Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Read and parse XML from construction systems - P6 schedules, BSDD exports, IFC-XML, COBie-XML. Convert to pandas DataFrames.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
XML is used in construction for P6 schedules (XER), IFC-XML, COBie-XML, and buildingSMART Data Dictionary exports. This skill parses XML and converts to structured DataFrames.
import xml.etree.ElementTree as ET
import pandas as pd
from typing import Dict, Any, List, Optional, Union
from dataclasses import dataclass
from pathlib import Path
import re
@dataclass
class XMLElement:
"""Parsed XML element."""
tag: str
attributes: Dict[str, str]
text: Optional[str]
children: List['XMLElement']
class ConstructionXMLReader:
"""Parse XML from construction systems."""
def __init__(self):
self.namespaces: Dict[str, str] = {}
def parse_file(self, file_path: str) -> ET.Element:
"""Parse XML file and return root element."""
tree = ET.parse(file_path)
root = tree.getroot()
# Extract namespaces
self._extract_namespaces(root)
return root
def parse_string(self, xml_string: str) -> ET.Element:
"""Parse XML from string."""
root = ET.fromstring(xml_string)
self._extract_namespaces(root)
return root
def _extract_namespaces(self, root: ET.Element):
"""Extract namespace mappings."""
# Find namespace declarations
for attr, value in root.attrib.items():
if attr.startswith('{'):
ns = attr[1:attr.index('}')]
self.namespaces[root.tag.split('}')[0][1:]] = ns
def find_elements(self, root: ET.Element,
tag: str,
namespace: str = None) -> List[ET.Element]:
"""Find all elements with given tag."""
if namespace:
tag = f"{{{namespace}}}{tag}"
return root.findall(f".//{tag}")
def element_to_dict(self, element: ET.Element,
include_children: bool = True) -> Dict[str, Any]:
"""Convert element to dictionary."""
result = {
'_tag': element.tag.split('}')[-1] if '}' in element.tag else element.tag,
'_text': element.text.strip() if element.text else None,
**element.attrib
}
if include_children:
for child in element:
child_tag = child.tag.split('}')[-1] if '}' in child.tag else child.tag
if child_tag in result:
# Multiple children with same tag - make list
if not isinstance(result[child_tag], list):
result[child_tag] = [result[child_tag]]
result[child_tag].append(self.element_to_dict(child))
else:
result[child_tag] = self.element_to_dict(child)
return result
def elements_to_dataframe(self, elements: List[ET.Element]) -> pd.DataFrame:
"""Convert list of elements to DataFrame."""
records = []
for elem in elements:
record = {'_tag': elem.tag.split('}')[-1]}
record.update(elem.attrib)
# Get direct text content
if elem.text and elem.text.strip():
record['_text'] = elem.text.strip()
# Get child values
for child in elem:
child_tag = child.tag.split('}')[-1]
if child.text and child.text.strip():
record[child_tag] = child.text.strip()
# Also get child attributes
for attr, val in child.attrib.items():
record[f"{child_tag}_{attr}"] = val
records.append(record)
return pd.DataFrame(records)
def flatten_xml(self, root: ET.Element,
target_tag: str = None) -> pd.DataFrame:
"""Flatten XML to DataFrame."""
if target_tag:
elements = self.find_elements(root, target_tag)
else:
elements = list(root)
return self.elements_to_dataframe(elements)
class P6XMLReader(ConstructionXMLReader):
"""Reader for Primavera P6 XML exports."""
def parse_activities(self, root: ET.Element) -> pd.DataFrame:
"""Parse activities from P6 XML."""
activities = self.find_elements(root, 'Activity')
return self.elements_to_dataframe(activities)
def parse_resources(self, root: ET.Element) -> pd.DataFrame:
"""Parse resources from P6 XML."""
resources = self.find_elements(root, 'Resource')
return self.elements_to_dataframe(resources)
def parse_wbs(self, root: ET.Element) -> pd.DataFrame:
"""Parse WBS from P6 XML."""
wbs = self.find_elements(root, 'WBS')
return self.elements_to_dataframe(wbs)
def parse_full_schedule(self, file_path: str) -> Dict[str, pd.DataFrame]:
"""Parse complete P6 schedule."""
root = self.parse_file(file_path)
return {
'activities': self.parse_activities(root),
'resources': self.parse_resources(root),
'wbs': self.parse_wbs(root)
}
class IFCXMLReader(ConstructionXMLReader):
"""Reader for IFC-XML files."""
def parse_entities(self, root: ET.Element) -> pd.DataFrame:
"""Parse IFC entities."""
# Find all Ifc* elements
all_entities = []
for elem in root.iter():
if elem.tag.startswith('Ifc'):
all_entities.append(elem)
return self.elements_to_dataframe(all_entities)
def get_entity_types(self, root: ET.Element) -> Dict[str, int]:
"""Count entity types."""
counts = {}
for elem in root.iter():
tag = elem.tag
if tag.startswith('Ifc'):
counts[tag] = counts.get(tag, 0) + 1
return counts
class COBieXMLReader(ConstructionXMLReader):
"""Reader for COBie XML files."""
COBIE_SHEETS = ['Facility', 'Floor', 'Space', 'Zone', 'Type',
'Component', 'System', 'Assembly', 'Connection',
'Spare', 'Resource', 'Job', 'Document', 'Attribute']
def parse_cobie(self, file_path: str) -> Dict[str, pd.DataFrame]:
"""Parse all COBie sheets."""
root = self.parse_file(file_path)
result = {}
for sheet in self.COBIE_SHEETS:
elements = self.find_elements(root, sheet)
if elements:
result[sheet] = self.elements_to_dataframe(elements)
return result
class BSDDXMLReader(ConstructionXMLReader):
"""Reader for buildingSMART Data Dictionary exports."""
def parse_classifications(self, root: ET.Element) -> pd.DataFrame:
"""Parse classification items."""
items = self.find_elements(root, 'Classification')
return self.elements_to_dataframe(items)
def parse_properties(self, root: ET.Element) -> pd.DataFrame:
"""Parse property definitions."""
props = self.find_elements(root, 'Property')
return self.elements_to_dataframe(props)
reader = ConstructionXMLReader()
# Parse XML file
root = reader.parse_file("schedule.xml")
# Find specific elements
activities = reader.find_elements(root, "Activity")
print(f"Found {len(activities)} activities")
# Convert to DataFrame
df = reader.elements_to_dataframe(activities)
p6_reader = P6XMLReader()
schedule = p6_reader.parse_full_schedule("p6_export.xml")
activities = schedule['activities']
print(f"Activities: {len(activities)}")
cobie_reader = COBieXMLReader()
cobie_data = cobie_reader.parse_cobie("facility_cobie.xml")
components = cobie_data.get('Component', pd.DataFrame())
ifc_reader = IFCXMLReader()
root = ifc_reader.parse_file("model.ifcxml")
# Count entity types
types = ifc_reader.get_entity_types(root)
for entity_type, count in sorted(types.items(), key=lambda x: -x[1])[:10]:
print(f"{entity_type}: {count}")
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Manage as-built documentation for project closeout. Track drawing markups, coordinate updates, and verify completeness.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.