Create app.py

app.py

@@ -0,0 +1,217 @@
+# app.py
+import os, io, json
+from datetime import datetime, timezone
+from dateutil import tz
+import pandas as pd
+import gradio as gr
+
+from huggingface_hub import (
+    HfApi,
+    HfFolder,
+    hf_hub_download,  # anonymous reads for public datasets
+)
+
+# --------------------
+# Config
+# --------------------
+DATA_REPO = os.environ.get("DATA_REPO", "jeffrey1963/Farm_Sim_Data")
+DATA_REPO_TYPE = "dataset"  # don't change
+
+# --------------------
+# HF helpers
+# --------------------
+def _api_readonly() -> HfApi:
+    """OK without token for public dataset reads."""
+    tok = HfFolder.get_token()
+    return HfApi(token=tok) if tok else HfApi()
+
+def _api_rw() -> HfApi:
+    """Require token for uploads."""
+    tok = HfFolder.get_token()
+    if not tok:
+        raise RuntimeError("Missing HF_TOKEN (add a Space secret named HF_TOKEN).")
+    return HfApi(token=tok)
+
+def _candidate_purchase_paths(student_id: str) -> list[str]:
+    """
+    Return all jsonl paths for this student.
+    Supports both:
+      - purchases/{id}.jsonl
+      - purchases/{id}-TIMESTAMP.jsonl  (your current store behavior)
+    """
+    api = _api_readonly()
+    try:
+        files = api.list_repo_files(repo_id=DATA_REPO, repo_type=DATA_REPO_TYPE)
+    except Exception:
+        return []
+    prefix = f"purchases/{student_id}"
+    out = []
+    for f in files:
+        if not f.startswith("purchases/") or not f.endswith(".jsonl"):
+            continue
+        if f == f"{prefix}.jsonl" or f.startswith(prefix + "-"):
+            out.append(f)
+    return sorted(out)  # oldest first
+
+def _download_to_local(path_in_repo: str) -> str | None:
+    try:
+        return hf_hub_download(
+            repo_id=DATA_REPO,
+            repo_type=DATA_REPO_TYPE,
+            filename=path_in_repo,
+        )
+    except Exception:
+        return None
+
+# --------------------
+# Core
+# --------------------
+def fetch_student_assets(student_id: str):
+    """Return list of assets purchased by this student (aggregate all files)."""
+    sid = (student_id or "").strip()
+    if not sid:
+        return []
+
+    paths = _candidate_purchase_paths(sid)
+    if not paths:
+        return []
+
+    rows = []
+    for p in paths:
+        local = _download_to_local(p)
+        if not local:
+            continue
+        with open(local, "r", encoding="utf-8") as f:
+            for line in f:
+                s = line.strip()
+                if not s:
+                    continue
+                try:
+                    rows.append(json.loads(s))
+                except Exception:
+                    pass
+
+    assets = []
+    for r in rows:
+        try:
+            ts = int(r["ts"])
+            dt = datetime.fromtimestamp(ts, tz=timezone.utc).astimezone(tz.tzlocal())
+            asset_id = f'{r.get("catalog_id","unknown")}-{ts}'
+            snap = r.get("snapshot", {}) or {}
+            assets.append({
+                "asset_id": asset_id,
+                "label": r.get("label", "(unknown)"),
+                "catalog_id": r.get("catalog_id", ""),
+                "purchase_ts": ts,
+                "purchase_date": dt.strftime("%Y-%m-%d"),
+                "cost": float(r.get("price", 0.0)),
+                "expected_life_years": snap.get("expected_life_years") or 10,
+                "salvage_value_pct": snap.get("salvage_value_pct") or 0.2,
+                "dep_method_default": (snap.get("dep_method_default") or "SL").upper(),
+            })
+        except Exception:
+            continue
+
+    return assets
+
+def straight_line_schedule(cost: float, life_years: int, salvage_value: float, start_year: int):
+    dep = (cost - salvage_value) / life_years
+    rows = []
+    beg = cost
+    acc = 0.0
+    for i in range(1, life_years + 1):
+        year = start_year + (i - 1)
+        end = max(salvage_value, beg - dep)
+        d = beg - end
+        acc += d
+        rows.append({
+            "Year": year,
+            "Begin BV": round(beg, 2),
+            "Depreciation": round(d, 2),
+            "Accum Dep": round(acc, 2),
+            "End BV": round(end, 2),
+        })
+        beg = end
+    return pd.DataFrame(rows)
+
+def build_schedule(student_id, asset_pick, life_years, salvage_pct):
+    if not student_id:
+        return None, "Enter Student ID."
+
+    assets = fetch_student_assets(student_id)
+    idx = {a["asset_id"]: a for a in assets}
+    if asset_pick not in idx:
+        if not assets:
+            return None, f"No purchases found for '{student_id}'."
+        return None, "Pick an asset."
+
+    a = idx[asset_pick]
+    life = int(life_years) if life_years else int(a["expected_life_years"])
+    spct = float(salvage_pct) if salvage_pct not in (None, "") else float(a["salvage_value_pct"])
+    salvage_val = spct * a["cost"]
+
+    df = straight_line_schedule(
+        cost=a["cost"],
+        life_years=life,
+        salvage_value=salvage_val,
+        start_year=int(a["purchase_date"][:4]),
+    )
+
+    # write schedule CSV back to dataset
+    csv_bytes = df.to_csv(index=False).encode()
+    api = _api_rw()
+    path_in_repo = f"schedules/{student_id}/{asset_pick}.csv"
+    api.upload_file(
+        path_or_fileobj=io.BytesIO(csv_bytes),
+        path_in_repo=path_in_repo,
+        repo_id=DATA_REPO,
+        repo_type=DATA_REPO_TYPE,
+    )
+    note = f"📄 Wrote schedule to dataset at {path_in_repo}"
+    return df, f"✅ Schedule generated for {a['label']} — {note}"
+
+def load_assets_for_ui(student_id):
+    if not student_id:
+        return gr.update(choices=[], value=None), "Enter Student ID then click “🔍 Load my assets”."
+    assets = fetch_student_assets(student_id)
+    choices = [(f"{a['label']} ({a['purchase_date']}) — ${a['cost']:,.0f}", a["asset_id"]) for a in assets]
+    if not choices:
+        # helpful hint: show what we looked for
+        paths = _candidate_purchase_paths(student_id)
+        hint = " none" if not paths else ("\n".join(f"- {p}" for p in paths))
+        return gr.update(choices=[], value=None), f"No purchases found. Looked for:\n{hint}"
+    return gr.update(choices=choices, value=choices[0][1]), f"Loaded {len(choices)} asset(s)."
+
+# --------------------
+# UI
+# --------------------
+with gr.Blocks(theme=gr.themes.Soft()) as app:
+    gr.Markdown("## 🧮 Jerry — Depreciation Helper")
+
+    with gr.Row():
+        student_id = gr.Textbox(label="Student ID", placeholder="e.g., jeff")
+        load_btn = gr.Button("🔍 Load my assets")
+
+    asset_dd = gr.Dropdown(label="Select an asset")
+
+    with gr.Row():
+        life_years = gr.Number(label="Service life (years)", value=None, precision=0)
+        salvage_pct = gr.Slider(label="Salvage % of cost", minimum=0, maximum=0.9, step=0.01, value=None)
+
+    build_btn = gr.Button("Build Straight-Line Schedule")
+    out_tbl = gr.Dataframe(label="Depreciation Schedule", interactive=False)
+    status = gr.Markdown()
+
+    load_btn.click(load_assets_for_ui, inputs=[student_id], outputs=[asset_dd, status])
+    build_btn.click(build_schedule, inputs=[student_id, asset_dd, life_years, salvage_pct],
+                    outputs=[out_tbl, status])
+
+    # allow prefill via URL like ?student_id=jeff
+    def prefill(req: gr.Request):
+        sid = req.query_params.get("student_id")
+        return sid or ""
+
+    app.load(prefill, inputs=None, outputs=[student_id])
+
+if __name__ == "__main__":
+    app.launch()