aws-samples / amazon-transcribe-comprehend-podcast
A demo application that transcribes and indexes podcast episodes so the listeners can explore and discover episodes of interest and podcast owners can do analytics on the content over time. This solution leverages Amazon Transcribe, Amazon Comprehend, Amazon ElasticSearch AWS Step Functions and AWS Lambda.
Summary
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| Main Code: 1,706 LOC (15 files) = PY (63%) + YAML (36%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 350 LOC (5); |
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| Duplication: 13% | |||
| File Size: 0% long (>1000 LOC), 50% short (<= 200 LOC) | |||
| Unit Size: 0% long (>100 LOC), 23% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 43% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (3 components) | ||
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3 years, 5 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
Latest commit date: 2020-04-07
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