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@BIGAL I think using powershell method would be similar. User launches AutoCAD then runs lisp that would write the registry key (that designates the current profile) into powershell script along with item to add to Startup. But after running the powershell script, user is prompted to exit AutoCAD (without launching Appload) in order for the added item in the registry to be read on the relaunch of AutoCAD.

Maybe like this and use a bat file that last line calls Autocad or Bricscad after editing the registry, note adding extra programs see second image.

For CAD manager, Developer, and Users accustomed to communicating via email, feel free to contact me anytime: vico@vedacad.com

I continue to monitor the situation and although we're still seeing the error message, the stats for this month indicate that bot activity is going down from a peak in September. Fingers crossed it continues to fall.

@LIU very simple. If UCSICON is set to OR (origin) and 0,0,0 of the current UCS is near to the left border of the graphics window boundary, or below the boundary, or not within the viewing window then the UCS ICON will move to be near the bottom left of the window and will not be postioned at 0,0. Note, the little square that you see on the icon indicates that you the WCS is active.

Python Slide(.SLD) to wxImage In the next release (3.1.16), I added a function, image: wx.Image = Gs.Core.slideToWxImage(test_slide_path, width, height, [R, G, B]) for people that are used to using slides in their dialogs.

Testing a new version of PyRx’s KDTree. Maybe a useful example import traceback import pandas as pd from pyrx import Ap, Db, Ge, Ed @Ap.Command() def doit(): try: # 1. Select the text and block objects in AutoCAD ps, ss = Ed.Editor.select([(0, "MTEXT,INSERT")]) if ps != Ed.PromptStatus.eOk: return # 2. Extract block positions for spatial matching pnts = Ge.Point3dArray() for blkid in ss.objectIds(Db.BlockReference.desc()): blkref = Db.BlockReference(blkid) pnts.append(blkref.position()) # Build a spatial K-d tree to find the nearest block for each MText tree = Ge.Point3dTree(pnts) # 3. Process matched data into a structured list rows = [] for tid in ss.objectIds(Db.MText.desc()): mt = Db.MText(tid) indexes, _distances = tree.knnSearch(mt.location(), 1) if indexes: row_data = {} nearest_pt = pnts[indexes[0]] # split TODO: /P text_lines = mt.text().splitlines() for idx, line in enumerate(text_lines): row_data[f"Line_{idx + 1}"] = line row_data["Block_X"] = round(nearest_pt.x, 2) row_data["Block_Y"] = round(nearest_pt.y, 2) row_data["Block_Z"] = round(nearest_pt.z, 2) rows.append(row_data) df = pd.DataFrame(rows) print(df) output_file = "e:/temp/output_cad_data.xlsx" df.to_excel(output_file, index=False, sheet_name="CAD Extract") print(f"Successfully exported {len(df)} rows to {output_file}") except Exception as e: traceback.print_exc()