields.add(q["bin"]["field"])
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for spec in q["derived"]:
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if "window" not in spec:
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fields.update(
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node.id
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for node in ast.walk(ast.parse(spec["expression"], mode="eval"))
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if isinstance(node, ast.Name)
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)
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if fields & temporal or any("window" in spec for spec in q["derived"]):
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raise QueryError(
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"Run-history metrics and rolling calculations require the runs source."
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)
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for key in ("color", "size"):
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if q[key] and (not q["plot"] or q[key] not in catalog):
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raise QueryError(f"{key} by requires a scatter plot and a numeric metric.")
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if q["flag"] and not q["baseline"]:
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raise QueryError("Add baseline previous N days before defining a flag.")
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if q["flag"] and (q["having"] or q["rank"] or q["limit"]):
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raise QueryError(
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"Persistent flags need every calendar bucket; remove having, rank and limit."
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)
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if q["baseline"] and (
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q["all_time"] or q["group"] not in {"day", "week", "month", "year"} or q["trend"]
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):
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raise QueryError(
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"Baselines need a bounded time period, calendar grouping and no trend transform."
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)
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if q["baseline"]:
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additive = {"count", "distance", "duration", "elevation", "calories"}
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selected = [
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q["metric"],
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*([] if q["secondary"] == "none" else [q["secondary"]]),
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*q["extra_metrics"],
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]
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supported = lambda key: (
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q["aggregates"][key]["function"] not in {"sum", "count", "stddev"}
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if key in q["aggregates"]
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else key not in additive
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)
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if not any(supported(key) for key in selected):
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raise QueryError("Baselines require a mean, median, percentile or non-additive metric.")
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if q["chart"] == "heatmap" and q["group"] != "day":
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raise QueryError("Calendar heatmaps require by day.")
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if q["chart"] == "heatmap" and (q["having"] or q["rank"] or q["limit"]):
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raise QueryError("Calendar heatmaps need every day; remove having, rank and limit.")
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if q["chart"] in {"box", "histogram"} and q["trend"]:
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raise QueryError("Distribution charts show per-run inputs; remove the trend transform.")
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if q["chart"] in {"box", "histogram", "heatmap"} and q["display"] == "overlay":
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raise QueryError("Use display separate for distributions and calendar heatmaps.")
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