I have created a pyDataset, 2R x 2C, I would like to convert it to dictionary then to jsonFormat.
An example for the pyDataset,
Header = [Fruit, Cost]
Row1 = [Apple, 5]
Row2 =[Pear, 1]
I have manage to do it manually, with the single code below. Is there any alternative to execute it if I have x amount of row and column in my dataset?
I manage to solve the conversion, below is the code:
MainData = []
i = 0
while i < pyData.getRowCount():
MainData.append("Data" + str(i))
i = i + 1
NewDict = {}
row = 0
col = 0
for j in MainData:
NewDict[j] = {}
for k in Header:
NewDict[j][k] = pyData.getValueAt(row, col)
col = col + 1
row = row + 1
col = 0
jsonNewStr = system.util.jsonEncode(NewDict, 5)
print jsonNewStr
Also, if you use zip you can iterate through multiple objects at once.
Also-also, list and dictionary comprehensions are useful to learn.
Header = pyData.getColumnNames()
NewDict= {}
for row, i in zip(pyData, range(pyData.getRowCount())):
NewDict['Data'+str(i)] = {colName:value for colName, value in zip(Header, list(row))}
def dictListToDataset(dictValues, defColumns=None):
"""
This will take a python list of dictionaries.
The dictionaries will contain Name/Value pairs where the Name field will become the Column Name for the resulting Ignition Dataset.
Each dictionary row MUST match, it must contain the same Name/Value pairs with the Values being the same data type.
Arguments:
dictValues: The input list of dictionaries
Results:
Dataset: A built dataset containing all the Rows and Columns extracted from the dictionaries.
"""
logger = shared.MWES.Logging.getLog(lib=libName, src=srcName, autoMethod=True )
data = []
columns = defColumns
for obj in dictValues:
if columns == None:
columns = obj.keys()
row = []
for column in columns:
row.append(obj[column])
data.append(row)
if columns != None:
logger.debug("Columns %s, Data %s" % (str(columns), str(data)))
return system.dataset.toDataSet(columns,data)
else:
raise ValueError('could not find dictionary keys in %s' % (str(dictValues)))
def datasetToDictList(dataset):
"""
This will take an Igntion Dataset and convert it to a real python list of dictionaries. Unlike the PyDataset type.
The resulting dictionaries will contain Name/Value pairs where the Name field is derived from the Column Name in the Ignition Dataset.
Arguments:
dataset: The input Ignition Dataset
Results:
List of Dictionary Elements: A built list of dictionary rows containing all the Rows and Columns extracted from the dataset.
"""
# logger = shared.MWES.Logging.getLog(lib=libName, src=srcName, autoMethod=True )
data = []
columns = list(system.dataset.getColumnHeaders(dataset))
pyDataset = system.dataset.toPyDataSet(dataset)
return pyDatasetToDictList ( pyDataset, columns )
def pyDatasetToDictList( *args, **kwargs ):
"""
This will take an Igntion PyDataset and convert it to a real python list of dictionaries. Unlike the PyDataset type.
The resulting dictionaries will contain Name/Value pairs where the Name field is derived from the Column Name in the Ignition PyDataset.
Arguments:
pyDataset: The input Ignition PyDataset
columns: Optional list of column names to extract
Results:
List of Dictionary Elements: A built list of dictionary rows containing all the Rows and Columns extracted from the dataset.
"""
# logger = shared.MWES.Logging.getLog(lib=libName, src=srcName, autoMethod=True )
pyDataset = None
columns = None
idx = 0
sz = len(args)
pyDataset = shared.MWES.Args.getParam( sz, idx, "PyDataset", False, True, args, kwargs )
idx+=1
columns = shared.MWES.Args.getParam( sz, idx, "Columns", None, False, args, kwargs )
idx+=1
data = []
if pyDataset == None:
return data
if columns == None:
columns = list(system.dataset.getColumnHeaders(system.dataset.toDataset(pyDataset)))
for row in pyDataset:
rowMap = {}
for col in columns:
rowMap[col] = row[col]
data.append(rowMap)
return data
It would have been really NICE if the pyDataset did the above for us!!!
I’ve used @sfitze 's code, but I want my table to have this as data and read it as an array.
But it’s making it an object of objects instead of an array of objects.
I can fix it by right clicking in the properties and using ‘change to array’, but it reverts when the data changes.
Is there a way to force it to interpret this as an array of objects?
Thanks
I actually managed this by using the my_dictionary.values() as the return, instead of just my_dictionary.
Thanks for the response though! I didn’t get a reply notification for some reason
Imagine several input boxes, numeric, text and drop down, then a button. The button will take all values from the input boxes, and move them into an array of objects. Now, a table is bound to this array. I manually created this array and entered the values: (the name, when copied and pasted, doesn't show, and neither does the object identifier: Name: temp_table, object identifier: 0
the table displays the field names and values, as expected, BUT, I am not sure how to add another object to this array with the button's script. So I found this thread, which I think might have some value here.
Bottom line of the function I would like is each time the button is clicked, for the values to be added to the array... Hm, unless of course the values are the same...
