USe {{r}} to not evaluate but just print these chunks
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@ -601,13 +601,13 @@ On subsequent runs, knitr will check to see if the code has changed, and if it h
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The caching system must be used with care, because by default it is based on the code only, not its dependencies.
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For example, here the `processed_data` chunk depends on the `raw-data` chunk:
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```{r}
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``` {{r}}
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#| label: raw-data
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rawdata <- readr::read_csv("a_very_large_file.csv")
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```
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```{r}
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``` {{r}}
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#| label: processed_data
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#| cache: true
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@ -619,7 +619,7 @@ processed_data <- rawdata |>
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Caching the `processed_data` chunk means that it will get re-run if the dplyr pipeline is changed, but it won't get rerun if the `read_csv()` call changes.
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You can avoid that problem with the `dependson` chunk option:
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```{r}
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``` {{r}}
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#| label: processed-data
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#| cache: true
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#| dependson: "raw-data"
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@ -638,7 +638,7 @@ This is an arbitrary R expression that will invalidate the cache whenever it cha
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A good function to use is `file.info()`: it returns a bunch of information about the file including when it was last modified.
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Then you can write:
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```{r}
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``` {{r}}
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#| label: raw-data
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#| cache.extra: file.info("a_very_large_file.csv")
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