|
import gradio as gr |
|
import pandas as pd |
|
from tabs.market_plots import ( |
|
plot_top_10_ranking_by_nr_trades, |
|
plot_trades_and_traders_ranking, |
|
plot_wordcloud_topics, |
|
) |
|
import logging |
|
from huggingface_hub import hf_hub_download |
|
|
|
|
|
def get_logger(): |
|
logger = logging.getLogger(__name__) |
|
logger.setLevel(logging.DEBUG) |
|
|
|
stream_handler = logging.StreamHandler() |
|
stream_handler.setLevel(logging.DEBUG) |
|
formatter = logging.Formatter( |
|
"%(asctime)s - %(name)s - %(levelname)s - %(message)s" |
|
) |
|
stream_handler.setFormatter(formatter) |
|
logger.addHandler(stream_handler) |
|
return logger |
|
|
|
|
|
def load_data(): |
|
|
|
closed_markets_df = hf_hub_download( |
|
repo_id="valory/Olas-predict-dataset", |
|
filename="closed_market_metrics.parquet", |
|
repo_type="dataset", |
|
) |
|
df = pd.read_parquet(closed_markets_df) |
|
|
|
return df |
|
|
|
|
|
logger = get_logger() |
|
logger.info("Loading data from Olas predict dataset") |
|
market_metrics = load_data() |
|
demo = gr.Blocks(theme=gr.themes.Origin()) |
|
with demo: |
|
gr.HTML("<h1>Prediction markets popularity dashboard (WIP)</h1>") |
|
gr.Markdown( |
|
"""This app shows the popularity ranking of prediction markets in Olas Predict. Popularity based on two main metrics: |
|
* number of generated trades on the market |
|
* number of traders active on the market. |
|
|
|
These are computed only for closed markets.""" |
|
) |
|
|
|
with gr.Tabs(): |
|
with gr.TabItem("🔥 Market Popularity metrics"): |
|
with gr.Row(): |
|
gr.Markdown("# 🔝 Top 10 markets based on number of trades") |
|
with gr.Row(): |
|
top_10_plot = plot_top_10_ranking_by_nr_trades( |
|
market_metrics=market_metrics |
|
) |
|
with gr.Row(equal_height=True): |
|
gr.Markdown( |
|
"# 🏁 Classification based on nr of trades and nr of traders" |
|
) |
|
with gr.Row(): |
|
scatterplot = plot_trades_and_traders_ranking( |
|
market_metrics=market_metrics |
|
) |
|
with gr.Row(): |
|
gr.Markdown( |
|
"# ☁️ Wordcloud composed with words from most popular markets" |
|
) |
|
with gr.Row(): |
|
wordcloud = plot_wordcloud_topics(market_metrics=market_metrics) |
|
|
|
demo.queue(default_concurrency_limit=40).launch() |
|
|
