Description:

csvsupdatesqlite 1.3.11

csvs-update-sqlite
Convert CSV files into a SQLite database. Browse and publish that SQLite database with Datasette.
Based on csvs-to-sqlite.
Basic usage:
csvs-update-sqlite myfile.csv mydatabase.db

This will create a new SQLite database called mydatabase.db containing a
single table, myfile, containing the CSV content.
You can provide multiple CSV files:
csvs-update-sqlite one.csv two.csv bundle.db

The bundle.db database will contain two tables, one and two.
This means you can use wildcards:
csvs-update-sqlite ~/Downloads/*.csv my-downloads.db

If you pass a path to one or more directories, the script will recursively
search those directories for CSV files and create tables for each one.
csvs-update-sqlite ~/path/to/directory all-my-csvs.db

Handling TSV (tab-separated values)
You can use the -s option to specify a different delimiter. If you want
to use a tab character you'll need to apply shell escaping like so:
csvs-update-sqlite my-file.tsv my-file.db -s $'\t'

Refactoring columns into separate lookup tables
Let's say you have a CSV file that looks like this:
county,precinct,office,district,party,candidate,votes
Clark,1,President,,REP,John R. Kasich,5
Clark,2,President,,REP,John R. Kasich,0
Clark,3,President,,REP,John R. Kasich,7

(Real example taken from the Open Elections project)
You can now convert selected columns into separate lookup tables using the new
--extract-column option (shortname: -c) - for example:
csvs-update-sqlite openelections-data-*/*.csv \
-c county:County:name \
-c precinct:Precinct:name \
-c office -c district -c party -c candidate \
openelections.db

The format is as follows:
column_name:optional_table_name:optional_table_value_column_name

If you just specify the column name e.g. -c office, the following table will
be created:
CREATE TABLE "office" (
"id" INTEGER PRIMARY KEY,
"value" TEXT
);

If you specify all three options, e.g. -c precinct:Precinct:name the table
will look like this:
CREATE TABLE "Precinct" (
"id" INTEGER PRIMARY KEY,
"name" TEXT
);

The original tables will be created like this:
CREATE TABLE "ca__primary__san_francisco__precinct" (
"county" INTEGER,
"precinct" INTEGER,
"office" INTEGER,
"district" INTEGER,
"party" INTEGER,
"candidate" INTEGER,
"votes" INTEGER,
FOREIGN KEY (county) REFERENCES County(id),
FOREIGN KEY (party) REFERENCES party(id),
FOREIGN KEY (precinct) REFERENCES Precinct(id),
FOREIGN KEY (office) REFERENCES office(id),
FOREIGN KEY (candidate) REFERENCES candidate(id)
);

They will be populated with IDs that reference the new derived tables.
Installation
$ pip install csvs-update-sqlite

csvs-update-sqlite --help

Usage: csvs-update-sqlite [OPTIONS] PATHS... DBNAME

PATHS: paths to individual .csv files or to directories containing .csvs

DBNAME: name of the SQLite database file to create

Options:
-s, --separator TEXT Field separator in input .csv
-q, --quoting INTEGER Control field quoting behavior per csv.QUOTE_*
constants. Use one of QUOTE_MINIMAL (0),
QUOTE_ALL (1), QUOTE_NONNUMERIC (2) or
QUOTE_NONE (3).

--skip-errors Skip lines with too many fields instead of
stopping the import

--replace-tables Replace tables if they already exist
--update-tables Manages an extra table .csvs-meta that keeps
track of each CSV file and the checksum of the
file. On subsequent runs, the CSVs will be
compared against the checksum in the table to
see what has updated, and only those specific
tables will be replaced.

-t, --table TEXT Table to use (instead of using CSV filename)
-c, --extract-column TEXT One or more columns to 'extract' into a
separate lookup table. If you pass a simple
column name that column will be replaced with
integer foreign key references to a new table
of that name. You can customize the name of
the table like so: state:States:state_name

This will pull unique values from the 'state'
column and use them to populate a new 'States'
table, with an id column primary key and a
state_name column containing the strings from
the original column.

-d, --date TEXT One or more columns to parse into ISO
formatted dates

-dt, --datetime TEXT One or more columns to parse into ISO
formatted datetimes

-df, --datetime-format TEXT One or more custom date format strings to try
when parsing dates/datetimes

-pk, --primary-key TEXT One or more columns to use as the primary key
-f, --fts TEXT One or more columns to use to populate a full-
text index

-i, --index TEXT Add index on this column (or a compound index
with -i col1,col2)

--shape TEXT Custom shape for the DB table - format is
csvcol:dbcol(TYPE),...

--filename-column TEXT Add a column with this name and populate with
CSV file name

--fixed-column <TEXT TEXT>... Populate column with a fixed string
--fixed-column-int <TEXT INTEGER>...
Populate column with a fixed integer
--fixed-column-float <TEXT FLOAT>...
Populate column with a fixed float
--no-index-fks Skip adding index to foreign key columns
created using --extract-column (default is to
add them)

--no-fulltext-fks Skip adding full-text index on values
extracted using --extract-column (default is
to add them)

--just-strings Import all columns as text strings by default
(and, if specified, still obey --shape,
--date/datetime, and --datetime-format)

--version Show the version and exit.
--help Show this message and exit.

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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