data/data.py

import os
import requests
import pandas as pd
from plotly.subplots import make_subplots
import plotly
import plotly.graph_objects as go
from tqdm import tqdm
from datetime import datetime
import pytz
import json
import base64

plotly.io.defaults.default_height = 720
plotly.io.defaults.default_width = 1440

GITHUB_TOKEN = os.getenv("GITHUB_TOKEN")
OWNER = os.getenv("OWNER")
REPO = os.getenv("REPO")

HEADERS = {
    "Authorization": f"token {GITHUB_TOKEN}",
}

FILEPATH = "data/data.json"
FILEURL = f"https://api.github.com/repos/{OWNER}/{REPO}/contents/{FILEPATH}"

def uf(filepath, content):
    fileurl = f"https://api.github.com/repos/{OWNER}/{REPO}/contents/{filepath}"

    response = requests.get(fileurl, headers=HEADERS)
    is_update = response.status_code == 200
    res = response.json()
    sha = res["sha"] if is_update else None

    if is_update and content == res: return

    data = {
        "message": "Update" if is_update else "Upload",
        "content": base64.b64encode(
            content.encode() if isinstance(content, str) else content
        ).decode()
    }
    if is_update: data["sha"] = sha

    resp = requests.put(fileurl, headers=HEADERS, json=data)
    print("✅ Upload success" if resp.ok else f"❌ Error: {resp.text}")

rf = lambda: base64.b64decode(response.json()['content']).decode() if (response := requests.get(FILEURL, headers=HEADERS)).status_code == 200 else "{}"

ir = lambda: json.loads(rf()) != {}

lhs = [7, 15, 30, 60, 90, 120, 240, 365, 1000, 1440]

header_fill_color = [
    "#d9d9d9",  # No - abu netral
    "#add8e6",  # Tgl Beli - biru muda (tanggal = waktu)
    "#9be7a3",  # Harga Beli/g - hijau terang (uang masuk)
    "#fdd9a0",  # Berat - oranye terang (fisik)
    "#f4b6c2",  # Modal - merah muda (biaya awal)
    "#87cefa",  # Tgl Jual - biru langit (tanggal = waktu)
    "#b2fab4",  # Harga Jual/g - hijau pastel (uang keluar / potensi untung)
    "#fff5ba",  # Nilai Jual - kuning pastel (nilai total)
    "#ffadc1",  # Profit/Loss - merah muda (untung/rugi)
]

cells_fill_color = [
    "#eeeeee",  # No - abu netral lebih lembut
    "#e6f2ff",  # Tgl Beli
    "#d5fbe3",  # Harga Beli/g
    "#ffecd9",  # Berat
    "#ffe0e8",  # Modal
    "#e0f2ff",  # Tgl Jual
    "#dcfce7",  # Harga Jual/g
    "#fff9db",  # Nilai Jual
    "#ffe6ef",  # Profit/Loss
]

data = None
data_dir = "data"
data_path = os.path.join(data_dir, "data.json")
os.makedirs(data_dir, exist_ok=True)

makeslcy = lambda x: -0.575 - (7 - x) * (0.575 / 7) * 5

def ambil_data_emas():
    data_is_ready = ir() # os.path.exists(data_path)
    data_is_change = False
    later_day = False
    jam_sudah_cukup = False

    if data_is_ready:
        # with open(data_path, "r") as f: data = json.load(f)
        data = json.loads(rf())

        # Ambil tanggal terakhir dari lastUpdate
        last_updates = [pd.to_datetime(d["lastUpdate"]) for d in data["data"]["priceList"]]
        last_update_date = max(last_updates)

        # Waktu sekarang
        now = datetime.now()

        # Periksa apakah tanggal hari ini lebih baru dari tanggal terakhir
        later_day = now.date() > last_update_date.date()

        # Periksa apakah jam sudah lewat dari jam 11 pagi
        jam_sudah_cukup = now.hour >= 11

    data_is_change = (later_day and jam_sudah_cukup) or not data_is_ready
    print("data_is_change", data_is_change)

    # Jika belum ada data, atau sudah lewat tanggal dan cukup jam
    if data_is_change:
        url = f"https://sahabat.pegadaian.co.id/gold/prices/chart?interval={max(lhs)}&isRequest=true"
        response = requests.get(url)
        if response.status_code != 200:
            raise Exception("Gagal mengambil data harga dari Pegadaian.")

        data = response.json()
        
        uf(FILEPATH, json.dumps(data, indent=4))
        with open(data_path, "w") as f:
            json.dump(data, f, indent=4)

    return data

fred = {
    60: "D",
    90: "2D",
    180: "3D",
    360: "4D",
    480: "5D",
    1000: "3W",
    2500: "6W",
    "Default": "9W"
}

frek = list(fred.keys())
frev = list(fred.values())

default_hari = 90

def get_freq(lama_hari):
    if len(frek) !=len(frev):
        raise Exception("Len Frek !=Len Frev")
    
    freq = frev[-1]
    for i in range(len(frek)):
        if frek[i] !=frek[-1] and lama_hari <=int(frek[i]) and lama_hari >=int(frek[i-1] if frek[i-1] !=frek[-1] else 0):
            freq = frev[i]
            break

    return freq

# Data pembelian
tanggal_beli = [
    pd.Timestamp(d) for d in [
        # "2025-04-10",
        "2025-04-14",
        "2025-06-04",
        "2025-06-08",
        "2025-06-10"
    ]
]
berat_gram = [
    # 1,
    0.0101,
    1.0817,
    0.2182,
    0.0816,
]
uang_awal = [
    # 1_671_000,
    18_648,
    2_000_000,
    400_000,
    150_000,
]
harga_beli_dan_jual_pada_saat_membeli = [
    [1_863_000, 1_797_000], [1_834_000, 1_769_000], [1_840_000, 1_775_000]
]
harga_beli_dan_jual_saat_ini = [1_840_000, 1_775_000]

tglf = lambda tgl: pd.to_datetime(tgl, format='%Y-%m-%d %H:%M:%S')

cwta = [2.5, 6.6, 11.75, 7, 10, 6.6, 12.5, 16.6, 11]

misy = "-"

data = ambil_data_emas()

# Ambil timestamp string dari data
timestamp_utc = data["timestamp"]

# Parsing ISO format ke datetime object (timezone-aware UTC)
dt_utc = datetime.fromisoformat(timestamp_utc.replace("Z", "+00:00"))

# Konversi ke zona waktu WIB (UTC+7)
wib = pytz.timezone("Asia/Jakarta")
dt_wib = dt_utc.astimezone(wib)

# Format menjadi string lokal
timestamp_lokal = dt_wib.strftime("%d %B %Y, %H:%M WIB")