I use this in my Python data processing scripts. That is, when I generate data, I generate it as Python literals, either lists or dictionaries. When I have to process it, minimal parsing needed, I just eval it into my code.
def parse_and_append(line, seq, str):
if str in line:
seq.append(eval(line[line.find(str) + len(str):]))
nums = []
mappings = {}
for line in data_file:
parse_and_append(line, nums, "nums: ")
parse_and_append(line, mappings, "mappings: ")
Terribly insecure for webpages, sure, but very efficient use of my time.
I see no reason to use JavaScript to process my data files - keep in mind this is data post-processing of experiments, not a user-facing application. And I enjoy Python, so I'll stick with it. But thanks for the pointer to literal_eval, I have not explored that part of the standard library.
I use this in my Python data processing scripts. That is, when I generate data, I generate it as Python literals, either lists or dictionaries. When I have to process it, minimal parsing needed, I just eval it into my code.
Terribly insecure for webpages, sure, but very efficient use of my time.