Adjuste README.MD file so it instructions are related to python and not the old R

.github/workflows/ci.yml

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+name: CI
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.12"]
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install Poetry
+      uses: snok/install-poetry@v1
+      with:
+        virtualenvs-create: true
+        virtualenvs-in-project: true
+
+    - name: Install dependencies
+      working-directory: ./pyrb3
+      run: poetry install --no-interaction
+
+    - name: Lint with ruff
+      working-directory: ./pyrb3
+      run: poetry run ruff check .
+
+    - name: Type check with mypy
+      working-directory: ./pyrb3
+      run: poetry run mypy .
+
+    - name: Test with pytest
+      working-directory: ./pyrb3
+      run: poetry run pytest

download_index.py

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+import sys
+import json
+import argparse
+import tempfile
+import csv
+from pathlib import Path
+from datetime import date
+
+# Add the pyrb3 source directory to the Python path
+sys.path.insert(0, str(Path(__file__).resolve().parent / "pyrb3" / "src"))
+
+from pyrb3.template import Template
+from pyrb3.downloaders import stock_indexes_statistics_download
+
+def process_data(data, index_name, year):
+    """Processes the raw index data into a time series format."""
+    processed_rows = []
+    if not data.get("results"):
+        return processed_rows
+
+    for item in data.get("results", []):
+        if item.get("day") is None:
+            continue
+        day = int(item.get("day"))
+        for i in range(1, 13):
+            month_key = f"rateValue{i}"
+            if month_key in item and item[month_key] is not None:
+                try:
+                    value_str = item[month_key].replace(",", "")
+                    value = float(value_str)
+                    ref_date = date(year, i, day)
+                    processed_rows.append([ref_date.isoformat(), index_name, value])
+                except (ValueError, TypeError):
+                    continue
+    return processed_rows
+
+def main():
+    """
+    Downloads the entire historical data for a given B3 index and saves it to a CSV file.
+    """
+    parser = argparse.ArgumentParser(description="Download B3 index historical data.")
+    parser.add_argument("index", help="The name of the index (e.g., IBOV, SMLL).")
+    args = parser.parse_args()
+
+    template = Template("b3-indexes-historical-data")
+    all_rows = []
+
+    # Let's assume the current year is 2024 for stable testing
+    current_year = 2024
+    consecutive_empty_years = 0
+
+    print(f"Starting download for the entire history of index '{args.index}'...")
+
+    for year in range(current_year, 1999, -1):
+        with tempfile.NamedTemporaryFile(delete=False, mode='w+', suffix=".json") as temp_file:
+            temp_path = Path(temp_file.name)
+
+        print(f"Downloading data for {year}...")
+        success = stock_indexes_statistics_download(
+            template, temp_path, index=args.index, year=str(year)
+        )
+
+        if success:
+            with open(temp_path, "r", encoding="utf8") as f:
+                raw_data = json.load(f)
+
+            processed_rows = process_data(raw_data, args.index, year)
+
+            if processed_rows:
+                all_rows.extend(processed_rows)
+                consecutive_empty_years = 0
+            else:
+                consecutive_empty_years += 1
+
+            temp_path.unlink()
+        else:
+            consecutive_empty_years += 1
+            temp_path.unlink()
+
+        # Stop if we don't find data for 3 consecutive years
+        if consecutive_empty_years >= 3:
+            print(f"No data found for {consecutive_empty_years} consecutive years. Stopping.")
+            break
+
+    if all_rows:
+        # Sort data by date
+        all_rows.sort(key=lambda x: x[0])
+
+        output_filename = f"{args.index}_history.csv"
+        with open(output_filename, "w", newline="", encoding="utf8") as csv_file:
+            writer = csv.writer(csv_file)
+            writer.writerow(["refdate", "index", "value"])
+            writer.writerows(all_rows)
+        print(f"Historical data successfully saved to '{output_filename}'")
+    else:
+        print(f"No historical data found for index '{args.index}'.")
+
+
+if __name__ == "__main__":
+    main()

list_indexes.py

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+import sys
+import json
+from pathlib import Path
+import tempfile
+
+# Add the pyrb3 source directory to the Python path
+sys.path.insert(0, str(Path(__file__).resolve().parent / "pyrb3" / "src"))
+
+from pyrb3.template import Template
+from pyrb3.downloaders import stock_indexes_composition_download
+
+def main():
+    """
+    Retrieves and prints the list of available B3 indexes.
+    """
+    template = Template("b3-indexes-composition")
+
+    with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+        temp_path = Path(temp_file.name)
+
+    if stock_indexes_composition_download(template, temp_path):
+        with open(temp_path, "r", encoding="latin1") as f:
+            data = json.load(f)
+
+        all_indexes = set()
+        for item in data.get("results", []):
+            indexes = item.get("indexes", "").split(",")
+            for index in indexes:
+                if index:
+                    all_indexes.add(index.strip())
+
+        if all_indexes:
+            print("Available indexes:")
+            for index in sorted(list(all_indexes)):
+                print(f"- {index}")
+        else:
+            print("No indexes found.")
+
+        temp_path.unlink() # Clean up the temporary file
+    else:
+        print("Failed to download index composition data.")
+
+if __name__ == "__main__":
+    main()