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In-Process, In-Memory & File-Based Relational Data Processing with SQLite, BetterSQLite3
Table of Contents generated with DocToc
DBay is built on better-sqlite3
, which is a NodeJS adapter
for SQLite. It provides convenient access to in-process, on-file and in-memory
relational databases.
DBay is the successor to and a re-write of ICQL-DBA. It is under development and nearing feature-parity with its predecessor while already providing some significant improvements in terms of ease of use and simplicity of implementation.
DBay provides
better-sqlite3
,In order to construct (instantiate) a DBay object, you can call the constructor without any arguments:
{ DBay } = require 'dbay'
db = new DBay()
The db
object will then have two properties db.sqlt1
and db.sqlt2
that are better-sqlite3
connections to the same temporary DB in the 'automatic location'.
The db
object will then have a (non-enumerable) property db.sqlt1
which is a better-sqlite3
connection
to a temporary DB in the 'automatic location'.
The so-called 'automatic location' is either
/dev/shm
on Linux systems that support SHared Memory (a.k.a a RAM disk)os.tmpdir()
In either case, a file with a random name will be created in that location.
Format dbay-NNNNNNNNNN.sqlite
, where N
is a digit [0-9]
.
You can also call the constructor with a configuration object that may have one or more of the following fields:
cfg.path
(?non-empty text
): Specifies which file system path to save the DB to; if the path given
is relative, it will be resolved in reference to the current directory (process.cwd()
). When not
specified, cfg.path
will be derived from DBay.C.autolocation
and a randomly
chosen filename.
cfg.temporary
(?boolean
): Specifies whether DB file is to be removed when process exits or
db.destry()
is called explicitly. cfg.temporary
defaults to false
if cfg.path
is given, and true
otherwise (when a random filename is chosen).
db.open cfg
: Attach a new or existing DB to the db
's
connections ( (db.sqlt1
, db.sqlt1
).db.sqlt1
).
cfg
:
schema
(non-empty string): Required property that specifies the name under which the newly attached
DB's objects can be accessed as; having attached a DB as, say, db.open { schema: 'foo', path: 'path/to/my.db', }
, one can then run queries like db "select * from foo.main;"
against it. Observe
that
db = new DBay()
) always has the implicit name main
, and
schema temp
is reserved for temporary databases.path
(string): FS path to existing or to-be-created DB file; for compatibility, this may also be set
to one of the special values that indicates a in-memory
DB, although that is not recommended.temporary
(boolean): Defaults to false
when a path
is given, and to true
otherwise.The custom SQLite library that is compiled when installing DBay has its SQLITE_LIMIT_ATTACHED
compilation parameter set to the maximum allowed value of 125 (instead of the default 10). This allows
developers to assemble a DB application from dozens of smaller pieces when desired.
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alt
ernative Connection to Avoid Connection Busy ErrorsSQLite imposes certain restrictions on what one can and cannot do in a concurrent fashion, one restriction
being that within the same connection, one cannot at the same time iterate over query results and insert
valuesβnot even into a completely unrelated table. There are ways to get around that limitation. For one,
the standard recommendation of the maker of better-sqlite3
is to just fetch all the needed rows from the
DB and then iterate over the list of values. This is totally doable and the simplest and most transparent
solution, but of course a nagging thought remainsβwhat if the dataset gets really huge? In reality, this may
turn out never to be a problem, realistically, but that consideration won't make that nagging thought
vanish.
There's a (seemingly) better way. Commit 57e062a
: make alt
an on-demand clone of present
instance
introduces the new (non-enumerable) property db.alt
which represents a clone of the db
object. Previous
versions had two underlying DB connections sqlt1
and sqlt2
which could be used for the purposes
described in this section, but their drawback was that one falls back to the underlying better-sqlite3
API
which can be a little confusing.
Let's have a look at a toy DB and see how to use db.alt
. This is the definition, two tables with one
integer field each:
#.................................................................................
db SQL"""
create table foo ( n integer );
create table bar ( n integer );"""
for n in [ 10 .. 12 ]
db SQL"insert into foo ( n ) values ( $n );", { n, }
And here's what we want to accomplish: read data from one table and, based on that data, insert records into another one. NaΓ―vely one would perhaps write it this way (the transaction being added because we need it later anyway):
db.with_transaction =>
for row from db SQL"select * from foo order by n;"
info '^806-2^', row
db SQL"insert into bar values ( $n );", { n: n ** 2, }
return null
This will not run, however, but fail with TypeError: This database connection is busy executing a query
.
This is where db.alt
comes in: we have to use one connection for the iteration and another one for the
insertion; this works:
#.................................................................................
# (1)
db.with_transaction =>
for { n, } from db.alt SQL"select * from foo order by n;"
# ^^^^^^
db SQL"insert into bar values ( $n ) returning *;", { n: n ** 2, }
return null
The following points should be kept in mind: Explicit transactions and explicit prepared statements are
they key factors for speedy insert
s. Since explicit transactions are crucial for concurrent inserts, it's
recommended to do all inserts within explicit transactions.
Therefore, because it's good practice to use explicit transactions and explicit prepared statements when
doing inserts, most of the time inserts should take on the form shown in snippets (2)
or (4)
:
#.................................................................................
# (2)
insert_into_bar = db.prepare SQL"insert into bar values ( $n ) returning *;"
db.with_transaction =>
for { n, } from db.alt SQL"select * from foo order by n;"
insert_into_bar.run { n: n ** 2, }
return null
Observe that we have to explicitly exhaust the iterator that is returned from insert ... returning
statements; to do so, either use db.first_row()
or call a prepared statement's .get()
(instead of
.run()
) method:
#.................................................................................
# (3)
db.with_transaction =>
for { n, } from db.alt SQL"select * from foo order by n;"
new_row = db.first_row SQL"insert into bar values ( $n ) returning *;", { n: n ** 2, }
return null
#.................................................................................
# (4)
insert_into_bar = db.prepare SQL"insert into bar values ( $n ) returning *;"
db.with_transaction =>
for { n, } from db.alt SQL"select * from foo order by n;"
new_row = insert_into_bar.get { n: n ** 2, }
return null
SQL
Tag Function for Better Embedded SyntaxMixing SQL and application code has the drawback that instead of editing SQL
in your SQL-aware text editor, now you are editing bland string literals in
your SQL-aware editor. If there only was a way to tell the editor that some
strings contain SQL and should be treated as such!βWell, now there is. The
combined power of [JavaScript Tagged Templates]
(https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Template_literals#tagged_template_literals)
and an (exprimental proof-of-concept level) [set of Sublime Text syntax
definitions called coffeeplus
]
(https://github.com/loveencounterflow/coffeeplus) makes it possible to embed
SQL into JavaScript (and CoffeeScript) source code. The way this works is by
providing a 'tag function' that can be prepended to string literals. The name
of the function together with the ensuing quotes can be recognized by the editor's
hiliter so that constructs like SQL"..."
, SQL"""..."""
and so will trigger
switching languages. The tag function does next to nothing; here is its definition:
class DBay
@SQL: ( parts, expressions... ) ->
R = parts[ 0 ]
for expression, idx in expressions
R += expression.toString() + parts[ idx + 1 ]
return R
It can be used like this:
{ DBay } = require 'dbay'
{ SQL } = DBay
db = new DBay { path: 'path/to/db.sqlite', }
for row from db SQL"select id, name, price from products order by 1;"
# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
# imagine proper embedded hiliting etc here
console.log row.id, row.name, row.price
Be aware that coffeeplus
is more of an MVP than a polished package. As such, not
even reckognizing backticks has been implemented yet so is probably best used
with CoffeeScript.
One thing that sets DBay apart from other database adapters is the fact that the object returned from new DBay()
is both the representative of the database opened and a callable function. This makes executing
statements and running queries very concise. This is an excerpt from the DBay test suite:
{ DBay } = require H.dbay_path
db = new DBay()
db ->
db SQL"drop table if exists texts;"
db SQL"create table texts ( nr integer not null primary key, text text );"
db SQL"insert into texts values ( 3, 'third' );"
db SQL"insert into texts values ( 1, 'first' );"
db SQL"insert into texts values ( ?, ? );", [ 2, 'second', ]
#.......................................................................................................
T?.throws /cannot start a transaction within a transaction/, ->
db ->
#.........................................................................................................
T?.throws /UNIQUE constraint failed: texts\.nr/, ->
db ->
db SQL"insert into texts values ( 3, 'third' );"
#.........................................................................................................
rows = db SQL"select * from texts order by nr;"
rows = [ rows..., ]
T?.eq rows, [ { nr: 1, text: 'first' }, { nr: 2, text: 'second' }, { nr: 3, text: 'third' } ]
Note In the above
SQL
has been set toString.raw
and has no further effect on the string it precedes; it is just used as a syntax marker (cool because then you can have nested syntax hiliting).
As shown by benchmarks, a crucial factor for getting maximum performance out of
using SQLite is strategically placed transactions. SQLite will not ever execute a DB query outside of a
transaction; when no transaction has been explicitly opened with begin transaction
, the DB engine will
precede each query implicitly with (the equivalent of) begin transaction
and follow it with either
commit
or rollback
. This means when a thousand insert
statements are run, a thousand transactions will
be started and committed, leavin performance pretty much in the dust.
To avoid that performance hit, users are advised to always start and commit transactions when doing many
consecutive queries. DBay's callable db
object makes that easy: just write db -> many; inserts; here;
(JS: db( () -> { many; inserts; here; })
), i.e. pass a function as the sole argument to db
, and DBay
will wrap that function with a transaction. In case an error should occur, DBay guarantees to call
rollback
(in a try ... finally ...
clause). Those who like to make things more explicit can also use
db.with_transaction ->
. Both formats allow to pass in a configuration object with an attribute mode
that
may be set to one of 'deferred'
, 'immediate'
, or
'exclusive'
, the default being 'deferred'
.
Another slight performance hit may be caused by the logic DBay uses to (look up an SQL text in a cache or)
prepare a statement and then decide whether to call better-sqlite3
's' Database::execute()
,
Statement::run()
or Statement::iterate()
; in order to circumvent that extra work, users may choose to
fall back on to better-sqlite3
explicitly:
insert = db.prepare SQL"insert into texts values ( ?, ? );" # returns a `better-sqlite3` `Statement` instance
db ->
insert.run [ 2, 'second', ]
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
Strings
std_str_reverse()
std_str_join()
std_str_split()
std_str_split_re()
std_str_split_first()
std_re_matches()
XXX
std_generate_series()
Output
std_echo()
std_debug()
std_info()
std_warn()
Exceptions and Assertions
std_raise( message )
βunconditionally throw an error with message given.std_raise_json( facets_json )
βunconditionally throw an error with informational properties encoded
as a JSON string.std_assert( test, message )
βthrow an error with message
if test
is falsy.std_warn_if( test, message )
βprint an error message
if test
is truthy.std_warn_unless()
βprint an error message
if test
is falsy.Variables
std_getv()
std_variables()
std_assert: ( test, message ) ->
throws error if test
is false(y)std_warn_unless: ( test, message ) ->
prints warning if test
is false(y)count(*)
.limit 1
where appropriate.select
*,
std_assert(
count(*) > 0,
'^2734-1^ expected one or more rows, got ' || count(*) ) as _message
from nnt
where true
and ( n != 0 );
select
*,
std_assert(
count(*) > 0, -- using `count(*)` will cause the function to be called
-- even in case there are no matching rows
'^2734-2^ expected one or more rows, got ' || count(*) ) as _message
from nnt
where true
and ( n != 0 )
and ( t = 'nonexistant' ); -- this condition is never fulfilled
std_getv( name )
to retrieve variable values which must have been set
immediately prior to accessing the view.DBay::prepare()
,
DBay::query()
and so, except when
values
list, as in select employee from employees where department in ( 'sales', 'HR' );
.db.sql.I: ( name ) ->
: returns a properly quoted and escaped SQL Identifier.db.sql.L: ( x ) ->
: returns a properly quoted and escaped SQL Value. Note that booleans
(true
, false
) will be converted to 1
and 0
, respectively.db.sql.V: ( x ) ->
: returns a bracketed SQL list of values (using db.sql.V()
for each list
element).db.interpolate( sql, values ) ->
accepts a template (a string with placeholder formulas) and a list
or object of values. It returns a string with the placeholder formulas replaced with the escaped values.
# using named placeholders
sql = SQL"select $:col_a, $:col_b where $:col_b in $V:choices"
d = { col_a: 'foo', col_b: 'bar', choices: [ 1, 2, 3, ], }
result = db.sql.interpolate sql, d
# > """select "foo", "bar" where "bar" in ( 1, 2, 3 )"""
# using positional placeholders
sql = SQL"select ?:, ?: where ?: in ?V:"
d = [ 'foo', 'bar', 'bar', [ 1, 2, 3, ], ]
result = db.sql.interpolate sql, d
# > """select "foo", "bar" where "bar" in ( 1, 2, 3 )"""
# using an unknown format
sql = SQL"select ?:, ?X: where ?: in ?V:"
d = [ 'foo', 'bar', 'bar', [ 1, 2, 3, ], ]
result = db.sql.interpolate sql, d
# throws "unknown interpolation format 'X'"
DBay offers limited support for the declarative generation of a small number of recurring classes of SQL statements. These facilities are in no way intended to constitute or grow into a full-blown Object-Relational Mapper (ORM); instead, they are meant to make working with relational data less of a repetitive chore.
To pick one case in point, SQL insert
statements when called from a procedural language have a nasty habit
of demanding not two, but three copies of a table's column names:
db SQL"""
create table xy (
a integer not null primary key,
b text not null,
c boolean not null );"""
db SQL"insert into xy ( b, c ) values ( $b, $c )", { b, c, }
# ^^^^^^^^ ^^^^^^^^^^ ^^^^^^^^^
insert
statements, one would still have to implement
almost all of SQL, as is evidenced by the screenshot of the SQLite insert
Statement Railroad Diagram that will
be displayed when clicking/tapping on this paragraph.Instead, we implement facilities to cover the most frequent use cases and offer opportunities to insert SQL fragments at strategic points.
Often, when an insert
statement is being called for, one wants to insert full rows (minus generate
d
columns, for which see below) into tables. This is the default that DBay makes easy: A call to
db.prepare_insert()
with the insertion target identified with into
will return a prepared statement that
can then be used as first argument to the db
callable:
insert_into_xy = db.prepare_insert { into: 'xy', }
db insert_into_xy, { a, b, c, }
Observe that named parameters (as opposed to positional ones) are used, so values must be passed as an object (as opposed to a list).
In case the actual SQL text of the statement is needed, call db.create_insert()
instead:
insert_sql = db.create_insert { into: 'xy', }
# 'insert into "main"."xy" ( "a", "b", "c" ) values ( $a, $b, $c );'
When one or more columns in a table are autoincrement
ed or have a
default
value, then those columns are often intended not to be set explicitly. What's more, columns with
generate
d values must not be set explicitly. For this reason, db.create_insert()
(and, by
extension, db.prepare_insert()
) will skip generate
d columns and allow to explicitly specify either
included columns (as fields
) or else excluded columns (as exclude
):
db SQL"""
create table t1(
a integer primary key,
b integer,
c text,
d integer generated always as (a*abs(b)) virtual,
e text generated always as (substr(c,b,b+1)) stored );"""
insert_into_t1 = db.create_insert { into: 't1', }
### Observe `d` and `e` are left out because they're generated, but `a` is present: ###
# 'insert into "main"."t1" ( "a", "b", "c" ) values ( $a, $b, $c );'
### You probably want either this: ###
insert_into_t1 = db.create_insert { into: 't1', fields: [ 'b', 'c', ], }
# 'insert into "main"."t1" ( "b", "c" ) values ( $b, $c );'
### Or this: ###
insert_into_t1 = db.create_insert { into: 't1', exclude: [ 'a', ], }
# 'insert into "main"."t1" ( "b", "c" ) values ( $b, $c );'
There's a subtle yet important semantic difference in how the
fields
andexclude
settings are handled: Whenfields
are explicitly given, the table does not have to exist when generating the SQL; however, whenfields
is not given, the table must already exist at the time of callingcreate_insert()
.In either case,
prepare_insert()
can only succeed when all referenced object in an SQL statement have already been created.
The next important thing one often wants in inserts is resolving conflicts. DBay create_insert()
supports
setting on_conflict
to either (1) an arbitrary string that should spell out a syntactically valid SQL
on conflict
clause, or (2) an object { update: true, }
to generate SQL that updates the explicitly
or implicitly selected columns. This form has been chosen to leave the door open to future expansions of
supported features.
When choosing the first option, observe that whatever string is passed in, create_insert()
will prepend
'on conflict '
to it; therefore, to create an insert statement that ignores insert conflicts, and
according to the upsert
syntax railroad diagram: β
β the right thing to do is to call db.create_insert { into: table_name, on_conflict: 'do nothing', }
.
Assuming table t1
has been declared as above, calling
db.create_insert { into: 't1', exclude: [ 'a', ], on_conflict: "do nothing", }
will generate the (unformatted but properly escaped) equivalent to:
insert into main.t1 ( b, c )
values ( $b, $c )
on conflict do nothing;
-- |<------>|
-- inserted string
while calling
db.create_insert { into: 't1', exclude: [ 'a', ], on_conflict: { update: true, }, }
wiil generate the (unformatted but properly escaped) equivalent to:
insert into main.t1 ( b, c )
values ( $b, $c )
on conflict do update set --| conflict resolution clause
b = excluded.b, --| mandated by { update: true, }
c = excluded.c; --| containing same fields as above
returning
ClauseIt is sometimes handy to have insert
statements that return a useful value. Here's a toy example
that demonstrates how one can have a table with generated columns:
db SQL"""
create table xy (
a integer not null primary key,
b text not null,
c text generated always as ( '+' || b || '+' ) );"""
insert_into_xy_sql = db.create_insert { into: 'xy', on_conflict: SQL"do nothing", returning: '*', }
# -> 'insert into "main"."xy" ( "a", "b" ) values ( $a, $b ) on conflict do nothing returning *;'
db.single_row insert_into_xy_sql, { a: 1, b: 'any', } # -> { a: 1, b: 'any', c: '+any+' }
db.single_row insert_into_xy_sql, { a: 2, b: 'duh', } # -> { a: 2, b: 'duh', c: '+duh+' }
db.single_row insert_into_xy_sql, { a: 3, b: 'foo', } # -> { a: 3, b: 'foo', c: '+foo+' }
Generally, the returning
clause must be defined by a non-empty string that is valid SQL for the position
after returning
and the end of the statement. A star *
will return the entire row that has been
inserted; we here use db.single_row()
to eschew the result iterator that would be returned by default.
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
SQLite principally differs from client/server RDBMSes in that it allows User Defined Functions (UDFs) only on the DB connection of the host application
these UDFs are written in the language and run in the environment of the host application
I believe UDFs are, as such, a huge boon because they help to push many chores to the DB and allow for such nifty things as having generated columns whose contents are not stored but indexed and that can call into existing code of the hosting app without code duplication and without network roundtrips (both of which are hallmarks of client/server architectures)
but the downside of connection-defined UDFs is that SQLite DBs created with UDFs will break when the
environment changes (e.g. when openening a second connection to the same DB without recreating all UDFs or
openening the DB with other tools such as the sqlite3
command line tool); an abortive error will occur
as soon as any function is enountered (one may be able to perform some operations that do not cause a
function to be called)
this means that a DB created with UDFs will not be amenable for any of the helpful tools that exist (like ER diagrammers and so on)
one can also not pass a DB file around for other people to have a gander into the dataβusing UDFs means your host application (or all the relevant parts of it) has to be reproduced on the other machine, and even then, only the host application can provide access to the dataβagain, no external tooling here
because UDFs are so useful, it's probably worthwhile to think about how to work around the limitations. Possible solutions include:
CREATE FUNCTION
; the body of such a function could be formulated in much the same way as the already existing
syntax for CREATE TRIGGER
which likewise allows to define a block with a sequence of SQL statements.
In its simplest form, CREATE FUNCTION
would allow for parametrized views, which would be incredibly
useful. Such a feature request has been issued before
(not listed on the Open Feature Requests page) in 2021 and
lead to an extended and informative discussion (see triggers, below), but so far, nothing has come of
it. Rating: +0 because while everyone is encouraged to do it, hopes are not high IMHO; however see
below for a draft that I think could have
some chances.sqlite3
command line tool, but even then, you must ship the extension alongside with the DB file, and
the receiving partner will have to do a bit more work to open the DB (and be willing to use the command
line). They must also be on a compatible system or your *.so
/*.dll
will not work, or else you must
compile the extension for multiple systems. Rating: -1 because who wants to do the authoring and
testing and compiling stuff when so little universal usability comes out of it.All of these solutions suck in one or the other way.
CREATE FUNCTION
statement; its body would be
much like the existing syntax for triggers. The default (and, initially, only) language to be used is SQL.Example:
CREATE FUNCTION product( a number, b number ) RETURNS number LANGUAGE SQL
BEGIN
SELECT a * b; /* or RETURN a * b; */
END;
END;
Notes:
- Type annotations and the
RETURNS
clause should be optional as inCREATE TABLE
statements, whereasLANGUAGE SQL
should initially be made mandatory to avoid premature fixation of a bad default.- Initially at least, functions should not be multi-dispatch (i.e. a name can only appear at most once).
- Nice-to-have:
CREATE OR REPLACE
,IF NOT EXISTS
,DROP FUNCTION
.
This form is already useful because now you can bundle and name recurrent expressionsβanything that can
appear in a scalar (single-values) SELECT
statement can be named and collected into libraries.
Extension Add to this RETURNS SETOF $TYPE
, RETURNS SETOF ROW
, and now you can have table-valued
functions a.k.a. parametrized views!
Extension Add to this statement sequences.
Extension Add to this branching (IF
/THEN
and/or CASE
/WHEN
). This extension would cross the line
where language inside a function declaration is significantly different from that outside. OTOH branching
could conceivably work outside of functions, much like C's preprocessor directives.
Extension Add to this LOOP/BREAK/BREAK IF
loops.
Extension Add to this YIELD
for use in table-valued functions.
Extension Add to this (function-local) variables. These are in principle already implemented in the form of function parameters.
Extension Some support for dynamic SQL that could potentially be much less clunky than what PostgreSQL
offers; at first one would only need a syntax to signify safe interpolation as identifier, e.g. SELECT * FROM @table_name;
or similar.
better-sqlite3
an 'Unsaved' DependencySince DBay depends on better-sqlite3
with a
custom-configured build of the SQLite C
engine, it is (for whatever
reason) important that better-sqlite3
must not be listed under package.json#dependencies
; otherwise,
compilation will not work properly. The build script will run npm install better-sqlite3@'^7.4.3'
but with an added --no-save
flag.
## Use npm, Not pnpm
Also, at the time of this writing (2021-09), while the project compiles fine using npm v7.21.1 (on NodeJS
v16.9.1 on Linux Mint), but it fails using pnpm v6.14.6 with Unknown options: 'build-from-source', 'sqlite3'
. Yarn has not been tried.
NoteβThese considerations only concern those who wish to fork/clone DBay to work on the code. Those who
just want to use DBay as a dependency of their project can both either run npm install dbay
or pnpm add dbay
, both package managers work fine.
[β] port foundational code from hengist &c
[β] at construction time, allow dbnick
when path
is given and ram
is false
[β] to solve the table-UDF-with-DB-access conundrum, consider
db.save()
. See
https://github.com/JoshuaWise/better-sqlite3/blob/master/docs/threads.mdselect * from foo( x ) as d;
to get select * from ( select a, b, c from blah order by 1 ) as d
(i.e. inline expansion)select
s from inside UDFs, so maybe there's a teeny, fixable difference between how both are
implemented that leads to the undesirable behavior[β] let users choose between SQLite-only RAM DBs and tmpfs
-based in-memory DBs (b/c the latter allow
pragma journal_mode = WAL
for better concurrent access). Cons include: tmpfs
-based RAM DBs necessitate
mounting a RAM disk which needs sudo
rights, so might as well just instruct users to mount RAM disk,
then use that path? Still, it would be preferrable to have some automatic copy-to-durable in place.
[β] implement context handler for discardable / temporary file
[β] allow to call DBay::do -> ...
with an asynchronous function
[β] implement DBay::open()
, DBay::close()
[β] ensure how cross-schema foreign keys work when re-attaching DBs / schemas one by one
[β] demote random
from a mixin to functions in helpers
.
[β] implement db.truncate()
/ db.delete()
; allow to retrieve SQL.
[β] implement DBay::insert_into.<table> [ 'field1', 'field2', ..., ], { field1, field2, ..., }
;
allow to retrieve SQL.
[β] clarify whether UDFs get called at all when any argument is null
b/c it looks like they
don't get called which would be unfortunate
[β] add schematic to clarify terms like database, schema, connection; hilite that UDFs are defined on connections (not schemas or databases as would be the case in e.g. PostgreSQL).
[β] allow to transparently treat key/value tables as caches
[β] implement escaping of dollar-prefixed SQL placeholders (needed by create_insert()
).
[β] implement
db.commit()
db.rollback()
[β] allow to use sets with sql.V()
[β] implement export/snapshot function that generates a DB with a simplified structure:
strict
and similar newer attributessqlite3
command line,
visualize-sqlite
[+] consider to implement trash functionality now moved to
DeSQLtrash()
as trash_to_sql()
(path
optional), trash_to_sqlite()
(path
optional)
[β] rewrite all uses of plain E
to @E
[β] limit support for schemas, especially in plugins; require a separate instance of DBay for each DB
file (so that all DB objects are in the default main
namespace and the SQL"#{schema}.xxx"
constructs
can become SQL"xxx"
). Complex DBs can still be assembled with db.open()
, but one must keep in mind
that in SQLite, foreign key
s do not work across schemas, only join
s so, so that limits the usefulness
of multi-schema connections.
[β] consider to change call
argument in UDFs to callee
[β] add fields to std_re_matches()
:
db.create_table_function
name: prefix + '_re_matches'
columns: [ 'match', 'capture', 'start', 'stop', ]
parameters: [ 'text', 'pattern', ]
rows: ( text, pattern ) ->
regex = new RegExp pattern, 'g'
while ( match = regex.exec text )?
[ m, c, ] = match
yield [ m, ( c ? null ), start: match.index, stop: match.index + m.length, ]
return null
[β] update to an SQLite version that includes
#9430ead7ba433cbf
to fix an issue with window
functions
[β] write a chapter about application architecture best practices, including:
sqlite3
CLI will not work)on insert
trigger that
performs inserts on another table using select from t
; ahould an error occur in the last step, SQLite
will still attribute it to the original insert
statement (without giving it any kind of locality or
mentioning t
's role))db SQL"do this;"
, db SQL"do that;"
over db SQL"do this; do that;"
)[β] implement select * from t
SQL generation
[β] could the SQL
string annotation / tagged literal function be syntactically extended to allow
simpler interpolation of escaped names? Could we instantiate it with a dictionary of values (implement in
Guy)
DBay::do()
as a method that unifies all of better-sqlite3
's Statement::run()
,
Statement::iterate()
, and Database::execute()
.DBay::do -> ...
with a synchronous function with the same semantics as
DBay::with_transaction -> ...
.DBay::do { mode: 'deferred', }, -> ...
.db = new DBay()
an instance of Function
that, when called, runs DBay::do()
Database::execute()
.
statement = DBay::prepare.insert_into.<table> [ 'field1', 'field2', ..., ]
Dbay
to DBay
to avoid spelling variant proliferationdb.do()
accept prepared statement objects.first_row()
, all_rows()
etc accept statements and stringscfg.prefix
for (inherently schema-less) UDF names (and require a trailing
underscore to be part of the prefix), and cfg.schema
for plugin-in-specific DB tables and views; in the
future, we should use a single parameter for both (and make the underscore implicit). In addition, it
should be possible to choose whether a plugin will create its objects with a prefix (in the same schema as
the main DB) or within another schema.insert
statements without explicit fieldsE
attribute to instance giving access to error classes (mainly for plugin use)as_object: ( key, sql, P... ) ->
YYYYMMDD-HHmmssZ
, e.g. 20220426-171916Z
is the time of this writingZ
instead of numerical offsetFAQs
In-Process, In-Memory & File-Based Relational Data Processing with SQLite, BetterSQLite3
The npm package dbay receives a total of 74 weekly downloads. As such, dbay popularity was classified as not popular.
We found that dbay demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.Β It has 0 open source maintainers collaborating on the project.
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