Version 6.0 of the PyEDS toolkit by Martin Strohalm was released recently.

The PyEDS is a Python library providing collection of utilities to conveniently access and display results from Thermo Discoverer software like Compound Discoverer or Proteome Discoverer. Although the data are stored in open format already (SQLite database), reading complex hierarchies is still not a trivial task and requires certain knowledge of internal mechanisms. Using PyEDS, all the hard work is done automatically, so you can focus more on your research instead of how to read the data.

The PyEDS library provides several tools to read data (pyeds.EDS), displaying tables metadata (pyeds.Summary) as well as displaying actual data in nicely formatted tables (pyeds.Review). In addition, a set of utilities is now available to simplify custom scripting nodes (pyeds.scripting).

import pyeds

# open result file using 'with' statement
with pyeds.EDS("examples/data.cdResult") as eds:
    
    # read top 10 most abundant compounds in specific RT range
    items_iter = eds.Read("Compounds",
        query = "RetentionTime > 3.8 AND RetentionTime < 4.1 AND Name != ''",
        order = "MaxArea",
        desc = True,
        limit = 10)
    
    # print some properties
    for item in items_iter:
        print(item.Name, item.Formula, item.RetentionTime)

…
Noroxycodone-d3 C17 H16 D3 N O4 3.8511594324229588
6-(1,2-Dihydroxypentyl)-4-methoxy-5,6-dihydropyran-2-one C11 H18 O5 3.8892103560637996
Striatisporolide A C11 H16 O4 3.8904788953324587
PEG n6 C12 H26 O7 3.8514281937047308
1,3-Butyleneglycol dimethacrylate C12 H18 O4 4.062345800093047
8-Epideoxyloganic acid C16 H24 O9 3.967517173120096
Propan-2-yl 2-hydroxy-4-methylsulfanylbutanoate C8 H16 O3 S 4.064400409011077
Striatisporolide A C11 H16 O4 4.09791974254791

import pyeds

# open result file using 'with' statement
with pyeds.Summary("examples/data.cdResult") as summary:
    
    # show full info
    summary.ShowAll()

The example above will open your web-browser and display a graphical, interactive network of all the information stored in your result file and how the tables are linked together. You can click on any of the nodes and it will show detailed information about all the data (columns) stored in the selected table.