quallmer (version 0.4.0)

accessors: Accessor functions for quallmer objects

Description

Functions to safely access and modify metadata from quallmer objects (qlm_coded, qlm_comparison, qlm_validation, qlm_codebook). These functions provide a stable API for accessing object metadata without directly manipulating internal attributes.

Metadata types

quallmer objects store metadata in three categories:

User metadata (type = "user"):

• name: Run identifier (settable)

• notes: Descriptive notes (settable)

• Plus any custom fields added via as_qlm_coded(..., metadata = list(...))

Object metadata (type = "object"):

• call: Function call that created the object

• parent: Parent run name (for replications)

• batch: Whether batch processing was used

• chat_args: Arguments passed to the LLM chat

• execution_args: Arguments for parallel/batch execution

• n_units: Number of coded units

• input_type: Type of input ("text", "image", or "human")

• source: Coding source ("human" or "llm")

• is_gold: Whether this is a gold standard

System metadata (type = "system"):

• timestamp: When the object was created

• ellmer_version: Version of ellmer package

• quallmer_version: Version of quallmer package

• R_version: Version of R

Functions

• qlm_meta(): Get metadata fields

• qlm_meta<-(): Set user metadata fields (only name and notes)

• codebook(): Extract codebook from coded objects

• inputs(): Extract original input data

See Also

• qlm_code() for creating coded objects

• as_qlm_coded() for converting human-coded data

• qlm_trail() for viewing coding history

Examples

# \donttest{
# Create a coded object
texts <- c("I love this!", "Terrible.", "It's okay.")
coded <- qlm_code(
  texts,
  data_codebook_sentiment,
  model = "openai/gpt-4o-mini",
  name = "run1",
  notes = "Initial coding run"
)

# Access metadata
qlm_meta(coded, "name")              # Get run name
qlm_meta(coded, type = "user")       # Get all user metadata
qlm_meta(coded, type = "system")     # Get system metadata

# Modify user metadata
qlm_meta(coded, "name") <- "updated_run1"
qlm_meta(coded, "notes") <- "Revised notes"

# Extract components
codebook(coded)                      # Get the codebook
inputs(coded)                        # Get original texts

# Custom metadata from human coding
human_data <- data.frame(
  .id = 1:5,
  sentiment = c("pos", "neg", "pos", "neg", "pos")
)
human_coded <- as_qlm_coded(
  human_data,
  name = "coder_A",
  metadata = list(
    coder_name = "Dr. Smith",
    experience = "5 years"
  )
)

# Access custom metadata
qlm_meta(human_coded, "coder_name")  # "Dr. Smith"
qlm_meta(human_coded, type = "user") # All user fields
# }