add http caching for OTHER metadata endpoint

[melange396]

caching for the one metadata endpoint was done in

• http caching for metadata #1222

the other metadata endpoint is used by the covidcast dashboard webapp, so it is quite important to protect it from repeated re-requests which could trigger rate limiting. The code for that endpoint is found here:

delphi-epidata/src/server/endpoints/covidcast.py

Lines 391 to 479 in ea84e37

	@bp.route("/meta", methods=("GET", "POST"))
	def handle_meta():
	"""
	similar to /covidcast_meta but in a structured optimized JSON form for the app
	"""
	filter_signal = parse_source_signal_arg("signal")
	flags = ",".join(request.values.getlist("flags")).split(",")
	filter_smoothed: Optional[bool] = None
	filter_weighted: Optional[bool] = None
	filter_cumulative: Optional[bool] = None
	filter_active: Optional[bool] = None
	filter_time_type: Optional[TimeType] = None
	if "smoothed" in flags:
	filter_smoothed = True
	elif "not_smoothed" in flags:
	filter_smoothed = False
	if "weighted" in flags:
	filter_weighted = True
	elif "not_weighted" in flags:
	filter_weighted = False
	if "cumulative" in flags:
	filter_cumulative = True
	elif "not_cumulative" in flags:
	filter_cumulative = False
	if "active" in flags:
	filter_active = True
	elif "inactive" in flags:
	filter_active = False
	if "day" in flags:
	filter_active = TimeType.day
	elif "week" in flags:
	filter_active = TimeType.week
	row = db.execute(text("SELECT epidata FROM covidcast_meta_cache LIMIT 1")).fetchone()
	data = loads(row["epidata"]) if row and row["epidata"] else []
	by_signal: Dict[Tuple[str, str], List[Dict[str, Any]]] = {}
	for row in data:
	entry = by_signal.setdefault((row["data_source"], row["signal"]), [])
	entry.append(row)
	user = current_user
	sources: List[Dict[str, Any]] = []
	for source in data_sources:
	src = source.db_source
	if src in sources_protected_by_roles:
	role = sources_protected_by_roles[src]
	if not (user and user.has_role(role)):
	# if this is a protected source
	# and the user doesnt have the allowed role
	# (or if we have no user)
	# then skip this source
	continue
	meta_signals: List[Dict[str, Any]] = []
	for signal in source.signals:
	if filter_active is not None and signal.active != filter_active:
	continue
	if filter_signal and all((not s.matches(signal.source, signal.signal) for s in filter_signal)):
	continue
	if filter_smoothed is not None and signal.is_smoothed != filter_smoothed:
	continue
	if filter_weighted is not None and signal.is_weighted != filter_weighted:
	continue
	if filter_cumulative is not None and signal.is_cumulative != filter_cumulative:
	continue
	if filter_time_type is not None and signal.time_type != filter_time_type:
	continue
	meta_data = by_signal.get((source.db_source, signal.signal))
	if not meta_data:
	continue
	row = meta_data[0]
	entry = CovidcastMetaEntry(signal, row["min_time"], row["max_time"], row["max_issue"])
	for row in meta_data:
	entry.intergrate(row)
	meta_signals.append(entry.asdict())
	if not meta_signals: # none found or no signals
	continue
	s = source.asdict()
	s["signals"] = meta_signals
	sources.append(s)
	return jsonify(sources)

[melange396]

We should do this for the /covidcast/anomalies endpoint too, since its used by the covidcast dashboard webapp and not exempt from rate limiting, it basically never changes, and it looks like it might be kinda expensive (pulls from gdocs, parses that as a csv, then does some pandas manipulations) :

delphi-epidata/src/server/endpoints/covidcast.py

Lines 546 to 556 in 921d0d4

	@bp.route("/anomalies", methods=("GET", "POST"))
	def handle_anomalies():
	"""
	proxy to the excel sheet about data anomalies
	"""
	df = read_csv(
	"https://docs.google.com/spreadsheets/d/e/2PACX-1vToGcf9x5PNJg-eSrxadoR5b-LM2Cqs9UML97587OGrIX0LiQDcU1HL-L2AA8o5avbU7yod106ih0_n/pub?gid=0&single=true&output=csv", skip_blank_lines=True
	)
	df = df[df["source"].notnull() & df["published"]]
	return print_pandas(df)

other ~static-ish resources could benefit from this too, but im not sure what they might be off the top of my head.