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====== Dinamica EGO and Python Coupling ======

=== Example: Calculate Python Expression ===

An expression that can be used:
<code>
dinamica.package("numpy")

a = numpy.arange(15).reshape(3, 5)
print(a)

print(dinamica.inputs)
for row in dinamica.inputs["t1"]:
 print(row)

for row in dinamica.inputs["t2"]:
 print(row)

dinamica.outputs["teste"] = 2
dinamica.outputs["teste2"] = 2.5
dinamica.outputs["teste3"] = 'a'
dinamica.outputs["outraSaida"] = "yoyo"
dinamica.outputs["tabela"] = dinamica.prepareTable(dinamica.inputs["t1"], 3)
dinamica.outputs["lut"] = dinamica.prepareLookupTable(dinamica.inputs["t2"])
</code>

where:
<code>
dinamica.package("numpy")
</code>
Ask the PIP to install the numpy package and import it:
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<code>
print(dinamica.inputs)
</code>
Prints the vector with all the entries passed by Dinamica:
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<code>
dinamica.outputs["teste2"] = 2.5
</code>
Place an output in the struct named "test2", containing a double with a value of 2.5:
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<code>
dinamica.outputs["tabela"] = dinamica.prepareTable(dinamica.inputs["t1"], 3)
</code>
Place an output in the struct named "table", containing a table with 3 key columns. This function is not necessary if the table already has '*' in the column names (so the user could only do dinamica.outputs ["teste2"] = dinamica.inputs ["t1"]). Every table in Python is treated as a list of lists, where each internal list corresponds to a ** row ** of the table:
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<code>
dinamica.outputs["lut"] = dinamica.prepareLookupTable(dinamica.inputs["t2"])
</code>
Put an output in the struct named "lut", containing a LookupTable (There is no other way to pass a LookupTable back):

----

=== Calculate Python Utilities ===

^ Utility Name ^ Description ^ Parameters ^
| package | It imports the module requested. | str packageName, str installPath=None, str loadPath=None | 
| prepareTable | It returns the table prepared to output. Input Table has to be in the form [[[header1...headerN][line1]...[lineM]]] where the first list contains the headers of the table and all the other lists are lines containing the data. | list(list) inputTable, int numKeys |
| prepareLookupTable | It returns the lookup table prepared to output. The lut has to be in the form [[[key,value][line1]...[lineM]]] where the first list contains the headers of the table and all the other lists are lines containing the data. | list(list) lut |
| toTable | It returns a valid representation of dinamica table to output. Input Table can be: [[[header1...headerN][line1]...[lineM]]] where the first list contains the headers of the table and all the other lists are lines containing the data; {header1: [valuesOfColumn1], header2: [valuesOfColumn2]...} where the valuesOfComlumn# are all values of that column in table; [[(header1...headerN)(line)...(lineM)]] where the first tuple contains the headers of the table and all the other tuples are lines containing the data; [value1, value2, ..., valueN], those are the values for a lookup table with sequential key; pandas.Dataframe is a commom structure table used to manipulate CSVs; numpy.array is a commom structure for matrix, that can be tables as well. The first line of matrix needs to be the table header. | list(list);dict(list);list(tuple);list;pandas.DataFrame;numpy.array inputTable |

See the documentation about [[Calculate Python Expression]] for further information about to use Python together with Dinamica EGO.

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