"""
DC/MD/VA Unemployment — Static HTML Report Generator
Run: python3 generate_report.py
Output: dc_md_va_unemployment_report.html (open in any browser)
"""
import requests
import json
import os
from datetime import datetime
from config import BLS_API_KEY, BLS_API_BASE
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
# ---------------------------------------------------------------------------
# Series config (same as dashboard script)
# ---------------------------------------------------------------------------
GEOS = ["DC", "MD", "VA", "DCMSA"]
LABELS = {
"DC": "District of Columbia",
"MD": "Maryland",
"VA": "Virginia",
"DCMSA": "DC Metro MSA",
}
COLORS = {
"DC": "#c0392b",
"MD": "#2471a3",
"VA": "#1e8449",
"DCMSA": "#7d3c98",
}
SERIES = {
"DC_rate": "LAUST110000000000003",
"DC_unemployed": "LAUST110000000000004",
"DC_employed": "LAUST110000000000005",
"DC_laborforce": "LAUST110000000000006",
"MD_rate": "LAUST240000000000003",
"MD_unemployed": "LAUST240000000000004",
"MD_employed": "LAUST240000000000005",
"MD_laborforce": "LAUST240000000000006",
"VA_rate": "LAUST510000000000003",
"VA_unemployed": "LAUST510000000000004",
"VA_employed": "LAUST510000000000005",
"VA_laborforce": "LAUST510000000000006",
"DCMSA_rate": "LAUMT114790000000003",
"DCMSA_unemployed":"LAUMT114790000000004",
"DCMSA_employed": "LAUMT114790000000005",
"DCMSA_laborforce":"LAUMT114790000000006",
}
# ---------------------------------------------------------------------------
# Data fetching
# ---------------------------------------------------------------------------
def fetch(series_ids, start_year, end_year):
payload = {
"seriesid": series_ids,
"startyear": str(start_year),
"endyear": str(end_year),
"registrationkey": BLS_API_KEY,
"catalog": True,
"calculations": True,
"annualaverage": False,
}
r = requests.post(f"{BLS_API_BASE}/timeseries/data/", json=payload, timeout=30)
r.raise_for_status()
body = r.json()
if body["status"] != "REQUEST_SUCCEEDED":
raise RuntimeError(f"BLS API error: {body['message']}")
return {s["seriesID"]: s["data"] for s in body["Results"]["series"]}
def latest(data):
for obs in data:
if obs["value"] != "-":
return obs
return {}
def chg(obs, window):
try:
return obs["calculations"]["net_changes"].get(window)
except (KeyError, TypeError):
return None
def pct_chg(obs, window):
try:
return obs["calculations"]["pct_changes"].get(window)
except (KeyError, TypeError):
return None
# ---------------------------------------------------------------------------
# Prepare chart data — chronological, last 24 months, no gaps
# ---------------------------------------------------------------------------
MONTH_ORDER = {f"M{i:02d}": i for i in range(1, 13)}
MONTH_NAMES = ["", "Jan", "Feb", "Mar", "Apr", "May", "Jun",
"Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
def sort_obs(data):
"""Return observations sorted chronologically, monthly only, no nulls."""
monthly = [o for o in data if o["period"].startswith("M") and o["value"] != "-"]
return sorted(monthly, key=lambda o: (o["year"], MONTH_ORDER.get(o["period"], 0)))
def build_rate_chart_data(results, months=24):
"""Return labels list and per-geo value lists for the rate trend chart."""
# Build a merged label set from all four geos
all_labels = {}
for geo in GEOS:
sid = SERIES[f"{geo}_rate"]
for obs in sort_obs(results.get(sid, [])):
key = (obs["year"], obs["period"])
m = MONTH_ORDER.get(obs["period"], 0)
label = f"{MONTH_NAMES[m]} {obs['year']}"
all_labels[key] = label
sorted_keys = sorted(all_labels.keys())[-months:]
labels = [all_labels[k] for k in sorted_keys]
datasets = []
for geo in GEOS:
sid = SERIES[f"{geo}_rate"]
obs_by_key = {
(o["year"], o["period"]): float(o["value"])
for o in sort_obs(results.get(sid, []))
}
values = [obs_by_key.get(k) for k in sorted_keys]
datasets.append({
"label": LABELS[geo],
"data": values,
"borderColor": COLORS[geo],
"backgroundColor": COLORS[geo] + "22",
"borderWidth": 2,
"pointRadius": 2,
"tension": 0.3,
"fill": False,
})
return labels, datasets
# ---------------------------------------------------------------------------
# HTML helpers
# ---------------------------------------------------------------------------
def arrow(val):
if val is None:
return '—'
try:
n = float(val)
if n > 0:
return f'▲ {n:+.1f}'
if n < 0:
return f'▼ {n:.1f}'
return f'— {n:.1f}'
except (ValueError, TypeError):
return '—'
def fmt_rate(val):
try:
return f"{float(val):.1f}%"
except (ValueError, TypeError):
return "—"
def fmt_num(val):
try:
return f"{float(val):,.0f}"
except (ValueError, TypeError):
return "—"
def build_cards(results):
cards_html = []
for geo in GEOS:
sid = SERIES[f"{geo}_rate"]
obs = latest(results.get(sid, []))
rate = fmt_rate(obs.get("value"))
mom = arrow(chg(obs, "1"))
yoy = arrow(chg(obs, "12"))
period = f"{obs.get('periodName', '')} {obs.get('year', '')}"
color = COLORS[geo]
cards_html.append(f"""
{LABELS[geo]}
{rate}
{period}
MoM {mom} pp
YoY {yoy} pp
""")
return "\n".join(cards_html)
def build_summary_table(results):
measures = [
("rate", "Unemp Rate", True),
("unemployed", "Unemployed", False),
("employed", "Employed", False),
("laborforce", "Labor Force", False),
]
rows = []
for measure, label, is_rate in measures:
row = f"| {label} | "
for geo in GEOS:
sid = SERIES[f"{geo}_{measure}"]
obs = latest(results.get(sid, []))
val = fmt_rate(obs.get("value")) if is_rate else fmt_num(obs.get("value"))
mom = chg(obs, "1")
yoy = chg(obs, "12")
suffix = "pp" if is_rate else ""
mom_html = arrow(mom)
yoy_html = arrow(yoy)
row += f"""
{val}
MoM {mom_html}{' ' + suffix if suffix else ''}
YoY {yoy_html}{' ' + suffix if suffix else ''}
| """
row += "
"
rows.append(row)
geo_headers = "".join(f'{LABELS[g]} | ' for g in GEOS)
return f"""
| Measure | {geo_headers}
|---|
{"".join(rows)}
"""
# ---------------------------------------------------------------------------
# Main HTML template
# ---------------------------------------------------------------------------
HTML_TEMPLATE = """
DC / MD / VA Unemployment Report — {report_date}
{cards}
Unemployment Rate Trend — Last 24 Months
▲ Red = rate rising (more unemployment). ▼ Green = rate falling.
Current Month Summary
{summary_table}
MoM = month-over-month net change | YoY = year-over-year net change | pp = percentage points
"""
# ---------------------------------------------------------------------------
# Entry point
# ---------------------------------------------------------------------------
def main():
current_year = datetime.now().year
start_year = current_year - 2 # 3 years covers 24+ months for the chart
print(f"Fetching {len(SERIES)} LAUS series ({start_year}–{current_year})...")
results = fetch(list(SERIES.values()), start_year, current_year)
report_date = datetime.now().strftime("%B %d, %Y")
chartjs_path = os.path.join(SCRIPT_DIR, "chart.umd.min.js")
with open(chartjs_path) as f:
chartjs = f.read()
labels, datasets = build_rate_chart_data(results, months=24)
rate_chart_json = json.dumps({"labels": labels, "datasets": datasets})
html = HTML_TEMPLATE.format(
report_date=report_date,
cards=build_cards(results),
summary_table=build_summary_table(results),
rate_chart_json=rate_chart_json,
chartjs=chartjs,
)
out = "dc_md_va_unemployment_report.html"
with open(out, "w") as f:
f.write(html)
print(f"Report written → {out}")
if __name__ == "__main__":
main()