1CSVSQL(1)                           csvkit                           CSVSQL(1)
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NAME

6       csvsql - csvsql Documentation
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DESCRIPTION

9       Generate  SQL  statements  for  a  CSV file or execute those statements
10       directly on a database. In  the  latter  case  supports  both  creating
11       tables and inserting data:
12
13          usage: csvsql [-h] [-d DELIMITER] [-t] [-q QUOTECHAR] [-u {0,1,2,3}] [-b]
14                        [-p ESCAPECHAR] [-z FIELD_SIZE_LIMIT] [-e ENCODING] [-L LOCALE]
15                        [-S] [--blanks] [--date-format DATE_FORMAT]
16                        [--datetime-format DATETIME_FORMAT] [-H] [-K SKIP_LINES] [-v]
17                        [-l] [--zero] [-V]
18                        [-i {firebird,mssql,mysql,oracle,postgresql,sqlite,sybase,crate}]
19                        [--db CONNECTION_STRING] [--query QUERY] [--insert]
20                        [--prefix PREFIX] [--tables TABLE_NAMES] [--no-constraints]
21                        [--unique-constraint UNIQUE_CONSTRAINT] [--no-create]
22                        [--create-if-not-exists] [--overwrite] [--db-schema DB_SCHEMA]
23                        [-y SNIFF_LIMIT] [-I] [--chunk-size NUM]
24                        [FILE [FILE ...]]
25
26          Generate SQL statements for one or more CSV files, or execute those statements
27          directly on a database, and execute one or more SQL queries.
28
29          positional arguments:
30            FILE                  The CSV file(s) to operate on. If omitted, will accept
31                                  input on STDIN.
32
33          optional arguments:
34            -h, --help            show this help message and exit
35            -i {firebird,mssql,mysql,oracle,postgresql,sqlite,sybase,crate}, --dialect {firebird,mssql,mysql,oracle,postgresql,sqlite,sybase,crate}
36                                  Dialect of SQL to generate. Only valid when --db is
37                                  not specified.
38            --db CONNECTION_STRING
39                                  If present, a sqlalchemy connection string to use to
40                                  directly execute generated SQL on a database.
41            --query QUERY         Execute one or more SQL queries delimited by ";" and
42                                  output the result of the last query as CSV. QUERY may
43                                  be a filename.
44            --insert              In addition to creating the table, also insert the
45                                  data into the table. Only valid when --db is
46                                  specified.
47            --prefix PREFIX       Add an expression following the INSERT keyword, like
48                                  OR IGNORE or OR REPLACE.
49            --tables TABLE_NAMES  A comma-separated list of names of tables to be
50                                  created. By default, the tables will be named after
51                                  the filenames without extensions or "stdin".
52            --no-constraints      Generate a schema without length limits or null
53                                  checks. Useful when sampling big tables.
54            --unique-constraint UNIQUE_CONSTRAINT
55                                  A column-separated list of names of columns to include
56                                  in a UNIQUE constraint.
57            --no-create           Skip creating a table. Only valid when --insert is
58                                  specified.
59            --create-if-not-exists
60                                  Create table if it does not exist, otherwise keep
61                                  going. Only valid when --insert is specified.
62            --overwrite           Drop the table before creating. Only valid when
63                                  --insert is specified and --no-create is not
64                                  specified.
65            --db-schema DB_SCHEMA
66                                  Optional name of database schema to create table(s)
67                                  in.
68            -y SNIFF_LIMIT, --snifflimit SNIFF_LIMIT
69                                  Limit CSV dialect sniffing to the specified number of
70                                  bytes. Specify "0" to disable sniffing entirely.
71            -I, --no-inference    Disable type inference when parsing the input.
72            --chunk-size NUM
73                                  Chunk size for batch insert into the table.
74                                  Only valid when --insert is specified.
75
76       See also: ../common_arguments.
77
78       For  information  on connection strings and supported dialects refer to
79       the SQLAlchemy documentation.
80
81       If you prefer not to enter your  password  in  the  connection  string,
82       store  the  password  securely  in  a PostgreSQL Password File, a MySQL
83       Options File or similar files for other systems.
84
85       NOTE:
86          Using the --query option may cause rounding (in Python 2) or  intro‐
87          duce         [Python         floating         point        issues](‐
88          https://docs.python.org/3.4/tutorial/floatingpoint.html) (in  Python
89          3).
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EXAMPLES

92       Generate a statement in the PostgreSQL dialect:
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94          csvsql -i postgresql examples/realdata/FY09_EDU_Recipients_by_State.csv
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96       Create a table and import data from the CSV directly into PostgreSQL:
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98          createdb test
99          csvsql --db postgresql:///test --tables fy09 --insert examples/realdata/FY09_EDU_Recipients_by_State.csv
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101       For  large  tables it may not be practical to process the entire table.
102       One solution to this is to analyze a sample of the table. In this  case
103       it  can  be  useful  to turn off length limits and null checks with the
104       --no-constraints option:
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106          head -n 20 examples/realdata/FY09_EDU_Recipients_by_State.csv | csvsql --no-constraints --tables fy09
107
108       Create tables for an entire folder of CSVs and import data  from  those
109       files directly into PostgreSQL:
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111          createdb test
112          csvsql --db postgresql:///test --insert examples/*_converted.csv
113
114       If those CSVs have identical headers, you can import them into the same
115       table by using csvstack first:
116
117          createdb test
118          csvstack examples/dummy?.csv | csvsql --db postgresql:///test --insert
119
120       Group rows by one column:
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122          csvsql --query "select * from 'dummy3' group by a" examples/dummy3.csv
123
124       You can also use CSVSQL to “directly” query  one  or  more  CSV  files.
125       Please  note  that  this  will  create an in-memory SQL database, so it
126       won’t be very fast:
127
128          csvsql --query  "select m.usda_id, avg(i.sepal_length) as mean_sepal_length from iris as i join irismeta as m on (i.species = m.species) group by m.species" examples/iris.csv examples/irismeta.csv
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130       Concatenate two columns:
131
132          csvsql --query "select a || b from 'dummy3'" examples/dummy3.csv
133
134       If a column contains null values, you must COALESCE the column:
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136          csvsql --query "select a || COALESCE(b, '') from 'sort_ints_nulls'" --no-inference examples/sort_ints_nulls.csv
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AUTHOR

139       Christopher Groskopf
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142       2020, Christopher Groskopf
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1471.0.4                            Jan 30, 2020                        CSVSQL(1)
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