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Match flat and matrix layouts to the export you have. Keep the units file with the data; choose flows or coefficients explicitly.

Import#

import mario

db = mario.parse_from_txt(
    path="iot_export_csv", table="IOT", mode="flows", _format="csv", flat=True,
)

Result · A MARIO database. Inspect db, db.get_index("all") and db.units before selecting quantities for your analysis.

Inputs and options#

Key arguments and directory layout

Use mario.parse_from_txt(...) for TXT or CSV payloads and mario.parse_from_parquet(...) for Parquet payloads.

Key arguments:

  • path: directory containing the files to parse;

  • table: choose "IOT" or "SUT";

  • mode: choose "flows" or "coefficients";

  • flat: set True for long-format payloads;

  • sep and _format: TXT or CSV only;

  • matrix_layouts: optional semantic declaration for non-standard matrix layouts;

  • tech_assumption: optional SUT selector for IT or PT.

Matrix-per-file payloads look like:

custom_txt_database/
├── Z.csv
├── Y.csv
├── V.csv
├── E.csv
├── EY.csv
└── units.csv

Flat payloads can use one combined data file plus units, or one flat file per matrix plus units. The same directory logic applies to Parquet.

Packaged example directories

The parser examples below use exported database folders bundled with the documentation:

Extract each archive locally and point path to the inner flows or coefficients directory shown in the code examples below.

import mario
Matrix-per-file TXT or CSV

Use flat=False for the historical matrix-per-file layout.

db = mario.parse_from_txt(
    path="/path/to/iot_export_csv/flows",
    table="IOT",
    mode="flows",
    _format="csv",
    flat=False,
)
Flat TXT or CSV

Use flat=True for long-format payloads. MARIO accepts either one combined data file or separate flat files per matrix, as long as units is present.

db = mario.parse_from_txt(
    path="/path/to/iot_export_csv",
    table="IOT",
    mode="coefficients",
    _format="csv",
    flat=True,
)
Flat Parquet

The same logic applies to Parquet exports.

db = mario.parse_from_parquet(
    path="/path/to/iot_export_parquet",
    table="IOT",
    mode="flows",
    flat=True,
)
Reference notes and caveats

These parsers are directory-based. path must point to one directory, not to one individual file.

Use flat=True for long-format payloads. For TXT or CSV parsing, _format and sep matter; for Parquet parsing they do not.

The same semantic rules used for custom Excel parsing also apply here: if one IOT layout carries extra semantic levels, declare them through matrix_layouts= instead of relying on filename conventions alone.

These formats are usually preferable to Excel when the data already comes from a MARIO export or from an automated preprocessing workflow.

Continue with Inspect and query a database or Calculate matrices.