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0.25.0
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@@ -1,3 +0,0 @@
|
||||
> 1%
|
||||
last 2 versions
|
||||
not dead
|
||||
@@ -1,5 +0,0 @@
|
||||
[*.{js,jsx,ts,tsx,vue}]
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
trim_trailing_whitespace = true
|
||||
insert_final_newline = true
|
||||
30
.eslintrc.js
@@ -1,30 +0,0 @@
|
||||
module.exports = {
|
||||
root: true,
|
||||
env: {
|
||||
node: true
|
||||
},
|
||||
extends: [
|
||||
'plugin:vue/essential',
|
||||
'@vue/standard'
|
||||
],
|
||||
parserOptions: {
|
||||
parser: 'babel-eslint'
|
||||
},
|
||||
rules: {
|
||||
'no-console': process.env.NODE_ENV === 'production' ? 'warn' : 'off',
|
||||
'no-debugger': process.env.NODE_ENV === 'production' ? 'warn' : 'off',
|
||||
'no-case-declarations': 'off',
|
||||
'max-len': [2, 100, 4, { ignoreUrls: true }]
|
||||
},
|
||||
overrides: [
|
||||
{
|
||||
files: [
|
||||
'**/__tests__/*.{j,t}s?(x)',
|
||||
'**/tests/**/*.spec.{j,t}s?(x)'
|
||||
],
|
||||
env: {
|
||||
mocha: true
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
17
.github/workflows/config.grenrc.js
vendored
@@ -1,17 +0,0 @@
|
||||
module.exports = {
|
||||
dataSource: 'milestones',
|
||||
ignoreIssuesWith: [
|
||||
'wontfix',
|
||||
'duplicate'
|
||||
],
|
||||
milestoneMatch: 'v{{tag_name}}',
|
||||
template: {
|
||||
issue: '- {{name}} [{{text}}]({{url}})',
|
||||
changelogTitle: "",
|
||||
release: "{{body}}",
|
||||
},
|
||||
groupBy: {
|
||||
'Enhancements': ["enhancement", "internal"],
|
||||
'Bug fixes': ["bug"]
|
||||
}
|
||||
}
|
||||
45
.github/workflows/main.yml
vendored
@@ -1,45 +0,0 @@
|
||||
name: Create release
|
||||
on:
|
||||
workflow_dispatch:
|
||||
push:
|
||||
tags:
|
||||
- '*'
|
||||
|
||||
jobs:
|
||||
deploy:
|
||||
name: Create release
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- name: Use Node.js
|
||||
uses: actions/setup-node@v1
|
||||
with:
|
||||
node-version: 10.x
|
||||
|
||||
- name: Update npm
|
||||
run: npm install -g npm@7
|
||||
|
||||
- name: npm install and build
|
||||
run: |
|
||||
npm install
|
||||
npm run build
|
||||
|
||||
- name: Create archives
|
||||
run: |
|
||||
cd dist
|
||||
zip -9 -r ../dist.zip . -x "js/*.map" -x "/*.map"
|
||||
zip -9 -r ../dist_map.zip .
|
||||
|
||||
- name: Create Release Notes
|
||||
run: |
|
||||
npm install github-release-notes@0.16.0 -g
|
||||
gren changelog --generate --config="/.github/workflows/config.grenrc.js"
|
||||
env:
|
||||
GREN_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Create release
|
||||
uses: ncipollo/release-action@v1
|
||||
with:
|
||||
artifacts: "dist.zip,dist_map.zip"
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
bodyFile: "CHANGELOG.md"
|
||||
37
.github/workflows/test.yml
vendored
@@ -1,37 +0,0 @@
|
||||
name: Run tests
|
||||
on:
|
||||
workflow_dispatch:
|
||||
push:
|
||||
branches:
|
||||
- 'master'
|
||||
pull_request:
|
||||
branches:
|
||||
- 'master'
|
||||
|
||||
jobs:
|
||||
test:
|
||||
name: Run tests
|
||||
runs-on: ubuntu-20.04
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
- name: Use Node.js
|
||||
uses: actions/setup-node@v1
|
||||
with:
|
||||
node-version: 10.x
|
||||
- name: Install browsers
|
||||
run: |
|
||||
export DEBIAN_FRONTEND=noninteractive
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y chromium-browser firefox
|
||||
|
||||
- name: Update npm
|
||||
run: npm install -g npm@7
|
||||
|
||||
- name: Install the project
|
||||
run: npm install
|
||||
|
||||
- name: Run lint
|
||||
run: npm run lint -- --no-fix
|
||||
|
||||
- name: Run karma tests
|
||||
run: npm run test
|
||||
23
.gitignore
vendored
@@ -1,23 +0,0 @@
|
||||
.DS_Store
|
||||
node_modules
|
||||
/dist
|
||||
/coverage
|
||||
|
||||
# local env files
|
||||
.env.local
|
||||
.env.*.local
|
||||
|
||||
# Log files
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
pnpm-debug.log*
|
||||
|
||||
# Editor directories and files
|
||||
.idea
|
||||
.vscode
|
||||
*.suo
|
||||
*.ntvs*
|
||||
*.njsproj
|
||||
*.sln
|
||||
*.sw?
|
||||
108
Basic-usage.md
Normal file
@@ -0,0 +1,108 @@
|
||||
# Basic usage
|
||||
|
||||
## Choose SQLite database, CSV file, JSON or NDJSON file
|
||||
|
||||
You can choose a database, a CSV file, a JSON or NDJSON file right on the welcom page (fig. 1). The
|
||||
supported file extentions: `.csv`, `.json`, `.ndjson`, `.db`,`.sqlite` and `.sqlite3`.
|
||||
|
||||

|
||||
|
||||
|
||||
If you choose a CSV, JSON or NDJSON file it will be parsed. Then sqliteviz creates a new
|
||||
database with data from the file. You can change table name
|
||||
in the dialog which is shown automatically if you choose a CSV, JSON or NDJSON file.
|
||||
For CSV you can also change parsing settings (fig. 2).
|
||||
|
||||

|
||||
|
||||
|
||||
If you don't have a database or CSV or JSON/NDJSON press `Create empty database` button and
|
||||
then fill an empty database using DDL and DML statements. A tab with an example
|
||||
of how to do it will be opened automatically (fig. 3).
|
||||
|
||||

|
||||
|
||||
|
||||
Database tables, columns and their types are shown in the left panel of the
|
||||
`Workspace` (fig. 4).
|
||||
|
||||

|
||||
|
||||
|
||||
## Create inquiry
|
||||
|
||||
### Open new tab
|
||||
|
||||
Press `Create` button in the top toolbar or use `Ctrl+b` (`Cmd+b` for MacOS)
|
||||
keyboard shortcut to open a new tab for an inquiry. An inquiry consists of three
|
||||
parts: SQL query, result set (result of the query execution) and visualisation
|
||||
of the result set. A tab consists of two panels. Each of them can show one of
|
||||
the three parts of inquiry. By default, the top panel shows SQL query editor and
|
||||
the bottom panel shows the result set. You can switch any panel to any other
|
||||
view with the corresponding buttons in the right side toolbar.
|
||||
|
||||
*  – Switch the panel to an SQL query editor. In that
|
||||
editor, you can specify and run not only a `SELECT` statement for getting data
|
||||
but also DDL/DML statements for modifying the database.
|
||||
*  – Switch the panel to the result set. Here you
|
||||
can see the result of the query execution.
|
||||
*  – Switch the panel to visualisation. This
|
||||
panel allows building a pivot table, a graph or charts from the result set.
|
||||
|
||||
> **Note:** The query editor can show you hints: SQL keywords, table and column
|
||||
> names. In a common case, column names are shown in the hint if you specify the
|
||||
> table name, e.g. `SELECT table_name.`. But if there is only one table in your
|
||||
> database column names will be always available in the hint. Press `Ctrl+Space`
|
||||
> to show a hint explicitly.
|
||||
|
||||
### Run query
|
||||
|
||||
Press  button in the right side toolbar of an SQL
|
||||
editor panel or use `Ctrl+r` or `Ctrl+Enter` (`Cmd+r` or `Cmd+Enter` for MacOS)
|
||||
keyboard shortcut to execute a query in the current open tab.
|
||||
|
||||
> **Note:** Running is not available if a query for the current tab is not
|
||||
> specified.
|
||||
|
||||
The query result will be displayed in the result panel (fig. 4).
|
||||
|
||||
### Create visualisation
|
||||
|
||||
After running a query switch any panel to the visualisation. Switch to the
|
||||
disired type of visualisation with buttons in the right side toolbar of the
|
||||
visualisation panel.
|
||||
|
||||
*  – Switch to a chart type visualisation.
|
||||
*  – Switch to a pivot type visualisation.
|
||||
*  – Switch to a graph type visualisation.
|
||||
|
||||
A pivot table can be represented as a regular or multi-header table or
|
||||
visualised with a chart.
|
||||
Read more details of working with pivot in [Pivot tables][2].
|
||||
|
||||
There are some requirements for the result set to build a graph.
|
||||
Read more in [Graph][3].
|
||||
|
||||
All customised charts in sqliteviz are created with a `react-chart-editor`
|
||||
component (fig. 5). The same component with some additional features is used in
|
||||
Plotly Chart Studio. Explore its [documentation][1] to learn how to build charts
|
||||
with `react-chart-editor`.
|
||||
|
||||

|
||||
|
||||
You can save any visualisation as an image by clicking .
|
||||
|
||||
## Save inquiry
|
||||
|
||||
Press `Save` button in the top toolbar or use `Ctrl+s` (`Cmd+s` for MacOS)
|
||||
keyboard shortcut to save an inquiry in the current opened tab to local storage
|
||||
of your browser.
|
||||
|
||||
After that, the inquiry will be in the list on `Inquiries` page.
|
||||
|
||||
> **Note:** Only the text of the SQL query and the visualisation settings will
|
||||
> be saved. The result of the query execution won't be saved.
|
||||
|
||||
[1]: https://plotly.com/chart-studio-help/tutorials/#basic
|
||||
[2]: ../Pivot-table
|
||||
[3]: ../Graph
|
||||
10
Diagnostic-information.md
Normal file
@@ -0,0 +1,10 @@
|
||||
# Diagnostic information
|
||||
|
||||
SQLite running in sqliteviz is compiled with particular [options][1] that can
|
||||
enable or disable some SQLite features. You can get a list of them in `App
|
||||
info` dialog (fig. 1) by clicking on  icon in the top
|
||||
toolbar.
|
||||
|
||||

|
||||
|
||||
[1]: https://sqlite.org/compile.html
|
||||
@@ -1,24 +0,0 @@
|
||||
# An easy way to run tests locally without Nodejs installed:
|
||||
#
|
||||
# docker build -t sqliteviz/test -f Dockerfile.test .
|
||||
#
|
||||
|
||||
FROM node:12.22-buster
|
||||
|
||||
RUN set -ex; \
|
||||
apt update; \
|
||||
apt install -y chromium firefox-esr; \
|
||||
npm install -g npm@7
|
||||
|
||||
WORKDIR /tmp/build
|
||||
|
||||
COPY package.json package-lock.json ./
|
||||
COPY lib lib
|
||||
RUN npm install
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN set -ex; \
|
||||
sed -i 's/browsers: \[.*\],/browsers: ['"'FirefoxHeadlessTouch'"'],/' karma.conf.js
|
||||
|
||||
RUN npm run lint -- --no-fix && npm run test
|
||||
6
Export-current-database.md
Normal file
@@ -0,0 +1,6 @@
|
||||
# Export current database
|
||||
|
||||
Sqliteviz allows running not only `SELECT` statements but DML/DDL statements
|
||||
too. You can save database modifications into a `.sqlite` file by clicking on
|
||||
icon  next to the database name on `Workspace`
|
||||
page.
|
||||
54
Graph.md
Normal file
@@ -0,0 +1,54 @@
|
||||
# Graph
|
||||
|
||||
## Pivot table UI
|
||||
|
||||
Sqliteviz allows building pivot tables and visualizing them. To build a graph
|
||||
run a query to get data. Then open visualisation panel by clicking 
|
||||
in any of the two side toolbars and choose a pivot mode by clicking .
|
||||
|
||||
A pivot visualisation has the following settings:
|
||||
|
||||
- Columns – choose one or more column names from the result set. The values in
|
||||
the chosen columns will be column names of the pivot table.
|
||||
- Rows – choose one or more column names from the result set. The values in the
|
||||
chosen columns will be row names of the pivot table.
|
||||
- Order of columns and rows.
|
||||
- Aggregator and its arguments – a function which will be used for pivot cell
|
||||
calculation. An aggregator can have from zero to two arguments. An aggregator
|
||||
argument is one of the columns of the result set.
|
||||
- View – pivot table visualisation. It can be a table, a heatmap, a chart,
|
||||
etc. See some examples of different views of the same pivot table below.
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
There are several built-in chart views for a pivot. But you can build your own
|
||||
with `Custom chart` view (fig. 4).
|
||||
|
||||

|
||||
|
||||
> **Note:** You can switch to other pivot views and back to `Custom chart` –
|
||||
> all your custom chart settings will be remembered. But if you switch the
|
||||
> visualisation mode from pivot to any other mode, unsaved changes will be lost.
|
||||
|
||||
You can save any visualisation as an image by clicking .
|
||||
|
||||
## Pivot table SQL
|
||||
|
||||
Pivot table (in the form of a result set) can be built on the SQL-level and,
|
||||
technically speaking, can be visualised as any other result set. Practically
|
||||
though there are a couple of challenges with that:
|
||||
|
||||
1. Visualising a dataset of long/tall shape is much more convenient in Plotly
|
||||
(chart editor) rather than one of wide/fat shape.
|
||||
2. SQLite doesn't have a special constructs like `PIVOT` or `CROSSTAB` in
|
||||
its SQL dialect.
|
||||
|
||||
[How to build a pivot table in SQL(ite)][1] explores two options with static
|
||||
(or beforehand-known) and dynamic columns.
|
||||
|
||||
[1]: ../How-to-build-a-pivot-table-in-SQ-Lite
|
||||
|
||||
36
Home.md
Normal file
@@ -0,0 +1,36 @@
|
||||
Welcome to the sqliteviz wiki!
|
||||
|
||||
# For users
|
||||
1. [Installation][0]
|
||||
2. [Basic usage][1]
|
||||
3. [Multiple file import][9]
|
||||
4. [Manage inquiries][2]
|
||||
5. [Export current database][4]
|
||||
6. [Graph][13]
|
||||
7. [Pivot table][3]
|
||||
8. [Predefined inquiries][5]
|
||||
9. [Sharing][11]
|
||||
10. [Diagnostic information][6]
|
||||
|
||||
## Examples and tutorials
|
||||
1. [How to rename tables and columns after CSV import][8]
|
||||
2. [How to build a pivot table in SQL(ite)][10]
|
||||
3. [How to rename tables and columns after CSV import][12]
|
||||
|
||||
# For developers
|
||||
1. [Integrate predefined inquiries][7]
|
||||
|
||||
[0]: Installation
|
||||
[1]: Basic-usage
|
||||
[2]: Manage-inquiries
|
||||
[3]: Pivot-table
|
||||
[4]: Export-current-database
|
||||
[5]: Predefined-inquiries
|
||||
[6]: Diagnostic-information
|
||||
[7]: Integrate-predefined-inquiries
|
||||
[8]: How-to-rename-tables-and-columns-after-CSV-import
|
||||
[9]: Multiple-CSV-file-import
|
||||
[10]: How-to-build-a-pivot-table-in-SQLite
|
||||
[11]: Sharing
|
||||
[12]: How-to-rename-tables-and-columns-after-csv-import
|
||||
[13]: Graph
|
||||
137
How-to-build-a-pivot-table-in-SQLite.md
Normal file
@@ -0,0 +1,137 @@
|
||||
# How to build a pivot table in SQLite
|
||||
|
||||
This how-to explores how to build pivot tables in SQLite, which doesn't have a
|
||||
special constructs like `PIVOT` or `CROSSTAB` in its SQL dialect.
|
||||
|
||||
## Static-column pivot table
|
||||
|
||||
If the columns of a pivot table are known beforehand, it's possible to write a
|
||||
standard, say SQL-92, query that would produce a pivot table in its result set.
|
||||
This example uses World Bank [country indicators][1]. This query calculates
|
||||
average fertility and life expectancy for a few country groups.
|
||||
|
||||
```sql
|
||||
SELECT
|
||||
"Country Name",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 196 AND "Indicator Name" LIKE 'Fertility rate%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "FR 196x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 196 AND "Indicator Name" LIKE 'Life expectancy%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "LE 196x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 197 AND "Indicator Name" LIKE 'Fertility rate%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "FR 197x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 197 AND "Indicator Name" LIKE 'Life expectancy%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "LE 197x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 198 AND "Indicator Name" LIKE 'Fertility rate%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "FR 198x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 198 AND "Indicator Name" LIKE 'Life expectancy%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "LE 198x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 199 AND "Indicator Name" LIKE 'Fertility rate%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "FR 199x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 199 AND "Indicator Name" LIKE 'Life expectancy%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "LE 199x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 200 AND "Indicator Name" LIKE 'Fertility rate%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "FR 200x",
|
||||
AVG(IIF(
|
||||
FLOOR(year / 10) = 200 AND "Indicator Name" LIKE 'Life expectancy%',
|
||||
value,
|
||||
NULL
|
||||
)) AS "LE 200x"
|
||||
FROM country_indicators
|
||||
WHERE "Country Name" IN(
|
||||
'Arab World',
|
||||
'Central Europe and the Baltics',
|
||||
'East Asia & Pacific',
|
||||
'European Union',
|
||||
'Latin America & Caribbean',
|
||||
'High income',
|
||||
'Middle income',
|
||||
'Low income'
|
||||
)
|
||||
GROUP BY 1
|
||||
ORDER BY
|
||||
CASE "Country Name"
|
||||
WHEN 'High income' THEN 1
|
||||
WHEN 'Middle income' THEN 2
|
||||
WHEN 'Low income' THEN 3
|
||||
WHEN 'European Union' THEN 4
|
||||
WHEN 'Central Europe and the Baltics' THEN 5
|
||||
WHEN 'East Asia & Pacific' THEN 6
|
||||
WHEN 'Latin America & Caribbean' THEN 7
|
||||
WHEN 'Arab World' THEN 8
|
||||
ELSE 99
|
||||
END
|
||||
```
|
||||
|
||||
## Dynamic-column pivot table
|
||||
|
||||
SQLite in sqliteviz is built with [pivot_vtab][2] extension. The same result set
|
||||
can be produced with this, arguably simpler and more maintainable, query.
|
||||
|
||||
```sql
|
||||
CREATE VIRTUAL TABLE temp.pivot USING pivot_vtab(
|
||||
(
|
||||
WITH t(country_name) AS (VALUES
|
||||
('High income'),
|
||||
('Middle income'),
|
||||
('Low income'),
|
||||
('European Union'),
|
||||
('Central Europe and the Baltics'),
|
||||
('East Asia & Pacific'),
|
||||
('Latin America & Caribbean'),
|
||||
('Arab World')
|
||||
)
|
||||
SELECT country_name FROM t
|
||||
),
|
||||
(
|
||||
SELECT
|
||||
FLOOR(year / 10) || '|' || "Indicator Name" column_key,
|
||||
CASE
|
||||
WHEN "Indicator Name" LIKE 'Fertility rate%' THEN 'FR'
|
||||
WHEN "Indicator Name" LIKE 'Life expectancy%' THEN 'LE'
|
||||
END || ' ' || FLOOR(year / 10) || 'x' column_name
|
||||
FROM country_indicators
|
||||
WHERE
|
||||
"Indicator Name" LIKE 'Fertility rate%'
|
||||
OR "Indicator Name" LIKE 'Life expectancy%'
|
||||
GROUP BY 1
|
||||
),
|
||||
(
|
||||
SELECT AVG(value)
|
||||
FROM country_indicators
|
||||
WHERE
|
||||
"Country Name" = :country_name
|
||||
AND FLOOR(year / 10) || '|' || "Indicator Name" = :column_key
|
||||
)
|
||||
);
|
||||
SELECT * FROM pivot
|
||||
```
|
||||
|
||||
[1]: https://github.com/plotly/datasets/blob/master/country_indicators.csv
|
||||
[2]: https://github.com/jakethaw/pivot_vtab
|
||||
26
How-to-migrate-to-sqliteviz-dot-com.md
Normal file
@@ -0,0 +1,26 @@
|
||||
# How to migrate to sqliteviz.com
|
||||
|
||||
All upcoming sqliteviz releases will be deployed on sqliteviz.com instead of
|
||||
[Github Pages](https://lana-k.github.io/sqliteviz/#/). The saved inquiries that
|
||||
you still care about can be imported to sqliteviz.com as usual.
|
||||
|
||||
## Step 1: export inquiries
|
||||
|
||||
- Click `Inquiries` in the main top menu
|
||||
- Select all inquiries by clicking the checkbox in the table header
|
||||
- Click `Export` and save your inquiries in a JSON file
|
||||
|
||||
## Step 2: uninstall sqliteviz
|
||||
|
||||
If you installed sqliteviz as PWA uninstall it before install the new version.
|
||||
|
||||
- Go to `chrome://apps/` in your browser
|
||||
- Right click on sqliteviz icon
|
||||
- Choose `Remove from Chrome`
|
||||
|
||||
## Step 3: import inquiries
|
||||
|
||||
- Go to [https://sqliteviz.com/app/#/workspace](https://sqliteviz.com/app/#/workspace)
|
||||
- Click `Inquiries` in the main top menu
|
||||
- Click `Import`
|
||||
- Choose the file where you exported your inquiries
|
||||
54
How-to-rename-tables-and-columns-after-CSV-import.md
Normal file
@@ -0,0 +1,54 @@
|
||||
# How to rename tables and columns after CSV import
|
||||
|
||||
## Rename columns
|
||||
|
||||
If sqliteviz parses CSV without `Use first row as column headers` option then
|
||||
it will name the columns like `col1`, `col2` etc. You can easily rename the
|
||||
columns after import with `ALTER TABLE` statements like this:
|
||||
|
||||
```sql
|
||||
ALTER TABLE your_table_name
|
||||
RENAME COLUMN current_column_name TO new_column_name;
|
||||
```
|
||||
|
||||
### Column rename example
|
||||
|
||||
There is a table `dots` with columns `col1`, `col2`, `col3`. Here are the steps
|
||||
to rename the columns to `x`, `y` and `z` respectively:
|
||||
|
||||
- Click `Create` in the top toolbar
|
||||
- In the opened query editor write a script
|
||||
|
||||
```sql
|
||||
ALTER TABLE dots
|
||||
RENAME COLUMN col1 TO x;
|
||||
|
||||
ALTER TABLE dots
|
||||
RENAME COLUMN col2 TO y;
|
||||
|
||||
ALTER TABLE dots
|
||||
RENAME COLUMN col3 TO z;
|
||||
```
|
||||
|
||||
- Click  to run the script
|
||||
|
||||
|
||||
## Rename table
|
||||
|
||||
```sql
|
||||
ALTER TABLE current_table_name
|
||||
RENAME TO new_table_name;
|
||||
```
|
||||
|
||||
### Table rename example
|
||||
|
||||
There is a table `dots`. Here are the steps to rename it to `point`:
|
||||
|
||||
- Click `Create` in the top toolbar
|
||||
- In the opened query editor write a script
|
||||
|
||||
```sql
|
||||
ALTER TABLE dots RENAME TO point
|
||||
```
|
||||
|
||||
- Click  to run the script
|
||||
16
Installation.md
Normal file
@@ -0,0 +1,16 @@
|
||||
# Installation
|
||||
|
||||
The latest release of sqliteviz is running on [sqliteviz.com/app][1].
|
||||
|
||||
Basically, you don't need to install sqliteviz. But if you want you can install
|
||||
it and use it as a regular desktop application with the following steps:
|
||||
|
||||
1. Open sqliteviz with [Chrome browser][2]
|
||||
2. At the top right of the address bar, click `Install`
|
||||
3. Confirm installation
|
||||
|
||||
See more about PWA on [Google Chrome Help][3].
|
||||
|
||||
[1]: https://sqliteviz.com/app/
|
||||
[2]: https://www.google.com/chrome
|
||||
[3]: https://support.google.com/chrome/answer/9658361?hl=en&ref_topic=7439636
|
||||
12
Integrate-predefined-inquiries.md
Normal file
@@ -0,0 +1,12 @@
|
||||
# Integrate predefined inquiries
|
||||
|
||||
If you run sqliteviz on your own server you can specify predefined inquiries.
|
||||
These inquiries will appear in `Inquiries` list for all users working with
|
||||
sqliteviz on your server.
|
||||
|
||||
To create a list of predefined inquiries choose inquiries in `Inquiries` list
|
||||
and export them to `inquiries.json`. Then (re)place this file on the server in
|
||||
the same directory as `index.html`.
|
||||
|
||||
A user can't edit, rename or delete a predefined inquiry. The rest operations
|
||||
are available.
|
||||
201
LICENSE
@@ -1,201 +0,0 @@
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
"Licensor" shall mean the copyright owner or entity authorized by
|
||||
the copyright owner that is granting the License.
|
||||
|
||||
"Legal Entity" shall mean the union of the acting entity and all
|
||||
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|
||||
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|
||||
"control" means (i) the power, direct or indirect, to cause the
|
||||
direction or management of such entity, whether by contract or
|
||||
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||
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|
||||
|
||||
"You" (or "Your") shall mean an individual or Legal Entity
|
||||
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|
||||
|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
END OF TERMS AND CONDITIONS
|
||||
|
||||
APPENDIX: How to apply the Apache License to your work.
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|
||||
To apply the Apache License to your work, attach the following
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||||
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|
||||
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|
||||
39
Manage-inquiries.md
Normal file
@@ -0,0 +1,39 @@
|
||||
# Manage inquiries
|
||||
|
||||
## Organise
|
||||
|
||||
You can find all inquiries that you saved in `Inquiries` (fig. 1).
|
||||
|
||||

|
||||
|
||||
To manipulate one inquiry hover the cursor over the row with the inquiry and
|
||||
choose the action:
|
||||
|
||||
*  – rename an inquiry
|
||||
*  – duplicate an inquiry
|
||||
*  – export an inquiry to JSON file
|
||||
*  – delete an inquiry
|
||||
|
||||
To edit a query or visualisation settings of an inquiry click on the respective
|
||||
row. You will be redirected to `Workspace` where the chosen inquiry will be
|
||||
opened in a tab.
|
||||
|
||||
> **Note:** After opening an inquiry there will be no visualisation for it even
|
||||
> if you specified it and saved. That is so because there is no data to build
|
||||
> the visualisation. Run the query and all saved chart settings will be applied.
|
||||
|
||||
You can also delete or export a group of inquiries to a JSON file. Select
|
||||
inquiries with checkboxes and press `Delete`/`Export` button above the grid
|
||||
(fig. 2).
|
||||
|
||||

|
||||
|
||||
> **Note:** Some operations are not available for predefined inquiries. Read
|
||||
> [Predefined inquiries][1] for details.
|
||||
|
||||
## Import
|
||||
|
||||
Click `Import` button on `Inquiries` page to import inquiries from a JSON file
|
||||
generated by export.
|
||||
|
||||
[1]: ../Predefined-inquiries
|
||||
12
Multiple-CSV-file-import.md
Normal file
@@ -0,0 +1,12 @@
|
||||
# Multiple CSV, JSON or NDJSON file import
|
||||
|
||||
Sometimes it's useful to import several files as tables in one database. For
|
||||
example, to be able to `JOIN` them in SQL.
|
||||
|
||||
In sqliteviz you can not only create a database from a CSV, JSON or NDJSON file, but also add
|
||||
another table from CSV, JSON or NDJSON to the existing database.
|
||||
|
||||
- Click  icon in the schema panel on `Workspace`
|
||||
page
|
||||
- Choose a file
|
||||
- Import it with `import` dialog.
|
||||
54
Pivot-table.md
Normal file
@@ -0,0 +1,54 @@
|
||||
# Pivot table
|
||||
|
||||
## Pivot table UI
|
||||
|
||||
Sqliteviz allows building pivot tables and visualizing them. To build a pivot
|
||||
run a query to get data. Then open visualisation panel by clicking 
|
||||
in any of the two side toolbars and choose a pivot mode by clicking .
|
||||
|
||||
A pivot visualisation has the following settings:
|
||||
|
||||
- Columns – choose one or more column names from the result set. The values in
|
||||
the chosen columns will be column names of the pivot table.
|
||||
- Rows – choose one or more column names from the result set. The values in the
|
||||
chosen columns will be row names of the pivot table.
|
||||
- Order of columns and rows.
|
||||
- Aggregator and its arguments – a function which will be used for pivot cell
|
||||
calculation. An aggregator can have from zero to two arguments. An aggregator
|
||||
argument is one of the columns of the result set.
|
||||
- View – pivot table visualisation. It can be a table, a heatmap, a chart,
|
||||
etc. See some examples of different views of the same pivot table below.
|
||||
|
||||

|
||||
|
||||

|
||||
|
||||

|
||||
|
||||
There are several built-in chart views for a pivot. But you can build your own
|
||||
with `Custom chart` view (fig. 4).
|
||||
|
||||

|
||||
|
||||
> **Note:** You can switch to other pivot views and back to `Custom chart` –
|
||||
> all your custom chart settings will be remembered. But if you switch the
|
||||
> visualisation mode from pivot to any other mode, unsaved changes will be lost.
|
||||
|
||||
You can save any visualisation as an image by clicking .
|
||||
|
||||
## Pivot table SQL
|
||||
|
||||
Pivot table (in the form of a result set) can be built on the SQL-level and,
|
||||
technically speaking, can be visualised as any other result set. Practically
|
||||
though there are a couple of challenges with that:
|
||||
|
||||
1. Visualising a dataset of long/tall shape is much more convenient in Plotly
|
||||
(chart editor) rather than one of wide/fat shape.
|
||||
2. SQLite doesn't have a special constructs like `PIVOT` or `CROSSTAB` in
|
||||
its SQL dialect.
|
||||
|
||||
[How to build a pivot table in SQL(ite)][1] explores two options with static
|
||||
(or beforehand-known) and dynamic columns.
|
||||
|
||||
[1]: ../How-to-build-a-pivot-table-in-SQ-Lite
|
||||
|
||||
16
Predefined-inquiries.md
Normal file
@@ -0,0 +1,16 @@
|
||||
# Predefined inquiries
|
||||
|
||||
Predefined inquiries come out of the box on the sqliteviz instance. In sqliteviz
|
||||
deployed on [Github Pages][1] there are no predefined inquiries, but you may
|
||||
see them if you use sqliteviz integrated into another app.
|
||||
|
||||
These inquiries are shown in `Inqueries` list with a special label on the mouse
|
||||
over (fig. 1).
|
||||
|
||||

|
||||
|
||||
As a user, you can't rename or delete a predefined inquiry. You can't save
|
||||
changes in a predefined inquiry, but you can save them as a new inquiry. The
|
||||
rest operations, copy and export, are available.
|
||||
|
||||
[1]: https://lana-k.github.io/sqliteviz
|
||||
44
README.md
@@ -1,44 +0,0 @@
|
||||
<p align="center">
|
||||
<img src="src/assets/images/Logo.svg"/>
|
||||
</p>
|
||||
|
||||
# sqliteviz
|
||||
|
||||
Sqliteviz is a single-page offline-first PWA for fully client-side visualisation
|
||||
of SQLite databases, CSV, JSON or NDJSON files.
|
||||
|
||||
With sqliteviz you can:
|
||||
- run SQL queries against a SQLite database and create [Plotly][11] charts and pivot tables based on the result sets
|
||||
- import a CSV/JSON/NDJSON file into a SQLite database and visualize imported data
|
||||
- export result set to CSV file
|
||||
- manage inquiries and run them against different databases
|
||||
- import/export inquiries from/to a JSON file
|
||||
- export a modified SQLite database
|
||||
- use it offline from your OS application menu like any other desktop app
|
||||
|
||||
https://user-images.githubusercontent.com/24638357/128249848-f8fab0f5-9add-46e0-a9c1-dd5085a8623e.mp4
|
||||
|
||||
## Quickstart
|
||||
The latest release of sqliteviz is deployed on [sqliteviz.com/app][6].
|
||||
|
||||
## Wiki
|
||||
For user documentation, check out sqliteviz [documentation][7].
|
||||
|
||||
## Motivation
|
||||
It's a kind of middleground between [Plotly Falcon][1] and [Redash][2].
|
||||
|
||||
## Components
|
||||
It is built on top of [react-chart-editor][3], [PivotTable.js][12], [sql.js][4] and [Vue-Codemirror][8] in [Vue.js][5]. CSV parsing is performed with [Papa Parse][9].
|
||||
|
||||
[1]: https://github.com/plotly/falcon
|
||||
[2]: https://github.com/getredash/redash
|
||||
[3]: https://github.com/plotly/react-chart-editor
|
||||
[4]: https://github.com/sql-js/sql.js
|
||||
[5]: https://github.com/vuejs/vue
|
||||
[6]: https://sqliteviz.com/app/
|
||||
[7]: https://sqliteviz.com/docs
|
||||
[8]: https://github.com/surmon-china/vue-codemirror#readme
|
||||
[9]: https://www.papaparse.com/
|
||||
[10]: https://github.com/lana-k/sqliteviz/wiki/Predefined-queries
|
||||
[11]: https://github.com/plotly/plotly.js
|
||||
[12]: https://github.com/nicolaskruchten/pivottable
|
||||
25
Sharing.md
Normal file
@@ -0,0 +1,25 @@
|
||||
# Sharing
|
||||
|
||||
You can generate a share link. That allows to share not only inquiries but also
|
||||
a database and inquiry display settings. Sqliteviz will automatically load
|
||||
database and inquiries, open them and run the query for the first inquiry.
|
||||
|
||||
The share link can have the following query parameters:
|
||||
|
||||
| Parameter | Values | Description |
|
||||
|--------------|----------------------------------|-------------|
|
||||
| `data_url` | | A URL to an SQLite database file. If not provided sqliteviz will run inquiries agains an empty database.|
|
||||
| `data_format`|`sqlite` | Currently share links support only "sqlite" data format.
|
||||
| `inquiry_url`| | A URL to an inquiry JSON file (you can make that file with inquiry export – see [Manage inquiries][3]).|
|
||||
| `inquiry_id` | | If `inquiry_id` is provided (can occure multiple times) sqliteviz will load only inquiries with provided IDs. If not provided it will get them all.|
|
||||
| `maximize` | `table`, `sqlEditor`, `dataView` | Specify which panel should be maximised for each inquiry. If not provided the inquiries will be opened in the default state: SQL editor on top and result set at the bottom.|
|
||||
|
||||
> **Note:** the server where you host your database or inquiry files must allow
|
||||
cross-origin access. For example you can place your files on [GitHub Gist][1].
|
||||
You can check your URLs with [CORS tester][2].
|
||||
|
||||
Use the following form to generate a share link:
|
||||
|
||||
[1]: https://gist.github.com/
|
||||
[2]: https://cors-test.codehappy.dev/?origin=https%3A%2F%2Fsqliteviz.com%2F&method=get
|
||||
[3]: ../Manage-inquiries
|
||||
@@ -1,5 +0,0 @@
|
||||
module.exports = {
|
||||
presets: [
|
||||
'@vue/cli-plugin-babel/preset'
|
||||
]
|
||||
}
|
||||
BIN
img/Screenshot_app_info.png
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|
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img/Screenshot_chart.png
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|
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|
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img/Screenshot_editor.png
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|
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img/Screenshot_editor_with_db.png
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|
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img/Screenshot_group.png
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|
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BIN
img/Screenshot_my_inquiries.png
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|
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img/Screenshot_pivot_barchart.png
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|
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BIN
img/Screenshot_pivot_custom_chart.png
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|
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BIN
img/Screenshot_pivot_heatmap.png
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|
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BIN
img/Screenshot_pivot_table.png
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|
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BIN
img/Screenshot_predefined.png
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|
After Width: | Height: | Size: 33 KiB |
BIN
img/Screenshot_query_tools.png
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|
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BIN
img/Screenshot_result.png
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|
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BIN
img/Screenshot_welcome.png
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|
After Width: | Height: | Size: 43 KiB |
10
img/add-csv.svg
Normal file
@@ -0,0 +1,10 @@
|
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<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
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<g clip-path="url(#clip0)">
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|
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<defs>
|
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<clipPath id="clip0">
|
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<rect width="18" height="18" fill="white"/>
|
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</clipPath>
|
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|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 739 B |
5
img/camera.svg
Normal file
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|
||||
<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
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<path d="M9 5.51953C6.57686 5.51953 4.60547 7.49092 4.60547 9.91406C4.60547 12.3372 6.57686 14.3086 9 14.3086C11.4231 14.3086 13.3945 12.3372 13.3945 9.91406C13.3945 7.49092 11.4231 5.51953 9 5.51953ZM9 12.9023C7.35226 12.9023 6.01172 11.5618 6.01172 9.91406C6.01172 8.26632 7.35226 6.92578 9 6.92578C10.6477 6.92578 11.9883 8.26632 11.9883 9.91406C11.9883 11.5618 10.6477 12.9023 9 12.9023Z" fill="#A2B1C6"/>
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<path d="M15.8906 3.41016H13.304C13.2221 3.41016 13.1483 3.36547 13.1104 3.29319L12.3948 1.78945C12.3928 1.78534 12.3908 1.78126 12.3887 1.77718C12.1117 1.22312 11.5548 0.878906 10.9353 0.878906H7.11478C6.49529 0.878906 5.93835 1.22312 5.66135 1.77722C5.65928 1.7813 5.65731 1.78538 5.65534 1.78949L4.9397 3.2933C4.90173 3.36547 4.82797 3.41016 4.74609 3.41016H2.10938C0.946266 3.41016 0 4.35642 0 5.51953V15.0117C0 16.1748 0.946266 17.1211 2.10938 17.1211H15.8906C17.0537 17.1211 18 16.1748 18 15.0117V5.51953C18 4.35642 17.0537 3.41016 15.8906 3.41016ZM16.5938 15.0117C16.5938 15.3994 16.2783 15.7148 15.8906 15.7148H2.10938C1.72167 15.7148 1.40625 15.3994 1.40625 15.0117V5.51953C1.40625 5.13183 1.72167 4.81641 2.10938 4.81641H4.74609C5.36555 4.81641 5.92249 4.47223 6.19952 3.91816C6.2016 3.91409 6.20357 3.90997 6.20557 3.90586L6.92121 2.40205C6.95914 2.32984 7.0329 2.28516 7.11478 2.28516H10.9353C11.0172 2.28516 11.091 2.32984 11.1289 2.40202L11.8445 3.90582C11.8465 3.90994 11.8485 3.91405 11.8506 3.91813C12.1276 4.47219 12.6846 4.81637 13.304 4.81637H15.8906C16.2783 4.81637 16.5938 5.13179 16.5938 5.5195V15.0117Z" fill="#A2B1C6"/>
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<path d="M15.1875 6.22266H13.7812V7.62891H15.1875V6.22266Z" fill="#A2B1C6"/>
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</svg>
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|
After Width: | Height: | Size: 1.7 KiB |
8
img/chart.svg
Normal file
@@ -0,0 +1,8 @@
|
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<svg width="19" height="18" viewBox="0 0 19 18" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M8.41943 16V10H10.4194V16H8.41943Z" fill="#A2B1C6"/>
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||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M2.41943 16L2.41943 10H4.41943V16H2.41943Z" fill="#A2B1C6"/>
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||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M11.4194 16V7H13.4194V16H11.4194Z" fill="#A2B1C6"/>
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||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M14.4194 16V8H16.4194V16H14.4194Z" fill="#A2B1C6"/>
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<path fill-rule="evenodd" clip-rule="evenodd" d="M7.41943 12V16H5.41943V12H7.41943Z" fill="#A2B1C6"/>
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<path fill-rule="evenodd" clip-rule="evenodd" d="M12.4332 1.80676L16.6265 6.00001L15.9194 6.70712L12.4055 3.19326L5.93169 9.1691L1.71436 5.55424L2.36515 4.79499L5.90707 7.83092L12.4332 1.80676Z" fill="#A2B1C6"/>
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</svg>
|
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|
After Width: | Height: | Size: 831 B |
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|
Before Width: | Height: | Size: 346 B After Width: | Height: | Size: 346 B |
8
img/graph.svg
Normal file
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||||
<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
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<path d="M17 7.5C17 8.88071 15.8807 10 14.5 10C13.1193 10 12 8.88071 12 7.5C12 6.11929 13.1193 5 14.5 5C15.8807 5 17 6.11929 17 7.5Z" fill="#A2B1C6"/>
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<path d="M8 13.5C8 14.8807 6.88071 16 5.5 16C4.11929 16 3 14.8807 3 13.5C3 12.1193 4.11929 11 5.5 11C6.88071 11 8 12.1193 8 13.5Z" fill="#A2B1C6"/>
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<path d="M2.93128 5.31436L3.90527 5.08778L5.48693 11.8867L4.51294 12.1133L2.93128 5.31436Z" fill="#A2B1C6"/>
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</svg>
|
||||
|
After Width: | Height: | Size: 858 B |
|
Before Width: | Height: | Size: 754 B After Width: | Height: | Size: 754 B |
6
img/pivot.svg
Normal file
@@ -0,0 +1,6 @@
|
||||
<svg width="19" height="18" viewBox="0 0 19 18" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M15.7661 5.13901L18.3407 9.43008H16.5161V12.8467C16.5161 13.7957 16.2783 14.6451 15.6714 15.2521C15.0645 15.859 14.215 16.0967 13.2661 16.0967H9.84942V17.9214L5.55835 15.3467L9.84942 12.7721V14.5967H13.2661C13.9838 14.5967 14.3844 14.4178 14.6108 14.1914C14.8372 13.965 15.0161 13.5645 15.0161 12.8467V9.43008H13.1914L15.7661 5.13901Z" fill="#A2B1C6"/>
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<path d="M6.41943 0H18.4194V4H6.41943V0Z" fill="#A2B1C6"/>
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<path d="M0.419434 6H4.41943V18H0.419434V6Z" fill="#A2B1C6"/>
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<path d="M0.419434 0H4.41943V4H0.419434V0Z" fill="#A2B1C6"/>
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||||
</svg>
|
||||
|
After Width: | Height: | Size: 687 B |
|
Before Width: | Height: | Size: 444 B After Width: | Height: | Size: 444 B |
3
img/run.svg
Normal file
@@ -0,0 +1,3 @@
|
||||
<svg width="12" height="13" viewBox="0 0 12 13" fill="none" xmlns="http://www.w3.org/2000/svg">
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||||
<path d="M11.1624 6.94358L0.770043 12.9436L0.770043 0.943573L11.1624 6.94358Z" fill="#A2B1C6"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 199 B |
11
img/sql.svg
Normal file
@@ -0,0 +1,11 @@
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||||
<svg width="18" height="19" viewBox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg">
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||||
<g clip-path="url(#clip0)">
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||||
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||||
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||||
<clipPath id="clip0">
|
||||
<rect width="18" height="18" fill="white" transform="translate(0 0.0134277)"/>
|
||||
</clipPath>
|
||||
</defs>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 2.8 KiB |
7
img/table.svg
Normal file
@@ -0,0 +1,7 @@
|
||||
<svg width="19" height="19" viewBox="0 0 19 19" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M15.0286 2.66757H3.97119C3.14619 2.66757 2.47119 3.34257 2.47119 4.16757V14.8324C2.47119 15.6574 3.14619 16.3324 3.97119 16.3324H15.0286C15.8613 16.3324 16.5286 15.6576 16.5286 14.8324V4.16757C16.5286 3.33757 15.8586 2.66757 15.0286 2.66757ZM15.03 4.16757H3.96997V14.8276H15.03V4.16757Z" fill="#A2B1C6"/>
|
||||
<line x1="7.52295" y1="3.81403" x2="7.52295" y2="15.1996" stroke="#A2B1C6" stroke-width="1.5"/>
|
||||
<line x1="11.5137" y1="3.80042" x2="11.5137" y2="15.1859" stroke="#A2B1C6" stroke-width="1.5"/>
|
||||
<line x1="2.98926" y1="7.22595" x2="16.0105" y2="7.22595" stroke="#A2B1C6" stroke-width="1.5"/>
|
||||
<line x1="2.98926" y1="11.3483" x2="16.0105" y2="11.3483" stroke="#A2B1C6" stroke-width="1.5"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 841 B |
12
img/visualisation.svg
Normal file
@@ -0,0 +1,12 @@
|
||||
<svg width="19" height="19" viewBox="0 0 19 19" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<g clip-path="url(#clip0)">
|
||||
<path d="M2.03345 13.6725L5.8465 10.2694L9.25264 13.2145L14.0613 8.16519L17.2235 11.38" stroke="#A2B1C6" stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<circle cx="6.00049" cy="6.50339" r="1.5" fill="#A2B1C6"/>
|
||||
<path fill-rule="evenodd" clip-rule="evenodd" d="M16.536 1.71786L2.46546 1.71298C1.64046 1.71298 0.965462 2.38798 0.965462 3.21298L0.964111 15.7821C0.964111 16.6071 1.63911 17.2821 2.46411 17.2821L16.5347 17.287C17.3674 17.287 18.0347 16.6121 18.0347 15.787L18.036 3.21786C18.036 2.38786 17.366 1.71786 16.536 1.71786ZM16.5374 3.21786L2.46424 3.21298L2.46289 15.7772L16.536 15.7821L16.5374 3.21786Z" fill="#A2B1C6"/>
|
||||
</g>
|
||||
<defs>
|
||||
<clipPath id="clip0">
|
||||
<rect width="18" height="18" fill="white" transform="translate(0.5 0.5)"/>
|
||||
</clipPath>
|
||||
</defs>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 909 B |
14
index.md
Executable file
@@ -0,0 +1,14 @@
|
||||
# Introduction
|
||||
|
||||
Sqliteviz is a single-page offline-first PWA for fully client-side visualisation of SQLite databases, CSV, JSON or NDJSON files.
|
||||
|
||||
With sqliteviz you can:
|
||||
|
||||
- run SQL queries against a SQLite database and create Plotly charts, graphs and pivot tables based on the result sets
|
||||
- import a CSV, JSON or NDJSON file into a SQLite database and visualize imported data
|
||||
- export result set to CSV file
|
||||
- manage inquiries and run them against different databases
|
||||
- import/export inquiries from/to a JSON file
|
||||
- export a modified SQLite database
|
||||
- use it offline from your OS application menu like any other desktop app
|
||||
|
||||
203
karma.conf.js
@@ -1,203 +0,0 @@
|
||||
// Karma configuration
|
||||
'use strict'
|
||||
const path = require('path')
|
||||
const VueLoaderPlugin = require('vue-loader/lib/plugin')
|
||||
|
||||
function resolve (dir) {
|
||||
return path.join(__dirname, dir)
|
||||
}
|
||||
|
||||
module.exports = function (config) {
|
||||
config.set({
|
||||
// base path that will be used to resolve all patterns (eg. files, exclude)
|
||||
basePath: '',
|
||||
|
||||
// frameworks to use
|
||||
// available frameworks: https://npmjs.org/browse/keyword/karma-adapter
|
||||
frameworks: ['mocha', 'sinon-chai'],
|
||||
|
||||
// list of files / patterns to load in the browser
|
||||
files: [
|
||||
'./karma.files.js',
|
||||
{
|
||||
pattern: 'node_modules/sql.js/dist/sql-wasm.wasm',
|
||||
watched: false,
|
||||
included: false,
|
||||
served: true,
|
||||
nocache: false
|
||||
}
|
||||
],
|
||||
|
||||
// list of files / patterns to exclude
|
||||
exclude: [],
|
||||
|
||||
// preprocess matching files before serving them to the browser
|
||||
// available preprocessors: https://npmjs.org/browse/keyword/karma-preprocessor
|
||||
preprocessors: {
|
||||
'./karma.files.js': ['webpack']
|
||||
},
|
||||
|
||||
// test results reporter to use
|
||||
// possible values: 'dots', 'progress'
|
||||
// available reporters: https://npmjs.org/browse/keyword/karma-reporter
|
||||
reporters: ['spec', 'coverage'],
|
||||
|
||||
coverageReporter: {
|
||||
dir: 'coverage',
|
||||
reporters: [{ type: 'lcov', subdir: '.' }, { type: 'text-summary' }]
|
||||
},
|
||||
|
||||
// !!DONOT delete this reporter, or vue-cli-addon-ui-karma doesnot work
|
||||
jsonResultReporter: {
|
||||
outputFile: 'report/karma-result.json',
|
||||
isSynchronous: true
|
||||
},
|
||||
|
||||
junitReporter: {
|
||||
outputDir: 'report', // results will be saved as $outputDir/$browserName.xml
|
||||
// if included, results will be saved as $outputDir/$browserName/$outputFile
|
||||
outputFile: undefined,
|
||||
suite: '', // suite will become the package name attribute in xml testsuite element
|
||||
useBrowserName: true, // add browser name to report and classes names
|
||||
// function (browser, result) to customize the name attribute in xml testcase element
|
||||
nameFormatter: undefined,
|
||||
// function (browser, result) to customize the classname attribute in xml testcase element
|
||||
classNameFormatter: undefined,
|
||||
properties: {} // key value pairs add to the <properties> section of the report
|
||||
},
|
||||
|
||||
// web server port
|
||||
port: 9876,
|
||||
|
||||
// enable / disable colors in the output (reporters and logs)
|
||||
colors: true,
|
||||
|
||||
// level of logging
|
||||
// possible values: config.LOG_DISABLE || config.LOG_ERROR || config.LOG_WARN ||
|
||||
// config.LOG_INFO || config.LOG_DEBUG
|
||||
logLevel: config.LOG_INFO,
|
||||
|
||||
// enable / disable watching file and executing tests whenever any file changes
|
||||
autoWatch: false,
|
||||
|
||||
customLaunchers: {
|
||||
FirefoxHeadlessTouch: {
|
||||
base: 'FirefoxHeadless',
|
||||
prefs: {
|
||||
'dom.w3c_touch_events.enabled': 1,
|
||||
'dom.events.asyncClipboard.clipboardItem': true
|
||||
}
|
||||
}
|
||||
},
|
||||
// start these browsers
|
||||
// available browser launchers: https://npmjs.org/browse/keyword/karma-launcher
|
||||
browsers: ['ChromiumHeadless', 'FirefoxHeadlessTouch'],
|
||||
|
||||
// Continuous Integration mode
|
||||
// if true, Karma captures browsers, runs the tests and exits
|
||||
singleRun: true,
|
||||
|
||||
// Concurrency level
|
||||
// how many browser should be started simultaneous
|
||||
concurrency: 2,
|
||||
|
||||
client: {
|
||||
captureConsole: true,
|
||||
mocha: {
|
||||
timeout: 7000
|
||||
}
|
||||
},
|
||||
browserConsoleLogOptions: {
|
||||
terminal: true,
|
||||
level: ''
|
||||
},
|
||||
webpack: {
|
||||
mode: 'development',
|
||||
entry: './src/main.js',
|
||||
resolve: {
|
||||
extensions: ['.js', '.vue', '.json'],
|
||||
alias: {
|
||||
vue$: 'vue/dist/vue.esm.js',
|
||||
'@': resolve('src')
|
||||
}
|
||||
},
|
||||
module: {
|
||||
rules: [
|
||||
{
|
||||
test: /\.js$/,
|
||||
exclude: /(node_modules|bower_components)/,
|
||||
use: [
|
||||
{
|
||||
loader: 'babel-loader'
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
test: /\.js$/,
|
||||
include: /src/,
|
||||
exclude: /(node_modules|bower_components|\.spec\.js$)/,
|
||||
use: [
|
||||
{
|
||||
loader: 'istanbul-instrumenter-loader',
|
||||
options: {
|
||||
esModules: true
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
test: /worker\.js$/,
|
||||
loader: 'worker-loader'
|
||||
},
|
||||
{
|
||||
test: /\.(png|jpe?g|gif|svg)(\?.*)?$/,
|
||||
loader: 'url-loader'
|
||||
},
|
||||
{
|
||||
test: /\.vue$/,
|
||||
loader: 'vue-loader',
|
||||
options: {
|
||||
loaders: {
|
||||
js: 'babel-loader'
|
||||
},
|
||||
postLoaders: {
|
||||
js: 'istanbul-instrumenter-loader?esModules=true'
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
test: /\.css$/,
|
||||
use: ['vue-style-loader', 'css-loader']
|
||||
},
|
||||
{
|
||||
test: /\.scss$/,
|
||||
use: ['vue-style-loader', 'css-loader', 'sass-loader']
|
||||
},
|
||||
{
|
||||
test: /\.(woff2?|eot|ttf|otf)(\?.*)?$/,
|
||||
loader: 'url-loader',
|
||||
options: {
|
||||
limit: 10000,
|
||||
name: resolve('fonts/[name].[hash:7].[ext]')
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
plugins: [new VueLoaderPlugin()],
|
||||
node: {
|
||||
fs: 'empty'
|
||||
}
|
||||
},
|
||||
webpackMiddleware: {
|
||||
watchOptions: {
|
||||
ignored: /node_modules/
|
||||
}
|
||||
},
|
||||
proxies: {
|
||||
'/_karma_webpack_/sql-wasm.wasm': '/base/node_modules/sql.js/dist/sql-wasm.wasm',
|
||||
'/base/sql-wasm.wasm': '/base/node_modules/sql.js/dist/sql-wasm.wasm'
|
||||
}
|
||||
})
|
||||
// Fix the timezone
|
||||
process.env.TZ = 'Europe/Amsterdam'
|
||||
}
|
||||
@@ -1,21 +0,0 @@
|
||||
import Vue from 'vue'
|
||||
import { VuePlugin } from 'vuera'
|
||||
import VModal from 'vue-js-modal'
|
||||
|
||||
Vue.use(VuePlugin)
|
||||
Vue.use(VModal)
|
||||
Vue.config.productionTip = false
|
||||
|
||||
// require all test files (files that ends with .spec.js)
|
||||
const testsContext = require.context('./tests', true, /\.spec.js$/)
|
||||
|
||||
// Read more about why we need to call testContext:
|
||||
// https://www.npmjs.com/package/require-context#context-api
|
||||
testsContext.keys().forEach(testsContext)
|
||||
|
||||
// require all src files except main.js and router/index.js for coverage.
|
||||
// you can also change this to match only the subset of files that
|
||||
// you want coverage for.
|
||||
// We don't include router/index.js to avoid installing VueRouter globally in tests
|
||||
const srcContext = require.context('./src', true, /^\.\/(?!(main|(router(\/)?(index)?))(\.js)?$)/)
|
||||
srcContext.keys().forEach(srcContext)
|
||||
@@ -1,2 +0,0 @@
|
||||
benchmark
|
||||
dist
|
||||
@@ -1,9 +0,0 @@
|
||||
FROM emscripten/emsdk:3.0.1
|
||||
|
||||
WORKDIR /tmp/build
|
||||
|
||||
COPY configure.py .
|
||||
RUN python3.8 configure.py
|
||||
|
||||
COPY build.py .
|
||||
RUN python3.8 build.py
|
||||
@@ -1,108 +0,0 @@
|
||||
# SQLite WebAssembly build
|
||||
|
||||
This directory contains Docker-based build script, `make.sh`, that builds
|
||||
a custom version of [sql.js][1]. It allows sqliteviz to have more recent
|
||||
version of SQLite build with a number of useful extensions.
|
||||
|
||||
`Makefile` from [sql.js][1] is rewritten as more comprehensible `configure.py`
|
||||
and `build.py` Python scripts that run in `emscripten/emsdk` Docker container.
|
||||
|
||||
## Extension
|
||||
|
||||
SQLite [amalgamation][2] extensions included:
|
||||
|
||||
1. [FTS5][4] -- virtual table module that provides full-text search
|
||||
functionality
|
||||
2. [FTS3/FTS4][15] -- older virtual table modules for full-text search
|
||||
3. [JSON1][16] -- scalar, aggregate and table-valued functions for managing JSON data
|
||||
|
||||
SQLite [contribution extensions][17]:
|
||||
|
||||
1. [extension-functions][18] -- mathematical and string extension functions for SQL queries.
|
||||
|
||||
Math: `acos`, `asin`, `atan`, `atn2`, `atan2`, `acosh`, `asinh`, `atanh`, `difference`,
|
||||
`degrees`, `radians`, `cos`, `sin`, `tan`, `cot`, `cosh`, `sinh`, `tanh`, `coth`,
|
||||
`exp`, `log`, `log10`, `power`, `sign`, `sqrt`, `square`, `ceil`, `floor`, `pi`.
|
||||
|
||||
String: `replicate`, `charindex`, `leftstr`, `rightstr`, `ltrim`, `rtrim`, `trim`,
|
||||
`replace`, `reverse`, `proper`, `padl`, `padr`, `padc`, `strfilter`.
|
||||
|
||||
Aggregate: `stdev`, `variance`, `mode`, `median`, `lower_quartile`, `upper_quartile`.
|
||||
|
||||
SQLite [miscellaneous extensions][3] included:
|
||||
|
||||
1. `generate_series` table-valued [series function][6] ([series.c][7])
|
||||
2. `transitive_closure` virtual table for
|
||||
[Querying Tree Structures in SQLite][11] ([closure.c][8])
|
||||
3. `uuid`, `uuid_str` and `uuid_blob` RFC-4122 UUID functions ([uuid.c][9])
|
||||
4. `regexp` (hence `REGEXP` operator) and `regexpi` functions ([regexp.c][10])
|
||||
5. `percentile` function ([percentile.c][13])
|
||||
6. `decimal`, `decimal_cmp`, `decimal_add`, `decimal_sub` and `decimal_mul` functions
|
||||
([decimal.c][14])
|
||||
|
||||
SQLite 3rd party extensions included:
|
||||
|
||||
1. [pivot_vtab][5] -- a pivot virtual table
|
||||
2. `pearson` correlation coefficient function extension from [sqlean][21]
|
||||
(which is part of [squib][20])
|
||||
3. [sqlitelua][22] -- a virtual table `luafunctions` which allows to define custom scalar,
|
||||
aggregate and table-valued functions in Lua
|
||||
|
||||
To ease the step to have working clone locally, the build is committed into
|
||||
the repository.
|
||||
|
||||
Examples of queries involving these extensions can be found in the test suite in
|
||||
[sqliteExtensions.spec.js][19].
|
||||
|
||||
## Build method
|
||||
|
||||
Basically it's extended amalgamation and `SQLITE_EXTRA_INIT` concisely
|
||||
described in [this message from SQLite Forum][12]:
|
||||
|
||||
> Simply append it to the end of the amalgamation file. The real problem is
|
||||
> how you get the init function called. The easiest way (to me at any rate) is
|
||||
> to append a function (after the extensions you want to add are all appended)
|
||||
> that adds the init function for each extension to the auto extension list
|
||||
> for new connections, and set the pre-processor symbol SQLITE_EXTRA_INIT to
|
||||
> the name of this function. [...]
|
||||
>
|
||||
> An example `SQLITE_EXTRA_INIT` function looks like this:
|
||||
>
|
||||
> ```
|
||||
> int core_init(const char* dummy)
|
||||
> {
|
||||
> int nErr = 0;
|
||||
>
|
||||
> nErr += sqlite3_auto_extension((void*)sqlite3_autobusy_init);
|
||||
> nErr += sqlite3_auto_extension((void*)sqlite3_ipaddress_init);
|
||||
>
|
||||
> return nErr ? SQLITE_ERROR : SQLITE_OK;
|
||||
> }
|
||||
> ```
|
||||
>
|
||||
> so you would then define `SQLITE_EXTRA_INIT=core_init` when compiling the
|
||||
> amalgamation code and the extensions would thereafter be automatically
|
||||
> initialized on each connection.
|
||||
|
||||
[1]: https://github.com/sql-js/sql.js
|
||||
[2]: https://sqlite.org/amalgamation.html
|
||||
[3]: https://sqlite.org/src/dir?ci=trunk&name=ext/misc
|
||||
[4]: https://sqlite.org/fts5.html
|
||||
[5]: https://github.com/jakethaw/pivot_vtab
|
||||
[6]: https://sqlite.org/series.html
|
||||
[7]: https://sqlite.org/src/file/ext/misc/series.c
|
||||
[8]: https://sqlite.org/src/file/ext/misc/closure.c
|
||||
[9]: https://sqlite.org/src/file/ext/misc/uuid.c
|
||||
[10]: https://sqlite.org/src/file/ext/misc/regexp.c
|
||||
[11]: https://charlesleifer.com/blog/querying-tree-structures-in-sqlite-using-python-and-the-transitive-closure-extension/
|
||||
[12]: https://sqlite.org/forum/forumpost/6ad7d4f4bebe5e06?raw
|
||||
[13]: https://sqlite.org/src/file/ext/misc/percentile.c
|
||||
[14]: https://sqlite.org/src/file/ext/misc/decimal.c
|
||||
[15]: https://sqlite.org/fts3.html
|
||||
[16]: https://sqlite.org/json1.html
|
||||
[17]: https://sqlite.org/contrib/
|
||||
[18]: https://sqlite.org/contrib//download/extension-functions.c?get=25
|
||||
[19]: https://github.com/lana-k/sqliteviz/blob/master/tests/lib/database/sqliteExtensions.spec.js
|
||||
[20]: https://github.com/mrwilson/squib/blob/master/pearson.c
|
||||
[21]: https://github.com/nalgeon/sqlean/blob/incubator/src/pearson.c
|
||||
[22]: https://github.com/kev82/sqlitelua
|
||||
4
lib/sql-js/benchmark/.gitignore
vendored
@@ -1,4 +0,0 @@
|
||||
/lib/build-*
|
||||
/lib/dist
|
||||
/build-*-result.json
|
||||
/sample.csv
|
||||
@@ -1,17 +0,0 @@
|
||||
FROM node:20.14-bookworm
|
||||
|
||||
RUN set -ex; \
|
||||
apt-get update; \
|
||||
apt-get install -y firefox-esr; \
|
||||
apt-get install -y chromium
|
||||
|
||||
WORKDIR /tmp/build
|
||||
|
||||
COPY package.json ./
|
||||
COPY lib/dist lib/dist
|
||||
COPY lib/package.json lib/package.json
|
||||
RUN npm install
|
||||
|
||||
COPY . .
|
||||
|
||||
CMD npm run benchmark
|
||||
@@ -1,25 +0,0 @@
|
||||
# SQLite WebAssembly build micro-benchmark
|
||||
|
||||
This directory contains a micro-benchmark for evaluating SQLite WebAssembly
|
||||
builds performance on read and write SQL queries, run from `make.sh` script. If
|
||||
the script has permission to `nice` processes and [Procpath][1] is installed,
|
||||
e.g. it is run with `sudo -E env PATH=$PATH ./make.sh`, it'll `renice` all
|
||||
processes running inside the benchmark containers. It can also serve as a smoke
|
||||
test (e.g. for memory leaks).
|
||||
|
||||
The benchmark operates on a set of SQLite WebAssembly builds expected in
|
||||
`lib/build-$NAME` directories each containing `sql-wasm.js` and
|
||||
`sql-wasm.wasm`. Then it creates a Docker image for each, and runs the
|
||||
benchmark in Firefox and Chromium using Karma in the container.
|
||||
|
||||
After successful run, the benchmark produces the following per each build:
|
||||
|
||||
- `build-$NAME-result.json`
|
||||
- `build-$NAME.sqlite` (if Procpath is installed)
|
||||
- `build-$NAME.svg` (if Procpath is installed)
|
||||
|
||||
These files can be analysed using `result-analysis.ipynb` Jupyter notebook.
|
||||
The SVG is a chart with CPU and RSS usage of each test container (i.e. Chromium
|
||||
run, then Firefox run per container).
|
||||
|
||||
[1]: https://pypi.org/project/Procpath/
|
||||
@@ -1,52 +0,0 @@
|
||||
module.exports = function (config) {
|
||||
const timeout = 15 * 60 * 1000
|
||||
config.set({
|
||||
|
||||
frameworks: ['mocha'],
|
||||
|
||||
files: [
|
||||
'suite.js',
|
||||
{ pattern: 'node_modules/sql.js/dist/sql-wasm.wasm', served: true, included: false },
|
||||
{ pattern: 'sample.csv', served: true, included: false }
|
||||
],
|
||||
|
||||
reporters: ['progress', 'json-to-file'],
|
||||
|
||||
singleRun: true,
|
||||
|
||||
customLaunchers: {
|
||||
ChromiumHeadlessNoSandbox: { base: 'ChromiumHeadless', flags: ['--no-sandbox'] }
|
||||
},
|
||||
browsers: ['ChromiumHeadlessNoSandbox', 'FirefoxHeadless'],
|
||||
concurrency: 1,
|
||||
|
||||
browserDisconnectTimeout: timeout,
|
||||
browserNoActivityTimeout: timeout,
|
||||
captureTimeout: timeout,
|
||||
browserSocketTimeout: timeout,
|
||||
pingTimeout: timeout,
|
||||
client: {
|
||||
captureConsole: true,
|
||||
mocha: { timeout: timeout }
|
||||
},
|
||||
|
||||
logLevel: config.LOG_INFO,
|
||||
browserConsoleLogOptions: { terminal: true, level: config.LOG_INFO },
|
||||
|
||||
preprocessors: { 'suite.js': [ 'webpack' ] },
|
||||
webpack: {
|
||||
mode: 'development',
|
||||
module: {
|
||||
noParse: [ __dirname + '/node_modules/benchmark/benchmark.js' ]
|
||||
},
|
||||
node: { fs: 'empty' }
|
||||
},
|
||||
|
||||
proxies: {
|
||||
'/sql-wasm.wasm': '/base/node_modules/sql.js/dist/sql-wasm.wasm'
|
||||
},
|
||||
|
||||
jsonToFileReporter: { outputPath: '.', fileName: 'suite-result.json' }
|
||||
|
||||
})
|
||||
}
|
||||
@@ -1,5 +0,0 @@
|
||||
{
|
||||
"name": "sql.js",
|
||||
"main": "./dist/sql-wasm.js",
|
||||
"private": true
|
||||
}
|
||||
@@ -1,47 +0,0 @@
|
||||
#!/bin/bash -e
|
||||
|
||||
cleanup () {
|
||||
rm -rf lib/dist "$renice_flag_file"
|
||||
docker rm -f sqljs-benchmark-run 2> /dev/null || true
|
||||
}
|
||||
trap cleanup EXIT
|
||||
|
||||
if [ ! -f sample.csv ]; then
|
||||
wget --header="accept-encoding: gzip" -q -O- \
|
||||
https://github.com/plotly/datasets/raw/547090bd/wellspublic.csv \
|
||||
| gunzip -c > sample.csv
|
||||
fi
|
||||
|
||||
PLAYBOOK=procpath/karma_docker.procpath
|
||||
|
||||
# for renice to work run like "sudo -E env PATH=$PATH ./make.sh"
|
||||
test_ni=$(nice -n -5 nice)
|
||||
if [ $test_ni == -5 ]; then
|
||||
renice_flag_file=$(mktemp)
|
||||
fi
|
||||
{
|
||||
while [ -f $renice_flag_file ]; do
|
||||
procpath --logging-level ERROR play -f $PLAYBOOK renice:watch
|
||||
done
|
||||
} &
|
||||
|
||||
shopt -s nullglob
|
||||
for d in lib/build-* ; do
|
||||
rm -rf lib/dist
|
||||
cp -r $d lib/dist
|
||||
sample_name=$(basename $d)
|
||||
|
||||
docker build -t sqliteviz/sqljs-benchmark .
|
||||
docker rm sqljs-benchmark-run 2> /dev/null || true
|
||||
docker run -d -it --cpus 2 --name sqljs-benchmark-run sqliteviz/sqljs-benchmark
|
||||
{
|
||||
rm -f ${sample_name}.sqlite
|
||||
procpath play -f $PLAYBOOK -o database_file=${sample_name}.sqlite track:record
|
||||
procpath play -f $PLAYBOOK -o database_file=${sample_name}.sqlite \
|
||||
-o plot_file=${sample_name}.svg track:plot
|
||||
} &
|
||||
|
||||
docker attach sqljs-benchmark-run
|
||||
docker cp sqljs-benchmark-run:/tmp/build/suite-result.json ${sample_name}-result.json
|
||||
docker rm sqljs-benchmark-run
|
||||
done
|
||||
@@ -1,23 +0,0 @@
|
||||
{
|
||||
"name": "sqlite-webassembly-microbenchmark",
|
||||
"private": true,
|
||||
"dependencies": {
|
||||
"@babel/core" : "^7.14.8",
|
||||
"babel-loader": "^8.2.2",
|
||||
"benchmark": "^2.1.4",
|
||||
"lodash": "^4.17.4",
|
||||
"papaparse": "^5.3.1",
|
||||
"mocha": "^9.0.3",
|
||||
"karma": "^6.3.4",
|
||||
"karma-chrome-launcher": "^3.1.0",
|
||||
"karma-firefox-launcher": "^2.1.1",
|
||||
"karma-json-to-file-reporter" : "^1.0.1",
|
||||
"karma-mocha": "^2.0.1",
|
||||
"karma-webpack": "^4.0.2",
|
||||
"webpack": "^4.46.0",
|
||||
"sql.js": "file:./lib"
|
||||
},
|
||||
"scripts": {
|
||||
"benchmark": "karma start karma.conf.js"
|
||||
}
|
||||
}
|
||||
@@ -1,28 +0,0 @@
|
||||
# This command may run when "sqljs-benchmark-run" does not yet exist or run
|
||||
[renice:watch]
|
||||
interval: 2
|
||||
repeat: 30
|
||||
environment:
|
||||
ROOT_PID=docker inspect -f "{{.State.Pid}}" sqljs-benchmark-run 2> /dev/null || true
|
||||
query:
|
||||
PIDS=$..children[?(@.stat.pid in [$ROOT_PID])]..pid
|
||||
command:
|
||||
echo $PIDS | tr , '\n' | xargs --no-run-if-empty -I{} -- renice -n -5 -p {}
|
||||
|
||||
# Expected input arguments: database_file
|
||||
[track:record]
|
||||
interval: 1
|
||||
stop_without_result: 1
|
||||
environment:
|
||||
ROOT_PID=docker inspect -f "{{.State.Pid}}" sqljs-benchmark-run
|
||||
query:
|
||||
$..children[?(@.stat.pid == $ROOT_PID)]
|
||||
pid_list: $ROOT_PID
|
||||
|
||||
# Expected input arguments: database_file, plot_file
|
||||
[track:plot]
|
||||
moving_average_window: 5
|
||||
title: Chromium vs Firefox (№1 RSS, №2 CPU)
|
||||
custom_query_file:
|
||||
procpath/top2_rss.sql
|
||||
procpath/top2_cpu.sql
|
||||
@@ -1,29 +0,0 @@
|
||||
WITH diff_all AS (
|
||||
SELECT
|
||||
record_id,
|
||||
ts,
|
||||
stat_pid,
|
||||
stat_utime + stat_stime - LAG(stat_utime + stat_stime) OVER (
|
||||
PARTITION BY stat_pid
|
||||
ORDER BY record_id
|
||||
) tick_diff,
|
||||
ts - LAG(ts) OVER (
|
||||
PARTITION BY stat_pid
|
||||
ORDER BY record_id
|
||||
) ts_diff
|
||||
FROM record
|
||||
), diff AS (
|
||||
SELECT * FROM diff_all WHERE tick_diff IS NOT NULL
|
||||
), one_time_pid_condition AS (
|
||||
SELECT stat_pid
|
||||
FROM record
|
||||
GROUP BY 1
|
||||
ORDER BY SUM(stat_utime + stat_stime) DESC
|
||||
LIMIT 2
|
||||
)
|
||||
SELECT
|
||||
ts,
|
||||
stat_pid pid,
|
||||
100.0 * tick_diff / (SELECT value FROM meta WHERE key = 'clock_ticks') / ts_diff value
|
||||
FROM diff
|
||||
JOIN one_time_pid_condition USING(stat_pid)
|
||||
@@ -1,13 +0,0 @@
|
||||
WITH one_time_pid_condition AS (
|
||||
SELECT stat_pid
|
||||
FROM record
|
||||
GROUP BY 1
|
||||
ORDER BY SUM(stat_rss) DESC
|
||||
LIMIT 2
|
||||
)
|
||||
SELECT
|
||||
ts,
|
||||
stat_pid pid,
|
||||
stat_rss / 1024.0 / 1024 * (SELECT value FROM meta WHERE key = 'page_size') value
|
||||
FROM record
|
||||
JOIN one_time_pid_condition USING(stat_pid)
|
||||
@@ -1,218 +0,0 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"import json\n",
|
||||
"from pathlib import Path\n",
|
||||
"\n",
|
||||
"import pandas\n",
|
||||
"from IPython.display import display, IFrame, Markdown\n",
|
||||
"from plotly import express"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"collapsed": false,
|
||||
"outputHidden": false,
|
||||
"inputHidden": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"render_format = 'svg'\n",
|
||||
"benchmark_path = Path()\n",
|
||||
"df_dict = {}\n",
|
||||
"stat_dict = {}\n",
|
||||
"for p in benchmark_path.glob('build-*-result.json'):\n",
|
||||
" build_name = p.stem.split('-', 2)[1]\n",
|
||||
" for browser_data in json.loads(p.read_text()):\n",
|
||||
" browser_name = f'{browser_data[\"browser\"][\"name\"]} {browser_data[\"browser\"][\"major\"]}'\n",
|
||||
" browser_name = browser_name.lower().replace('chrome headless', 'chromium')\n",
|
||||
" for result in (r for i, r in browser_data['result'].items() if i.isdigit()):\n",
|
||||
" key = build_name, browser_name, result['name']\n",
|
||||
" df_dict[key] = result['stats']['sample']\n",
|
||||
" stat_dict[key] = result['stats']\n",
|
||||
"\n",
|
||||
"min_sample_size = min(len(v) for v in df_dict.values())\n",
|
||||
"df_dict = {k: v[:min_sample_size] for k, v in df_dict.items()}\n",
|
||||
" \n",
|
||||
"wide_df = pandas.DataFrame(df_dict).reset_index()\n",
|
||||
"df = pandas.melt(\n",
|
||||
" wide_df, \n",
|
||||
" id_vars='index', \n",
|
||||
" var_name=['build', 'browser', 'test'], \n",
|
||||
" value_name='duration',\n",
|
||||
")\n",
|
||||
"df = df.rename(columns={'index': 'run'})\n",
|
||||
"df.sort_values(['build', 'run'], inplace=True)"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"# sql.js build comparison\n",
|
||||
"\n",
|
||||
"<style>\n",
|
||||
"@page {\n",
|
||||
" size: 215mm 297mm;\n",
|
||||
" margin: 0;\n",
|
||||
"}\n",
|
||||
"</style>"
|
||||
],
|
||||
"metadata": {}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"!du -b lib | head -n 2"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"collapsed": false,
|
||||
"outputHidden": false,
|
||||
"inputHidden": true
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"stat_df = pandas.DataFrame(stat_dict)\n",
|
||||
"stat_df = stat_df.loc[['mean', 'rme']].transpose()\n",
|
||||
"stat_df.index = stat_df.index.set_names(['build', 'browser', 'test'])\n",
|
||||
"stat_df = stat_df.reset_index().sort_values(['test', 'browser'], ascending=False)\n",
|
||||
"for index, row in stat_df.iterrows():\n",
|
||||
" print('\\t'.join([\n",
|
||||
" row['build'],\n",
|
||||
" row['browser'],\n",
|
||||
" row['test'],\n",
|
||||
" f'{row[\"mean\"]:.2f} s ± {row[\"rme\"]:.1f}%'\n",
|
||||
" ]))"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"fig = express.box(df, x='browser', y='duration', points='all', color='build', facet_row='test')\n",
|
||||
"fig.update_yaxes(matches=None)\n",
|
||||
"fig.show(render_format)"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"fig = express.line(\n",
|
||||
" df, x='run', y='duration', color='build', facet_col='browser', facet_row='test'\n",
|
||||
")\n",
|
||||
"fig.update_yaxes(matches=None)\n",
|
||||
"fig.show(render_format)"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"plot_df = df.groupby(['browser', 'build', 'test'])['duration'].mean().reset_index()\n",
|
||||
"plot_df['pct'] = (\n",
|
||||
" plot_df\n",
|
||||
" .groupby(['browser', 'test'])['duration']\n",
|
||||
" .pct_change()\n",
|
||||
" .fillna('')\n",
|
||||
" .map(lambda v: '{:.2%}'.format(v) if v else v)\n",
|
||||
")\n",
|
||||
"fig = express.bar(\n",
|
||||
" plot_df, \n",
|
||||
" x='browser', \n",
|
||||
" y='duration', \n",
|
||||
" color='build', \n",
|
||||
" text='pct', \n",
|
||||
" barmode='overlay', \n",
|
||||
" facet_row='test',\n",
|
||||
")\n",
|
||||
"fig.update_yaxes(matches=None)\n",
|
||||
"fig.show(render_format)"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"for p in sorted(benchmark_path.glob('build-*.svg')):\n",
|
||||
" display(Markdown(p.stem))\n",
|
||||
" display(IFrame(p, 640, 480))"
|
||||
],
|
||||
"outputs": [],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"collapsed": false,
|
||||
"outputHidden": false,
|
||||
"inputHidden": true,
|
||||
"outputExpanded": false
|
||||
}
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"name": "stats",
|
||||
"language": "python",
|
||||
"display_name": "Stats (Python 3.10)"
|
||||
},
|
||||
"language_info": {
|
||||
"name": "python",
|
||||
"version": "3.10.14",
|
||||
"mimetype": "text/x-python",
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"pygments_lexer": "ipython3",
|
||||
"nbconvert_exporter": "python",
|
||||
"file_extension": ".py"
|
||||
},
|
||||
"widgets": {
|
||||
"application/vnd.jupyter.widget-state+json": {
|
||||
"state": {},
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
}
|
||||
},
|
||||
"kernel_info": {
|
||||
"name": "stats"
|
||||
},
|
||||
"nteract": {
|
||||
"version": "0.14.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -1,140 +0,0 @@
|
||||
import benchmark from 'benchmark'
|
||||
import initSqlJs from 'sql.js'
|
||||
import lodash from 'lodash'
|
||||
import Papa from 'papaparse'
|
||||
import useragent from 'ua-parser-js'
|
||||
|
||||
|
||||
describe('SQLite build benchmark', function () {
|
||||
let parsedCsv
|
||||
let sqlModule
|
||||
let selectDb
|
||||
|
||||
before(async function () {
|
||||
parsedCsv = await parseCsv('http://localhost:9876/base/sample.csv')
|
||||
sqlModule = await initSqlJs()
|
||||
|
||||
selectDb = new sqlModule.Database()
|
||||
importToTable(selectDb, parsedCsv)
|
||||
})
|
||||
|
||||
function benchmarkImport () {
|
||||
const db = new sqlModule.Database()
|
||||
try {
|
||||
importToTable(db, parsedCsv)
|
||||
} finally {
|
||||
db.close()
|
||||
}
|
||||
}
|
||||
|
||||
function benchmarkSelect () {
|
||||
const result = selectDb.exec(`
|
||||
SELECT county, AVG(avg_depth) avg_depth_c
|
||||
FROM (
|
||||
SELECT s.county, s.town, COUNT(*) cnt, AVG(s.DrilledDepth) avg_depth
|
||||
FROM csv_import s
|
||||
JOIN csv_import USING(hole)
|
||||
WHERE s.town IS NOT NULL
|
||||
GROUP BY 1, 2
|
||||
ORDER BY 4 DESC
|
||||
)
|
||||
GROUP BY 1
|
||||
ORDER BY 2 DESC
|
||||
`)
|
||||
console.assert(result.values.length == 56, 'Unexpected size of result set')
|
||||
}
|
||||
|
||||
it('run', async function () {
|
||||
const suite = createSuite()
|
||||
suite.add('import', { initCount: 3, minSamples: 50, fn: benchmarkImport })
|
||||
suite.add('select', { initCount: 3, minSamples: 50, fn: benchmarkSelect })
|
||||
await run(suite)
|
||||
})
|
||||
|
||||
})
|
||||
|
||||
|
||||
function importToTable (db, parsedCsv, chunkSize = 1024) {
|
||||
const columnListString = parsedCsv.meta.fields.join(', ')
|
||||
db.exec(`CREATE TABLE csv_import(${columnListString})`)
|
||||
|
||||
const params = parsedCsv.meta.fields.map(name => '?').join(', ')
|
||||
const insertStmt = db.prepare(`INSERT INTO csv_import VALUES(${params})`)
|
||||
chunkArray(parsedCsv.data, chunkSize).map(function (chunk) {
|
||||
db.exec('BEGIN')
|
||||
chunk.map(row => insertStmt.run(Object.values(row)))
|
||||
db.exec('COMMIT')
|
||||
})
|
||||
}
|
||||
|
||||
|
||||
class PromiseWrapper {
|
||||
constructor() {
|
||||
this.promise = new Promise((resolve, reject) => {
|
||||
this.reject = reject
|
||||
this.resolve = resolve
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
function parseCsv(url) {
|
||||
return new Promise((resolve, reject) => {
|
||||
Papa.parse(url, {
|
||||
header: true,
|
||||
download: true,
|
||||
skipEmptyLines: 'greedy',
|
||||
complete: results => resolve(results),
|
||||
error: (error, file) => reject(error)
|
||||
})
|
||||
})
|
||||
}
|
||||
|
||||
function chunkArray (arr, size) {
|
||||
return arr.reduce(function (result, value, index) {
|
||||
const chunkIndex = Math.floor(index / size)
|
||||
|
||||
if(!(chunkIndex in result)) {
|
||||
result[chunkIndex] = []
|
||||
}
|
||||
result[chunkIndex].push(value)
|
||||
|
||||
return result
|
||||
}, [])
|
||||
}
|
||||
|
||||
|
||||
function createSuite () {
|
||||
// Combined workaround from:
|
||||
// - https://github.com/bestiejs/benchmark.js/issues/106
|
||||
// - https://github.com/bestiejs/benchmark.js/issues/237
|
||||
|
||||
// Benchmark could not pick up lodash otherwise
|
||||
const bm = benchmark.runInContext({ _: lodash })
|
||||
// Avoid `ReferenceError: Benchmark is not defined` error because Benchmark is assumed
|
||||
// to be in window
|
||||
window.Benchmark = bm
|
||||
|
||||
return new bm.Suite()
|
||||
}
|
||||
|
||||
function run (suite) {
|
||||
const suiteResult = new PromiseWrapper()
|
||||
suite
|
||||
.on('cycle', function (event) {
|
||||
console.info(String(event.target))
|
||||
})
|
||||
.on('complete', function () {
|
||||
console.log(JSON.stringify({
|
||||
browser: useragent(navigator.userAgent).browser,
|
||||
result: this.filter('successful')
|
||||
}))
|
||||
suiteResult.resolve()
|
||||
})
|
||||
.on('error', function (event) {
|
||||
console.error('Benchmark failed', String(event.target))
|
||||
suiteResult.reject()
|
||||
})
|
||||
.run({async: true})
|
||||
|
||||
return suiteResult.promise
|
||||
}
|
||||
@@ -1,99 +0,0 @@
|
||||
import logging
|
||||
import subprocess
|
||||
from pathlib import Path
|
||||
|
||||
# See the setting descriptions on these pages:
|
||||
# - https://emscripten.org/docs/optimizing/Optimizing-Code.html
|
||||
# - https://github.com/emscripten-core/emscripten/blob/main/src/settings.js
|
||||
cflags = (
|
||||
# SQLite configuration
|
||||
'-DSQLITE_DEFAULT_CACHE_SIZE=-65536', # 64 MiB
|
||||
'-DSQLITE_DEFAULT_MEMSTATUS=0',
|
||||
'-DSQLITE_DEFAULT_SYNCHRONOUS=0',
|
||||
'-DSQLITE_DISABLE_LFS',
|
||||
'-DSQLITE_DQS=0',
|
||||
'-DSQLITE_ENABLE_FTS3',
|
||||
'-DSQLITE_ENABLE_FTS3_PARENTHESIS',
|
||||
'-DSQLITE_ENABLE_FTS5',
|
||||
'-DSQLITE_ENABLE_NORMALIZE',
|
||||
'-DSQLITE_EXTRA_INIT=extra_init',
|
||||
'-DSQLITE_OMIT_DEPRECATED',
|
||||
'-DSQLITE_OMIT_LOAD_EXTENSION',
|
||||
'-DSQLITE_OMIT_SHARED_CACHE',
|
||||
'-DSQLITE_THREADSAFE=0',
|
||||
# Compile-time optimisation
|
||||
'-Os', # reduces the code size about in half comparing to -O2
|
||||
'-flto',
|
||||
'-Isrc', '-Isrc/lua',
|
||||
)
|
||||
emflags = (
|
||||
# Base
|
||||
'--memory-init-file', '0',
|
||||
'-s', 'ALLOW_TABLE_GROWTH=1',
|
||||
# WASM
|
||||
'-s', 'WASM=1',
|
||||
'-s', 'ALLOW_MEMORY_GROWTH=1',
|
||||
'-s', 'ENVIRONMENT=web,worker',
|
||||
# Link-time optimisation
|
||||
'-Os',
|
||||
'-flto',
|
||||
# sql.js
|
||||
'-s', 'EXPORTED_FUNCTIONS=@src/sqljs/exported_functions.json',
|
||||
'-s', 'EXPORTED_RUNTIME_METHODS=@src/sqljs/exported_runtime_methods.json',
|
||||
'--pre-js', 'src/sqljs/api.js',
|
||||
)
|
||||
|
||||
|
||||
def build(src: Path, dst: Path):
|
||||
out = Path('out')
|
||||
out.mkdir()
|
||||
|
||||
logging.info('Building LLVM bitcode for sqlite3.c')
|
||||
subprocess.check_call([
|
||||
'emcc',
|
||||
*cflags,
|
||||
'-c', src / 'sqlite3.c',
|
||||
'-o', out / 'sqlite3.o',
|
||||
])
|
||||
logging.info('Building LLVM bitcode for extension-functions.c')
|
||||
subprocess.check_call([
|
||||
'emcc',
|
||||
*cflags,
|
||||
'-c', src / 'extension-functions.c',
|
||||
'-o', out / 'extension-functions.o',
|
||||
])
|
||||
logging.info('Building LLVM bitcode for SQLite Lua extension')
|
||||
subprocess.check_call([
|
||||
'emcc',
|
||||
*cflags,
|
||||
'-shared',
|
||||
*(src / 'lua').glob('*.c'),
|
||||
*(src / 'sqlitelua').glob('*.c'),
|
||||
'-o', out / 'sqlitelua.o',
|
||||
])
|
||||
|
||||
logging.info('Building WASM from bitcode')
|
||||
subprocess.check_call([
|
||||
'emcc',
|
||||
*emflags,
|
||||
out / 'sqlite3.o',
|
||||
out / 'extension-functions.o',
|
||||
out / 'sqlitelua.o',
|
||||
'-o', out / 'sql-wasm.js',
|
||||
])
|
||||
|
||||
logging.info('Post-processing build and copying to dist')
|
||||
(out / 'sql-wasm.wasm').rename(dst / 'sql-wasm.wasm')
|
||||
with (dst / 'sql-wasm.js').open('w') as f:
|
||||
f.write((src / 'sqljs' / 'shell-pre.js').read_text())
|
||||
f.write((out / 'sql-wasm.js').read_text())
|
||||
f.write((src / 'sqljs' / 'shell-post.js').read_text())
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
logging.basicConfig(level='INFO', format='%(asctime)s %(levelname)s %(name)s %(message)s')
|
||||
|
||||
src = Path('src')
|
||||
dst = Path('dist')
|
||||
dst.mkdir()
|
||||
build(src, dst)
|
||||
@@ -1,150 +0,0 @@
|
||||
import logging
|
||||
import re
|
||||
import shutil
|
||||
import subprocess
|
||||
import sys
|
||||
import tarfile
|
||||
import zipfile
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
from urllib import request
|
||||
|
||||
|
||||
amalgamation_url = 'https://sqlite.org/2023/sqlite-amalgamation-3410000.zip'
|
||||
|
||||
# Extension-functions
|
||||
# ===================
|
||||
# It breaks amalgamation if appended as other extension because it redefines
|
||||
# several functions, so build it separately. Note that sql.js registers these
|
||||
# extension functions by calling ``registerExtensionFunctions`` itself.
|
||||
contrib_functions_url = 'https://sqlite.org/contrib/download/extension-functions.c?get=25'
|
||||
|
||||
extension_urls = (
|
||||
# Miscellaneous extensions
|
||||
# ========================
|
||||
('https://sqlite.org/src/raw/8d79354f?at=series.c', 'sqlite3_series_init'),
|
||||
('https://sqlite.org/src/raw/dbfd8543?at=closure.c', 'sqlite3_closure_init'),
|
||||
('https://sqlite.org/src/raw/5bb2264c?at=uuid.c', 'sqlite3_uuid_init'),
|
||||
('https://sqlite.org/src/raw/5853b0e5?at=regexp.c', 'sqlite3_regexp_init'),
|
||||
('https://sqlite.org/src/raw/b9086e22?at=percentile.c', 'sqlite3_percentile_init'),
|
||||
('https://sqlite.org/src/raw/09f967dc?at=decimal.c', 'sqlite3_decimal_init'),
|
||||
# Third-party extension
|
||||
# =====================
|
||||
('https://github.com/jakethaw/pivot_vtab/raw/9323ef93/pivot_vtab.c', 'sqlite3_pivotvtab_init'),
|
||||
('https://github.com/nalgeon/sqlean/raw/95e8d21a/src/pearson.c', 'sqlite3_pearson_init'),
|
||||
# Third-party extension with own dependencies
|
||||
# ===========================================
|
||||
('https://github.com/kev82/sqlitelua/raw/db479510/src/main.c', 'sqlite3_luafunctions_init'),
|
||||
)
|
||||
|
||||
lua_url = 'http://www.lua.org/ftp/lua-5.3.5.tar.gz'
|
||||
sqlitelua_url = 'https://github.com/kev82/sqlitelua/archive/db479510.zip'
|
||||
|
||||
sqljs_url = 'https://github.com/sql-js/sql.js/archive/refs/tags/v1.7.0.zip'
|
||||
|
||||
|
||||
def _generate_extra_init_c_function(init_function_names):
|
||||
auto_ext_calls = '\n'.join([
|
||||
'nErr += sqlite3_auto_extension((void*){});'.format(init_fn)
|
||||
for init_fn in init_function_names
|
||||
])
|
||||
return '''
|
||||
int extra_init(const char* dummy)
|
||||
{
|
||||
int nErr = 0;
|
||||
%s
|
||||
return nErr ? SQLITE_ERROR : SQLITE_OK;
|
||||
}
|
||||
''' % auto_ext_calls
|
||||
|
||||
|
||||
def _get_amalgamation(tgt: Path):
|
||||
logging.info('Downloading and extracting SQLite amalgamation %s', amalgamation_url)
|
||||
archive = zipfile.ZipFile(BytesIO(request.urlopen(amalgamation_url).read()))
|
||||
archive_root_dir = zipfile.Path(archive, archive.namelist()[0])
|
||||
for zpath in archive_root_dir.iterdir():
|
||||
with zpath.open() as fr, (tgt / zpath.name).open('wb') as fw:
|
||||
shutil.copyfileobj(fr, fw)
|
||||
|
||||
|
||||
def _get_lua(tgt: Path):
|
||||
# Library definitions from lua/Makefile
|
||||
lib_str = '''
|
||||
CORE_O= lapi.o lcode.o lctype.o ldebug.o ldo.o ldump.o lfunc.o lgc.o llex.o \
|
||||
lmem.o lobject.o lopcodes.o lparser.o lstate.o lstring.o ltable.o \
|
||||
ltm.o lundump.o lvm.o lzio.o
|
||||
LIB_O= lauxlib.o lbaselib.o lbitlib.o lcorolib.o ldblib.o liolib.o \
|
||||
lmathlib.o loslib.o lstrlib.o ltablib.o lutf8lib.o loadlib.o linit.o
|
||||
LUA_O= lua.o
|
||||
'''
|
||||
header_only_files = {'lprefix', 'luaconf', 'llimits', 'lualib'}
|
||||
lib_names = set(re.findall(r'(\w+)\.o', lib_str)) | header_only_files
|
||||
|
||||
logging.info('Downloading and extracting Lua %s', lua_url)
|
||||
archive = tarfile.open(fileobj=BytesIO(request.urlopen(lua_url).read()))
|
||||
(tgt / 'lua').mkdir()
|
||||
for tarinfo in archive:
|
||||
tarpath = Path(tarinfo.name)
|
||||
if tarpath.match('src/*') and tarpath.stem in lib_names:
|
||||
with (tgt / 'lua' / tarpath.name).open('wb') as fw:
|
||||
shutil.copyfileobj(archive.extractfile(tarinfo), fw)
|
||||
|
||||
logging.info('Downloading and extracting SQLite Lua extension %s', sqlitelua_url)
|
||||
archive = zipfile.ZipFile(BytesIO(request.urlopen(sqlitelua_url).read()))
|
||||
archive_root_dir = zipfile.Path(archive, archive.namelist()[0])
|
||||
(tgt / 'sqlitelua').mkdir()
|
||||
for zpath in (archive_root_dir / 'src').iterdir():
|
||||
if zpath.name != 'main.c':
|
||||
with zpath.open() as fr, (tgt / 'sqlitelua' / zpath.name).open('wb') as fw:
|
||||
shutil.copyfileobj(fr, fw)
|
||||
|
||||
|
||||
def _get_contrib_functions(tgt: Path):
|
||||
request.urlretrieve(contrib_functions_url, tgt / 'extension-functions.c')
|
||||
|
||||
|
||||
def _get_extensions(tgt: Path):
|
||||
init_functions = []
|
||||
sqlite3_c = tgt / 'sqlite3.c'
|
||||
with sqlite3_c.open('ab') as f:
|
||||
for url, init_fn in extension_urls:
|
||||
logging.info('Downloading and appending to amalgamation %s', url)
|
||||
with request.urlopen(url) as resp:
|
||||
f.write(b'\n')
|
||||
shutil.copyfileobj(resp, f)
|
||||
init_functions.append(init_fn)
|
||||
|
||||
logging.info('Appending SQLITE_EXTRA_INIT to amalgamation')
|
||||
f.write(_generate_extra_init_c_function(init_functions).encode())
|
||||
|
||||
|
||||
def _get_sqljs(tgt: Path):
|
||||
logging.info('Downloading and extracting sql.js %s', sqljs_url)
|
||||
archive = zipfile.ZipFile(BytesIO(request.urlopen(sqljs_url).read()))
|
||||
archive_root_dir = zipfile.Path(archive, archive.namelist()[0])
|
||||
(tgt / 'sqljs').mkdir()
|
||||
for zpath in (archive_root_dir / 'src').iterdir():
|
||||
with zpath.open() as fr, (tgt / 'sqljs' / zpath.name).open('wb') as fw:
|
||||
shutil.copyfileobj(fr, fw)
|
||||
|
||||
|
||||
def configure(tgt: Path):
|
||||
_get_amalgamation(tgt)
|
||||
_get_contrib_functions(tgt)
|
||||
_get_lua(tgt)
|
||||
_get_extensions(tgt)
|
||||
_get_sqljs(tgt)
|
||||
|
||||
subprocess.check_call(['emcc', '--version'])
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
if sys.version_info < (3, 8):
|
||||
print('Python 3.8 or higher is expected', file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
logging.basicConfig(level='INFO', format='%(asctime)s %(levelname)s %(name)s %(message)s')
|
||||
|
||||
src = Path('src')
|
||||
src.mkdir()
|
||||
configure(src)
|
||||
94
lib/sql-js/dist/sql-wasm.js
vendored
BIN
lib/sql-js/dist/sql-wasm.wasm
vendored
@@ -1,9 +0,0 @@
|
||||
#!/bin/bash -e
|
||||
|
||||
docker build -t sqliteviz/sqljs .
|
||||
|
||||
rm -r dist || true
|
||||
|
||||
CONTAINER=$(docker create sqliteviz/sqljs)
|
||||
docker cp $CONTAINER:/tmp/build/dist .
|
||||
docker rm $CONTAINER
|
||||
@@ -1,5 +0,0 @@
|
||||
{
|
||||
"name": "sql.js",
|
||||
"main": "./dist/sql-wasm.js",
|
||||
"private": true
|
||||
}
|
||||
46570
package-lock.json
generated
63
package.json
@@ -1,63 +0,0 @@
|
||||
{
|
||||
"name": "sqliteviz",
|
||||
"version": "0.25.0",
|
||||
"license": "Apache-2.0",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"serve": "vue-cli-service serve",
|
||||
"build": "NODE_OPTIONS=--max_old_space_size=4096 vue-cli-service build",
|
||||
"test": "vue-cli-service karma",
|
||||
"lint": "vue-cli-service lint"
|
||||
},
|
||||
"dependencies": {
|
||||
"codemirror": "^5.57.0",
|
||||
"core-js": "^3.6.5",
|
||||
"dataurl-to-blob": "^0.0.1",
|
||||
"html2canvas": "^1.1.4",
|
||||
"jquery": "^3.6.0",
|
||||
"nanoid": "^3.1.12",
|
||||
"papaparse": "^5.4.1",
|
||||
"pivottable": "^2.23.0",
|
||||
"plotly.js": "^1.58.4",
|
||||
"promise-worker": "^2.0.1",
|
||||
"react": "^16.13.1",
|
||||
"react-chart-editor": "^0.45.0",
|
||||
"react-dom": "^16.13.1",
|
||||
"sql.js": "file:./lib/sql-js",
|
||||
"vue": "^2.6.11",
|
||||
"vue-codemirror": "^4.0.6",
|
||||
"vue-js-modal": "^2.0.0-rc.6",
|
||||
"vue-multiselect": "^2.1.6",
|
||||
"vue-router": "^3.2.0",
|
||||
"vue2-teleport": "^1.0.1",
|
||||
"vuejs-paginate": "^2.1.0",
|
||||
"vuera": "^0.2.7",
|
||||
"vuex": "^3.4.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@vue/cli-plugin-babel": "^4.4.0",
|
||||
"@vue/cli-plugin-eslint": "^4.4.0",
|
||||
"@vue/cli-plugin-router": "^4.4.0",
|
||||
"@vue/cli-plugin-vuex": "^4.4.0",
|
||||
"@vue/cli-service": "^4.4.0",
|
||||
"@vue/eslint-config-standard": "^5.1.2",
|
||||
"@vue/test-utils": "^1.1.2",
|
||||
"babel-eslint": "^10.1.0",
|
||||
"chai": "^4.1.2",
|
||||
"chai-as-promised": "^7.1.1",
|
||||
"eslint": "^6.7.2",
|
||||
"eslint-plugin-import": "^2.20.2",
|
||||
"eslint-plugin-node": "^11.1.0",
|
||||
"eslint-plugin-promise": "^4.2.1",
|
||||
"eslint-plugin-standard": "^4.0.0",
|
||||
"eslint-plugin-vue": "^6.2.2",
|
||||
"flush-promises": "^1.0.2",
|
||||
"karma": "^3.1.4",
|
||||
"karma-firefox-launcher": "^2.1.0",
|
||||
"karma-webpack": "^4.0.2",
|
||||
"vue-cli-plugin-ui-karma": "^0.2.5",
|
||||
"vue-template-compiler": "^2.6.11",
|
||||
"workbox-webpack-plugin": "^6.1.5",
|
||||
"worker-loader": "^3.0.8"
|
||||
}
|
||||
}
|
||||
|
Before Width: | Height: | Size: 11 KiB |
|
Before Width: | Height: | Size: 1.1 KiB |
|
Before Width: | Height: | Size: 68 KiB |
|
Before Width: | Height: | Size: 774 B |
@@ -1,102 +0,0 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=edge">
|
||||
<meta name="viewport" content="width=device-width,initial-scale=1.0">
|
||||
<link rel="icon" href="<%= BASE_URL %>favicon.png">
|
||||
<link rel="manifest" href="<%= BASE_URL %>manifest.webmanifest">
|
||||
<title><%= htmlWebpackPlugin.options.title %></title>
|
||||
<style>
|
||||
#sqliteviz-loading-wrapper {
|
||||
position: fixed;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
left: 0;
|
||||
top: 0;
|
||||
background-color: white;
|
||||
}
|
||||
|
||||
#sqliteviz-loading-text {
|
||||
display: block;
|
||||
position: absolute;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
color: #506784;
|
||||
font-family: sans-serif;
|
||||
font-size: 20px;
|
||||
}
|
||||
|
||||
#sqliteviz-loading-wrapper svg {
|
||||
display: block;
|
||||
position: absolute;
|
||||
left: 50%;
|
||||
top: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
}
|
||||
|
||||
#sqliteviz-loading-wrapper circle {
|
||||
position: absolute;
|
||||
left: 0; right: 0; top: 0; bottom: 0;
|
||||
fill: none;
|
||||
stroke-width: 5px;
|
||||
stroke-linecap: round;
|
||||
stroke: #119DFF;
|
||||
}
|
||||
|
||||
#sqliteviz-loading-wrapper circle.bg {
|
||||
stroke: #C8D4E3;
|
||||
}
|
||||
|
||||
#sqliteviz-loading-wrapper circle.front {
|
||||
stroke-dasharray: 402px;
|
||||
animation: sqliteviz-loading 2s linear 0s infinite;
|
||||
}
|
||||
|
||||
@keyframes sqliteviz-loading {
|
||||
0% {
|
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stroke-dasharray: 100px 402px;
|
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stroke-dashoffset: 0;
|
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}
|
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50% {
|
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stroke-dasharray: 251px;
|
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stroke-dashoffset: -251px;
|
||||
}
|
||||
100% {
|
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stroke-dasharray: 100px 402px;
|
||||
stroke-dashoffset: -502px;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
<!-- head extention slot start -->
|
||||
<!-- head extention slot end -->
|
||||
</head>
|
||||
<body>
|
||||
<noscript>
|
||||
<strong>We're sorry but <%= htmlWebpackPlugin.options.title %> doesn't work properly without JavaScript enabled. Please enable it to continue.</strong>
|
||||
</noscript>
|
||||
<div id="app">
|
||||
<div id="sqliteviz-loading-wrapper">
|
||||
<div id="sqliteviz-loading-text">LOADING</div>
|
||||
<svg height="170" width="170" viewBox="0 0 170 170">
|
||||
<circle
|
||||
class="bg"
|
||||
cx="85"
|
||||
cy="85"
|
||||
r="80"
|
||||
/>
|
||||
<circle
|
||||
class="front"
|
||||
cx="85"
|
||||
cy="85"
|
||||
r="80"
|
||||
/>
|
||||
</svg>
|
||||
</div>
|
||||
</div>
|
||||
<!-- extention slot start -->
|
||||
<!-- extention slot end -->
|
||||
<!-- built files will be auto injected -->
|
||||
</body>
|
||||
</html>
|
||||
@@ -1 +0,0 @@
|
||||
[]
|
||||
@@ -1,30 +0,0 @@
|
||||
{
|
||||
"background_color": "white",
|
||||
"description": "Sqliteviz is a single-page application for fully client-side visualisation of SQLite databases, CSV, JSON or NDJSON.",
|
||||
"display": "fullscreen",
|
||||
"icons": [
|
||||
{
|
||||
"src": "favicon.png",
|
||||
"sizes": "32x32",
|
||||
"type": "image/png"
|
||||
},
|
||||
{
|
||||
"src": "Logo48x48.png",
|
||||
"sizes": "48x48",
|
||||
"type": "image/png"
|
||||
},
|
||||
{
|
||||
"src": "Logo192x192.png",
|
||||
"sizes": "192x192",
|
||||
"type": "image/png"
|
||||
},
|
||||
{
|
||||
"src": "Logo512x512.png",
|
||||
"sizes": "512x512",
|
||||
"type": "image/png"
|
||||
}
|
||||
],
|
||||
"name": "sqliteviz",
|
||||
"short_name": "sqliteviz",
|
||||
"start_url": "index.html"
|
||||
}
|
||||
33
sidebar.json
Normal file
@@ -0,0 +1,33 @@
|
||||
[{
|
||||
"sections": [{
|
||||
"title": "For users",
|
||||
"items": [
|
||||
"/docs/",
|
||||
"/docs/installation/",
|
||||
"/docs/basic-usage/",
|
||||
"/docs/multiple-csv-file-import/",
|
||||
"/docs/manage-inquiries/",
|
||||
"/docs/export-current-database/",
|
||||
"/docs/graph/",
|
||||
"/docs/pivot-table/",
|
||||
"/docs/predefined-inquiries/",
|
||||
"/docs/sharing/",
|
||||
"/docs/diagnostic-information/"
|
||||
]
|
||||
},
|
||||
{
|
||||
"title": "Examples and tutorials",
|
||||
"items": [
|
||||
"/docs/how-to-migrate-to-sqliteviz-dot-com/",
|
||||
"/docs/how-to-build-a-pivot-table-in-sq-lite/",
|
||||
"/docs/how-to-rename-tables-and-columns-after-csv-import/"
|
||||
]
|
||||
},
|
||||
{
|
||||
"title": "For developers",
|
||||
"items": [
|
||||
"/docs/integrate-predefined-inquiries/"
|
||||
]
|
||||
}
|
||||
]
|
||||
}]
|
||||
66
src/App.vue
@@ -1,66 +0,0 @@
|
||||
<template>
|
||||
<div id="app">
|
||||
<router-view/>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<style>
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-Regular.woff2");
|
||||
font-weight: 400;
|
||||
font-style: normal;
|
||||
}
|
||||
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-SemiBold.woff2");
|
||||
font-weight: 600;
|
||||
font-style: normal;
|
||||
}
|
||||
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-Bold.woff2");
|
||||
font-weight: 700;
|
||||
font-style: normal;
|
||||
}
|
||||
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-Italic.woff2");
|
||||
font-weight: 400;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-SemiBoldItalic.woff2");
|
||||
font-weight: 600;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
@font-face {
|
||||
font-family: "Open Sans";
|
||||
src: url("~@/assets/fonts/OpenSans-BoldItalic.woff2");
|
||||
font-weight: 700;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
#app,
|
||||
input,
|
||||
label,
|
||||
button,
|
||||
.plotly_editor * {
|
||||
font-family: "Open Sans", Helvetica, Arial, sans-serif;
|
||||
-webkit-font-smoothing: antialiased;
|
||||
-moz-osx-font-smoothing: grayscale;
|
||||
}
|
||||
|
||||
body {
|
||||
margin: 0;
|
||||
}
|
||||
.CodeMirror-hints {
|
||||
z-index: 999 !important;
|
||||
}
|
||||
</style>
|
||||
@@ -1,13 +0,0 @@
|
||||
<svg width="300" height="184" viewBox="0 0 300 184" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<rect width="300" height="183.736" fill="white"/>
|
||||
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||||
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<path d="M106.093 125.98C103.706 127.654 101.182 128.492 98.5201 128.492C95.4083 128.492 93.3338 127.386 92.2965 125.174C91.6967 123.924 91.3467 122.343 91.2468 120.431C91.2093 119.556 91.1905 118.594 91.1905 117.544C91.1905 116.482 91.1968 115.413 91.2093 114.339C91.2343 113.264 91.3155 112.27 91.453 111.358C91.5904 110.446 91.8029 109.627 92.0903 108.902C92.3903 108.165 92.8152 107.54 93.365 107.028C94.5023 105.966 96.2519 105.434 98.6138 105.434C100.988 105.434 103.513 106.072 106.187 107.347L106.487 105.809H109.186L109.205 136.646H106.093V125.98ZM106.093 109.933C103.844 108.809 101.669 108.246 99.5699 108.246C98.0452 108.246 97.0392 108.371 96.5518 108.621C96.0644 108.871 95.6895 109.196 95.4271 109.596C95.1771 109.996 94.9709 110.546 94.8085 111.246C94.521 112.558 94.3773 114.72 94.3773 117.732V118.144C94.3773 120.918 94.721 122.862 95.4083 123.974C96.0957 125.111 97.3516 125.68 99.1762 125.68H99.4574C101.182 125.68 102.944 125.205 104.744 124.255C105.256 123.993 105.706 123.724 106.093 123.449V109.933Z" fill="#2A3F5F"/>
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<path d="M118.072 96.249L121.165 95.9866V128.117H118.109L118.072 96.249Z" fill="#2A3F5F"/>
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<path d="M132.45 100.467C131.613 100.467 131.075 100.348 130.838 100.111C130.463 99.7232 130.275 99.1921 130.275 98.5173C130.275 97.8299 130.313 97.3425 130.388 97.0551C130.475 96.7552 130.6 96.524 130.763 96.3615C131.063 96.0616 131.519 95.9116 132.131 95.9116C132.756 95.9116 133.2 95.9429 133.462 96.0053C133.737 96.0678 133.962 96.1866 134.137 96.3615C134.437 96.6614 134.587 97.1551 134.587 97.8424C134.587 98.5173 134.549 99.0047 134.474 99.3046C134.412 99.592 134.299 99.8232 134.137 99.9982C133.825 100.311 133.262 100.467 132.45 100.467ZM130.931 105.809H134.006V128.117H130.969L130.931 105.809Z" fill="#2A3F5F"/>
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||||
<path d="M154.026 127.048C151.989 128.011 150.108 128.492 148.384 128.492C145.259 128.492 143.485 127.154 143.06 124.48C142.96 123.843 142.91 122.918 142.91 121.706V108.415H140.211V106.109L142.91 105.809L143.397 100.711H146.003V105.809H152.508V108.415H146.003V121.649C146.003 123.187 146.115 124.168 146.34 124.593C146.753 125.367 147.578 125.755 148.815 125.755C150.052 125.755 151.433 125.374 152.958 124.611L154.026 127.048Z" fill="#2A3F5F"/>
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<path d="M209.232 100.467C208.395 100.467 207.858 100.348 207.62 100.111C207.245 99.7232 207.058 99.1921 207.058 98.5173C207.058 97.8299 207.095 97.3425 207.17 97.0551C207.258 96.7552 207.383 96.524 207.545 96.3615C207.845 96.0616 208.301 95.9116 208.914 95.9116C209.538 95.9116 209.982 95.9429 210.245 96.0053C210.52 96.0678 210.744 96.1866 210.919 96.3615C211.219 96.6614 211.369 97.1551 211.369 97.8424C211.369 98.5173 211.332 99.0047 211.257 99.3046C211.194 99.592 211.082 99.8232 210.919 99.9982C210.607 100.311 210.045 100.467 209.232 100.467ZM207.714 105.809H210.788V128.117H207.751L207.714 105.809Z" fill="#2A3F5F"/>
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</svg>
|
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|
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|
Before Width: | Height: | Size: 83 KiB |
@@ -1,3 +0,0 @@
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<svg width="20" height="20" viewBox="0 0 20 20" fill="none" xmlns="http://www.w3.org/2000/svg">
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|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 550 B |
@@ -1,3 +0,0 @@
|
||||
<svg width="20" height="20" viewBox="0 0 20 20" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<path d="M4.51581 7.54801C4.95181 7.10201 5.55881 7.06701 6.09181 7.54801L9.99981 11.295L13.9078 7.54801C14.4408 7.06701 15.0488 7.10201 15.4818 7.54801C15.9178 7.99301 15.8898 8.74501 15.4818 9.16301C15.0758 9.58101 10.7868 13.665 10.7868 13.665C10.5698 13.888 10.2848 14 9.99981 14C9.71481 14 9.42981 13.888 9.21081 13.665C9.21081 13.665 4.92381 9.58101 4.51581 9.16301C4.10781 8.74501 4.07981 7.99301 4.51581 7.54801V7.54801Z" fill="#C8D4E3"/>
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||||
</svg>
|
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|
Before Width: | Height: | Size: 550 B |