new
This commit is contained in:
Azmikun1
parent
8817cefa56
commit
9e96949373
145
app.py
145
app.py
|
|
@ -85,69 +85,104 @@ html, body, [class*="css"] { font-family: "Inter", "DejaVu Sans", sans-serif; }
|
|||
|
||||
@st.cache_data(ttl="1h")
|
||||
def load_eth_data():
|
||||
"""
|
||||
Metode Hybrid (Tumpuk Data):
|
||||
1. Baca Data Lama dari CSV.
|
||||
2. Download Data Baru (dari tanggal terakhir CSV sampai Hari Ini).
|
||||
3. Gabung (Concat) tanpa mengubah/mengisi data kosong.
|
||||
"""
|
||||
ticker = "ETH-USD"
|
||||
df = None
|
||||
df_final = None
|
||||
|
||||
# 1. COBA ONLINE
|
||||
# --- BAGIAN 1: BACA DATA LAMA (BASE) ---
|
||||
try:
|
||||
df_base = pd.read_csv("eth_backup.csv")
|
||||
|
||||
df = yf.download(
|
||||
ticker,
|
||||
start="2024-01-01",
|
||||
end=date.today() + timedelta(days=1),
|
||||
progress=False,
|
||||
auto_adjust=True,
|
||||
multi_level_index=False
|
||||
)
|
||||
# Bersihkan kolom sampah
|
||||
if "Unnamed: 0" in df_base.columns:
|
||||
df_base = df_base.drop(columns=["Unnamed: 0"])
|
||||
|
||||
if df is not None and not df.empty:
|
||||
# Bersihkan Index & Kolom
|
||||
df = df.reset_index()
|
||||
# Standarisasi kolom Date
|
||||
if "Date" not in df_base.columns:
|
||||
# Cek kolom pertama
|
||||
df_base = df_base.rename(columns={df_base.columns[0]: "Date"})
|
||||
|
||||
new_cols = []
|
||||
for col in df.columns:
|
||||
col_name = col[0] if isinstance(col, tuple) else str(col)
|
||||
new_cols.append(col_name)
|
||||
df.columns = new_cols
|
||||
|
||||
# Pastikan kolom pertama adalah Date
|
||||
if 'Date' not in df.columns:
|
||||
df = df.rename(columns={df.columns[0]: 'Date'})
|
||||
|
||||
# Hapus Timezone
|
||||
df['Date'] = pd.to_datetime(df['Date']).dt.tz_localize(None)
|
||||
|
||||
# Simpan Backup (Timpa file lama agar fresh)
|
||||
try:
|
||||
df.to_csv("eth_backup.csv", index=False)
|
||||
except:
|
||||
pass
|
||||
|
||||
return df, "online"
|
||||
|
||||
except Exception as e:
|
||||
print(f"Gagal Online: {e}")
|
||||
|
||||
# 2. COBA BACKUP (JIKA ONLINE GAGAL)
|
||||
try:
|
||||
df_backup = pd.read_csv("eth_backup.csv")
|
||||
|
||||
# Bersihkan kolom sampah jika ada
|
||||
if "Unnamed: 0" in df_backup.columns:
|
||||
df_backup = df_backup.drop(columns=["Unnamed: 0"])
|
||||
|
||||
# Pastikan kolom Date dikenali
|
||||
if "Date" in df_backup.columns:
|
||||
df_backup["Date"] = pd.to_datetime(df_backup["Date"])
|
||||
elif df_backup.columns[0].lower() == "date":
|
||||
df_backup = df_backup.rename(columns={df_backup.columns[0]: "Date"})
|
||||
df_backup["Date"] = pd.to_datetime(df_backup["Date"])
|
||||
|
||||
return df_backup, "backup"
|
||||
df_base["Date"] = pd.to_datetime(df_base["Date"]).dt.tz_localize(None)
|
||||
|
||||
except FileNotFoundError:
|
||||
# 3. GAGAL TOTAL
|
||||
return None, "error"
|
||||
# Jika tidak ada file, buat dataframe kosong
|
||||
df_base = pd.DataFrame(columns=["Date", "Open", "High", "Low", "Close", "Volume"])
|
||||
|
||||
# --- BAGIAN 2: DOWNLOAD DATA BARU (INCREMENTAL) ---
|
||||
today = date.today()
|
||||
|
||||
# Tentukan tanggal mulai download (Lanjutkan dari data terakhir di CSV)
|
||||
if not df_base.empty:
|
||||
last_date_csv = df_base["Date"].max()
|
||||
start_download = last_date_csv + timedelta(days=1)
|
||||
else:
|
||||
start_download = pd.to_datetime("2020-01-01")
|
||||
|
||||
# Hanya download jika ada selisih hari
|
||||
if start_download.date() <= today:
|
||||
try:
|
||||
# Download dari tanggal terakhir CSV s/d Hari Ini
|
||||
df_new = yf.download(
|
||||
ticker,
|
||||
start=start_download,
|
||||
end=today + timedelta(days=1),
|
||||
progress=False,
|
||||
auto_adjust=True,
|
||||
multi_level_index=False
|
||||
)
|
||||
|
||||
if df_new is not None and not df_new.empty:
|
||||
df_new = df_new.reset_index()
|
||||
|
||||
# Rapikan kolom (Hapus MultiIndex jika ada)
|
||||
new_cols = []
|
||||
for col in df_new.columns:
|
||||
col_name = col[0] if isinstance(col, tuple) else str(col)
|
||||
new_cols.append(col_name)
|
||||
df_new.columns = new_cols
|
||||
|
||||
# Pastikan kolom Date benar
|
||||
if 'Date' not in df_new.columns:
|
||||
df_new = df_new.rename(columns={df_new.columns[0]: 'Date'})
|
||||
|
||||
df_new['Date'] = pd.to_datetime(df_new['Date']).dt.tz_localize(None)
|
||||
|
||||
# --- BAGIAN 3: GABUNGKAN (CONCAT) ---
|
||||
# Tumpuk data lama (Base) dengan data baru (New)
|
||||
df_final = pd.concat([df_base, df_new], ignore_index=True)
|
||||
|
||||
else:
|
||||
# Jika download kosong (misal libur/gagal), pakai data lama saja
|
||||
df_final = df_base
|
||||
|
||||
except Exception as e:
|
||||
print(f"Gagal update online: {e}")
|
||||
df_final = df_base # Jika error, tetap tampilkan data lama (Safety Net)
|
||||
else:
|
||||
# Data CSV sudah paling update
|
||||
df_final = df_base
|
||||
|
||||
# --- FINALISASI ---
|
||||
if df_final is not None and not df_final.empty:
|
||||
# Hapus duplikat (jika ada irisan tanggal)
|
||||
df_final = df_final.drop_duplicates(subset="Date", keep="last")
|
||||
|
||||
# Urutkan berdasarkan tanggal
|
||||
df_final = df_final.sort_values("Date").reset_index(drop=True)
|
||||
|
||||
# Filter hanya kolom standar (buang kolom sampah)
|
||||
target_cols = ['Date', 'Open', 'High', 'Low', 'Close', 'Volume']
|
||||
available = [c for c in target_cols if c in df_final.columns]
|
||||
df_final = df_final[available]
|
||||
|
||||
return df_final, "mixed" # Status mixed (Gabungan)
|
||||
|
||||
return None, "error"
|
||||
|
||||
def validate_scaler(scaler):
|
||||
"""Validasi scaler agar konsisten dengan training."""
|
||||
|
|
|
|||
Loading…
Reference in New Issue