Published January 15, 2024 | Version 3.4.5
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REPOPSI Metadata Enricher (Python)

  • 1. University of Belgrade - Vinča Institute of Nuclear Sciences

Description

This upload contains a copy of the repopsi_csv_metadata.py file with annotations in English.

To run the Python script, you must install Python 3 (minimum version 3.8.5) on your computer. You can download official Python distributions from Python.org. Installing Python is relatively simple and many excellent online tutorials on that subject exist.

After Python is installed, it is necessary to install two additional Python libraries: pandas and requests. That can be done by following these steps:
1. open Windows Command Prompt;
2. type "pip install requests==2.31.0" (without quotations);
3. press Enter;
Repeat the same process for pandas library, just in step 2. type "pip install pandas==2.0.2".

Other libraries necessary for the script to work come with Python installation by default.

Download the script and move it to a desired (preferably empty) folder. Run a script and XML documents with enriched metadata will be generated in the same folder where the script is located. To run a Python script you can check out this tutorial: https://realpython.com/run-python-scripts/.

The script will open a black Command Prompt window with the line "Input row number: " where you enter the number of the row from the REPOPSI_inventory.csv file that needs to be parsed. After pressing the Enter button, the window will close and a new XML document will be generated in the same folder where the script is located.

The Python script was written by Obrad Vučkovac, with the help and support from other members of the REPOPSI project team (Aleksandra Lazić, Danka Purić, Ljiljana Lazarević, and Iris Žeželj).

Notes

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101017536 and is supported by the EOSC Future (https://eoscfuture.eu/) through the RDA (https://www.rd-alliance.org/) Open Call mechanism (https://eoscfuture-grants.eu/provider/research-data-alliance), based on evaluations of external, independent experts.

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readme.txt

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