Difference between revisions of "Statistical Algorithms Importer: Python Project"
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| − | :This page explains how to create a Python project using the Statistical Algorithms Importer (SAI) portlet. | + | :This page explains how to create a Python project using the [[Statistical_Algorithms_Importer|Statistical Algorithms Importer (SAI)]] portlet.Currently two types of projects can be created, one specific for version 3.6 and one generic one which is executed with version 2.7. |
[[Image:StatisticalAlgorithmsImporter_PythonBlackBox0.png|thumb|center|250px|Python Project, SAI]] | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox0.png|thumb|center|250px|Python Project, SAI]] | ||
| + | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox5.png|thumb|center|250px|Python 3.6 Project, SAI]] | ||
==Project Configuration== | ==Project Configuration== | ||
:Define project's metadata | :Define project's metadata | ||
| − | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox1.png|thumb|center| | + | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox1.png|thumb|center|750px|Python Info, SAI]] |
:Add input and output parameters and click on "Set Code" to indicate the main file to execute (i.e. the .py file) | :Add input and output parameters and click on "Set Code" to indicate the main file to execute (i.e. the .py file) | ||
| − | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox2.png|thumb|center| | + | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox2.png|thumb|center|750px|Python I/O, SAI]] |
:Add information about the running environment (e.g. Python version etc.) | :Add information about the running environment (e.g. Python version etc.) | ||
| − | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox3.png|thumb|center| | + | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox3.png|thumb|center|750px|Python Interpreter, SAI]] |
:After the [https://wiki.gcube-system.org/gcube/Statistical_Algorithms_Importer:_Create_Software software creation phase] a Main.R file and a Taget folder are created | :After the [https://wiki.gcube-system.org/gcube/Statistical_Algorithms_Importer:_Create_Software software creation phase] a Main.R file and a Taget folder are created | ||
| − | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox4.png|thumb|center| | + | [[Image:StatisticalAlgorithmsImporter_PythonBlackBox4.png|thumb|center|750px|Python Create, SAI]] |
== Example Code == | == Example Code == | ||
:Python code in sample: | :Python code in sample: | ||
| − | < | + | <source lang='python'> |
# | # | ||
# author Giancarlo Panichi | # author Giancarlo Panichi | ||
| Line 34: | Line 35: | ||
out_file.write("Hello World\n"+arg+"\n") | out_file.write("Hello World\n"+arg+"\n") | ||
out_file.close() | out_file.close() | ||
| − | </ | + | </source> |
==Example Download== | ==Example Download== | ||
[[File:PythonBlackBox.zip|PythonBlackBox.zip]] | [[File:PythonBlackBox.zip|PythonBlackBox.zip]] | ||
| + | |||
| + | ==Inheritance of Global and Infrastructure Variables== | ||
| + | At each run of the process the '''globalvariables.csv''' file is created locally to the process (i.e. it can be read as ./globalvariables.csv), which contains the following global variables that are meant to allow the process to properly contact the e-Infrastructure services: | ||
| + | |||
| + | * '''gcube_username''' (the user who run the computation, e.g. gianpaolo.coro) | ||
| + | |||
| + | * '''gcube_context''' (the VRE the process was run in, e.g. d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab) | ||
| + | |||
| + | * '''gcube_token''' (the token of the user for the VRE, e.g. 1234-567-890) | ||
| + | |||
| + | The format of the CSV file is like the one of the following example: | ||
| + | |||
| + | <source lang='vim'> | ||
| + | globalvariable,globalvalue | ||
| + | gcube_username,gianpaolo.coro | ||
| + | gcube_context,/d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab | ||
| + | gcube_token,1234-567-890 | ||
| + | </source> | ||
<!-- | <!-- | ||
Latest revision as of 16:04, 22 November 2018
- This page explains how to create a Python project using the Statistical Algorithms Importer (SAI) portlet.Currently two types of projects can be created, one specific for version 3.6 and one generic one which is executed with version 2.7.
Project Configuration
- Define project's metadata
- Add input and output parameters and click on "Set Code" to indicate the main file to execute (i.e. the .py file)
- Add information about the running environment (e.g. Python version etc.)
- After the software creation phase a Main.R file and a Taget folder are created
Example Code
- Python code in sample:
# # author Giancarlo Panichi # # HelloWorld # import sys for arg in sys.argv: 1 out_file = open("helloworld.txt","w") out_file.write("Hello World\n"+arg+"\n") out_file.close()
Example Download
Inheritance of Global and Infrastructure Variables
At each run of the process the globalvariables.csv file is created locally to the process (i.e. it can be read as ./globalvariables.csv), which contains the following global variables that are meant to allow the process to properly contact the e-Infrastructure services:
- gcube_username (the user who run the computation, e.g. gianpaolo.coro)
- gcube_context (the VRE the process was run in, e.g. d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab)
- gcube_token (the token of the user for the VRE, e.g. 1234-567-890)
The format of the CSV file is like the one of the following example:
globalvariable,globalvalue gcube_username,gianpaolo.coro gcube_context,/d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab gcube_token,1234-567-890
