| yaml_agent_string | R Documentation |
With pointblank YAML, we can serialize an agent's validation plan (with
yaml_write()), read it back later with a new agent (with
yaml_read_agent()), or perform an interrogation on the target data table
directly with the YAML file (with yaml_agent_interrogate()). The
yaml_agent_string() function allows us to inspect the YAML generated by
yaml_write() in the console, giving us a look at the YAML without needing
to open the file directly. Alternatively, we can provide an agent to the
yaml_agent_string() and view the YAML representation of the validation plan
without needing to write the YAML to disk beforehand.
yaml_agent_string(agent = NULL, filename = NULL, path = NULL, expanded = FALSE)
agent |
An agent object of class |
filename |
The name of the YAML file that contains fields related to an
agent. If a file name is provided here, then agent object must not be
provided in |
path |
An optional path to the YAML file (combined with |
expanded |
Should the written validation expressions for an agent be
expanded such that tidyselect expressions for columns are evaluated,
yielding a validation function per column? By default, this is |
Nothing is returned. Instead, text is printed to the console.
There's a YAML file available in the pointblank package that's called
"agent-small_table.yml". The path for it can be accessed through
system.file():
yml_file_path <-
system.file(
"yaml", "agent-small_table.yml",
package = "pointblank"
)
We can view the contents of the YAML file in the console with the
yaml_agent_string() function.
yaml_agent_string(filename = yml_file_path)
type: agent
tbl: ~ tbl_source("small_table", "tbl_store.yml")
tbl_name: small_table
label: A simple example with the `small_table`.
lang: en
locale: en
actions:
warn_fraction: 0.1
stop_fraction: 0.25
notify_fraction: 0.35
steps:
- col_exists:
columns: vars(date)
- col_exists:
columns: vars(date_time)
- col_vals_regex:
columns: vars(b)
regex: '[0-9]-[a-z]{3}-[0-9]{3}'
- rows_distinct:
columns: ~
- col_vals_gt:
columns: vars(d)
value: 100.0
- col_vals_lte:
columns: vars(c)
value: 5.0
Incidentally, we can also use yaml_agent_string() to print YAML in the
console when supplying an agent object as the input. This can be useful for
previewing YAML output just before writing it to disk with yaml_write().
11-5
Other pointblank YAML:
yaml_agent_interrogate(),
yaml_agent_show_exprs(),
yaml_exec(),
yaml_informant_incorporate(),
yaml_read_agent(),
yaml_read_informant(),
yaml_write()
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