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Jupyter Notebook. Jupyter notebooks. Code cells, their outputs and Markdown notes in one JSON file. 124 formats it can become, 175 that become it.

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IPYNB becomes.

Every path the planner knows from a IPYNB, the common ones first. One hop is a single engine. More hops go through another format on the way.

124 targets

JSONonefidelity 0.852 hops~1.3 sHTMLonefidelity 0.901 hop~600 msMDonefidelity 0.901 hop~400 msTXTonefidelity 0.851 hop~400 msCSVmanyfidelity 0.774 hops~2.4 sTSVmanyfidelity 0.774 hops~2.4 sJSONLonefidelity 0.813 hops~1.4 sSRTonefidelity 0.794 hops~6.2 sVTTonefidelity 0.794 hops~6.2 sYAMLonefidelity 0.813 hops~1.4 sXMLonefidelity 0.723 hops~1.4 sASSonefidelity 0.794 hops~6.2 sLRConefidelity 0.634 hops~6.2 sSQLITEonefidelity 0.813 hops~1.8 sPARQUETonefidelity 0.813 hops~1.8 sICSonefidelity 0.813 hops~1.5 s

Becomes IPYNB.

Every format that can be turned into a IPYNB.

175 sources

JSONmanyfidelity 0.774 hops~1.6 sHTMLonefidelity 0.772 hops~600 msMDonefidelity 0.901 hop~300 msTXTonefidelity 0.693 hops~800 msCSVonefidelity 0.852 hops~500 msTSVmanyfidelity 0.804 hops~1.1 sJSONLmanyfidelity 0.774 hops~1.6 sSRTonefidelity 0.853 hops~650 msVTTonefidelity 0.853 hops~650 msYAMLonefidelity 0.683 hops~600 msXMLonefidelity 0.683 hops~600 msASSonefidelity 0.814 hops~850 msLRConefidelity 0.814 hops~850 msSQLITEmanyfidelity 0.813 hops~1.1 sPARQUETonefidelity 0.813 hops~1.0 sICSonefidelity 0.683 hops~600 ms

Two commands.

cv targets answers this page for any file. cv convert runs any row above.

~/filescv 0.1
$ cv targets --from ipynb
ipynb ->
  json     one   fidelity 0.85  hops 2  ~1.3 s
  html     one   fidelity 0.90  hops 1  ~600 ms
  md       one   fidelity 0.90  hops 1  ~400 ms
  txt      one   fidelity 0.85  hops 1  ~400 ms
$ cv convert file.ipynb file.json
file.json -> file.json