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| find . -type f -exec bash -c 'paste -d "|" <(yes $0) <(yes $(stat -c %y "$0")) "$0" | head -n `cat "$0" | wc -l`' '{}' \; |
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| """ | |
| Example: | |
| greet = magic_def("object", object="World")("Hello {object}!".format) | |
| greet() # Hello World! | |
| greet("John Doe") # Hello John Doe! | |
| """ | |
| def magic_def(*argument_names, **default_values): | |
| def wrapper(func): | |
| values = dict(default_values.iteritems()) |
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| frame | source | target | weight | |
|---|---|---|---|---|
| 0 | K Smith | A Lock | 0.21173905130640522 | |
| 0 | K Smith | A Lee | 0.27582121148579053 | |
| 0 | K Smith | B Day | 0.447456581342536 | |
| 0 | K Smith | C Smith | 0.9025337081161997 | |
| 0 | B Doe | K Doe | 0.27733344115465336 | |
| 0 | B Doe | A Lock | 0.26563752260276363 | |
| 0 | B Doe | B Day | 0.2381991164770027 | |
| 0 | B Doe | J Smith | 0.781246002686131 | |
| 0 | B Doe | H Smith | 0.47396925684947644 |
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| { | |
| "component": "root", | |
| "args": {"title": "Hello World"}, | |
| "data": [ | |
| {"component": "text", | |
| "args": {"tagName": "h1"}, | |
| "data": "Hello World!" | |
| }, | |
| {"component": "text", | |
| "args": {"tagName": "p"}, |
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| { | |
| "component": "root", | |
| "args": {"title": "Cereals"}, | |
| "data": [ | |
| {"component": "text", | |
| "args": {"tagName": "h1"}, | |
| "data": "Cereals" | |
| }, | |
| {"component": "text", | |
| "args": {"tagName": "h2"}, |
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| dashboard "Cereals": | |
| - h1 text: "Cereals" | |
| - h2 text: "By calories" | |
| - bar chart: | |
| - attr:query: '{"columns": [(sort_by(-(.calories | tonumber)) | .[] | [.name, .calories])]}' | |
| - data: https://gist.githubusercontent.com/ZeningQu/6184eaf8faa533e320abc938c4738c3e/raw/40f237de825061faa8721c2293b79c46979780b4/cereals.csv | |
| - h2 text: "By nutritional profile" | |
| - 4 columns: | |
| - attr:query: '.[] | {"component": "rows", "data": [{"component": "text", "args": {"tagName": "h3"}, "data": .name}, {"component": "chart", "args": {"type": "pie"}, "data": {"columns": [["protein", .protein], ["carbo", .carbo], ["sugars", .sugars], ["fat", .fat]]}}]}' | |
| - data: https://gist.githubusercontent.com/ZeningQu/6184eaf8faa533e320abc938c4738c3e/raw/40f237de825061faa8721c2293b79c46979780b4/cereals.csv |
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| dashboard "Food": | |
| - h1 text: Food | |
| - h2 text: By caloric content | |
| - 3 columns: | |
| - rows: | |
| - h3 text: Bananas | |
| - pie chart: { | |
| "columns": [ | |
| ["Protein", 5], ["Sugar", 10], ["Other carbs", 40], ["Fat", 1] | |
| ] |
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| {"component":"root","args":{"title":"Hello World"},"data":[{"component":"text","args":{"tagName":"h1"},"data":"Hello"},{"component":"text","args":{"query":".[0]","tagName":"h2"},"data":["Hello World!"]}]} |
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| { | |
| "Bananas": [["Protein", 5], ["Sugar", 10], ["Other carbs", 40], ["Fat", 1]], | |
| "Tofu" : [["Protein", 30], ["Sugar", 0], ["Other carbs", 40], ["Fat", 3]], | |
| "Peanut butter": [["Protein", 20], ["Sugar", 2], ["Other carbs", 20], ["Fat", 50]] | |
| } |
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| dashboard "Food": | |
| - h1 text: Food | |
| - h2 text: By caloric content | |
| - 3 columns: | |
| - attr:query: '[to_entries | .[] | {"component": "rows", "data": [ | |
| {"component": "text", "args": {"tagName": "h3"}, "data": .key}, | |
| {"component": "chart", "args": {"type": "pie"}, "data": {"columns": .value}} | |
| ]}]' | |
| - data: https://gist.githubusercontent.com/kantord/2b2e3b22cb70be0415a7d50c395fa411/raw/47542f8a3db0d65aeeb48e28ddfaa8feabbc72b5/nutri.json |
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