This release is a pre-release and may not be stable for production use.
PSR Factory
Factory is a library that helps to manage SDDP cases. It contains functions that create, load, and save studies, and also functions that create, access, and modify objects in a study.
Installation
Open the command prompt and run the following command:
pip install psr-factory
Factory will be available to all Python scripts in your system after importing it:
import psr.factory
Usage sample
import psr.factory
study = psr.factory.load_study(r"C:\temp\my\study")
system_1 = study.find("System.*")[0]
battery = study.create("Battery")
battery.code = 1
battery.name = "Battery 1"
battery.set("InstalledCapacity", 10.0)
battery.set("RefSystem", system_1)
study.add(battery)
study.save(r"C:\temp\my\updated_study")
Reading results
load_dataframe reads a result file whole. When one is too large for that --
an hourly case easily is -- scan_dataframe reads it in batches, so memory
follows the batch size and not the file size:
import psr.factory
with psr.factory.scan_dataframe(r"C:\case\gerter.hdr",
batch_rows=100_000,
filter_agents=["Thermal 1"]) as scan:
peak = max(float(batch["Thermal 1"].max()) for batch in scan)
psr.factory.write_dataframe(destination, scan) writes one back the same
way, so a whole file-to-file transform never holds either end. Batches are
ordinary DataFrame objects: index them with numpy, or convert with
to_pandas() / to_polars(), or hand them straight to pyarrow, polars or
DuckDB through the Arrow protocol.
Setting psr.factory.set_setting("FAST_RESULT_READER", True) selects a
faster reader for the common result formats, falling back automatically for
the rest.
Full documentation
The full documentation and reference is available at https://docs.psr-inc.com/knowledgehub/solutions/additional_tools/factory/getting_started/introduction.html.
Releases
New releases can be found in PyPI website at https://pypi.org/project/psr-factory.
And the release notes at https://psrenergy-docs.github.io/factory/releases.html.
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