mirror of
https://github.com/aljazceru/hummingbot-dashboard.git
synced 2025-12-29 03:04:19 +01:00
(feat) add protocols analysis page
This commit is contained in:
cardosofede
2
.gitignore
vendored
2
.gitignore
vendored
@@ -6,6 +6,8 @@ __pycache__/
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# C extensions
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*.
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*.ipynb
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.idea/*
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# Distribution / packaging
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83
pages/5_🦉_TVL_vs_MCAP_Analysis.py
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83
pages/5_🦉_TVL_vs_MCAP_Analysis.py
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@@ -0,0 +1,83 @@
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from xml.dom.pulldom import default_bufsize
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import numpy as np
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import streamlit as st
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import pandas as pd
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import plotly.express as px
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from defillama import DefiLlama
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from traitlets import default
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MIN_TVL = 1000000.
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MIN_MCAP = 1000000.
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@st.cache
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def get_tvl_mcap_data():
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# initialize api client
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llama = DefiLlama()
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# Get all protocols data
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df = pd.DataFrame(llama.get_all_protocols())
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tvl_mcap_df = df.loc[(df["tvl"]>0) & (df["mcap"]>0), ["name", "tvl", "mcap", "chain", "category", "slug"]].sort_values(by=["mcap"], ascending=False)
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return tvl_mcap_df[(tvl_mcap_df["tvl"] > MIN_TVL) & (tvl_mcap_df["mcap"]> MIN_MCAP)]
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def get_protocols_by_chain_category(protocols: pd.DataFrame, group_by: list, nth: list):
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return protocols.sort_values('tvl', ascending=False).groupby(group_by).nth(nth).reset_index()
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st.set_page_config(layout='wide')
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st.title("🦉 TVL vs MCAP Analysis")
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st.write("---")
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st.code("💡 Source: [DefiLlama](https://defillama.com/)")
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with st.spinner(text='In progress'):
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tvl_mcap_df = get_tvl_mcap_data()
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default_chains = ["Ethereum", "Solana", "Binance", "Polygon", "Multi-Chain", "Avalanche"]
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# st.write("### Protocols filter 🦅")
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# tokens = st.multiselect(
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# "Select the protocols to analyze:",
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# options=tvl_mcap_df["name"],
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# default=tvl_mcap_df[tvl_mcap_df["chain"].isin(default_chains)]["name"])
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st.sidebar.write("### Chains filter 🔗")
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chains = st.sidebar.multiselect(
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"Select the chains to analyze:",
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options=tvl_mcap_df["chain"].unique(),
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default=default_chains)
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scatter = px.scatter(
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data_frame=tvl_mcap_df[tvl_mcap_df["chain"].isin(chains)],
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x="tvl",
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y="mcap",
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color="chain",
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trendline="ols",
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log_x=True,
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log_y=True,
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height=800,
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hover_data=["name"],
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template="plotly_dark",
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title="TVL vs MCAP",
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labels={
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"tvl": 'TVL (USD)',
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'mcap': 'Market Cap (USD)'
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})
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st.plotly_chart(scatter, use_container_width=True)
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st.sidebar.write("---")
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st.sidebar.write("### SunBurst filter 🔗")
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groupby = st.sidebar.selectbox('Group by:', [['chain', 'category'], ['category', 'chain']])
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nth = st.sidebar.slider('Top protocols by Category', min_value=1, max_value=5)
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proto_agg = get_protocols_by_chain_category(tvl_mcap_df[tvl_mcap_df["chain"].isin(chains)], groupby, np.arange(0, nth, 1).tolist())
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groupby.append("slug")
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sunburst = px.sunburst(
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proto_agg,
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path=groupby,
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values='tvl',
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height=800,
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title="SunBurst",
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template="plotly_dark",)
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st.plotly_chart(sunburst, use_container_width=True)
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st.sidebar.write("# Data filters 🏷")
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st.sidebar.code("🧳 New filters coming. \nReach us on discord \nif you want to propose one!")
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@@ -5,19 +5,19 @@ argon2-cffi-bindings==21.2.0
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asttokens==2.0.5
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attrs==21.4.0
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backcall==0.2.0
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backports.zoneinfo==0.2.1
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beautifulsoup4==4.11.1
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bleach==5.0.0
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bleach==5.0.1
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blinker==1.4
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boltons==21.0.0
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cachetools==5.2.0
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certifi==2022.5.18.1
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cffi==1.15.0
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charset-normalizer==2.0.12
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certifi==2022.6.15
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cffi==1.15.1
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charset-normalizer==2.1.0
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click==8.1.3
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commonmark==0.9.1
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debugpy==1.6.0
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debugpy==1.6.2
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decorator==5.1.1
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DeFiLlama==1.1.0
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defusedxml==0.7.1
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entrypoints==0.4
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executing==0.8.3
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@@ -27,38 +27,38 @@ gitdb==4.0.9
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GitPython==3.1.27
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glom==22.1.0
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idna==3.3
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importlib-metadata==4.11.4
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importlib-resources==5.7.1
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ipykernel==6.13.1
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importlib-metadata==4.12.0
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ipykernel==6.15.1
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ipython==8.4.0
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ipython-genutils==0.2.0
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ipywidgets==7.7.0
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ipywidgets==7.7.1
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jedi==0.18.1
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Jinja2==3.1.2
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jsonschema==4.6.0
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jupyter-client==7.3.3
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jupyter-core==4.10.0
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jsonschema==4.7.2
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jupyter-client==7.3.4
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jupyter-core==4.11.1
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jupyterlab-pygments==0.2.2
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jupyterlab-widgets==1.1.0
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jupyterlab-widgets==1.1.1
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MarkupSafe==2.1.1
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matplotlib-inline==0.1.3
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mistune==0.8.4
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nbclient==0.6.4
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nbclient==0.6.6
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nbconvert==6.5.0
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nbformat==5.4.0
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nest-asyncio==1.5.5
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notebook==6.4.12
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numpy==1.22.4
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numpy==1.23.1
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packaging==21.3
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pandas==1.4.2
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pandas==1.4.3
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pandocfilters==1.5.0
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parso==0.8.3
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patsy==0.5.2
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pexpect==4.8.0
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pickleshare==0.7.5
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Pillow==9.1.1
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plotly==5.8.0
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Pillow==9.2.0
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plotly==5.9.0
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prometheus-client==0.14.1
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prompt-toolkit==3.0.29
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prompt-toolkit==3.0.30
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protobuf==3.20.1
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psutil==5.9.1
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ptyprocess==0.7.0
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@@ -74,30 +74,32 @@ pyrsistent==0.18.1
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python-dateutil==2.8.2
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pytz==2022.1
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pytz-deprecation-shim==0.1.0.post0
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pyzmq==23.1.0
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requests==2.27.1
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rich==12.4.4
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pyzmq==23.2.0
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requests==2.28.1
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rich==12.5.1
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scipy==1.8.1
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semver==2.13.0
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Send2Trash==1.8.0
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six==1.16.0
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smmap==5.0.0
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soupsieve==2.3.2.post1
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stack-data==0.2.0
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stack-data==0.3.0
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statsmodels==0.13.2
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streamlit==1.10.0
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tenacity==8.0.1
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terminado==0.15.0
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tinycss2==1.1.1
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toml==0.10.2
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toolz==0.11.2
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tornado==6.1
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traitlets==5.2.2.post1
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typing_extensions==4.2.0
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toolz==0.12.0
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tornado==6.2
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traitlets==5.3.0
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typing_extensions==4.3.0
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tzdata==2022.1
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tzlocal==4.2
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urllib3==1.26.9
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urllib3==1.26.10
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validators==0.20.0
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watchdog==2.1.8
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watchdog==2.1.9
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wcwidth==0.2.5
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webencodings==0.5.1
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widgetsnbextension==3.6.0
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zipp==3.8.0
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widgetsnbextension==3.6.1
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zipp==3.8.1
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@@ -1,54 +0,0 @@
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import time
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from pycoingecko import CoinGeckoAPI
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import pandas as pd
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import re
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class CoinGeckoUtils:
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def __init__(self):
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self.connector = CoinGeckoAPI()
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def get_all_coins_df(self):
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coin_list = self.connector.get_coins_list()
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return pd.DataFrame(coin_list)
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def get_all_coins_markets_df(self):
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coin_list = self.connector.get_coins_markets(vs_currency="USD")
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return pd.DataFrame(coin_list)
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def get_coin_tickers_by_id(self, coin_id: str):
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coin_tickers = self.connector.get_coin_ticker_by_id(id=coin_id)
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coin_tickers_df = pd.DataFrame(coin_tickers["tickers"])
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coin_tickers_df["token_id"] = coin_id
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return coin_tickers_df
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def get_coin_tickers_by_id_list(self, coins_id: list):
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dfs = []
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for coin_id in coins_id:
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df = self.get_coin_tickers_by_id(coin_id)
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dfs.append(df)
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time.sleep(1)
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coin_tickers_df = pd.concat(dfs)
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coin_tickers_df["exchange"] = coin_tickers_df["market"].apply(
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lambda x: re.sub("Exchange", "", x["name"]))
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coin_tickers_df.drop(columns="market", inplace=True)
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coin_tickers_df["trading_pair"] = coin_tickers_df.base + "-" + coin_tickers_df.target
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return coin_tickers_df
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def get_all_exchanges_df(self):
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exchanges_list = self.connector.get_exchanges_list()
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return pd.DataFrame(exchanges_list)
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def get_exchanges_markets_info_by_id_list(self, exchanges_id: list):
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dfs = []
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for exchange_id in exchanges_id:
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df = pd.DataFrame(self.connector.get_exchanges_by_id(exchange_id)["tickers"])
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dfs.append(df)
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exchanges_spreads_df = pd.concat(dfs)
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exchanges_spreads_df["exchange"] = exchanges_spreads_df["market"].apply(
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lambda x: re.sub("Exchange", "", x["name"]))
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exchanges_spreads_df.drop(columns="market", inplace=True)
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exchanges_spreads_df["trading_pair"] = exchanges_spreads_df.base + "-" + exchanges_spreads_df.target
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return exchanges_spreads_df
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@@ -1,62 +0,0 @@
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import pandas as pd
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import requests
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from glom import *
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class MinerUtils:
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MARKETS_ENDPOINT = "https://api.hummingbot.io/bounty/markets"
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@staticmethod
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def reward_splitter(base, reward_dict):
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tmp = {"rewards_HBOT": 0, "rewards_STABLE": 0, "rewards_base": 0, }
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if "HBOT" in reward_dict:
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tmp["rewards_HBOT"] += reward_dict["HBOT"]
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if "USDC" in reward_dict:
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tmp["rewards_STABLE"] += reward_dict["USDC"]
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if "USDT" in reward_dict:
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tmp["rewards_STABLE"] += reward_dict["USDT"]
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if base in reward_dict:
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tmp["rewards_base"] += reward_dict[base]
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return pd.Series(tmp, dtype=float)
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@staticmethod
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def exchange_coingecko_id(exchange: str):
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converter = {
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"kucoin": "kucoin",
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"binance": "binance",
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"gateio": "gate",
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"ascendex": "bitmax"
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}
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return converter[exchange]
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def get_miner_stats_df(self):
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miner_data = requests.get(self.MARKETS_ENDPOINT).json()
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spec = {
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'market_id': ('markets', ['market_id']),
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'trading_pair': ('markets', ['trading_pair']),
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'exchange': ('markets', ['exchange_name']),
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'base': ('markets', ['base_asset']),
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'quote': ('markets', ['quote_asset']),
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'start_timestamp': ('markets', [("active_bounty_periods", ['start_timestamp'])]),
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'end_timestamp': ('markets', [("active_bounty_periods", ['end_timestamp'])]),
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'budget': ('markets', [("active_bounty_periods", ['budget'])]),
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'spread_max': ('markets', [("active_bounty_periods", ['spread_max'])]),
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'payout_asset': ('markets', [("active_bounty_periods", ['payout_asset'])]),
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'return': ('markets', ['return']),
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'last_snapshot_ts': ('markets', ['last_snapshot_ts']),
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'hourly_payout_usd': ('markets', ['hourly_payout_usd']),
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'bots': ('markets', ['bots']),
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'last_hour_bots': ('markets', ['last_hour_bots']),
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'filled_24h_volume': ('markets', ['filled_24h_volume']),
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'weekly_reward_in_usd': ('markets', ['weekly_reward_in_usd']),
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'weekly_reward': ('markets', ['weekly_reward']),
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'market_24h_usd_volume': ('markets', ['market_24h_usd_volume'])
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}
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r = glom(miner_data, spec)
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df = pd.DataFrame(r)
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df = pd.concat([df, df.apply(lambda x: self.reward_splitter(x.base, x.weekly_reward), axis=1)], axis=1)
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df["trading_pair"] = df.apply(lambda x: x.base + "-" + x.quote, axis=1)
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df["exchange_coingecko_id"] = df.apply(lambda x: self.exchange_coingecko_id(x.exchange), axis=1)
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return df
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