AutoCAD, Python and Pandas

 

Pandas “pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.”

 You can also use pandas in AutoCAD as a data extraction tool. I’m just learning pandas myself, thankfully there’s good documentation

In this example, I want to search for all block references that begin with ‘SPK’,  to create a takeoff of what sprinkler systems are in this drawing. Then, I’ll use pandas to combine rows and format the output. I’m just printing the output to the command line, but it’s simple enough to create a table or export the data to Excel

 here's the code

import PyRx as Rx

import PyGe as Ge

import PyGi as Gi

import PyDb as Db

import PyAp as Ap

import PyEd as Ed

import traceback

import pandas as pd

#get the attribues and return them as a list

def getAttValues(ref: Db.BlockReference)->list[str]:

    v = [ref.getBlockName()]

    for attrefid in ref.attributeIds():

        attref = Db.AttributeReference(attrefid)

        match attref.tag():

            case 'PART#':

                v.append(attref.textString())

            case 'DESCRIPTION':

                v.append(attref.textString())

            case _:

                pass

    return v

def PyRxCmd_doit():

    try:

        spkIds = []

        db = Db.curDb()

        #define our columns

        data = {'Name': [],

                'PART#': [],

                'DESCRIPTION': [],

                'QTY': []}

        #search for blocks that start with 'SPK'

        bt = Db.BlockTable(db.blockTableId())

        for name, id in bt.toDict().items():

            if name.startswith('SPK'):

                spkIds.append(id)

        for id in spkIds:

            btr = Db.BlockTableRecord(id)

            for refid in btr.getBlockReferenceIds():

                ref = Db.BlockReference(refid)

                values = getAttValues(ref)

               

                #pandas wants equal length lists

                if len(values) != 3:

                    continue

               

                data['Name'].append(values[0].rstrip('.dwg'))

                data['PART#'].append(values[1])

                data['DESCRIPTION'].append(values[2])

                data['QTY'].append(1) #we know we have one

        #create the dataframe, then group by

        df = pd.DataFrame(data)

        dfgr = df.groupby(['Name', 'PART#', 'DESCRIPTION'],

                         sort=False, as_index=False).agg({'QTY': 'sum'})

       

        print(dfgr.to_string())

    except Exception as err:

        traceback.print_exception(err)