Vendored wheels and FRED snapshot

.gitignore

@@ -1,11 +1,9 @@
-# Python ###
+# Byte-code / venv
 __pycache__/
-*.py[cod]
-*$py.class
-
-# Virtualenv ###
 venv/
 
-# Data & outputs ###
+# Local data & wheels
-data/
+wheelhouse/*.log
-outputs/
+wheelhouse/*.md
+# keep wheel files themselves!
+data/*.bak

repo-context.txt

@@ -143,7 +143,7 @@ This project is released under the MIT License.
 ## python_charts/requirements.txt
 ```
 pandas>=1.5.0
-pandas\_datareader>=0.10.0
+pandas_datareader>=0.10.0    # good
 matplotlib>=3.5.0
 lxml>=4.6.0
 python-dateutil>=2.8.1

requirements.txt

@@ -1,5 +1,5 @@
 pandas>=1.5.0
-pandas_datareader>=0.10.0    # good
+pandas_datareader>=0.10.0
 matplotlib>=3.5.0
 lxml>=4.6.0
 python-dateutil>=2.8.1

scripts/lagged_oil_unrate_chart_styled.py

@@ -2,119 +2,202 @@
 """
 lagged_oil_unrate_chart_styled.py
 ---------------------------------
-Fetch and plot UNRATE vs. WTI oil price with a configurable lag,
+Offline version: reads UNRATE & WTI series from data/fred.db (populated
-date range, and polished dual-axis styling.
+by scripts/refresh_data.py) and plots them with a configurable lag.
 
-Usage:
+Usage
-    python lagged_oil_unrate_chart_styled.py \
+-----
-        --offset 18 \
+  python scripts/lagged_oil_unrate_chart_styled.py \
-        --start 1973-01-01 \
+      --offset 18 \
-        --end 2025-05-31 \
+      --start 1973-01-01 \
-        --extend-years 3
+      --end   2025-05-31 \
-
+      --extend-years 3
-Dependencies:
-    pip install pandas pandas_datareader matplotlib python-dateutil
 """
+
+from __future__ import annotations
+
 import argparse
 from datetime import datetime
-from dateutil.relativedelta import relativedelta
+from pathlib import Path
 
 import matplotlib.dates as mdates
 import matplotlib.pyplot as plt
 import pandas as pd
-import pandas_datareader.data as web
+from dateutil.relativedelta import relativedelta
+import sqlite3
 
 
-def fetch_series(start, end):
+# ──────────────────────────────────────────────────────────────────────────
-    # FRED series
+# Data helpers
-    unrate = web.DataReader("UNRATE", "fred", start, end)
+# ──────────────────────────────────────────────────────────────────────────
-    oil   = web.DataReader("DCOILWTICO", "fred", start, end)
+def fetch_series(
+    start: datetime,
+    end: datetime,
+    db_path: str | Path = Path("data/fred.db"),
+) -> tuple[pd.DataFrame, pd.DataFrame]:
+    """
+    Load UNRATE and DCOILWTICO from a local SQLite DB, then:
+
+    * convert UNRATE to month-end timestamps
+    * average WTI daily prices to month-end
+    """
+    db_path = Path(db_path)
+    if not db_path.exists():
+        raise FileNotFoundError(
+            f"{db_path} not found.  Run scripts/refresh_data.py on a "
+            "machine with internet, commit the new DB, then retry."
+        )
+
+    with sqlite3.connect(db_path) as conn:
+        unrate = (
+            pd.read_sql(
+                "SELECT date, UNRATE AS value FROM UNRATE", conn,
+                parse_dates=["date"], index_col="date"
+            )
+            .loc[start:end]
+        )
+        oil = (
+            pd.read_sql(
+                "SELECT date, DCOILWTICO AS value FROM DCOILWTICO", conn,
+                parse_dates=["date"], index_col="date"
+            )
+            .loc[start:end]
+        )
 
     # Resample WTI to month-end average
     oil_monthly = oil.resample("M").mean()
-    # Ensure UNRATE is at month-end timestamps, too
+    # Ensure UNRATE is at month-end, too
     unrate.index = unrate.index.to_period("M").to_timestamp("M")
     return unrate, oil_monthly
 
 
+# ──────────────────────────────────────────────────────────────────────────
+# Plotting
+# ──────────────────────────────────────────────────────────────────────────
 def plot_lagged(
     unrate: pd.DataFrame,
     oil: pd.DataFrame,
     offset_months: int,
     start_date: datetime,
     end_date: datetime,
-    extend_years: int
+    extend_years: int,
-):
+) -> None:
-    # Shift oil by offset: positive = lag; negative = lead
+    """Render the dual-axis chart."""
     oil_shifted = oil.shift(offset_months)
 
-    # Build figure
     fig, ax1 = plt.subplots(figsize=(14, 7))
     plt.title("Unemployment Rate and US Oil Price", fontsize=20, weight="bold")
     plt.suptitle(
         "Civilian Unemployment Rate and WTI Crude Oil Price",
         fontsize=14,
-        y=0.93
+        y=0.93,
     )
 
-    # Plot UNRATE on left axis
+    # Left axis – UNRATE
-    ax1.plot(unrate.index, unrate["UNRATE"], 
+    ax1.plot(
-             label="UNRATE (LHS)", linewidth=2.5, color="#1f77b4")
+        unrate.index,
+        unrate["value"],
+        label="UNRATE (LHS)",
+        linewidth=2.5,
+        color="#1f77b4",
+    )
     ax1.set_ylabel("Unemployment rate (%)", fontsize=12)
-    ax1.set_ylim(0, unrate["UNRATE"].max() * 1.1)
+    ax1.set_ylim(0, unrate["value"].max() * 1.1)
     ax1.yaxis.set_major_formatter("{x:.0f}%")
     ax1.grid(axis="y", linestyle="--", alpha=0.4)
 
-    # Plot shifted oil on right axis
+    # Right axis – shifted oil
     ax2 = ax1.twinx()
-    ax2.plot(oil_shifted.index, oil_shifted["DCOILWTICO"],
+    ax2.plot(
-             label="USOIL (RHS)", linewidth=2, linestyle="-", alpha=0.8, color="#FF9900")
+        oil_shifted.index,
+        oil_shifted["value"],
+        label="USOIL (RHS)",
+        linewidth=2,
+        linestyle="-",
+        alpha=0.8,
+        color="#FF9900",
+    )
     ax2.set_ylabel("Oil price (USD)", fontsize=12)
-    ax2.set_ylim(0, oil_shifted["DCOILWTICO"].max() * 1.1)
+    ax2.set_ylim(0, oil_shifted["value"].max() * 1.1)
     ax2.yaxis.set_major_formatter("${x:,.0f}")
 
-    # X-axis formatting
+    # X-axis
     ax1.set_xlim(start_date, end_date + relativedelta(years=extend_years))
     ax1.xaxis.set_major_locator(mdates.YearLocator(base=5))
     ax1.xaxis.set_minor_locator(mdates.YearLocator(1))
     ax1.xaxis.set_major_formatter(mdates.DateFormatter("%Y"))
     plt.setp(ax1.get_xticklabels(), rotation=0, fontsize=11)
 
-    # Combine legends
+    # Legends
     lines, labels = ax1.get_legend_handles_labels()
     l2, l2l = ax2.get_legend_handles_labels()
     ax1.legend(lines + l2, labels + l2l, loc="upper left", frameon=False, fontsize=12)
 
-    # Footnotes
+    # Footnote
     foot = (
-        f"Dates: {start_date.strftime('%Y')} through {unrate.index[-1].strftime('%d %b %Y')}.\n"
+        f"Dates: {start_date.strftime('%Y')} through "
-        "Source: FRED, pandas_datareader."
+        f"{unrate.index[-1].strftime('%d %b %Y')}.\n"
+        "Source: Local FRED snapshot (offline)."
     )
     plt.annotate(
         foot,
-        (0,0), (0, -40), 
+        (0, 0),
-        xycoords="axes fraction", textcoords="offset points",
+        (0, -40),
-        va="top", fontsize=10, color="gray"
+        xycoords="axes fraction",
+        textcoords="offset points",
+        va="top",
+        fontsize=10,
+        color="gray",
     )
 
     fig.tight_layout(rect=[0, 0.03, 1, 0.95])
     plt.show()
 
 
-if __name__ == "__main__":
+# ──────────────────────────────────────────────────────────────────────────
+# CLI
+# ──────────────────────────────────────────────────────────────────────────
+def main() -> None:
     p = argparse.ArgumentParser()
-    p.add_argument("-o", "--offset", type=int, default=18,
+    p.add_argument(
-                   help="lag in months (positive=lag, negative=lead)")
+        "-o",
-    p.add_argument("--start", type=str, default="1973-01-01",
+        "--offset",
-                   help="series start date (YYYY-MM-DD)")
+        type=int,
-    p.add_argument("--end", type=str, default=datetime.today().strftime("%Y-%m-%d"),
+        default=18,
-                   help="series end date (YYYY-MM-DD)")
+        help="lag in months (positive=lag, negative=lead)",
-    p.add_argument("--extend-years", type=int, default=3,
+    )
-                   help="how many years beyond end_date to show on the x-axis")
+    p.add_argument(
+        "--start",
+        type=str,
+        default="1973-01-01",
+        help="series start date (YYYY-MM-DD)",
+    )
+    p.add_argument(
+        "--end",
+        type=str,
+        default=datetime.today().strftime("%Y-%m-%d"),
+        help="series end date (YYYY-MM-DD)",
+    )
+    p.add_argument(
+        "--extend-years",
+        type=int,
+        default=3,
+        help="how many years beyond end_date to show on the x-axis",
+    )
+    p.add_argument(
+        "--db",
+        type=str,
+        default="data/fred.db",
+        help="path to local FRED SQLite file",
+    )
     args = p.parse_args()
 
     start_dt = datetime.fromisoformat(args.start)
-    end_dt   = datetime.fromisoformat(args.end)
+    end_dt = datetime.fromisoformat(args.end)
 
-    unrate, oil = fetch_series(start_dt, end_dt)
+    unrate, oil = fetch_series(start_dt, end_dt, args.db)
     plot_lagged(unrate, oil, args.offset, start_dt, end_dt, args.extend_years)
+
+
+if __name__ == "__main__":
+    main()