def _get_legacy_firefox_metric_summary()

in etl/firefox_legacy_etl.py [0:0]

• 33 lines of code
• 8 McCabe index (conditional complexity)

def _get_legacy_firefox_metric_summary(probe_data, activity_mapping):
    """
    Get a summary of legacy firefox metrics, which we can use as a search index
    """
    probe_summary = {}

    for probe_id, probe in probe_data.items():
        if probe["type"] == "event":
            # let's just skip legacy firefox events, since we're just doing
            # this for GLAM's benefit (which doesn't display events)
            continue
        if probe["history"].get("nightly"):
            most_recent_metadata = probe["history"]["nightly"][0]
        else:
            most_recent_metadata = probe["history"]["beta"][0]

        normalized_probe_name = probe["name"].lower().replace(".", "_")
        if probe_id.startswith("scalar/"):
            # scalar names are camelCased, but we want snake_case
            # to match the convention used in bigquery-etl
            # see: https://github.com/mozilla/glam/issues/1956
            normalized_probe_name = snake_case(probe_id.split("/")[1]).lower().replace(".", "_")

        probe_summary[normalized_probe_name] = {
            "name": normalized_probe_name,
            "id": probe_id,
            "type": probe["type"],
            "description": most_recent_metadata["description"],
            "bug_numbers": most_recent_metadata["bug_numbers"],
            "details": most_recent_metadata["details"],
            "optout": most_recent_metadata["optout"],
            "kind": most_recent_metadata["details"]["kind"],
            "versions": {
                channel: channel_data[0]["versions"]
                for (channel, channel_data) in probe["history"].items()
            },
            "active": normalized_probe_name in activity_mapping,
            "seen_in_processes": activity_mapping.get(normalized_probe_name, []),
        }

        if most_recent_metadata["details"].get("labels") is not None:
            probe_summary[normalized_probe_name]["labels"] = most_recent_metadata["details"][
                "labels"
            ]

    return probe_summary