majorsilence-reporting

Installation

Install from PyPI (Python 3.10+ required):

# PyPI
pip install majorsilence-reporting

# Or editable from source
pip install -e .

No runtime dependencies — uses only the Python standard library (subprocess, ctypes, tempfile).

Integration modes

Three classes are available depending on how you deploy the reporting engine:

Report — subprocess (dotnet)

from majorsilence_reporting import Report

rpt = Report(
    report_path  = '/path/to/report.rdl',
    rdl_cmd_path = '/path/to/RdlCmd.dll',
)
rpt.set_connection_string('Data Source=/path/to/data.db')
rpt.set_parameter('StartDate', '2026-01-01')

# Save to a file
rpt.export('pdf', '/tmp/output.pdf')

# Or get bytes in memory (e.g. for a Flask response)
data = rpt.export_to_memory('pdf')
return Response(data, mimetype='application/pdf')

ReportAot — AOT binary

Same API as Report but points at a self-contained binary instead of a DLL. No .NET runtime required on the server.

from majorsilence_reporting import ReportAot

rpt = ReportAot(
    report_path  = '/path/to/report.rdl',
    rdl_cmd_path = '/path/to/RdlCmd',   # self-contained binary, no .dll extension
)
rpt.set_connection_string('Data Source=/path/to/data.db')
data = rpt.export_to_memory('xlsx')

# ReportAot also supports xlsx_table, tifb, and mht
data = rpt.export_to_memory('xlsx_table')

report_native — in-process FFI

The native mode loads librdlnative.so directly into the Python process via ctypes. No child process is spawned, making it the lowest-latency option. It also supports true in-memory rendering — the report bytes are returned directly from the native buffer without writing a temp file.

from majorsilence_reporting.report_native import load_library, Report

# Call once at process startup. Loads librdlnative.so and all sibling libraries.
lib = load_library('/path/to/librdlnative.so')

rpt = Report(lib, report_path='/path/to/report.rdl')
rpt.set_connection_string('Data Source=/path/to/data.db')

# Returns bytes directly from the native buffer — no temp file written
data = rpt.export_to_memory('pdf')

# Pass to Django / FastAPI / Flask as a binary response
return Response(data, media_type='application/pdf')

Core API

All three classes share the same interface:

In-memory datasets

report_native.Report supports supplying data entirely in memory via add_data() — no database connection required. Pass a dataset name and a list of dicts where every value is a string.

from majorsilence_reporting.report_native import load_library, Report

lib = load_library('/path/to/librdlnative.so')
rpt = Report(lib, report_path='/path/to/report.rdl')

rpt.add_data('SalesData', [
    {'Product': 'PDF Library Pro',  'Revenue': '1200.00', 'Units': '3'},
    {'Product': 'Report Designer',   'Revenue': '250.00',  'Units': '1'},
    {'Product': 'Support (12 mo.)',  'Revenue': '500.00',  'Units': '1'},
])

data = rpt.export_to_memory('pdf')

Export formats