optional inputs : species, pi, glycan , cell type
file type - for now msa
outputs : json of everything. *.msa files . 
possibly if images are selected then bundle all as an html.

For now only interested in msa files. Ignoring everything else. i.e. if a match has no msa I do nothing serious just print to stdout

basic functional version
python cfg_get_glycan_from_cells.py  -s Human -p "Crocker,Paul" 

gets the msa 
Human_B-Cells_Crocker_N-Linked_10000007.msa  Human_K562_Crocker_N-Linked_7301.msa   Human_Monocytes_Crocker_N-Linked_10000006.msa             Human_T-Cells_Crocker_O-Linked_10000011.msa
Human_B-Cells_Crocker_O-Linked_10000008.msa  Human_K562_Crocker_O-Linked_7302.msa   Human_Monocytes_Crocker_O-Linked_10000005.msa             Human_THP-1_Crocker_N-Linked_7309.msa
Human_HL-60_Crocker_N-Linked_7330.msa        Human_KG-1a_Crocker_N-Linked_7317.msa  Human_Natural Killer Cells_Crocker_N-Linked_10000012.msa  Human_VG37_Crocker_N-Linked_7305.msa
Human_HL-60_Crocker_O-Linked_7314.msa        Human_KG-1a_Crocker_O-Linked_7318.msa  Human_Natural Killer Cells_Crocker_O-Linked_10000013.msa

writes out output.json with other info

prints messages on stdout:
no msa for  Human T-Cells Crocker,Paul N-Linked
no msa for  Human VG37 Crocker,Paul O-Linked


because any number of the outputs can be generated, Number of Output datasets cannot be determined until tool run
However ... these discovered datasets cannot be used with workflows and require the user to refresh their history before they are shown. (1)
Another option is to use an html file and link to all the data (2)
I am trying part 1 first.