#!/usr/bin/env python3

import os
import sys
from pathlib import Path
from ruamel import yaml

# Converts a set of metric docs in the integrations repo to the metadata.yaml
# format that are picked up by the selfdescribe module to generate agent
# documentation.

# E.g. to sync collectd-kafka run:
# INTEGRATIONS_REPO=~/work/integrations ./metric-doc-to-agent collectd-kafka internal/monitors/collectd/kafka

SCRIPT_DIR = Path(__file__).parent.resolve()

INTEGRATION = sys.argv[1]
METADATA_DIR = Path(sys.argv[2]).resolve()

INTEGRATIONS_REPO = Path(os.environ.get("INTEGRATIONS_REPO", SCRIPT_DIR / "../../../integrations"))

if not INTEGRATIONS_REPO.is_dir():
    print("Please set INTEGRATIONS_REPO to the local path to the SignalFx integrations repo", file=sys.stderr)
    sys.exit(1)

metadata_path = METADATA_DIR / "metadata.yaml"
metadata = yaml.round_trip_load(metadata_path.read_bytes())
if len(metadata) != 1:
    print("This script not meant for metadata.yaml with more than one monitor", file=sys.stderr)
    sys.exit(2)

metrics = metadata["monitors"][0]["metrics"]

for f in (INTEGRATIONS_REPO / INTEGRATION).glob("docs/*.md"):
    if f.name == "readme.md":
        continue

    metric_name = f.with_suffix("").name

    if metric_name not in metrics:
        metrics[metric_name] = {}

    content = f.read_text()

    meta = yaml.safe_load("\n".join(content.splitlines()[:4]))

    typ = meta.get("metric_type")
    if "cumulative" in typ.lower():
        typ = "cumulative"

    metrics[metric_name]["type"] = typ

    desc = "\n".join(content.splitlines()[6:]).strip().lstrip("> ")
    metrics[metric_name]["description"] = yaml.scalarstring.LiteralScalarString(desc)
    metrics[metric_name].setdefault("default", False)

metadata_path.write_text(yaml.round_trip_dump(metadata))