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 di‐
10       rectly on a database. In the latter case supports both creating  tables
11       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 ...]]
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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.
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78       For  information  on connection strings and supported dialects refer to
79       the SQLAlchemy documentation.
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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 Op‐
83       tions 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:
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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:
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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       2022, Christopher Groskopf
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1471.0.4                            Jan 21, 2022                        CSVSQL(1)
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