from flask import Flask, render_template import yfinance as yf import pandas as pd import ta

app = Flask(name)

def fetch_data(symbol): data = yf.download(symbol, period="30d", interval="1h") data.dropna(inplace=True)

# محاسبه RSI و MACD
data["RSI"] = ta.momentum.RSIIndicator(data["Close"]).rsi()
macd = ta.trend.MACD(data["Close"])
data["MACD"] = macd.macd()
data["Signal"] = macd.macd_signal()

return data.tail(50)

@app.route("/") def index(): btc = fetch_data("BTC-USD") eth = fetch_data("ETH-USD")

return render_template("index.html", btc=btc.tail(10).to_dict(orient="records"), 
                                     eth=eth.tail(10).to_dict(orient="records"))

if name == "main": app.run(debug=True)- 👋 Hi, I’m @saeedsaeedi1990

• 👀 I’m interested in ...
• 🌱 I’m currently learning ...
• 💞️ I’m looking to collaborate on ...
• 📫 How to reach me ...
• 😄 Pronouns: ...
• ⚡ Fun fact: ...

from flask import Flask, render_template import yfinance as yf import pandas as pd import ta

app = Flask(name)

def fetch_data(symbol): data = yf.download(symbol, period="30d", interval="1h") data.dropna(inplace=True)

# محاسبه RSI و MACD
data["RSI"] = ta.momentum.RSIIndicator(data["Close"]).rsi()
macd = ta.trend.MACD(data["Close"])
data["MACD"] = macd.macd()
data["Signal"] = macd.macd_signal()

return data.tail(50)

@app.route("/") def index(): btc = fetch_data("BTC-USD") eth = fetch_data("ETH-USD")

return render_template("index.html", btc=btc.tail(10).to_dict(orient="records"), 
                                     eth=eth.tail(10).to_dict(orient="records"))

if name == "main": app.run(debug=True)unzip *.zipcripto-project.zipgit add . git commit -m "توضیح کوتاه درباره تغییرات" git push origin mainmainstreamlit run app.pypip install streamlitrm file-8xFcyxGqUFBEp9ZVTWA1M1.zipunzip file-8xFcyxGqUFBEp9ZVTWA1M1.zipimport streamlit as st

st.title("تحلیل ارز دیجیتال") st.write("سلام! این پروژه تحلیل بیت‌کوین و اتریومه. به زودی ویژگی‌های حرفه‌ای اضافه می‌شه.")import streamlit as st import yfinance as yf import pandas as pd import plotly.graph_objects as go

st.set_page_config(page_title="Crypto Dashboard", layout="wide")

st.title("Crypto Dashboard - Bitcoin & Ethereum")

crypto_options = {"Bitcoin": "BTC-USD", "Ethereum": "ETH-USD"} selected_crypto = st.selectbox("Select Cryptocurrency", list(crypto_options.keys())) symbol = crypto_options[selected_crypto]

@st.cache_data def get_data(symbol): data = yf.download(symbol, period="6mo", interval="1d") data.dropna(inplace=True) return data

df = get_data(symbol)

st.subheader(f"{selected_crypto} Price Chart") fig = go.Figure() fig.add_trace(go.Candlestick(x=df.index, open=df['Open'], high=df['High'], low=df['Low'], close=df['Close'], name='Candlestick')) fig.update_layout(xaxis_rangeslider_visible=False, height=500) st.plotly_chart(fig, use_container_width=True)

delta = df['Close'].diff() gain = (delta.where(delta > 0, 0)).rolling(window=14).mean() loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean() rs = gain / loss rsi = 100 - (100 / (1 + rs))

st.subheader("RSI Indicator") st.line_chart(rsi)

exp1 = df['Close'].ewm(span=12, adjust=False).mean() exp2 = df['Close'].ewm(span=26, adjust=False).mean() macd = exp1 - exp2 signal = macd.ewm(span=9, adjust=False).mean()

st.subheader("MACD Indicator") macd_df = pd.DataFrame({"MACD": macd, "Signal": signal}) st.line_chart(macd_df)import streamlit as st import yfinance as yf import pandas as pd import plotly.graph_objects as go

st.set_page_config(page_title="Crypto Dashboard", layout="wide")

st.title("Crypto Dashboard - Bitcoin & Ethereum")

crypto_options = {"Bitcoin": "BTC-USD", "Ethereum": "ETH-USD"} selected_crypto = st.selectbox("Select Cryptocurrency", list(crypto_options.keys())) symbol = crypto_options[selected_crypto]

@st.cache_data def get_data(symbol): data = yf.download(symbol, period="6mo", interval="1d") data.dropna(inplace=True) return data

df = get_data(symbol)

st.subheader(f"{selected_crypto} Price Chart") fig = go.Figure() fig.add_trace(go.Candlestick(x=df.index, open=df['Open'], high=df['High'], low=df['Low'], close=df['Close'], name='Candlestick')) fig.update_layout(xaxis_rangeslider_visible=False, height=500) st.plotly_chart(fig, use_container_width=True)

delta = df['Close'].diff() gain = (delta.where(delta > 0, 0)).rolling(window=14).mean() loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean() rs = gain / loss rsi = 100 - (100 / (1 + rs))

st.subheader("RSI Indicator") st.line_chart(rsi)

from data import get_crypto_data from analysis import calculate_indicators from sentiment import get_sentiment from history import get_price_history from database import save_to_db, load_from_db

st.set_page_config(page_title="Crypto Dashboard", layout="wide") st.title("Crypto Dashboard")

coin = st.sidebar.selectbox("Select a cryptocurrency", ["Bitcoin", "Ethereum"]) days = st.sidebar.slider("Days of data", 7, 90, 30)

df = get_crypto_data(coin, days) if df is not None: df = calculate_indicators(df)

st.subheader(f"{coin} Price Chart")
st.line_chart(df['Close'])

st.subheader("Technical Indicators")
st.line_chart(df[['RSI', 'MACD']])

st.subheader("Market Sentiment")
sentiment = get_sentiment(coin)
st.write(f"Sentiment score for {coin}: {sentiment}")

if st.button("Save data to database"):
    save_to_db(df, coin)
    st.success("Data saved successfully!")

if st.button("Load saved data"):
    saved_df = load_from_db(coin)
    st.write(saved_df.tail())

else: st.error("Failed to fetch data. Please check your API key or connection.")git remote add origin https://github.com/saeedsaeedi1990/crypto_dashboard.git git branch -M main git push -u origin maincrypto_dashboard/ ├── main.py ├── requirements.txt ├── run_dashboard.sh ├── README.md ├── utils/ │ ├── data.py │ ├── analysis.py │ ├── sentiment.py │ └── database.py └── pages/ ├── dashboard.py ├── settings.py ├── sentiment_page.py └── history.pyDescription (optional)import streamlit as st import yfinance as yf import pandas as pd import matplotlib.pyplot as plt

st.set_page_config(layout="wide") st.title("تحلیل ارز دیجیتال - بیت‌کوین و اتریوم")

coin = st.selectbox("انتخاب ارز:", ["Bitcoin (BTC)", "Ethereum (ETH)"]) symbol = "BTC-USD" if "BTC" in coin else "ETH-USD"

@st.cache_data def load_data(symbol): data = yf.download(symbol, period='90d', interval='1d') data.dropna(inplace=True) return data

df = load_data(symbol)

def compute_rsi(data, window=14): delta = data['Close'].diff() gain = (delta.where(delta > 0, 0)).rolling(window=window).mean() loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean() rs = gain / loss rsi = 100 - (100 / (1 + rs)) return rsi

def compute_macd(data): exp1 = data['Close'].ewm(span=12).mean() exp2 = data['Close'].ewm(span=26).mean() macd = exp1 - exp2 signal = macd.ewm(span=9).mean() return macd, signal

df['RSI'] = compute_rsi(df) df['MACD'], df['Signal'] = compute_macd(df)

st.subheader("نمودار قیمت و اندیکاتورها")

fig, ax = plt.subplots(3, 1, figsize=(12, 10), sharex=True)

ax[0].plot(df['Close'], label='قیمت', color='blue') ax[0].set_title('قیمت')

ax[1].plot(df['RSI'], label='RSI', color='green') ax[1].axhline(70, color='red', linestyle='--') ax[1].axhline(30, color='red', linestyle='--') ax[1].set_title('RSI')

ax[2].plot(df['MACD'], label='MACD', color='purple') ax[2].plot(df['Signal'], label='Signal', color='orange') ax[2].set_title('MACD') ax[2].legend()

st.pyplot(fig)

st.subheader("دانلود دیتا") csv = df.to_csv().encode('utf-8') st.download_button("دانلود CSV", data=csv, file_name=f'{symbol}_analysis.csv', mime='text/csv')#!/data/data/com.termux/files/usr/bin/bash

pkg update -y pkg upgrade -y pkg install -y python wget unzip git

pip install --upgrade pip pip install streamlit

PROJECT_PATH="/sdcard/Download/crypto_dashboard_advanced"

cd "$PROJECT_PATH" || { echo "مسیر پروژه پیدا نشد!" exit 1 }

pip install -r requirements.txt

echo "در حال اجرای Streamlit..." nohup streamlit run main.py &

if [ ! -f "$PROJECT_PATH/ngrok" ]; then echo "در حال دانلود Ngrok..." wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-arm.zip unzip ngrok-stable-linux-arm.zip chmod +x ngrok fi

if ! grep -q "authtoken" ~/.ngrok2/ngrok.yml 2>/dev/null; then echo "توکن Ngrok تنظیم نشده!" echo "لطفا این دستور رو یک بار دستی بزن:" echo "./ngrok config add-authtoken <توکن تو از ngrok.com>" exit 1 fi

echo "در حال اجرای Ngrok..." ./ngrok http 8501pkg update pkg install python pip install --upgrade pippkg update pkg upgrade pkg install python pkg install git pip install --upgrade piphttp://localhost:8501cd path/to/crypto_dashboard_advancedpip install -r requirements.txthttps://huggingface.co/spaces/your-username/crypto-dashboard# file: dashboard.py

import streamlit as st from technical_analysis import get_historical_data, add_indicators, plot_chart

st.set_page_config(page_title="Crypto Analyzer", layout="wide")

st.title("داشبورد تحلیل ارز دیجیتال")

coin = st.selectbox("ارز مورد نظر:", ["bitcoin", "ethereum"])

days = st.slider("بازه زمانی (روز):", min_value=7, max_value=90, value=30)

with st.spinner("در حال دریافت داده‌ها..."): df = get_historical_data(coin, "usd", days) df = add_indicators(df)

st.subheader("نمودار قیمت و میانگین‌های متحرک") plot_chart(df) # تابع Plotly داخل فایل قبلی

st.dataframe(df.tail(10))crypto_dashboard/ │ ├── dashboard.py ← فایل اصلی Streamlit ├── historical_data.py ← دریافت داده از CoinGecko ├── technical_analysis.py ← محاسبه اندیکاتورها ├── sentiment.py ← تحلیل احساسات ساده └── requirements.txt ← لیست کتابخانه‌ها# file: technical_analysis.py

import pandas as pd import plotly.graph_objs as go from historical_data import get_historical_data # از فایل قبلی ایمپورت می‌کنیم

def add_indicators(df): df["SMA_7"] = df["price"].rolling(window=7).mean() df["EMA_7"] = df["price"].ewm(span=7, adjust=False).mean() return df

def plot_chart(df): fig = go.Figure()

# قیمت
fig.add_trace(go.Scatter(x=df["date"], y=df["price"], mode="lines", name="Price"))
# SMA
fig.add_trace(go.Scatter(x=df["date"], y=df["SMA_7"], mode="lines", name="SMA 7-day"))
# EMA
fig.add_trace(go.Scatter(x=df["date"], y=df["EMA_7"], mode="lines", name="EMA 7-day"))

fig.update_layout(
    title="Bitcoin Price & Moving Averages",
    xaxis_title="Date",
    yaxis_title="Price (USD)",
    template="plotly_dark"
)

fig.show()

if name == "main": df = get_historical_data("bitcoin", "usd", 30) df = add_indicators(df) plot_chart(df)pip install requests pandas streamlit plotly# file: historical_data.py

import requests import pandas as pd from datetime import datetime

def get_historical_data(coin_id="bitcoin", currency="usd", days=30): url = f"https://api.coingecko.com/api/v3/coins/{coin_id}/market_chart" params = { "vs_currency": currency, "days": days, "interval": "daily" } response = requests.get(url, params=params) data = response.json()

prices = data["prices"]  # [timestamp, price]

# تبدیل به DataFrame
df = pd.DataFrame(prices, columns=["timestamp", "price"])
df["date"] = pd.to_datetime(df["timestamp"], unit="ms").dt.date
df = df[["date", "price"]]
return df

if name == "main": df = get_historical_data("bitcoin", "usd", 30) print(df)# file: crypto_data.py

import requests import pandas as pd

def get_price(coin_id="bitcoin", currency="usd"): url = f"https://api.coingecko.com/api/v3/simple/price" params = { "ids": coin_id, "vs_currencies": currency, "include_24hr_change": "true" } response = requests.get(url, params=params) data = response.json() price = data[coin_id][currency] change = data[coin_id][f"{currency}_24h_change"] return price, change

if name == "main": coins = ["bitcoin", "ethereum"] for coin in coins: price, change = get_price(coin) print(f"{coin.capitalize()} - قیمت: {price} دلار | تغییر ۲۴ ساعته: {change:.2f}%")