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Nós temos um resumo completo e guia de início rápido em Português Brasileiro disponível!

pyreps¶

Python report generation — CSV, XLSX, and PDF with Rust performance. :zap:

High Performance

Streaming pipeline with constant memory. XLSX via Rust, JSON via orjson. 500K rows using < 1 MB of RAM.
Easy Integration

Supports list[dict], JSON, SQL. Optional declarative types. Ready for Django, FastAPI, Celery.
3 Formats

CSV, XLSX, and PDF with a single API. Switch formats by changing a parameter.
Lightweight & No Bloat

3 runtime dependencies. No pandas, no numpy. Install and use in seconds.

Installation¶

pip install pyreps

Or with uv:

uv add pyreps

Quickstart¶

from pyreps import ColumnSpec, ReportSpec, generate_report

# data sample
data = [
    {"id": 1, "customer": {"name": "Ana"}, "total": 100.50},
    {"id": 2, "customer": {"name": "Bruno"}, "total": 250.00},
]

spec = ReportSpec(
    output_format="csv",  # or "xlsx" or "pdf"
    columns=[
        ColumnSpec(label="ID", source="id", type="int"),
        ColumnSpec(label="Customer", source="customer.name"),
        ColumnSpec(label="Total", source="total", type="float",
                   formatter=lambda v: f"$ {v:.2f}"),
    ],
)

generate_report(data_source=data, spec=spec, destination="sales.csv")

Next step

Check the Quickstart for full examples for each format.

Architecture¶

graph LR
    A[Data Source] --> B[InputAdapter]
    B --> C[Mapping + Coercion]
    C --> D[Renderer]
    D --> E[CSV / XLSX / PDF]

    style A fill:#e3f2fd
    style E fill:#e8f5e9

The pipeline is 100% streaming for CSV and XLSX — each record is processed and discarded without accumulating in memory. PDF uses chunked streaming (O(chunk_size)); see Performance for details.

Links¶