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.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
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+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
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+# Rope project settings
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+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the enitre vscode folder
+# .vscode/
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+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore

app.py

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+"""Точка входа в приложение."""
+import streamlit as st
+from nav import analysis, main_page, dashboard
+
+
+st.set_page_config(page_title="Home", layout="wide")
+
+pages = [
+    st.Page("./nav/main_page.py", title="Главная"),
+    st.Page("./nav/dashboard.py", title="Дашборд"),
+    st.Page("./nav/analysis.py", title="Анализ")
+]
+
+if __name__ == "__main__":
+    selected_page = st.navigation(pages, position="sidebar")
+    selected_page.run()

crypto_lstm.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:278fc646348c3b4219a6c4669f2a8c54ba8f1c4e6526f3f527d3a8c5d53a252b
+size 3403625

nav/analysis.py

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+"""Страница анализа с получением прогноза модели."""
+import streamlit as st
+import onnxruntime as ort
+import numpy as np
+from nav.dashboard import get_coin_klines, plot_klines
+from nav.main_page import get_ticker_info
+
+
+def init_page():
+    """Инициализирует страницу."""
+    st.header("Анализ")
+    
+    # данные берутся за последние 72 часа с интервалом 1 час
+    klines_df = get_coin_klines("BTC", interval=60, limit=72)
+    plot_klines("BTC", klines_df)
+    last_price = get_ticker_info("BTCUSDT")["last_price"]
+    st.metric("Текущая цена", f"{last_price:.2f}$", border=True)
+
+    # отбрасываем временные метки и добавляем +1 размерность к данным
+    # (это особенность работы модели)
+    klines_df = klines_df.drop("Timestamp", axis=1)
+    klines_df = klines_df.to_numpy(dtype=np.float32)
+    klines_df = np.expand_dims(klines_df, axis=0)
+
+    # получение прогноза от модели и вывод
+    model = load_model()
+    predict = model.run(["output"], {"input": klines_df})
+    predict = inverse_scale(predict[0][0])
+
+    st.metric("Прогноз цены открытия на следующий час", f"{predict:.2f}$", 
+              delta=f"{(predict - last_price):.2f}$", border=True)
+
+def load_model():
+    """Загружает прудобученную LSTM-модель."""
+    sess = ort.InferenceSession("crypto_lstm.onnx")
+    return sess
+
+def inverse_scale(data):
+    """Приводит прогноз модели к ненормализованному виду.
+    Необходимо, т.к. изначально модель обучалась на нормализованных данных
+    (min-max нормализация в диапазоне 0-1). Глобальный минимум и максимум взят 
+    на основе исторических данных."""
+    data = data * (111805.0 - 15613.0) + 15613.0
+    return data
+
+
+if __name__ == "__main__":
+    init_page()

nav/dashboard.py

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+"""Страница дашборда с графиками."""
+import requests
+import streamlit as st
+import plotly.graph_objects as go
+import pandas as pd
+
+
+KLINE_URL = "https://api.bybit.com/v5/market/kline"
+COINS = ["BTC", "ETH"]
+INTERVALS = {"День": "D", "Неделя": "W", "Месяц": "M"}
+
+
+def init_page():
+    """Инициализирует страницу."""
+    st.header("Дашборд")
+    coin = st.sidebar.selectbox("Монета", options=COINS)
+    interval = st.sidebar.selectbox("Интервал", options=INTERVALS, index=1)
+    interval = INTERVALS[interval]
+
+    klines_df = get_coin_klines(coin, interval)
+
+    # свечной график
+    plot_klines(coin, klines_df)
+
+    # линейный график
+    plot_klines_linear(coin, klines_df)
+
+@st.cache_data
+def get_coin_klines(coin, interval, limit=1000):
+    """Возвращает датафрейм со свечами для указанного тикера."""
+    params = {
+        "category": "spot",
+        "symbol": f"{coin.upper()}USDT",
+        "interval": interval,
+        "limit": limit,
+    }
+    response = requests.get(KLINE_URL, params=params).json()
+    klines_df = pd.DataFrame(response["result"]["list"], columns=["Timestamp", "Open", "High", "Low", "Close", "Volume", "Turnover"])
+    klines_df["Timestamp"] = pd.to_datetime(klines_df["Timestamp"], unit="ms")
+    klines_df.drop(["Volume", "Turnover"], axis=1, inplace=True)
+
+    return klines_df
+
+def plot_klines(coin_name, klines_df):
+    """Строит свечной график на основе свеч."""
+    kline_plot = go.Figure(data=go.Candlestick(
+        x=klines_df["Timestamp"],
+        open=klines_df["Open"],
+        high=klines_df["High"],
+        low=klines_df["Low"],
+        close=klines_df["Close"]
+    ))
+    kline_plot.update_layout(
+        title=f"Свечной график {coin_name}/USDT",
+        xaxis_title="Дата",
+        yaxis_title="Цена ($)",
+        yaxis={"autorange": True, "fixedrange": False},
+        height=800,
+        plot_bgcolor='rgba(0,0,0,0.15)',
+        xaxis=dict(
+            showgrid=True,
+            showticklabels=True
+        ),
+        hovermode='x unified',
+        hoverlabel=dict(
+            bgcolor='rgba(0,0,0,0.8)',
+            font_size=12
+        )
+    )
+
+    with st.container(border=True):
+        st.plotly_chart(kline_plot, use_container_width=True)
+
+def plot_klines_linear(coin_name, klines_df):
+    """Строит линейный график на основе свеч."""
+    line_plot = go.Figure(data=go.Scatter(
+        x=klines_df["Timestamp"],
+        y=klines_df["High"],
+        line=dict(
+            shape='spline',
+            smoothing=1, 
+            width=2,
+        )
+    ))
+    line_plot.update_layout(
+        title=f"Линейный график {coin_name}/USDT",
+        xaxis_title="Дата",
+        yaxis_title="Цена ($)",
+        height=600,
+        plot_bgcolor='rgba(0,0,0,0.15)',
+        xaxis=dict(
+            showgrid=True,
+            showticklabels=True
+        ),
+        yaxis=dict(
+            showgrid=True,
+            gridcolor='rgba(200,200,200,0.2)',
+            gridwidth=0.5,
+            tickprefix='$'
+        ),
+        hovermode='x unified',
+        hoverlabel=dict(
+            bgcolor='rgba(0,0,0,0.8)',
+            font_size=12
+        )
+    )
+
+    with st.container(border=True):
+        st.plotly_chart(line_plot, use_container_width=True)
+
+if __name__ == "__main__":
+    init_page()

nav/main_page.py

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+"""Главная страница с общей информацией."""
+import requests
+import streamlit as st
+import pandas as pd
+import plotly.graph_objects as go
+
+from nav.dashboard import get_coin_klines
+
+
+GLOBAL_MARKET_INFO_URL = "https://api.coinlore.net/api/global/"
+TICKER_URL = "https://api.bybit.com/v5/market/tickers"
+ORDER_BOOK_URL = "https://api.binance.com/api/v3/depth"
+
+
+def init_page():
+    """Инициализирует страницу."""
+    st.header("Главная")
+    market_info = get_market_info()
+    display_market_info(market_info)
+
+def display_market_info(market_info):
+    """Разметка страницы и вывод показателей."""
+    global_container = st.container()
+    common_stat_col, order_book_col, exchange_rate_col = global_container.columns([0.2, 0.4, 0.4])
+    
+    # общая статистика
+    with common_stat_col:
+        st.subheader("📌 Общая статистика")
+        with st.container(border=True):
+            st.metric("Монет в обращении", market_info["coins_count"])
+            st.divider()
+            st.metric("Активных торговых пар", market_info["active_markets"])
+            st.divider()
+            st.metric("Общая капитализация", f"${market_info['total_mcap'] / 1e9:.2f} млрд")
+            st.divider()
+            st.metric("Суточный объем торгов", f"${market_info['total_volume'] / 1e9:.2f} млрд")
+
+    # курсы
+    with exchange_rate_col:
+        st.subheader("💲 Курсы криптовалют")
+        btc_info = get_ticker_info("BTCUSDT")
+        eth_info = get_ticker_info("ETHUSDT")
+
+        btc_col, eth_col = st.columns(2)
+        btc_price_delta = round((btc_info["last_price"] - btc_info["prev_price"]), 2)
+        eth_price_delta = round((eth_info["last_price"] - eth_info["prev_price"]), 2)
+        # BTC метрики
+        with btc_col:
+            with st.container(border=True, height=500):
+                st.metric("BTC/USDT", f"{btc_info['last_price']}$", delta=f"{btc_price_delta}$")
+                st.metric("Изменение BTC/USDT", " ", delta=f"{btc_info['price_change']}%")
+                st.metric("Доминирование Bitcoin (BTC)", f"{market_info['btc_d']}%")
+                st.divider()
+                plot_order_book("BTC")
+
+        # ETH метрики
+        with eth_col:
+            with st.container(border=True, height=500):
+                st.metric("ETH/USDT", f"{eth_info['last_price']}$", delta=f"{eth_price_delta}$")
+                st.metric("Изменение ETH/USDT", " ", delta=f"{eth_info['price_change']}%")
+                st.metric("Доминирование Ethereum (ETH)", f"{market_info['eth_d']}%")
+                st.divider()
+                plot_order_book("ETH")
+
+    # мини-графики с курсами
+    with order_book_col:
+        st.subheader("⚖️ Курсы")
+        plot_klines_mini("BTC", get_coin_klines("BTC", "1", 60), dynamic=btc_price_delta)
+        plot_klines_mini("ETH", get_coin_klines("ETH", "1", 60), dynamic=eth_price_delta)
+    
+    st.divider()
+
+    change_col, max_col = st.columns(2)
+    with change_col:
+        # изменения за 24ч
+        st.subheader("📈 Динамика за 24 часа")
+        st.metric("Изменение капитализации", " ", delta=f"{market_info['mcap_change']}%", border=True)
+        st.metric("Изменение объема", " ", delta=f"{market_info['volume_change']}%", border=True)
+        st.metric("Среднее изменение цен", " ", delta=f"{market_info['avg_change_percent']}%", border=True)
+
+    # исторические максимумы
+    with max_col:
+        st.subheader("🚀 Популярные биржи")
+        # st.container(border=True)
+        st.link_button("Binance", "https://www.binance.com/ru", use_container_width=True)
+        st.link_button("Bybit", "https://www.bybit.com/en/", use_container_width=True)
+        st.link_button("OKX", "https://www.okx.com/", use_container_width=True)
+        st.link_button("Bitget", "https://www.bitget.com/", use_container_width=True)
+        st.link_button("MEXC", "https://www.mexc.com/", use_container_width=True)
+        st.link_button("Upbit", "https://upbit.com/", use_container_width=True)
+
+    # увеличение размера текста для дельт
+    st.markdown("""
+    <style>
+    [data-testid="stMetricLabel"],
+    [data-testid="stMetricDelta"] {
+        font-size: 26px !important;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+    get_ticker_info("BTCUSDT")
+  
+def get_market_info():
+    """Возвращает общие данные о рынке криптовалют."""
+    response = requests.get(GLOBAL_MARKET_INFO_URL)
+    if response.status_code != 200:
+        st.write("Не удалось получить глобальные данные")
+
+    market_info = response.json()[0]
+    return market_info
+
+@st.cache_data
+def get_ticker_info(symbol):
+    """Возвращает данные о конкретном тикере."""
+    params = {"category": "spot", "symbol": symbol}
+    response = requests.get(TICKER_URL, params=params)
+    if response.status_code != 200:
+        st.write("Не удалось получить данные тикера")
+
+    response = response.json()["result"]["list"][0]
+    ticker_info = {
+        "last_price": float(response["lastPrice"]),                         # последняя цена продажи
+        "prev_price": float(response["prevPrice24h"]),                      # цена продажи 24ч назад
+        "price_change": round(float(response["price24hPcnt"]) * 100, 2),    # изменение цены за 24ч (проценты)
+        "volume": float(response["volume24h"])                              # объем торгов за 24ч
+    }
+
+    return ticker_info
+
+# @st.cache_data
+def get_order_book_info(symbol):
+    """Возвращает датафреймы спроса и предложения из книги ордеров."""
+    params = {"symbol": symbol, "limit": 100}
+    response = requests.get(ORDER_BOOK_URL, params=params)
+    if response.status_code != 200:
+        st.write("Не удалось получить данные о спросе/предложении")
+
+    response = response.json()
+    bids = pd.DataFrame(data=response["bids"], columns=["price", "volume"], dtype=float)
+    asks = pd.DataFrame(data=response["asks"], columns=["price", "volume"], dtype=float)
+
+    return bids, asks
+
+def plot_order_book(symbol):
+    """Строит график баланса спроса/предложения"""
+    # получение данных
+    bids, asks = get_order_book_info(f"{symbol}USDT")
+    bids.sort_values("price", ascending=False, inplace=True)
+    asks.sort_values("price", ascending=True, inplace=True)
+
+    # кумулятивные суммы объемов 
+    bids["volume_cumsum"] = bids["volume"].cumsum()
+    asks["volume_cumsum"] = asks["volume"].cumsum()
+
+    # макс. объем для нормализации
+    max_volume = max(bids["volume_cumsum"].max(), asks["volume_cumsum"].max())
+
+    # построение графика
+    fig = go.Figure()
+    fig.add_trace(go.Bar(
+        x=[bids["volume_cumsum"].iloc[-1]],
+        y=[""],
+        name="Покупка",
+        hoverinfo="name",
+        orientation="h",
+        marker_color="rgb(61, 213, 109)",
+    ))
+    fig.add_trace(go.Bar(
+        x=[asks["volume_cumsum"].iloc[-1]],
+        y=[""],
+        name="Продажа",
+        hoverinfo="name",
+        orientation="h",
+        marker_color="rgb(255, 75, 75)",
+        base=bids["volume_cumsum"].iloc[-1]
+    ))
+    fig.update_layout(
+        barmode="stack",
+        title=f"Баланс ордеров {symbol}",
+        height=100,
+        xaxis={"range": [0, max_volume * 1.1]},
+        showlegend=False
+    )
+    fig.update_xaxes(showticklabels=False)
+
+    st.plotly_chart(fig, use_container_width=True, config={"displayModeBar": False})
+
+def plot_klines_mini(coin_name, klines_df, dynamic=None):
+    """Строит компактный гладкий линейный график для главной страницы."""
+    # цвет линии под динамику курса за последние сутки
+    if not dynamic:
+        dynamic = "#4b8bff"
+    else:
+        dynamic = "rgb(61, 213, 109)" if dynamic > 0 else "rgb(255, 75, 75)"
+
+    mini_plot = go.Figure(data=go.Scatter(
+        x=klines_df["Timestamp"],
+        y=klines_df["High"],
+        line=dict(
+            shape='spline',  # Сглаживание линий
+            smoothing=1, 
+            width=2,     
+            color=dynamic
+        ),
+        hoverinfo='x+y',
+        hovertemplate='<b>%{x|%d %b %H:%M}</b><br>%{y:$.2f}<extra></extra>'
+    ))
+    
+    mini_plot.update_layout(
+        title=f"{coin_name}/USDT",
+        margin=dict(l=20, r=20, t=40, b=20), 
+        height=250,
+        plot_bgcolor='rgba(0,0,0,0)',
+        xaxis=dict(
+            showgrid=True,
+            showticklabels=True,
+            tickformat='%H:%M',
+            spikecolor="rgb(255, 255, 255)"
+        ),
+        yaxis=dict(
+            showgrid=True,
+            gridcolor='rgba(200,200,200,0.2)',
+            gridwidth=0.5,
+            tickprefix='$'
+        ),
+        hovermode='x unified',
+        hoverlabel=dict(
+            bgcolor='rgba(0,0,0,0.8)',
+            font_size=12,
+        )
+    )
+
+    with st.container(border=True):
+        st.plotly_chart(mini_plot, use_container_width=True, config={'displayModeBar': False})
+
+
+if __name__ == "__main__":
+    init_page()

requirements.txt

@@ -1,3 +1,44 @@
-altair
-pandas
-streamlit
+altair==5.5.0
+attrs==25.3.0
+blinker==1.9.0
+cachetools==6.1.0
+certifi==2025.6.15
+charset-normalizer==3.4.2
+click==8.2.1
+coloredlogs==15.0.1
+flatbuffers==25.2.10
+gitdb==4.0.12
+GitPython==3.1.44
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