Note that the log_print()
function has two aliases:
put()
and sep()
.
The put()
function is exactly like
log_print()
, but it is shorter and easier to type.
The sep()
function is a slight variant of
log_print()
that prints separators above and below the
message text. It is useful for creating sections in your log. Breaking
your log into sections makes it easier to read and understand.
Here is example showing these aliases at work:
library(logr)
library(magrittr)
# Create temp file location
<- file.path(tempdir(), "test.log")
tmp
# Open log
<- log_open(tmp)
lf
# Create log section
sep("Illustration of put() and sep()")
# Send message to log
put("High Mileage Cars Subset")
# Perform operations
<- subset(mtcars, mtcars$mpg > 20) %>%
hmc put() # prints pipeline result to log
# Close log
log_close()
# View results
writeLines(readLines(lf))
Here is the log from the above alias example:
=========================================================================
Log Path: C:/Users/User/AppData/Local/Temp/RtmpioAPbg/log/test.log
Working Directory: C:/packages/Testing
User Name: User
R Version: 4.0.3 (2020-10-10)
Machine: DESKTOP-1F27OR8 x86-64
Operating System: Windows 10 x64 build 18363
Base Packages: stats graphics grDevices utils datasets methods base
Other Packages: logr_1.2.7 dplyr_1.0.7
Log Start Time: 2020-12-21 14:18:33
=========================================================================
=========================================================================
Illustration of put() and sep()
=========================================================================
High Mileage Cars Subset
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
=========================================================================
Log End Time: 2020-12-21 14:18:33
Log Elapsed Time: 0 00:00:00
=========================================================================
Next: tidylog Integration