Help for package awkreader

Title:

File Reading with Pre-Filtering, Pattern Searching, and Distributed Files

Version:

0.1.0

Description:

Provides high-performance tools for out-of-core text processing and data ingestion by leveraging system 'AWK' utilities. Allows users to count records, filter rows, and compute streaming aggregations—such as group-by means, streaming medians, standard deviations, and correlations—directly on disk prior to reading data into R. By delegating line-by-line filtering and summarization to system-level 'AWK' commands and streaming results back through data.table::fread(), the package significantly reduces memory footprint and execution times when working with large individual files or multi-file directory structures.

License:

MIT + file LICENSE

Encoding:

UTF-8

RoxygenNote:

7.3.3

Suggests:

knitr, rmarkdown, testthat (≥ 3.0.0)

VignetteBuilder:

knitr

Config/testthat/edition:

Imports:

data.table

NeedsCompilation:

Packaged:

2026-08-23 16:23:18 UTC; akshat

Author:

David Shilane [aut], Akshat Maurya [aut, cre], Jason Livingston [aut], Chung-Woo (Caffrey) Lee [aut], Mayur Bansal [aut], Srivastav Budugutta [aut]

Maintainer:

Akshat Maurya <codingmaster902@gmail.com>

Repository:

CRAN

Date/Publication:

2026-09-03 12:20:11 UTC

Fast Stream Aggregation of Delimited Files via AWK

Description

High-performance aggregation and streaming of multiple tabular data files using an optimized AWK engine pipeline. This function parses columns, groups multi-file inputs, and calculates summarizations (like sum(), mean(), and sd()) natively in the shell before pulling structured aggregates back into R. It safely evaluates scalar mathematical transformations passed as strings (e.g., "sqrt(col)").

Usage

aggregated.fread(
  the.files,
  value.code = "data",
  delim = ",",
  file.pattern = NULL,
  recursive = FALSE,
  num.batches = 1,
  num.files.per.batch = 1000,
  summarize.with = NULL,
  return.as = "result",
  group.by = NULL,
  path.to.awk = "awk",
  file.header = "file",
  include.filename = FALSE,
  skip = 0,
  show.warnings = TRUE,
  nrows = Inf,
  sample.size.median = -1,
  return.data.table = TRUE
)

Arguments

the.files

A character vector containing paths to the targeted delimited text datasets.

value.code

A internal character tracking string for code generation mappings. Defaults to "data".

delim

A character string defining the field separator delimiter within files. Defaults to ",".

file.pattern

Optional character string to filter file names when the.files contains directory paths. Accepts simple extensions (e.g., "csv" or ".csv"), wildcards (e.g., "*.csv"), or regular expressions (e.g., "\.csv$"). Default is NULL (includes all files).

recursive

Logical. Should directory searches recurse into subdirectories when the.files contains directory paths? Default is FALSE.

num.batches

An integer defining the processing grouping structure. Defaults to 1.

num.files.per.batch

An integer specifying the maximum threshold of files targeted per concurrent process execution loop. Defaults to 1000.

summarize.with

A named list specifying operations and target columns. Names must match supported functions: "sum", "mean", or "sd". Elements can include raw columns or functional call strings like "sqrt(price)". Defaults to NULL.

return.as

A character string defining what data is returned to the environment. Options include "result" (aggregated dataset), "code" (generated AWK commands), or "all" (a combined list of both). Defaults to "result".

group.by

A character vector or list containing column names to act as the aggregation grouping dimensions. Defaults to NULL.

path.to.awk

A character string declaring the binary location execution path. Defaults to "awk".

A character string tracking column identification titles when filenames are tracked. Defaults to "file".

include.filename

A logical value indicating whether the tracking origin file string column should append to final structures. Defaults to FALSE.

skip

An integer, list, or character regex pattern. Controls metadata/line skipping configuration routines before row parsing evaluations trigger. Defaults to 0.

show.warnings

A logical value determining whether underlying structural data warnings should surface during operation execution cycles. Defaults to TRUE.

nrows

A numeric ceiling threshold limiting output aggregation allocations. Defaults to Inf.

sample.size.median

Integer. Maximum number of observations per group used to compute streaming medians via the P-Square algorithm. A positive integer caps the sample size per group for faster execution on large datasets. Set to -1 (default) or 0 to compute across all rows without sampling.

return.data.table

A logical value. If TRUE, returns a data.table object; otherwise, reverts the format to a standard base data.frame. Defaults to TRUE.

Value

Depending on the configuration argument passed to return.as, returns either a data.table (data.frame if return.data.table = FALSE), a character vector representing full system executable command configurations, or a combined metadata list package object.

Examples


# Create a sample CSV file using base R mtcars dataset
tmp_file <- tempfile(fileext = ".csv")
write.csv(mtcars, tmp_file, row.names = FALSE)

# Aggregate data over multiple columns grouped by cylinders
agg_res <- aggregated.fread(
  the.files = tmp_file,
  group.by = "cyl",
  summarize.with = list(
    mean = list("hp", "mpg"),
    sd = "wt"
  ),
  return.as = "all"
)
print(agg_res$result)

# Clean up temporary file
unlink(tmp_file)

Fast Batch Combining of Flat Files via AWK

Description

A streamlined wrapper around filtered.fread() designed to quickly read, process, and combine multiple flat files into a single dataset without applying row filters.

Usage

combined.fread(
  the.files,
  path.to.awk = NULL,
  header = TRUE,
  the.variables = ".",
  file.pattern = NULL,
  recursive = FALSE,
  include.filename = TRUE,
  skip = 0,
  file.header = "file",
  num.files.per.batch = 1000,
  return.as = "result",
  envir = parent.frame(),
  show.warnings = FALSE,
  return.data.table = TRUE,
  nrows = Inf,
  drop = NULL,
  ...
)

Arguments

the.files

A character vector of file paths to process. Non-existent files are automatically filtered out.

path.to.awk

A character string specifying the path to the AWK binary. If NULL (default), the function attempts to invoke a global system call to "awk".

header

A logical value indicating whether the target files contain a header row. Default is TRUE.

the.variables

A character vector specifying which columns to retain. Use "." (default) to retain all columns.

file.pattern

recursive

Logical. Should directory searches recurse into subdirectories when the.files contains directory paths? Default is FALSE.

include.filename

A logical value indicating whether to include a source file tracking column in the returned dataset. Default is TRUE.

skip

A numeric offset, a character regex pattern, or a structured list indicating lines to bypass. If a list is used, it must follow dot notation:

skip.metadata.rows: An integer count or a character regex pattern used to identify where the metadata block ends.
skip.data.rows: An integer specifying the number of data rows to explicitly skip after the header.

Default is 0.

A character string defining the column name for the tracked file origin. Only utilized if include.filename = TRUE. Default is "file".

num.files.per.batch

An integer specifying how many files to aggregate per AWK system pipeline call. Default is 1000.

return.as

A character string specifying the desired return object. Options are "result" (default), "code" (returns raw generated AWK scripts), or "all" (returns both).

envir

The environment context in which evaluation variables are evaluated. Default is parent.frame().

show.warnings

A logical value determining whether underlying data.table::fread() messages should be displayed or suppressed. Default is FALSE.

return.data.table

A logical value indicating whether to return a data.table object or a standard data.frame. Default is TRUE.

nrows

An integer specifying the maximum total rows to parse out from the batch pipeline. Default is Inf.

drop

A character or numeric index vector specifying columns that should be explicitly excluded from the final output.

...

Extra parameters forwarded to underlying internal setup routines inside filtered.fread().

Value

A data.table (or data.frame), or a character vector containing the raw shell commands, depending on the value passed to return.as.

Examples


# Create sample CSV files with metadata rows
f1 <- tempfile(fileext = ".csv")
f2 <- tempfile(fileext = ".csv")

writeLines(c("# Title: Jan Log", "# Status: Active", "id,val", "1,10", "2,20"), f1)
writeLines(c("# Title: Feb Log", "# Status: Active", "id,val", "3,30", "4,40"), f2)

# Combine multiple log files while skipping the 2 metadata rows
all_logs <- combined.fread(
  the.files = c(f1, f2),
  skip = list(skip.metadata.rows = 2, skip.data.rows = 0)
)
print(all_logs)

# Clean up temporary files
unlink(c(f1, f2))

Execute AWK Script over Batches of Files (Internal Engine)

Description

An internal helper function that splits file processing into batches, constructs systemic shell commands to invoke AWK, and streams the processed text strings back into R via data.table::fread.

Usage

execute.awk.stream(
  awk.script.content,
  the.files,
  value.code,
  header.names,
  include.filename,
  num.batches,
  num.files.per.batch,
  path.to.awk,
  total.files,
  show.warnings,
  nrows,
  file.header,
  return.as
)

Arguments

awk.script.content

A character string containing the raw body of the AWK script logic.

the.files

A character vector of normalized paths to the target files.

value.code

A character string indicating the identifier for code-only return mode.

header.names

A character vector of column names to assign to the resulting dataset.

include.filename

A logical value indicating whether to append the source filename tracking column.

num.batches

An integer specifying the total number of batches to chunk files into.

num.files.per.batch

An integer specifying the maximum number of files processed per AWK execution window.

path.to.awk

A character string designating the system path or command name for the AWK binary.

total.files

An integer tracking the total count of valid files to process.

show.warnings

A logical value. If FALSE, wraps the internal engine reading in suppressWarnings.

nrows

A numeric value restricting the maximum number of rows to read per batch chunk.

A character string establishing the column header name for file origin logging.

return.as

A character string controlling the return type format ("result", "code", or "all").

Value

A named list containing two elements:

list.data

A list of data tables containing parsed chunk outputs.

expanded.statements

A character vector containing the raw shell strings passed to the system command pipeline.

Fast, Filtered Reading of Multiple Files via AWK

Description

Translates R-style filtering statements into highly efficient AWK commands to process, filter, and select specific columns from multiple flat files simultaneously. Batched outputs are fast-loaded and bound together into a single dataset.

Usage

filtered.fread(
  the.files,
  path.to.awk = NULL,
  file.pattern = NULL,
  recursive = FALSE,
  header = TRUE,
  delim = ",",
  the.filter = NULL,
  the.variables = ".",
  include.filename = TRUE,
  skip = 0,
  file.header = "file",
  num.files.per.batch = 1000,
  return.as = "result",
  envir = parent.frame(),
  and.symbol = "&",
  or.symbol = "|",
  in.symbol = "%in%",
  nin.symbol = "%nin%",
  show.warnings = FALSE,
  return.data.table = TRUE,
  nrows = Inf,
  drop = NULL,
  ...
)

Arguments

the.files

A character vector of file paths to process. Non-existent files are automatically filtered out.

path.to.awk

A character string specifying the path to the AWK binary. If NULL (default), the function attempts to invoke a global system call to "awk".

file.pattern

recursive

Logical. Should directory searches recurse into subdirectories when the.files contains directory paths? Default is FALSE.

header

A logical value indicating whether the target files contain a header row. Default is TRUE. If FALSE, columns are auto-assigned as V1, V2, etc.

delim

A character string specifying the column separator within the files. Default is ",".

the.filter

A character string or unquoted expression outlining the filtering logic to pass to AWK. Supports implicit translation of basic math and symbolic calls. Default is NULL (no filtering).

the.variables

A character vector specifying which columns to retain. Use "." (default) to retain all columns.

include.filename

A logical value indicating whether to include a source file tracking column in the returned dataset. Default is TRUE.

skip

A numeric offset, a character regex pattern, or a structured list indicating lines to bypass. If a list is used, it must follow dot notation:

skip.metadata.rows: An integer count or a character regex pattern used to identify where the metadata block ends before hitting the core table.
skip.data.rows: An integer specifying the number of data rows to explicitly skip after the header.

Default is 0.

A character string defining the column name for the tracked file origin. Only utilized if include.filename = TRUE. Default is "file".

num.files.per.batch

An integer specifying how many files to aggregate per AWK system pipeline call. Default is 1000.

return.as

A character string specifying the desired return object. Options are:

"result" (default): Returns the compiled dataset.
"code": Bypasses compilation and returns a character vector of the raw generated AWK scripts.
"all": Returns a structured list containing both the compiled dataset and the underlying AWK statements.

envir

The environment context in which evaluation characters or external metadata strings are parsed. Default is parent.frame().

and.symbol

A character replacement flag for logical AND statements. Default is "&".

or.symbol

A character replacement flag for logical OR statements. Default is "|".

in.symbol

A character replacement flag for inclusion tests. Default is "%in%".

nin.symbol

A character replacement flag for exclusion tests. Default is "%nin%".

show.warnings

A logical value determining whether underlying data.table::fread() shell messages should be displayed or suppressed. Default is FALSE.

return.data.table

A logical value indicating whether to return a data.table object or a standard data.frame. Default is TRUE.

nrows

An integer specifying the maximum total rows to parse out from the batch pipeline. Default is Inf.

drop

A character or numeric index vector specifying columns that should be explicitly excluded from the final output.

...

Extra parameters forwarded to underlying internal setup routines.

Value

A data.table (or data.frame), or a character vector containing the raw shell commands, depending on the value passed to return.as.

Examples


# Create a sample CSV file using base R mtcars dataset
tmp_file <- tempfile(fileext = ".csv")
write.csv(mtcars, tmp_file, row.names = FALSE)

# Standard usage with a numeric filter and dot-notation row skipping
my_data <- filtered.fread(
  the.files = tmp_file,
  the.filter = "hp > 100",
  skip = list(skip.metadata.rows = 0, skip.data.rows = 2)
)
print(my_data)

# Clean up temporary file
unlink(tmp_file)

Intelligent Auto-Detection for System AWK Binary

Description

An internal helper that searches the system environment and common Windows installation paths (Rtools, Git Bash) to find a working AWK interpreter.

Usage

find.awk.binary()

Value

A character string representing the absolute path to the AWK binary.

Pattern-Based Subsetting and Reading of Multiple Files via AWK

Description

Reads and aggregates multiple flat files concurrently, filtering rows based on regular expression patterns processed directly via AWK before parsing the data into R.

Usage

pattern.fread(
  the.files,
  path.to.awk = NULL,
  header = TRUE,
  the.patterns = NULL,
  file.pattern = NULL,
  recursive = FALSE,
  tf = TRUE,
  delim = ",",
  connectors = "or",
  the.variables = ".",
  include.filename = TRUE,
  skip = 0,
  file.header = "file",
  num.files.per.batch = 1000,
  return.as = "result",
  envir = parent.frame(),
  show.warnings = FALSE,
  return.data.table = TRUE,
  nrows = Inf,
  drop = NULL,
  ...
)

Arguments

the.files

A character vector of file paths to process. Non-existent files are automatically filtered out.

path.to.awk

A character string specifying the path to the AWK binary. If NULL (default), the function attempts to invoke a global system call to "awk".

header

A logical value indicating whether the target files contain a header row. Default is TRUE.

the.patterns

A character vector containing the regular expression patterns to match against data rows. Default is NULL.

file.pattern

recursive

Logical. Should directory searches recurse into subdirectories when the.files contains directory paths? Default is FALSE.

tf

A logical value determining whether to include rows that match the patterns (TRUE) or exclude rows that match them (FALSE). Default is TRUE.

delim

A character string specifying the column separator within the files. Default is ",".

connectors

A character string defining how multiple patterns should be combined logically. Options are "or" (default) or "and".

the.variables

A character vector specifying which columns to retain. Use "." (default) to retain all columns.

include.filename

A logical value indicating whether to include a source file tracking column in the returned dataset. Default is TRUE.

skip

A numeric offset, a character regex pattern, or a structured list indicating lines to bypass. If a list is used, it must follow dot notation:

skip.metadata.rows: An integer count or a character regex pattern used to identify where the metadata block ends.
skip.data.rows: An integer specifying the number of data rows to explicitly skip after the header.

Default is 0.

A character string defining the column name for the tracked file origin. Only utilized if include.filename = TRUE. Default is "file".

num.files.per.batch

An integer specifying how many files to aggregate per AWK system pipeline call. Default is 1000.

return.as

A character string specifying the desired return object. Options are "result" (default), "code", or "all".

envir

The environment context in which evaluation characters are parsed. Default is parent.frame().

show.warnings

A logical value determining whether underlying terminal messages should be shown. Default is FALSE.

return.data.table

A logical value indicating whether to return a data.table or standard data.frame. Default is TRUE.

nrows

An integer specifying the maximum total rows to parse out. Default is Inf.

drop

A character or numeric index vector specifying columns to explicitly exclude.

...

Extra parameters forwarded to internal setup routines.

Value

A data.table (or data.frame) containing rows satisfying the pattern configurations.

Examples


# Create sample log files
log1 <- tempfile(fileext = ".log")
log2 <- tempfile(fileext = ".log")
writeLines(c("INFO: System started", "Error: Disk full"), log1)
writeLines(c("INFO: User login", "Critical: Database unreachable"), log2)

# Extract rows matching "Error" or "Critical" across log files
errors <- pattern.fread(
  the.files = c(log1, log2),
  the.patterns = c("Error", "Critical"),
  connectors = "or"
)
print(errors)

# Clean up temporary files
unlink(c(log1, log2))

Efficient Record and Row Counting via AWK

Description

Computes the total number of records matching specific logical filtering criteria across multiple large files using AWK. This performs counting at the shell level, eliminating the overhead of loading whole datasets into memory.

Usage

record.count(
  the.files,
  path.to.awk = NULL,
  delim = ",",
  the.filter = NULL,
  file.pattern = NULL,
  recursive = FALSE,
  the.variables = ".",
  include.filename = TRUE,
  skip = 0,
  file.header = "file",
  num.files.per.batch = 1000,
  return.as = "result",
  envir = parent.frame(),
  and.symbol = "&",
  or.symbol = "|",
  in.symbol = "%in%",
  nin.symbol = "%nin%",
  show.warnings = FALSE,
  nrows = Inf,
  drop = NULL,
  ...
)

Arguments

the.files

A character vector of file paths to scan. Non-existent files are automatically filtered out.

path.to.awk

A character string specifying the path to the AWK binary. If NULL (default), the function attempts to invoke a global system call to "awk".

delim

A character string specifying the column separator within the files. Default is ",".

the.filter

A character string or unquoted expression outlining the filtering logic to pass to AWK. Default is NULL (counts all records matching layout rules).

file.pattern

recursive

Logical. Should directory searches recurse into subdirectories when the.files contains directory paths? Default is FALSE.

the.variables

A character vector specifying active evaluation columns. Default is ".".

include.filename

A logical value indicating whether to retain tracking metrics grouped by individual files. Default is TRUE.

skip

A numeric offset, a character regex pattern, or a structured list indicating lines to bypass. If a list is used, it must follow dot notation:

skip.metadata.rows: An integer count or a character regex pattern used to identify where the metadata block ends.
skip.data.rows: An integer specifying the number of data rows to explicitly skip after the header.

Default is 0.

A character string defining the tracking header index. Default is "file".

num.files.per.batch

An integer specifying how many files to aggregate per pipeline call. Default is 1000.

return.as

A character string specifying the desired return format. Options are "result" (default), "code", or "all".

envir

The environment context in which variables are parsed. Default is parent.frame().

and.symbol

A character replacement flag for logical AND statements. Default is "&".

or.symbol

A character replacement flag for logical OR statements. Default is "|".

in.symbol

A character replacement flag for inclusion tests. Default is "%in%".

nin.symbol

A character replacement flag for exclusion tests. Default is "%nin%".

show.warnings

A logical value determining whether terminal messages are displayed. Default is FALSE.

nrows

An integer specifying the maximum total matching record sets to count. Default is Inf.

drop

A character or numeric index vector specifying columns to exclude from mapping.

...

Extra parameters forwarded to underlying internal setup routines.

Value

A data.table summarizing record counts per file (or overall), or raw shell string arrays.

Examples


# Create a sample CSV file with price data
tmp_file <- tempfile(fileext = ".csv")
write.csv(data.frame(id = 1:3, price = c(500, 15000, 20000)), tmp_file, row.names = FALSE)

# Get matching transaction counts without importing full rows
total_expensive_items <- record.count(
  the.files = tmp_file,
  the.filter = "price > 10000"
)
print(total_expensive_items)

# Clean up temporary file
unlink(tmp_file)

Core Translation Pipeline for Filtering Expressions

Description

Orchestrates the parsing and conversion of R-style filtering strings or logical statements into valid, executable AWK syntax expressions. Maps variables to their positional column indices (e.g., $1, $2) and handles operating-system-specific quote adjustments.

Usage

translate.filtering.statement(
  the.filter,
  the.variables,
  envir = parent.frame(),
  and.symbol = "&",
  or.symbol = "|",
  in.symbol = "%in%",
  nin.symbol = "%nin%",
  equation.symbols = c(">=", ">", "<=", "<", "!=", "==")
)

Arguments

the.filter

A character string or unquoted expression containing the R filtering statement.

the.variables

A character vector containing the full ordered variable names from the data header.

envir

The environment context in which variable evaluations are evaluated. Default is .GlobalEnv.

and.symbol

A character tracking key for logical AND operations. Default is "&".

or.symbol

A character tracking key for logical OR operations. Default is "|".

in.symbol

A character tracking key for membership matching operations. Default is "%in%".

nin.symbol

A character tracking key for excluded membership operations. Default is "%nin%".

equation.symbols

A character vector listing the recognized relational comparison operators. Default is c(">=", ">", "<=", "<", "!=", "==").

Value

A character string representing the compiled logic statement formatted for direct injection into an AWK pipeline execution.

Translate R Vector Membership Filters to AWK Logic

Description

Parses explicit vector membership statements containing the %in% operator, translating them into structurally matching compound matching loops or array validations in AWK syntax.

Usage

translate.in.statement(
  in.statement,
  the.variables,
  nin.symbol = "%nin%",
  in.symbol = "%in%",
  envir = parent.frame()
)

Arguments

in.statement

A character string representing an isolated membership statement fragment.

the.variables

A character vector matching data frame column names to map to column indexes.

nin.symbol

A character structural definition string representing negative matches. Default is "%nin%".

in.symbol

A character structural definition string representing positive matches. Default is "%in%".

envir

The evaluation context environment frame. Default is .GlobalEnv.

Value

A character string containing the mapped structural subset layout for the AWK statement block.

Global Scope Evaluation Framework for Membership Vectors

Description

Evaluates membership variables that point directly to larger active environment structures (like global character vectors) rather than internal row variables, building optimized inline conditional maps.

Usage

translate.in.statement.global(
  in.statement,
  the.variables,
  in.symbol,
  envir = .GlobalEnv
)

Arguments

in.statement

A character expression fragment mapping lookup requirements.

the.variables

A character vector matching the positional target mapping structure.

in.symbol

The specific string structure pattern to catch.

envir

The active R runtime environment containing the target variable content array. Default is .GlobalEnv.

Value

A resolved logical text mapping line compatible with text extraction shell commands.

Parse and Translate Standard R Logical Operators

Description

Evaluates low-level logical connectors within a segment of text, converting R's boolean layout terms (such as & or |) into corresponding AWK relational syntax blocks.

Usage

translate.logical.statement(
  the.statement,
  the.variables,
  envir = parent.frame()
)

Arguments

the.statement

A character string isolating a single logical operation block.

the.variables

A character vector containing the recognized file variable headers.

envir

The environment context in which the evaluation elements reside. Default is .GlobalEnv.

Value

A processed character string containing translated logical characters compatible with AWK.

Translate Negated R Vector Membership Filters to AWK Logic

Description

Special-case handler designed to invert membership matching statements containing the %nin% operation rules, converting them cleanly into negated validation criteria strings for AWK.

Usage

translate.nin.statement(
  nin.statement,
  the.variables,
  nin.symbol = "%nin%",
  in.symbol = "%in%",
  envir = parent.frame()
)

Arguments

nin.statement

A character string representing an isolated negative matching fragment.

the.variables

A character vector identifying known variable column allocations.

nin.symbol

The target string pattern matching an exclusion declaration. Default is "%nin%".

in.symbol

The target string pattern matching an inclusion declaration. Default is "%in%".

envir

The system environment lookup layer for evaluating vectors. Default is .GlobalEnv.

Value

An isolated, translated character block containing negated relational checks.

Package {awkreader}

Fast Stream Aggregation of Delimited Files via AWK

Description

Usage

Arguments

Value

Examples

Fast Batch Combining of Flat Files via AWK

Description

Usage

Arguments

Value

Examples

Execute AWK Script over Batches of Files (Internal Engine)

Description

Usage

Arguments

Value

Fast, Filtered Reading of Multiple Files via AWK

Description

Usage

Arguments

Value

Examples

Intelligent Auto-Detection for System AWK Binary

Description

Usage

Value

Pattern-Based Subsetting and Reading of Multiple Files via AWK

Description

Usage

Arguments

Value

Examples

Efficient Record and Row Counting via AWK

Description

Usage

Arguments

Value

Examples

Core Translation Pipeline for Filtering Expressions

Description

Usage

Arguments

Value

Translate R Vector Membership Filters to AWK Logic

Description

Usage

Arguments

Value

Global Scope Evaluation Framework for Membership Vectors

Description

Usage

Arguments

Value

Parse and Translate Standard R Logical Operators

Description

Usage

Arguments

Value

Translate Negated R Vector Membership Filters to AWK Logic

Description

Usage

Arguments

Value