mitai-jinkendo/backend/routers/csv_import.py
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feat(csv-import): Update CSV import functionality and enhance analysis features
- Bumped version of csv_import to 0.3.0, reflecting new analysis capabilities.
- Modified analyze_csv endpoint to allow optional module filtering, improving flexibility in template selection.
- Enhanced the import process to support both system and user-defined templates, ensuring backward compatibility.
- Updated frontend to streamline mapping choices and improve user experience during CSV analysis and import.
- Added detailed error handling and user feedback for import operations.
2026-04-10 06:15:21 +02:00

499 lines
17 KiB
Python

"""
CSV-Import: Nutzer-Endpunkte für Analyse, Mappings, Limits (Issue #21).
"""
from __future__ import annotations
import logging
from typing import Any, Optional
from fastapi import APIRouter, Depends, File, Form, Header, HTTPException, UploadFile
from pydantic import BaseModel
from psycopg2.extras import Json
from auth import require_auth, check_feature_access, increment_feature_usage
from feature_logger import log_feature_usage
from db import get_db, get_cursor, r2d
from routers.profiles import get_pid
from csv_parser.executor import run_universal_csv_import
from csv_parser.core import (
decode_raw_bytes,
column_signature,
get_csv_import_limits,
headers_signature_match_score,
normalize_header_for_signature,
parse_csv_sample,
)
from csv_parser.module_registry import get_module_definition, list_modules, validate_field_mappings
router = APIRouter(prefix="/api/csv", tags=["csv-import"])
logger = logging.getLogger(__name__)
def _load_import_limits() -> dict[str, int]:
with get_db() as conn:
cur = get_cursor(conn)
cur.execute("SELECT value FROM system_config WHERE key = %s", ("csv_import",))
row = cur.fetchone()
return get_csv_import_limits(r2d(row) if row else None)
def _mapping_to_summary(m: dict) -> dict:
return {
"id": m["id"],
"module": m["module"],
"name": m["mapping_name"],
"description": m.get("description"),
"is_system": m["is_system"],
"usage_count": m.get("usage_count"),
"success_rate": m.get("success_rate"),
"last_used_at": m.get("last_used_at"),
"created_at": m.get("created_at"),
}
@router.get("/modules")
def csv_modules(session: dict = Depends(require_auth)):
"""Unterstützte Import-Module und Felddefinitionen."""
out = []
for mid in list_modules():
d = get_module_definition(mid)
if d:
out.append({"id": mid, "table": d["table"], "fields": d["fields"]})
return {"modules": out}
@router.get("/limits")
def csv_limits(session: dict = Depends(require_auth)):
"""Admin-konfigurierbare Import-Limits (system_config.csv_import)."""
return _load_import_limits()
@router.get("/mappings")
def list_csv_mappings(
module: Optional[str] = None,
session: dict = Depends(require_auth),
):
"""System-Templates + eigene User-Mappings."""
pid = str(session["profile_id"])
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT id, module, mapping_name, description, is_system, profile_id,
usage_count, success_rate, last_used_at, created_at
FROM csv_field_mappings
WHERE is_system = true
AND (%s::text IS NULL OR module = %s)
ORDER BY usage_count DESC NULLS LAST, mapping_name
""",
(module, module),
)
system_rows = [r2d(r) for r in cur.fetchall()]
cur.execute(
"""
SELECT id, module, mapping_name, description, is_system, profile_id,
usage_count, success_rate, last_used_at, created_at
FROM csv_field_mappings
WHERE is_system = false AND profile_id = %s::uuid
AND (%s::text IS NULL OR module = %s)
ORDER BY last_used_at DESC NULLS LAST, mapping_name
""",
(pid, module, module),
)
user_rows = [r2d(r) for r in cur.fetchall()]
return {
"system_templates": [_mapping_to_summary(m) for m in system_rows],
"user_mappings": [_mapping_to_summary(m) for m in user_rows],
}
class CopyMappingBody(BaseModel):
name: Optional[str] = None
@router.post("/mappings/{mapping_id}/copy")
def copy_csv_mapping(
mapping_id: int,
body: CopyMappingBody | None = None,
session: dict = Depends(require_auth),
):
"""System- oder eigenes Mapping als neues User-Mapping kopieren."""
pid = str(session["profile_id"])
with get_db() as conn:
cur = get_cursor(conn)
cur.execute(
"""
SELECT * FROM csv_field_mappings WHERE id = %s
""",
(mapping_id,),
)
src = r2d(cur.fetchone())
if not src:
raise HTTPException(404, "Mapping nicht gefunden")
if not src["is_system"] and str(src.get("profile_id")) != pid:
raise HTTPException(403, "Kein Zugriff auf dieses Mapping")
base_name = (body.name if body and body.name else None) or f"{src['mapping_name']} (Kopie)"
name = base_name
n = 1
while True:
cur.execute(
"""
SELECT 1 FROM csv_field_mappings
WHERE profile_id = %s::uuid AND module = %s AND mapping_name = %s
""",
(pid, src["module"], name),
)
if not cur.fetchone():
break
n += 1
name = f"{base_name} {n}"
cur.execute(
"""
INSERT INTO csv_field_mappings (
profile_id, is_system, module, mapping_name, description,
column_signature, delimiter, encoding, has_header,
field_mappings, type_conversions, usage_count, success_rate
) VALUES (
%s::uuid, false, %s, %s, %s,
%s, %s, %s, %s, %s, %s, 0, 1.0
) RETURNING id
""",
(
pid,
src["module"],
name,
src.get("description"),
src["column_signature"],
src["delimiter"],
src["encoding"],
src["has_header"],
Json(src["field_mappings"]),
Json(src["type_conversions"]) if src.get("type_conversions") is not None else None,
),
)
new_id = cur.fetchone()["id"]
return {"new_mapping_id": new_id, "mapping_name": name}
@router.post("/analyze")
async def analyze_csv(
file: UploadFile = File(...),
module: Optional[str] = Form(default=None),
delimiter: Optional[str] = Form(default=None),
session: dict = Depends(require_auth),
):
"""
Erste Zeilen parsen, Signatur bilden, Vorlagen nach Ähnlichkeit ranken.
Ohne `module`: alle System- + eigene User-Vorlagen (echte Format-Erkennung über Spalten-Signatur).
Mit `module`: nur Vorlagen dieses Moduls (Abwärtskompatibilität).
"""
if module and not get_module_definition(module):
raise HTTPException(400, f"Unbekanntes Modul: {module}")
pid = str(session["profile_id"])
raw = await file.read()
limits = _load_import_limits()
max_bytes = limits.get("max_file_bytes", 52_428_800)
if len(raw) > max_bytes:
raise HTTPException(
413,
f"Datei zu groß (max. {max_bytes} Bytes laut Systemkonfiguration)",
)
text = decode_raw_bytes(raw)
max_rows = limits.get("max_rows_per_file", 50_000)
if text.count("\n") > max_rows + 5:
raise HTTPException(
413,
f"Zu viele Zeilen (>{max_rows}) laut Systemkonfiguration csv_import.max_rows_per_file",
)
delim = delimiter if delimiter in (",", ";", "\t") else None
headers, sample_rows, used_delim = parse_csv_sample(text, delimiter=delim, max_data_rows=5)
sig = column_signature(headers)
mod_def = get_module_definition(module) if module else None
available_fields = mod_def["fields"] if mod_def else None
with get_db() as conn:
cur = get_cursor(conn)
if module:
cur.execute(
"""
SELECT id, module, mapping_name, description, column_signature,
delimiter, encoding, has_header, field_mappings, type_conversions, is_system
FROM csv_field_mappings
WHERE module = %s
AND (is_system = true OR (is_system = false AND profile_id = %s::uuid))
""",
(module, pid),
)
else:
cur.execute(
"""
SELECT id, module, mapping_name, description, column_signature,
delimiter, encoding, has_header, field_mappings, type_conversions, is_system
FROM csv_field_mappings
WHERE is_system = true OR (is_system = false AND profile_id = %s::uuid)
""",
(pid,),
)
templates = [r2d(r) for r in cur.fetchall()]
ranked = []
for t in templates:
t_sig = list(t["column_signature"]) if t["column_signature"] else []
t_norm = sorted({normalize_header_for_signature(str(s)) for s in t_sig})
score = headers_signature_match_score(sig, t_norm)
ranked.append(
{
"mapping_id": t["id"],
"module": t["module"],
"mapping_name": t["mapping_name"],
"is_system": bool(t.get("is_system")),
"confidence": round(score, 4),
"match_type": "signature_jaccard",
}
)
ranked.sort(key=lambda x: -x["confidence"])
top = ranked[:25]
recommended = top[0] if top and (top[0]["confidence"] or 0) > 0 else None
return {
"module_filter": module,
"filename": file.filename,
"encoding_note": "utf-8/latin-1 mit BOM-Strip",
"delimiter": used_delim,
"columns": headers,
"column_signature_normalized": sig,
"sample_rows": sample_rows,
"detected_mappings": top,
"recommended": recommended,
"available_fields": available_fields,
}
def _fetch_mapping_row(
cur,
mapping_id: int,
profile_id: str,
module: Optional[str] = None,
) -> dict:
cur.execute(
"""
SELECT * FROM csv_field_mappings WHERE id = %s
""",
(mapping_id,),
)
m = r2d(cur.fetchone())
if not m:
raise HTTPException(404, "Mapping nicht gefunden")
if module is not None and m.get("module") != module:
raise HTTPException(400, "Mapping gehört zu einem anderen Modul")
if not m.get("is_system"):
if str(m.get("profile_id") or "") != profile_id:
raise HTTPException(403, "Kein Zugriff auf dieses Mapping")
return m
def _check_module_feature_access(pid: str, module: str) -> None:
if module == "nutrition":
access = check_feature_access(pid, "nutrition_entries")
log_feature_usage(pid, "nutrition_entries", access, "csv_universal_import")
if not access["allowed"]:
raise HTTPException(
403,
f"Limit erreicht (Ernährungseinträge): {access.get('used')}/{access.get('limit')}",
)
elif module == "weight":
access = check_feature_access(pid, "weight_entries")
log_feature_usage(pid, "weight_entries", access, "csv_universal_import")
if not access["allowed"]:
raise HTTPException(
403,
f"Limit erreicht (Gewichtseinträge): {access.get('used')}/{access.get('limit')}",
)
@router.post("/import")
async def csv_import_execute(
file: UploadFile = File(...),
mapping_id: int = Form(...),
module: Optional[str] = Form(default=None),
x_profile_id: Optional[str] = Header(default=None),
session: dict = Depends(require_auth),
):
"""
Universal-CSV-Import: Zielmodul kommt aus der gewählten Vorlage (`mapping_id`).
Optional `module` dient nur der Absicherung (muss mit Vorlage übereinstimmen).
"""
pid = get_pid(x_profile_id)
access_di = check_feature_access(pid, "data_import")
log_feature_usage(pid, "data_import", access_di, "csv_universal_import")
if not access_di["allowed"]:
raise HTTPException(
403,
"Limit erreicht (Daten importieren): "
f"{access_di.get('used')}/{access_di.get('limit')}",
)
raw = await file.read()
limits = _load_import_limits()
max_bytes = limits.get("max_file_bytes", 52_428_800)
if len(raw) > max_bytes:
raise HTTPException(
413,
f"Datei zu groß (max. {max_bytes} Bytes laut Systemkonfiguration)",
)
text = decode_raw_bytes(raw)
if not text.strip():
raise HTTPException(400, "Leere Datei")
max_rows = limits.get("max_rows_per_file", 50_000)
if text.count("\n") > max_rows + 5:
raise HTTPException(
413,
f"Zu viele Zeilen (>{max_rows}) laut Systemkonfiguration",
)
log_id: int | None = None
err_response: HTTPException | None = None
result: dict | None = None
resolved_module: str | None = None
try:
with get_db() as conn:
cur = get_cursor(conn)
m = _fetch_mapping_row(cur, mapping_id, pid, module)
exec_module = m["module"]
resolved_module = exec_module
if exec_module == "activity":
raise HTTPException(
501,
"Aktivitäts-CSV über den Universal-Importer ist noch nicht freigeschaltet "
"(Training-Type-Mapping). Bitte weiterhin /api/activity/import nutzen.",
)
if not get_module_definition(exec_module):
raise HTTPException(
400,
f"Modul der Vorlage wird vom Importer noch nicht unterstützt: {exec_module}",
)
_check_module_feature_access(pid, exec_module)
cur.execute(
"""
INSERT INTO csv_import_log (
profile_id, mapping_id, module, filename,
rows_total, rows_imported, rows_updated, rows_skipped, rows_errors,
status, error_details, affected_ids
) VALUES (
%s::uuid, %s, %s, %s,
0, 0, 0, 0, 0,
'running', NULL, NULL
) RETURNING id
""",
(pid, mapping_id, exec_module, file.filename or "upload.csv"),
)
log_id = cur.fetchone()["id"]
cur.execute("SAVEPOINT csv_import_exec")
try:
result = run_universal_csv_import(
cur,
pid,
exec_module,
text,
file.filename or "upload.csv",
m,
)
except Exception as exec_err:
cur.execute("ROLLBACK TO SAVEPOINT csv_import_exec")
cur.execute(
"""
UPDATE csv_import_log SET
finished_at = CURRENT_TIMESTAMP,
status = 'failed',
error_details = %s
WHERE id = %s
""",
(Json([{"error": str(exec_err)}]), log_id),
)
err_response = HTTPException(500, f"Import fehlgeschlagen: {exec_err}")
else:
cur.execute("RELEASE SAVEPOINT csv_import_exec")
cur.execute(
"""
UPDATE csv_import_log SET
finished_at = CURRENT_TIMESTAMP,
status = 'success',
rows_total = %s,
rows_imported = %s,
rows_updated = %s,
rows_skipped = %s,
rows_errors = %s,
error_details = %s,
affected_ids = %s
WHERE id = %s
""",
(
result["rows_total"],
result["rows_imported"],
result["rows_updated"],
result["rows_skipped"],
result["rows_errors"],
Json(result["error_details"]),
Json(result["affected_ids"]),
log_id,
),
)
cur.execute(
"""
UPDATE csv_field_mappings SET
usage_count = usage_count + 1,
last_used_at = CURRENT_TIMESTAMP,
updated_at = CURRENT_TIMESTAMP
WHERE id = %s
""",
(mapping_id,),
)
except HTTPException:
raise
if err_response:
raise err_response
assert result is not None
increment_feature_usage(pid, "data_import")
ne = result.get("new_entries", result["rows_imported"])
if resolved_module == "nutrition":
for _ in range(ne):
increment_feature_usage(pid, "nutrition_entries")
elif resolved_module == "weight":
for _ in range(ne):
increment_feature_usage(pid, "weight_entries")
return {
"success": True,
"import_log_id": log_id,
"module": resolved_module,
"stats": {
"total_rows": result["rows_total"],
"imported": result["rows_imported"],
"updated": result["rows_updated"],
"skipped": result["rows_skipped"],
"errors": result["rows_errors"],
},
"error_details": result["error_details"],
}