How adrian-1bos/radar-financeiro works
Radar Financeiro is a Streamlit app for exploring an asset’s news sentiment, price trend, and price history. The user selects an asset and period, then starts an analysis: the app loads asset and keyword data, fetches and filters news, computes sentiment and trend, and displays news findings and price views. The graph separates news acquisition, sentiment analysis, and price handling. Source excerpts show these calls and external integrations; the README is empty, so undocumented capabilities are not inferred.
Main entry points: app.py Streamlit dashboard · dados.py Keyword dictionaries · news.py News aggregator · analise.py Batch sentiment analysis
Components 18
User workflow
- Streamlit dashboard
app.py - Asset catalog
core/dados.py - Asset database
data/ativos.db - Relevant-news filter
app.py - Analysis results view
app.py
News acquisition
- News aggregator
core/news.py - NewsAPI
- Currents API
Sentiment analysis
- Keyword dictionaries
core/dados.py - General keywords
data/chave.json - Sector keywords
data/chave_setor.json - Batch sentiment analysis
core/analise.py - FinBERT model
Market data and views
- Price trend analysis
core/analise.py - Price history loader
core/grafico.py - Yahoo Finance
- Price metrics and charts
core/grafico.py
Other components
- Investor
Connections 18
- Investor → Streamlit dashboard: selects and starts
app.py - Streamlit dashboard → Asset catalog: loads assets
app.py - Asset catalog → Asset database: reads
core/dados.py - Streamlit dashboard → Keyword dictionaries: loads dictionaries
app.py - Keyword dictionaries → General keywords: reads
core/dados.py - Keyword dictionaries → Sector keywords: reads
core/dados.py - Streamlit dashboard → News aggregator: fetches news
app.py - News aggregator → NewsAPI: requests articles
core/news.py - News aggregator → Currents API: requests articles
core/news.py - Streamlit dashboard → Relevant-news filter: filters news
app.py - Relevant-news filter → Batch sentiment analysis: analyzes relevant news
app.py - Batch sentiment analysis → FinBERT model: scores text
core/analise.py - Batch sentiment analysis → Keyword dictionaries: uses keyword filters
core/analise.py - Streamlit dashboard → Price history loader: loads price history
app.py - Price history loader → Yahoo Finance: downloads prices
core/grafico.py - Streamlit dashboard → Price trend analysis: analyzes trend
app.py - Streamlit dashboard → Price metrics and charts: displays price views
app.py - Streamlit dashboard → Analysis results view: displays findings
app.py