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Preview the table structure contained in a Feather file.

Source: R/file_helpers.R
file_schema_feather.Rd

The file_schema_feather() function returns a data frame with the schema of a Feather file. This function is used to preview the table structure contained in a Feather file, by reading only the metadata of the file. It inspects the input file metadata to read the field identifiers' names and data types, then converts them to the candidate data frame columns' names and data types. The dataset contained in the input file is not read in to memory, only meta-data are accessed.

Usage

file_schema_feather(input_file, id_quote_method = "DB_NAMES")

Arguments

input_file

File name (including path) to be read

id_quote_method

character, used to specify how to build the SQLite columns' names using the fields' identifiers read from the input file. For details see the description of the quote_method parameter of the format_column_names() function. Defaults to DB_NAMES.

Value

a data frame with these columns:

  • col_names: columns' names, after applying the selected quote method;

  • col_names_unquoted: columns' names, unquoted; if id_quote_method is set to DB_NAMES they will be the same as col_names; for other quote methods they will be the unquoted versions of col_names, that is generally the same as src_names unless src_names contain the quoting characters;

  • col_types: columns' R data types;

  • sql_types: columns' SQLite data types;

  • src_names: columns' names as they appear in the input file;

  • src_types: the Arrow's data type of each column.

References

The implementation is based on this question on Stackoverflow. # nolint: line_length_linter.

Examples

# Inspect Feather file schema
data_path <- system.file("extdata", package = "RSQLite.toolkit")

# Get schema information for penguins Feather file
schema_info <- file_schema_feather(
  input_file = file.path(data_path, "penguins.feather")
)

# Display schema information
print(schema_info[, c("col_names", "col_types", "sql_types", "src_names")])
#>           col_names col_types sql_types         src_names
#> 1           species character      TEXT           species
#> 2  culmen_length_mm    double      REAL  culmen_length_mm
#> 3   culmen_depth_mm    double      REAL   culmen_depth_mm
#> 4 flipper_length_mm    double      REAL flipper_length_mm
#> 5       body_mass_g    double      REAL       body_mass_g
#> 6               sex character      TEXT               sex

# Check specific columns
print(paste("Number of columns:", nrow(schema_info)))
#> [1] "Number of columns: 6"
print(paste("Column names:", paste(schema_info$col_names, collapse = ", ")))
#> [1] "Column names: species, culmen_length_mm, culmen_depth_mm, flipper_length_mm, body_mass_g, sex"