read_log(file, col_names = FALSE, col_types = NULL, skip = 0, n_max = -1, progress = interactive()) Files ending in .gz, .bz2, .xz, or .zip will
be automatically uncompressed. Files starting with http://,
https://, ftp://, or ftps:// will be automatically
downloaded.
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).
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.
NULL, a list, a named list or a string. If NULL, the column type will be imputed from the first 30 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 list, it must contain one "collector" for each column.
If you only want to read a subset of the columns, you can use a named list
(where the names give the column names). If a column is not mentioned by
name, it will not be included in the output.
Alternatively, you can use a compact string representation where each
character represents one column: c = character, d = double, i = integer,
l = logical and _ skips the column.
read_log(system.file("extdata/example.log", package = "readr"))
Run the code above in your browser using DataLab