Read common/combined log file into a tibble

This is a fairly standard format for log files - it uses both quotes and square brackets for quoting, and there may be literal quotes embedded in a quoted string. The dash, "-", is used for missing values.

read_log(file, col_names = FALSE, col_types = NULL, skip = 0,
  n_max = Inf, progress = show_progress())

Arguments

file	Either a path to a file, a connection, or literal data (either a single string or a raw vector). Files ending in .gz, .bz2, .xz, or .zip will be automatically uncompressed. Files starting with http://, https://, ftp://, or ftps:// will be automatically downloaded. Remote gz files can also be automatically downloaded and decompressed. Literal data is most useful for examples and tests. It must contain at least one new line to be recognised as data (instead of a path) or be a vector of greater than length 1. Using a value of clipboard() will read from the system clipboard.
col_names	Either TRUE, FALSE or a character vector of column names. If TRUE, the first row of the input will be used as the column names, and will not be included in the data frame. If FALSE, column names will be generated automatically: X1, X2, X3 etc. If col_names is a character vector, the values will be used as the names of the columns, and the first row of the input will be read into the first row of the output data frame. Missing (NA) column names will generate a warning, and be filled in with dummy names X1, X2 etc. Duplicate column names will generate a warning and be made unique with a numeric prefix.
col_types	One of NULL, a cols() specification, or a string. See vignette("readr") for more details. If NULL, all column types will be imputed from the first 1000 rows on the input. This is convenient (and fast), but not robust. If the imputation fails, you'll need to supply the correct types yourself. If a column specification created by cols(), it must contain one column specification for each column. If you only want to read a subset of the columns, use cols_only(). Alternatively, you can use a compact string representation where each character represents one column: c = character, i = integer, n = number, d = double, l = logical, f = factor, D = date, T = date time, t = time, ? = guess, or _/- to skip the column.
skip	Number of lines to skip before reading data.
n_max	Maximum number of records to read.
progress	Display a progress bar? By default it will only display in an interactive session and not while knitting a document. The display is updated every 50,000 values and will only display if estimated reading time is 5 seconds or more. The automatic progress bar can be disabled by setting option readr.show_progress to FALSE.

Examples

read_log(readr_example("example.log"))
#> Parsed with column specification:
#> cols(
#>   X1 = col_character(),
#>   X2 = col_logical(),
#>   X3 = col_character(),
#>   X4 = col_character(),
#>   X5 = col_character(),
#>   X6 = col_double(),
#>   X7 = col_double()
#> )
#> # A tibble: 2 x 7
#>   X1        X2    X3          X4             X5                         X6    X7
#>   <chr>     <lgl> <chr>       <chr>          <chr>                   <dbl> <dbl>
#> 1 172.21.1… NA    "Microsoft… 08/Apr/2001:1… GET /scripts/iisadmin/…   200  3401
#> 2 127.0.0.1 NA    "frank"     10/Oct/2000:1… GET /apache_pb.gif HTT…   200  2326