diff --git a/clen_tools/sample_crystfel-ls.py b/clen_tools/sample_crystfel-ls.py
new file mode 100644
index 0000000..8d99bc2
--- /dev/null
+++ b/clen_tools/sample_crystfel-ls.py
@@ -0,0 +1,73 @@
+#!/usr/bin/python
+
+# author J.Beale
+
+"""
+# aim
+input a list file made by the SwissFEL daq and a sample number get out a random selection
+of files of that number
+
+# usage
+python sample_crystfel-ls.py -l <path-to-list-file> -s sample
+
+# output
+.lst file containing the required number of random image links - with naming convention
+<input-lst-name>_<sample-size>.lst
+"""
+
+# modules
+import pandas as pd
+import os
+import argparse
+
+def h5_sample( lst, sample ):
+
+    # create sample of images from run
+    # read h5.lst - note - removes // from image column
+    print( "reading SwissFEL ls file" )
+    # scrub file name
+    lst_name = os.path.basename( lst )
+
+    cols = [ "h5", "image" ]
+    sample_df = pd.read_csv( lst, sep="\s//", engine="python", names=cols )
+    print( "done" )
+
+    print( "taking {0} image sample".format( sample ) )
+    # take defined sample
+    sample_df = sample_df.sample( sample )
+
+    # sort list
+    sample_df = sample_df.sort_index()
+
+    # re-add // to image columm
+    sample_df[ "image" ] = "//" + sample_df.image.astype( str )
+    print( "done" )
+
+    # write sample to file
+    print( "writing to file" )
+    sample_file = "{0}_{1}.lst".format( lst_name, sample )
+    sample_df.to_csv( sample_file, sep=" ", index=False, header=False )
+    print( "done" )
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "-l",
+        "--list",
+        help="give the path to SwissFEL daq list file",
+        type=str
+    )
+    parser.add_argument(
+        "-s",
+        "--sample",
+        help="number of random sample images to select",
+        type=int
+    )
+    args = parser.parse_args()
+    # run geom converter
+    h5_sample( args.list, args.sample )
+
+
+
+