## NAME

v.db.select - Prints vector map attributes.

## KEYWORDS

vector, attribute table, database, SQL, export

## SYNOPSIS

v.db.select
v.db.select --help
v.db.select [-rcef] map=name [layer=string] [columns=name[,name,...]] [where=sql_query] [group=string] format=name [separator=character] [vertical_separator=character] [null_value=string] [file=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

### Flags:

-r
  Print minimal region extent of selected vector features instead of attributes
-c
  Do not include column names in output
-e
  Escape newline and backslash characters
-f
  Exclude attributes not linked to features
--overwrite
  Allow output files to overwrite existing files
--help
  Print usage summary
--verbose
  Verbose module output
--quiet
  Quiet module output
--ui
  Force launching GUI dialog

### Parameters:

map=name [required]
  Name of vector map
  Or data source for direct OGR access
layer=string
  Layer number or name
  Vector features can have category values in different layers. This number determines which layer to use. When used with direct OGR access this is the layer name.
  Default: 1
columns=name[,name,...]
  Name of attribute column(s)
where=sql_query
  WHERE conditions of SQL statement without 'where' keyword
  Example: income < 1000 and population >= 10000
group=string
  GROUP BY conditions of SQL statement without 'group by' keyword
format=name [required]
  Output format
  Options: plain, csv, json, vertical
  Default: plain
  plain: Configurable plain text output
  csv: CSV (Comma Separated Values)
  json: JSON (JavaScript Object Notation)
  vertical: Plain text vertical output (instead of horizontal)
separator=character
  Field separator
  Special characters: pipe, comma, space, tab, newline
vertical_separator=character
  Output vertical record separator
  Special characters: pipe, comma, space, tab, newline
null_value=string
  String representing NULL value
file=name
  Name for output file (if omitted or "-" output to stdout)

## DESCRIPTION

v.db.select prints attributes of a vector map from one or several user selected attribute table columns.

### Output formats

Four different formats can be used depending on the circumstances using the format option: plain text, CSV, JSON, and vertical plain text.

#### Plain text

The plain text is the default output which is most suitable for reading by humans, e.g., when working in the command line or obtaining specific values from the attribute table using the v.db.select GUI dialog.

The individual fields (attribute values) are separated by a pipe (`|`) which can be customized using the separator option. The records (rows) are separated by newlines.

Example with a pipe as a separator (the default):

    cat|road_name|multilane|year|length
    1|NC-50|no|2001|4825.369405
    2|NC-50|no|2002|14392.589058
    3|NC-98|no|2003|3212.981242
    4|NC-50|no|2004|13391.907552

When escaping is enabled, the following characters in the fields are escaped: backslash (`\\`), carriage return (`\r`), line feed (`\n`), tabulator (`\t`), form feed (`\f`), and backslash (`\b`).

No quoting or escaping is performed by default, so if these characters are in the output, they look just like the separators. This is usually not a problem for humans looking at the output to get a general idea about query result or attribute table content.

Consequently, this format is not recommended for computers, e.g., for reading attribute data in Python scripts. It works for further parsing in limited cases when the values don't contain separators or when the separators are set to one of the escaped characters.

#### CSV

CSV (comma-separated values) has many variations. This module by default produces CSV with comma (`,`) as the field separator (delimiter). All text fields (based on the type) are quoted with double quotes. Double quotes in fields are represented as two double quotes. Newline characters in the fields are present as-is in the output. Header is included by default containing column names.

All full CSV parsers such as the ones in LibreOffice or Python are able to parse this format when configured to the above specification.

Example with default settings:

    cat,road_name,multilane,year,length
    1,"NC-50","no",2001,4825.369405
    2,"NC-50","no",2002,14392.589058
    3,"NC-98","no",2003,3212.981242
    4,"NC-50","no",2004,13391.907552

If desired, the separator can be customized and escaping can be enabled with the same characters being escaped as for the plain text. Notably, newlines and tabs are escaped, double quotes are not, and the separator is not escaped either (unless it is a tab). However, the format is guaranteed only for the commonly used separators such as comma, semicolon, pipe, and tab.

Note that using multi-character separator is allowed, but not recommended as it is not generally supported by CSV readers.

CSV is the recommended format for further use in another analytical applications, especially for use with spreadsheet applications. For scripting, it is advantageous when tabular data is needed (rather than key-value pairs).

#### JSON

JSON (JavaScript Object Notation) format is produced according to the specification so it is readily readable by JSON parsers. The standard JSON escapes are performed (backslash, carriage return, line feed, tabulator, form feed, backslash, and double quote) for string values. Numbers in the database such as integers and doubles are represented as numbers, while texts (TEXT, VARCHAR, etc.) and dates in the database are represented as strings in JSON. NULL values in database are represented as JSON `null`. Indentation and newlines in the output are minimal and not guaranteed.

Records which are the result of the query are stored under key `records` as an array (list) of objects (collections of key-value pairs). The keys for attributes are lowercase or uppercase depending on how the columns were defined in the database.

The JSON also contains information about columns stored under key `info`. Column names and types are under key `columns`. Each column has SQL data type under `sql_type` in all caps. A boolean `is_number` specifies whether the value is a number, i.e., integer or floating point number. The `is_number` value is aded for convenience and it is recommended to rely on the types derived from the JSON representation or the SQL types. The definition of `is_number` may change in the future.

Example with added indentation:

    {
      "info": {
        "columns": [
          {
            "name": "road_name",
            "sql_type": "CHARACTER",
            "is_number": false
          },
          {
            "name": "year",
            "sql_type": "INTEGER",
            "is_number": true
          },
          {
            "name": "length",
            "sql_type": "DOUBLE PRECISION",
            "is_number": true
          }
        ]
      },
      "records": [
        {
          "road_name": "NC-50",
          "year": 2001,
          "length": 4825.369405
        },
        {
          "road_name": "NC-50",
          "year": 2001,
          "length": 14392.589058
        }
      ]
    }

JSON is the recommended format for reading the data in Python and for any uses and environments where convenient access to individual values is desired and JSON parser is available.

#### Vertical plain text

In the vertical plain text format, each value is on a single line and is preceded by the name of the attribute (column) which is separated by separator. The individual records can be separated by the vertical separator (vertical_separator option).

Example with (horizontal) separator `=` and vertical separator `newline`:

    cat=1
    road_name=NC-50
    multilane=no
    year=2001
    length=4825.369405

    cat=2
    road_name=NC-50
    multilane=no
    year=2002
    length=14392.589058

Newline is automatically added after a vertical separator unless it is a newline which allows for separating the records, e.g., by multiple dashes. The escaping (-e) need to should be enabled in case the output is meant for reading by a computer rather than just as a data overview for humans. Escaping will ensure that values with newlines will be contained to a single line. This format is for special uses in scripting, for example, in combination with columns option set to one column only and escaping (-e) and no column names flags (-c). It is also advantageous when you need implement the parsing yourself.

## NOTES

- CSV and JSON were added in version 8.0 as new primary formats for further consumption by scripts and other applications.
- Escaping of plain and vertical formats was extended from just backslash and newlines to all escapes from JSON except for double quote character.

## EXAMPLES

All examples are based on the North Carolina sample dataset.

### Select and show entire table

    v.db.select map=roadsmajor
    cat|MAJORRDS_|ROAD_NAME|MULTILANE|PROPYEAR|OBJECTID|SHAPE_LEN
    1|1|NC-50|no|0|1|4825.369405
    2|2|NC-50|no|0|2|14392.589058
    3|3|NC-98|no|0|3|3212.981242
    4|4|NC-50|no|0|4|13391.907552
    ...

### Select and show single column from table

Note: multiple columns can be specified as comma separated list.

    v.db.select map=roadsmajor column=ROAD_NAME
    NC-50
    NC-50
    NC-98
    NC-50
    NC-98
    ...

### Print region extent of selected vector features

    v.db.select -r map=roadsmajor where="ROAD_NAME = 'NC-98'"
    n=248425.389891
    s=245640.640081
    w=635906.517653
    e=661979.801880

### Select empty vector features (no data entries)

    v.db.select geonames_wake where="ALTERNATEN IS NULL"
    cat|GEONAMEID|NAME|ASCIINAME|ALTERNATEN|FEATURECLA|FEATURECOD|...
    8|4498303|West Raleigh|West Raleigh||P|PPL|US||NC|338759|123|...
    14|4459467|Cary|Cary||P|PPL|US||NC|103945|146|152|America/Iqaluit|...
    31|4452808|Apex|Apex||P|PPL|US||NC|30873|167|134|America/Iqaluit|...
    ...

### Select not empty vector features (no data entries)

    v.db.select geonames_wake where="ALTERNATEN IS NOT NULL"
    cat|GEONAMEID|NAME|ASCIINAME|ALTERNATEN|FEATURECLA|FEATURECOD|...
    9|4487042|Raleigh|Raleigh|Raleigh,...
    31299|4487056|Raleigh-Durham Airport|Raleigh-Durham Airport|...
    ...

### Select features with distinct road names

    v.db.select map=roadsmajor columns=ROAD_NAME group=ROAD_NAME
    ROAD_NAME

    I-40
    I-440
    I-540
    NC-231
    NC-39
    NC-42
    ...

It is also possible to combine with where option

    v.db.select map=roadsmajor columns=ROAD_NAME,MULTILANE group=ROAD_NAME where='ROAD_NAME is not null'
    ROAD_NAME|MULTILANE
    I-40|yes
    I-440|yes
    I-540|yes
    NC-231|no
    NC-39|no
    NC-42|no
    NC-50|no
    NC-54|no
    NC-55|no
    NC-96|no
    NC-97|no
    NC-98|no
    US-1|
    US-401|no
    US-64|yes
    US-70|yes

It can also use more columns in group option

    v.db.select map=roadsmajor columns=ROAD_NAME,MULTILANE group=ROAD_NAME,MULTILANE where='ROAD_NAME is not null'
    ROAD_NAME|MULTILANE
    I-40|yes
    I-440|yes
    I-540|yes
    NC-231|no
    NC-39|no
    NC-42|no
    NC-50|no
    NC-54|no
    NC-55|no
    NC-96|no
    NC-97|no
    NC-98|no
    US-1|
    US-1|yes
    US-401|no
    US-401|yes
    US-64|yes
    US-70|yes

### Read results in Python

The json package in the standard Python library can load a JSON string obtained as output from the v.db.select module through the read_command function:

    import json
    import grass.script as gs

    text = gs.read_command("v.db.select", map="roadsmajor", format="json")
    data = json.loads(text)
    for row in data["records"]:
        print(row["ROAD_NAME"])

## SEE ALSO

db.select

GRASS SQL interface

## AUTHORS

Radim Blazek, ITC-Irst, Trento, Italy
Minimal region extent added by Martin Landa, FBK-irst (formerly ITC-irst), Trento, Italy
Group option added by Luca Delucchi, Fondazione Edmund Mach, Trento, Italy
Huidae Cho (JSON output, escaping and features-only flags)
Vaclav Petras (true CSV output, format option and documentation)

## SOURCE CODE

Available at: v.db.select source code (history)

Accessed: Thursday Oct 30 22:17:55 2025

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