Dados do evento de 2026

pyproject.toml

@@ -16,6 +16,8 @@ dependencies = [
     "rich (>=14.0.0,<15.0.0)",
     "dash (>=3.1.0,<4.0.0)",
     "dash-bootstrap-components (>=2.0.3,<3.0.0)",
+    "numpy (>=2.5.2,<3.0.0)",
+    "matplotlib (>=3.11.1,<4.0.0)",
 ]
 
 [tool.poetry]

scripts/csv-to-graphs.py

@@ -0,0 +1,94 @@
+import re
+import textwrap
+
+from datetime import date
+from pathlib import Path
+from matplotlib import pyplot as plt
+from pandas import read_csv, DataFrame
+from typer import Typer
+from rich.console import Console
+
+
+COLUMNS_TO_EXPORT = [
+    r'.*python.*',
+    r'.*identi.*',
+    r'.*define.*',
+    r'.*defici.ncia.*',
+]
+
+cli = Typer()
+console = Console()
+
+
+def get_columns_to_export(csv: DataFrame):
+    for column_to_remove in COLUMNS_TO_EXPORT:
+        for column_name in csv.columns:
+            if re.match(column_to_remove, column_name, re.IGNORECASE):
+                yield column_name
+
+
+@cli.command()
+def main(csv: Path, year: int | None = None):
+    # Reading the CSV file
+    console.print(f'Reading the file [bold]{csv}[/bold]...')
+    csv_content = read_csv(csv)
+
+    # Reading the year from the CSV file name if not provided
+    if not year:
+        if re.match(r'\d{4}', csv.name):
+            year = int(re.search(r'\d{4}', csv.name).group())
+        else:
+            year = date.today().year
+
+    # Creating the export folder
+    export_path = Path(f'graphs/{year}')
+    export_path.mkdir(parents=True, exist_ok=True)
+
+    # Get only the interesting columns to export
+    columns_to_plot = list(get_columns_to_export(csv_content))
+    console.print(f'Exporting the columns [bold]{", ".join(columns_to_plot)}[/bold]...')
+
+    for column in columns_to_plot:
+        file = export_path / f'{column.replace("?", "")}.png'
+        console.print(f'Exporting [bold]{file}[/bold]...')
+
+        # Counting the column values
+        count = csv_content[column].value_counts()
+
+        # Formatting the labels to fit in the graph
+        labels = [
+            textwrap.fill(str(label), width=15)
+            for label in count.index
+        ]
+
+        plot = count.plot(
+            kind='bar',
+            xlabel='',
+            figsize=(18, 9),
+            fontsize=16,
+            color="#0C23F7",
+        )
+        plot.bar_label(
+            plot.containers[0],
+            labels=count,
+            fontsize=16,
+        )
+
+        # Adding the formatted labels
+        plot.set_xticklabels(labels)
+
+        # Keep the x-axis labels horizontal
+        plot.tick_params(
+            axis='x',
+            labelrotation=0
+        )
+
+        # Saving the graph to a file
+        figure = plot.get_figure()
+        figure.tight_layout()
+        figure.savefig(file)
+        plt.close(figure)
+
+
+if __name__ == '__main__':
+    cli()

scripts/pretix-excel-to-csv.py

@@ -0,0 +1,75 @@
+import re
+
+from pathlib import Path
+from pandas import read_excel, DataFrame
+from typer import Typer
+from rich.console import Console
+
+
+EMPTY_CELL_TEXT = 'Não respondeu'
+SHEET_NAME = 'Posição dos pedidos'
+COLUMNS_TO_REMOVE = [
+    r'.*do.evento',
+    r'.*do.pedido',
+    r'.*id\s.*',
+    r'status',
+    r'email',
+    r'.*telefone.*',
+    r'varia.*o',
+    r'taxa.*',
+    r'regra.*',
+    r'valor.*',
+    r'nome.do.*',
+    r'zona.do.*',
+    r'fileira.do.*',
+    r'n.mero.do.*',
+    r'empresa.*',
+    r'endere.o',
+    r'c.digo.*',
+    r'voucher.*',
+    r'segredo.*',
+    r'bloqueado',
+    r'v.lido.*',
+    r'coment.rio.*',
+    r'.*fatura.*',
+    r'.*acompanhamento',
+    r'.*vendas',
+    r'.*check-in',
+    r'.*link.*',
+]
+
+
+cli = Typer()
+console = Console()
+
+
+def get_columns_to_remove(excel_content: DataFrame):
+    for column_to_remove in COLUMNS_TO_REMOVE:
+        for column_name in excel_content.columns:
+            if re.match(column_to_remove, column_name, re.IGNORECASE):
+                yield column_name
+
+
+@cli.command()
+def convert(excel: Path):
+    # Reading the Excel file
+    console.print(f'Reading the file [bold]{excel}[/bold]...')
+    excel_content = read_excel(excel, sheet_name=SHEET_NAME)
+
+    # Removing columns with sensive data
+    columns_to_remove = list(get_columns_to_remove(excel_content))
+    console.print(f'Removing columns [bold]{", ".join(columns_to_remove)}[/bold]...')
+    excel_content.drop(columns=columns_to_remove, inplace=True)
+
+    # Filling empty cells with a default text
+    console.print(f'Filling empty cells...')
+    excel_content.fillna(EMPTY_CELL_TEXT, inplace=True)
+
+    # Writting the output CSV file
+    output_path = excel.with_suffix('.csv')
+    console.print(f'Saving data to [bold]{output_path}[/bold]...')
+    excel_content.to_csv(output_path, index=False)
+
+
+if __name__ == '__main__':
+    cli()