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SRA_PRUDENTIAL_RUN

Records the prudential run details for each prudential date

Column Schema

PRUDENTIAL_DATE

The prudential date of the run.

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is mandatory, and a primary key.

Example: 2022/10/12 04:00:05

PRUDENTIAL_RUNNO

The prudential run number for the run

SQL Type: NUMBER(8) Polars Type: pl.UInt32

This column is mandatory, and a primary key.

Examples: 1, 25

New Data Timing

After each settlement run

Code Examples

Polars

Casting is enums, categoricals etc is not essential, but may speed up parsing. Swapping int for pl.UInt16, pl.Int32 would also speed up parsing. However some of the datatypes are inferred, so they may be wrong.

This code deduplicates for you. Deduplication is normally only required across multiple months.

This code assumes that all columns are present, which may not be true for older files.

import polars as pl
import polars.selectors as cs

# e.g. "2029/03/15 00:05:00"
dt_s_fmt = "%Y/%m/%d %H:%M:%S"

csv_paths = ["SOMEFILE.CSV", "OTHERFILE.CSV"]

lf = (
    pl.concat(
        [
            pl.scan_csv(
                csv_path,  # must be unzipped beforehand
                skip_rows=1,  # skip the header
                infer_schema=False,  # much faster
            )
            .filter(cs.by_index(0) == "D")  # drop the footer
            .select(~cs.by_index(range(4)))  # drop metadata columns
            for csv_path in csv_paths
        ],
        how="diagonal_relaxed",
    )
    .with_columns(
        pl.col("PRUDENTIAL_DATE").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast({"PRUDENTIAL_RUNNO": int})  # or pl.UInt32
    # Deduplicate
    # We want one row per ['PRUDENTIAL_DATE', 'PRUDENTIAL_RUNNO']
    .unique(subset=["PRUDENTIAL_DATE", "PRUDENTIAL_RUNNO"], keep="any")
)

Nemosis

This table is not yet available in Nemosis.

Example File

From PUBLIC_ARCHIVE_SRA_PRUDENTIAL_RUN_FILE01_202609010000.zip

PRUDENTIAL_DATEPRUDENTIAL_RUNNO
2023/09/29 20:00:053
2023/09/30 04:00:001
2023/09/30 11:00:052
2023/09/30 20:00:053
2023/10/01 04:00:051
2023/10/01 11:00:052
2023/10/01 20:00:053
2023/10/02 04:00:051
2023/10/02 11:00:052
2023/10/02 20:00:053
2023/10/03 04:00:051
...

CSETP.WORLDDVD_SRA_PRUDENTIAL_RUNAEMOPUBLIC2026/10/0916:34:11001791527651195MONTHLY_ARCHIVE001791527651195
IIRAUCTIONSRA_PRUDENTIAL_RUN1PRUDENTIAL_DATEPRUDENTIAL_RUNNO
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/09/29 20:00:053
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/09/30 04:00:001
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/09/30 11:00:052
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/09/30 20:00:053
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/01 04:00:051
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/01 11:00:052
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/01 20:00:053
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/02 04:00:051
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/02 11:00:052
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/02 20:00:053
DIRAUCTIONSRA_PRUDENTIAL_RUN12023/10/03 04:00:051
...
CEND OF REPORT1003

PRUDENTIAL_DATE,PRUDENTIAL_RUNNO
"2023/09/29 20:00:05",3
"2023/09/30 04:00:00",1
"2023/09/30 11:00:05",2
"2023/09/30 20:00:05",3
"2023/10/01 04:00:05",1
"2023/10/01 11:00:05",2
"2023/10/01 20:00:05",3
"2023/10/02 04:00:05",1
"2023/10/02 11:00:05",2
"2023/10/02 20:00:05",3
"2023/10/03 04:00:05",1
...

C,SETP.WORLD,DVD_SRA_PRUDENTIAL_RUN,AEMO,PUBLIC,2026/10/09,16:34:11,001791527651195,MONTHLY_ARCHIVE,001791527651195
I,IRAUCTION,SRA_PRUDENTIAL_RUN,1,PRUDENTIAL_DATE,PRUDENTIAL_RUNNO
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/09/29 20:00:05",3
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/09/30 04:00:00",1
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/09/30 11:00:05",2
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/09/30 20:00:05",3
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/01 04:00:05",1
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/01 11:00:05",2
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/01 20:00:05",3
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/02 04:00:05",1
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/02 11:00:05",2
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/02 20:00:05",3
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,"2023/10/03 04:00:05",1
...
C,"END OF REPORT",1003

Availability

Visibility: Public

This table is in the public monthly MMSDM archive.

I have collated the list of all those files into one place, in this CSV metadata file. (Columns year, month, url, compressed_size in bytes).

The earliest available data is month 8 of 2024. The most recent available data is month 9 of 2026.

Every month in between has a file. (No gaps.)

Data Size

Each year of data is approximately 254 KB when zipped, 3 MB as unzipped CSV.

Deduplication and PDR Loader Configuration

The primary keys are:

The transaction type is "insert", which means that you will usually not see duplicate data. If you do, you can deduplicate based on the primary keys, without sorting first. Rows from different files with the same primary keys should have the same values.

PDR Loader configuration is:

Report Name Report Subtype Version
IRAUCTION SRA_PRUDENTIAL_RUN 1

This means that the CSV files start with metadata columns:

I,IRAUCTION,SRA_PRUDENTIAL_RUN,1,...
D,IRAUCTION,SRA_PRUDENTIAL_RUN,1,...

This page as JSON (schema documented here, but may change)

Download a JSON Schema specification for this table.

Official AEMO schema documentation

Other Information

Package: IRAUCTION