Update How-to-get-result-set-suitable-for-graph-visualisation.md

.browserslistrc

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-> 1%
-last 2 versions
-not dead

.editorconfig

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-[*.{js,jsx,ts,tsx,vue}]
-indent_style = space
-indent_size = 2
-trim_trailing_whitespace = true
-insert_final_newline = true

.eslintrc.cjs

@@ -1,29 +0,0 @@
-module.exports = {
-  root: true,
-  env: {
-    node: true,
-    es2022: true
-  },
-  extends: ['eslint:recommended', 'plugin:vue/vue3-recommended', 'prettier'],
-  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 }],
-    'vue/multi-word-component-names': 'off',
-    'vue/no-mutating-props': 'warn',
-    'vue/no-reserved-component-names': 'warn',
-    'vue/no-v-model-argument': 'off',
-    'vue/require-default-prop': 'off',
-    'vue/custom-event-name-casing': ['error', 'camelCase'],
-    'vue/attribute-hyphenation': ['error', 'never']
-  },
-  overrides: [
-    {
-      files: ['**/__tests__/*.{j,t}s?(x)', '**/tests/**/*.spec.{j,t}s?(x)'],
-      env: {
-        mocha: true
-      }
-    }
-  ]
-}

.github/workflows/config.grenrc.cjs

@@ -1,14 +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']
-  }
-}

.github/workflows/main.yml

@@ -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: 18.x
-
-      - name: Update npm
-        run: npm install -g npm@10
-
-      - name: npm install and build
-        run: |
-          npm install
-          npm run build
-
-      - name: Create archives
-        run: |
-          cd dist
-          zip -9 -r ../dist.zip . -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.cjs"
-        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'

.github/workflows/test.yml

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-name: Run tests
-on:
-  workflow_dispatch:
-  push:
-    branches:
-      - 'master'
-  pull_request:
-    branches:
-      - 'master'
-
-jobs:
-  test:
-    name: Run tests
-    runs-on: ubuntu-24.04
-    steps:
-      - uses: actions/checkout@v2
-      - name: Use Node.js
-        uses: actions/setup-node@v1
-        with:
-          node-version: 18.x
-      - name: Install browsers
-        run: |
-          export DEBIAN_FRONTEND=noninteractive
-          sudo add-apt-repository -y ppa:mozillateam/ppa
-          sudo apt-get update
-          sudo apt-get install -y chromium-browser firefox-esr
-
-      - name: Update npm
-        run: npm install -g npm@10
-
-      - name: Install the project
-        run: npm install
-
-      - name: Run lint
-        run: npm run lint -- --no-fix
-
-      - name: Run karma tests
-        run: npm run test

.gitignore

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-.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?

.prettierrc

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-{
-  "trailingComma": "none",
-  "tabWidth": 2,
-  "semi": false,
-  "singleQuote": true,
-  "arrowParens": "avoid"
-}

Basic-usage.md

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+# 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`.
+
+![Fig. 1: Welcome page](./img/Screenshot_welcome.png)
+
+
+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).
+
+![Fig. 2: CSV import dialog](./img/Screenshot_csv.png)
+
+
+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).
+
+![Fig. 3: Workspace (empty database)](./img/Screenshot_editor.png)
+
+
+Database tables, columns and their types are shown in the left panel of the
+`Workspace` (fig. 4).
+
+![Fig. 4: Workspace (not empty database)](./img/Screenshot_editor_with_db.png)
+
+
+## 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.
+
+* ![](./img/sql.svg) – 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.
+* ![](./img/table.svg) – Switch the panel to the result set. Here you
+  can see the result of the query execution.
+* ![](./img/visualisation.svg) – 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 ![](./img/run.svg) 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.
+
+* ![](./img/chart.svg) – Switch to a chart type visualisation.
+* ![](./img/pivot.svg) – Switch to a pivot type visualisation.
+* ![](./img/graph.svg) – 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`.
+
+![Fig. 5: Visualisation with a chart](./img/Screenshot_chart.png)
+
+You can save any visualisation as an image by clicking ![](./img/camera.svg).
+
+## 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

Diagnostic-information.md

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+# 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 ![](./img/info.svg) icon in the top
+toolbar.
+
+![Fig. 1: App info dialog](./img/Screenshot_app_info.png)
+
+[1]: https://sqlite.org/compile.html

Dockerfile.test

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-# An easy way to run tests locally without Nodejs installed:
-#
-#     docker build -t sqliteviz/test -f Dockerfile.test .
-#
-
-FROM node:12.22-bullseye
-
-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

Export-current-database.md

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+# 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 ![](./img/file-export.svg) next to the database name on `Workspace`
+page.

Graph.md

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+# Graph
+
+Sqliteviz allows building a graph. To build a graph, run a query to get data. 
+Then open the visualisation panel by clicking ![](./img/visualisation.svg)
+in any of the two side toolbars and choose a graph mode by clicking ![](./img/graph.svg).
+
+## Requirements for result set
+
+To build a graph, a result set must follow the following requirements:
+
+- the first column must contain JSONs (the rest columns in the result set will be ignored)
+- each JSON has a common key indicating if the record represents a node (value 0) or an edge (value 1)
+- each JSON representing a node has a common key with a node id
+- each JSON representing an edge has a common key with the edge source and a common key with the edge target
+
+That is the minimum required for a graph, but each JSON can have more fields used in graph styling 
+(read [Graph styling](#graph-styling)).
+
+See also an example in [How to get result set suitable for graph visualisation][1].
+
+## Graph structure
+
+Start building a graph by setting a mapping from your records to nodes and edge properties.
+Go to `Structure` > `Graph` and set the following fields:
+
+- Object type – a field containing 0 for node records and 1 for edge records.
+- Node Id – a field containing the node identifier
+- Edge source - a field keeping a node identifier where the edge starts.
+- Edge target - a field keeping a node identifier where the edge ends.
+
+This is already enough to build a graph with default styling and circular layout.
+
+![Fig. 1: Graph structure settings](./img/Screenshot_graph_structure.png)
+
+## Graph styling
+
+### General
+
+Set a background color of the graph in `Style` > `General` panel.
+
+### Nodes
+
+There are the following settings in `Style` > `Nodes` panel:
+
+- Label - a field containing a node label. Note that if the graph has too many nodes or the node size
+  is too small, some labels can be visible only at a certain zoom level.
+- Label Color - a color of node labels
+- Size - set a node size. There are 3 modes of node sizing: constant, variable and calculated.
+
+  `Constant` means that all nodes have the same size.
+  
+  `Variable` allows you to choose a field where the node size will be taken.
+  
+  `Calculated` allows to choose a method that will be used to calculate the node size.
+  Currently, 3 methods are available: total node degree, degree by in-edges and degree by out-edges.
+
+  For variable and calculated sizing it's also possible to set scale, the minimum size and the sizing mode - area or diameter.
+  In the diameter mode the difference between node sizes will be more noticeable.
+  
+- Color - set a node color. There are 3 modes of node color: constant, variable and calculated.
+
+  `Constant` means that all nodes have the same color.
+  
+  `Variable` allows you to choose a field by which the color will be determined.
+  With this option you can also choose if the color value should be taken directly or mapped to a color palette.
+  `Direct` mode means that in JSON representing a node, the value available by the selected field will be used as a color.
+  The color value in the JSON can be set in different ways:
+
+  **As Hex, 8-digit (RGBA) Hex**
+  ```
+  "#000"
+  "000"
+  "#369C"
+  "369C"
+  "#f0f0f6"
+  "f0f0f6"
+  "#f0f0f688"
+  "f0f0f688"
+  ```
+  **RGB, RGBA**
+  ```
+  "rgb (255, 0, 0)"
+  "rgb 255 0 0"
+  "rgba (255, 0, 0, .5)"
+  { "r": 255, "g": 0, "b": 0 }
+  ```
+
+  **HSL, HSLA**
+  ```
+  "hsl(0, 100%, 50%)"
+  "hsla(0, 100%, 50%, .5)"
+  "hsl(0, 100%, 50%)"
+  "hsl 0 1.0 0.5"
+  { "h": 0, "s": 1, "l": .5 }
+  ```
+
+  **HSV, HSVA**
+  ```
+  "hsv(0, 100%, 100%)"
+  "hsva(0, 100%, 100%, .5)"
+  "hsv (0 100% 100%)"
+  "hsv 0 1 1"
+  { "h": 0, "s": 100, "v": 100 }
+  ```
+
+  **Named colors**
+  
+  Case insenstive names are accepted, using the list of [colors in the CSS spec][3].
+  ```
+  "RED"
+  "blanchedalmond"
+  "darkblue"
+  ```
+
+  When `Map to` option is selected, the value by the selected field can be anything because it won't be used directly as a color.
+  In this case each distinct value will be mapped to a certain color, so nodes with the same value will have the same color.
+  Click on a color palette to open a palette selector.
+  
+  `Calculated` color mode allows to choose a method that will be used to determine a color.
+  Currently, 3 methods are available: total node degree, degree by in-edges and degree by out-edges. You can also choose a color palette
+  that will be used in a mapping of calculated values into an actual color.
+
+- Color As - defines how color mapping should work - continuously or categorically.
+  
+    Continuous mode is more suitable when the mapped values have a meaningful order. It looks more informative with sequential palettes.
+    In that case the lowest value corresponds to the first color in the palette and the highest value - to the last color.
+    The color of each intermediate value reflects the position of that value in the range.
+
+    Categorical mode just uses the next color in the palette for each new distinct value.
+
+- Colorscale Direction - use a selected palette as is or reverse it.  
+
+### Edges
+
+There are the following settings in `Style` > `Edges` panel:
+
+- Direction - show an edges with or without arrows
+- Label - a field containing an edge label. Note that if the graph has too many edges,
+  some labels can be visible only at a certain zoom level.
+- Label Color - a color of edge labels
+- Size - set an edge thickness. There are 2 modes of edge sizing: constant and variable.
+
+  `Constant` means that all edges have the same thickness.
+  
+  `Variable` allows you to choose a field where the edge size will be taken.
+
+  For variable sizing it's also possible to set scale and the minimum size.
+  
+- Color - set an edge color. There are 2 modes of edge color: constant and variable. They work similar to node color modes.
+
+- Color As - defines how color mapping should work - continuously or categorically, similar to the same node color setting.
+
+- Colorscale Direction - use a selected palette as is or reverse it.  
+
+### Layout
+
+#### Circular
+In this layout all nodes are just placed along a circle.
+
+#### Random
+This layout places nodes randomly for each seed value. The seed value allows you to restore the random layout you liked
+when you open the inquiry and run the query next time.
+
+![Fig. 2: Random layout](./img/Screenshot_graph_random.png)
+
+#### Circle pack
+Arranges nodes as a bubble chart according to specified attributes. You can choose multiple hierarchy attributes used to group nodes.
+
+![Fig. 3: Circle pack layout](./img/Screenshot_graph_circle_pack.png)
+
+#### ForceAtlas2
+A continuous graph layout algorithm. Read more details about the algorithm and its settings in the [article][4].
+The algorithm works in iterations. When you choose ForceAtlas2 layout or run the query, it will automatically run 50 iterations of the algorithm.
+You can change the amount of steps run automatically in `Initial Iterations`. 
+You can also run and stop the algorithm manually by clicking `Start`/`Stop` button.
+
+![Fig. 3: ForceAtlas2 layout](./img/Screenshot_graph_force_atlas2.png)
+[How to build a pivot table in SQL(ite)][1] explores two options with static
+(or beforehand-known) and dynamic columns.
+
+[1]: ./How-to-get-result-set-suitable-for-graph-visualisation
+[2]: https://github.com/bgrins/TinyColor?tab=readme-ov-file#accepted-string-input
+[3]: https://www.w3.org/TR/css-color-4/#named-colors
+[4]: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098679
+

Home.md

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+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

How-to-build-a-pivot-table-in-SQLite.md

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+# 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

How-to-get-result-set-suitable-for-graph-visualisation.md

@@ -0,0 +1,112 @@
+# How to get result set suitable for graph visualisation
+
+There are some [requirements for result sets][1] if you want to build a graph.
+Here is an example of building a query that returns a result set appropriate for graph visualisation.
+
+Let's say, you have 2 tables:
+
+house:
+| name       | points |
+| ---------- | ------ |
+| Gryffindor | 100    |
+| Hufflepuff | 90     |
+| Ravenclaw  | 95     |
+| Slytherin  | 80     |
+
+student:
+| id | name           | house      |
+| -- | -------------- | ---------- |
+| 1  | Harry Potter   | Gryffindor |
+| 2  | Ron Weasley    | Gryffindor |
+| 3  | Draco Malfoy'  | Slytherin  |
+| 4  | Luna Lovegood  | Ravenclaw  |
+| 5  | Cedric Diggory | Hufflepuff |
+
+Each student belongs to a certain house. 
+Let's say you want to build a graph with houses and students as nodes, where each house is linked with its students.
+
+We are going to use [json_object][2] function to form JSONs. The result set should contain both nodes and edges 
+and we have to provide a field indicating if the record represents a node (0) or and edge (1).
+Let's provide it as 'object_type':
+
+```sql
+SELECT json_object('object_type', 0)
+FROM house
+UNION ALL
+SELECT json_object('object_type', 0)
+FROM student
+UNION ALL
+SELECT json_object('object_type', 1)
+FROM student
+```
+Note that we included `student` table twice. That is because the table contains not only students but also their relationship to houses. 
+So the records from the first union of `student` will be used as nodes and from the second one - as edges.
+
+Then we need to provide an ID for each node. Let's put it in `node_id` field. 
+The `node_id` value for students is taken from `id` column and for houses - from `name`: 
+
+```sql
+SELECT json_object('object_type', 0, 'node_id', name)
+FROM house
+UNION ALL
+SELECT json_object('object_type', 0, 'node_id', id)
+FROM student
+UNION ALL
+SELECT json_object('object_type', 1)
+FROM student
+```
+
+Each edge record must provide a node id where the edge starts and where it ends. Let's put it in `source` and `target`:
+
+```sql
+SELECT json_object('object_type', 0, 'node_id', name)
+FROM house
+UNION ALL
+SELECT json_object('object_type', 0, 'node_id', id)
+FROM student
+UNION ALL
+SELECT json_object('object_type', 1, 'source', house, 'target', id)
+FROM student
+```
+Basically, that is enough to build a graph. But it won't be meaningful without labels.
+Also, it would be nice to distinguish house nodes from student nodes by color.
+Let's put additional fields `label` and `type` that can be used in graph styling.
+
+```sql
+SELECT json_object('object_type', 0, 'node_id', name, 'label', name, 'type', 'house')
+FROM house
+UNION ALL
+SELECT json_object('object_type', 0, 'node_id', id, 'label', name, 'type', 'student')
+FROM student
+UNION ALL
+SELECT json_object('object_type', 1, 'source', house, 'target', id)
+FROM student
+```
+
+Run the query, the result set will look like this:
+
+| json_object('object_type', 0, 'node_id', name, 'label', name, 'type', 'house') |
+| ------------------------------------------------------------------------------ |
+| {"object_type":0,"node_id":"Gryffindor","label":"Gryffindor","type":"house"}   |
+| {"object_type":0,"node_id":"Hufflepuff","label":"Hufflepuff","type":"house"}   |
+| {"object_type":0,"node_id":"Ravenclaw","label":"Ravenclaw","type":"house"}     |
+| {"object_type":0,"node_id":"Slytherin","label":"Slytherin","type":"house"}     |
+| {"object_type":0,"node_id":1,"label":"Harry Potter","type":"student"}          |
+| {"object_type":0,"node_id":2,"label":"Ron Weasley","type":"student"}           |
+| {"object_type":0,"node_id":3,"label":"Draco Malfoy","type":"student"}          |
+| {"object_type":0,"node_id":4,"label":"Luna Lovegood","type":"student"}         |
+| {"object_type":0,"node_id":5,"label":"Cedric Diggory","type":"student"}        |
+| {"object_type":1,"node_source":"Gryffindor","target":1}                        |
+| {"object_type":1,"node_source":"Gryffindor","target":2}                        |
+| {"object_type":1,"node_source":"Slytherin","target":3}                         |
+| {"object_type":1,"node_source":"Ravenclaw","target":4}                         |
+| {"object_type":1,"node_source":"Hufflepuff","target":5}                        |
+
+Now in the graph editor, we can set mapping of the result set records into node and edge properties,
+set graph styles and get the following visualisation:
+
+![Fig. 1: Graph visualisation example](./img/Screenshot_potter_example.png)
+
+
+[1]: ./graph#requirements-for-result-set
+[2]: https://sqlite.org/json1.html#jobj

How-to-migrate-to-sqliteviz-dot-com.md

@@ -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

How-to-rename-tables-and-columns-after-CSV-import.md

@@ -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 ![](./img/run.svg) 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 ![](./img/run.svg) to run the script

Installation.md

@@ -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

Integrate-predefined-inquiries.md

@@ -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.

LICENSE

@@ -1,201 +0,0 @@
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Manage-inquiries.md

@@ -0,0 +1,39 @@
+# Manage inquiries
+
+## Organise
+
+You can find all inquiries that you saved in `Inquiries` (fig. 1).
+
+![Fig. 1: Inquiries](./img/Screenshot_my_inquiries.png)
+
+To manipulate one inquiry hover the cursor over the row with the inquiry and
+choose the action:
+
+* ![](./img/rename.svg) – rename an inquiry
+* ![](./img/copy.svg) – duplicate an inquiry
+* ![](./img/file-export.svg) – export an inquiry to JSON file
+* ![](./img/delete.svg) – 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).
+
+![Fig. 2: Inquiries: a group of inquiries is selected](./img/Screenshot_group.png)
+
+> **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

Multiple-CSV-file-import.md

@@ -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 ![](./img/add-csv.svg) icon in the schema panel on `Workspace`
+  page
+- Choose a file
+- Import it with `import` dialog.

Pivot-table.md

@@ -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 ![](./img/visualisation.svg)
+in any of the two side toolbars and choose a pivot mode by clicking ![](./img/pivot.svg).
+
+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.
+
+![Fig. 1: Table](./img/Screenshot_pivot_table.png)
+
+![Fig. 2: Heatmap](./img/Screenshot_pivot_heatmap.png)
+
+![Fig. 3: Horizontal Stacked Bar Chart](./img/Screenshot_pivot_barchart.png)
+
+There are several built-in chart views for a pivot. But you can build your own
+with `Custom chart` view (fig. 4).
+
+![Fig. 4: Custom Chart](./img/Screenshot_pivot_custom_chart.png)
+
+> **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 ![](./img/camera.svg).
+
+## 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
+

Predefined-inquiries.md

@@ -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).
+
+![Fig. 1: Predefined inquiry](./img/Screenshot_predefined.png)
+
+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

README.md

@@ -1,49 +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

Sharing.md

@@ -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

babel.config.js

@@ -1,3 +0,0 @@
-module.exports = {
-  presets: ['@vue/cli-plugin-babel/preset']
-}

img/add-csv.svg

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+<g clip-path="url(#clip0)">
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+</g>
+<defs>
+<clipPath id="clip0">
+<rect width="18" height="18" fill="white"/>
+</clipPath>
+</defs>
+</svg>

img/camera.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="M15.1875 6.22266H13.7812V7.62891H15.1875V6.22266Z" fill="#A2B1C6"/>
+</svg>

img/chart.svg

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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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+</svg>

img/graph.svg

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+<svg width="18" height="18" viewBox="0 0 18 18" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M5 4C5 5.10457 4.10457 6 3 6C1.89543 6 1 5.10457 1 4C1 2.89543 1.89543 2 3 2C4.10457 2 5 2.89543 5 4Z" fill="#A2B1C6"/>
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+</svg>

img/pivot.svg

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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="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"/>
+<path d="M6.41943 0H18.4194V4H6.41943V0Z" fill="#A2B1C6"/>
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+<path d="M0.419434 0H4.41943V4H0.419434V0Z" fill="#A2B1C6"/>
+</svg>

img/run.svg

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+<svg width="12" height="13" viewBox="0 0 12 13" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M11.1624 6.94358L0.770043 12.9436L0.770043 0.943573L11.1624 6.94358Z" fill="#A2B1C6"/>
+</svg>

img/sql.svg

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+<svg width="18" height="19" viewBox="0 0 18 19" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g clip-path="url(#clip0)">
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+<defs>
+<clipPath id="clip0">
+<rect width="18" height="18" fill="white" transform="translate(0 0.0134277)"/>
+</clipPath>
+</defs>
+</svg>

img/table.svg

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+<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"/>
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+<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>

img/visualisation.svg

@@ -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>

index.html

@@ -1,98 +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="favicon.png" />
-    <link rel="manifest" href="manifest.webmanifest" />
-    <title>sqliteviz</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% {
-          stroke-dasharray: 100px 402px;
-          stroke-dashoffset: 0;
-        }
-        50% {
-          stroke-dasharray: 251px;
-          stroke-dashoffset: -251px;
-        }
-        100% {
-          stroke-dasharray: 100px 402px;
-          stroke-dashoffset: -502px;
-        }
-      }
-    </style>
-    <!-- head extention slot start -->
-    <!-- head extention slot end -->
-  </head>
-  <body>
-    <noscript>
-      <strong>
-        We're sorry but this app 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 -->
-    <script type="module" src="/src/main.js"></script>
-  </body>
-</html>

index.md

@@ -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
+

jsconfig.json

@@ -1,10 +0,0 @@
-{
-  "include": ["src/**/*", "tests/**/*"],
-  "exclude": ["node_modules", "dist"],
-  "compilerOptions": {
-    "baseUrl": "./",
-    "paths": {
-      "@*": ["./src/*"]
-    }
-  }
-}

karma.conf.cjs

@@ -1,122 +0,0 @@
-module.exports = function (config) {
-  config.set({
-    vite: {
-      config: {
-        resolve: {
-          alias: {
-            vue: 'vue/dist/vue.esm-bundler.js'
-          }
-        },
-        server: {
-          preTransformRequests: false
-        }
-      },
-      coverage: {
-        enable: true,
-        include: 'src/*',
-        exclude: ['node_modules', 'src/components/svg/*'],
-        extension: ['.js', '.vue'],
-        requireEnv: false
-      }
-    },
-    // 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', 'vite'],
-
-    // list of files / patterns to load in the browser
-    files: [
-      {
-        pattern: 'test.setup.js',
-        type: 'module',
-        watched: false,
-        served: false
-      },
-      {
-        pattern: 'tests/**/*.spec.js',
-        type: 'module',
-        watched: false,
-        served: false
-      },
-      {
-        pattern: 'src/assets/styles/*.css',
-        type: 'css',
-        watched: false,
-        served: false
-      }
-    ],
-
-    plugins: [
-      'karma-vite',
-      'karma-mocha',
-      'karma-sinon-chai',
-      'karma-firefox-launcher',
-      'karma-chrome-launcher',
-      'karma-spec-reporter',
-      'karma-coverage'
-    ],
-
-    // list of files / patterns to exclude
-    exclude: [],
-
-    // 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' }]
-    },
-
-    // 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: ''
-    }
-  })
-  // Fix the timezone
-  process.env.TZ = 'Europe/Amsterdam'
-}

lib/sql-js/.dockerignore

@@ -1,2 +0,0 @@
-benchmark
-dist

lib/sql-js/Dockerfile

@@ -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

lib/sql-js/README.md

@@ -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

lib/sql-js/benchmark/.gitignore

@@ -1,4 +0,0 @@
-/lib/build-*
-/lib/dist
-/build-*-result.json
-/sample.csv

lib/sql-js/benchmark/Dockerfile

@@ -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

lib/sql-js/benchmark/README.md

@@ -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/

lib/sql-js/benchmark/karma.conf.js

@@ -1,57 +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' }
-  })
-}

lib/sql-js/benchmark/lib/package.json

@@ -1,5 +0,0 @@
-{
-  "name": "sql.js",
-  "main": "./dist/sql-wasm.js",
-  "private": true
-}

lib/sql-js/benchmark/make.sh

@@ -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

lib/sql-js/benchmark/package.json

@@ -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"
-  }
-}

lib/sql-js/benchmark/procpath/karma_docker.procpath

@@ -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

lib/sql-js/benchmark/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)

lib/sql-js/benchmark/procpath/top2_rss.sql

@@ -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)

lib/sql-js/benchmark/result-analysis.ipynb

@@ -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
-}

lib/sql-js/benchmark/suite.js

@@ -1,137 +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
-}

lib/sql-js/build.py

@@ -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)

lib/sql-js/configure.py

@@ -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/2025/sqlite-amalgamation-3500300.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/e212edb2?at=series.c', 'sqlite3_series_init'),
-    ('https://sqlite.org/src/raw/5559daf1?at=closure.c', 'sqlite3_closure_init'),
-    ('https://sqlite.org/src/raw/5bb2264c?at=uuid.c', 'sqlite3_uuid_init'),
-    ('https://sqlite.org/src/raw/388e7f23?at=regexp.c', 'sqlite3_regexp_init'),
-    ('https://sqlite.org/src/raw/72e05a21?at=percentile.c', 'sqlite3_percentile_init'),
-    ('https://sqlite.org/src/raw/228d47e9?at=decimal.c', 'sqlite3_decimal_init'),
-    # Third-party extension
-    # =====================
-    ('https://github.com/jakethaw/pivot_vtab/raw/e7705f34/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)

lib/sql-js/make.sh

@@ -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

lib/sql-js/package.json

@@ -1,5 +0,0 @@
-{
-  "name": "sql.js",
-  "main": "./dist/sql-wasm.js",
-  "private": true
-}

package.json

@@ -1,79 +0,0 @@
-{
-  "name": "sqliteviz",
-  "version": "0.27.1",
-  "license": "Apache-2.0",
-  "private": true,
-  "type": "module",
-  "scripts": {
-    "dev": "vite",
-    "build": "vite build",
-    "serve": "vite preview",
-    "test": "karma start karma.conf.cjs",
-    "lint": "eslint --ext .js,.vue --ignore-path .gitignore --fix src",
-    "format": "prettier .  --write"
-  },
-  "dependencies": {
-    "buffer": "^6.0.3",
-    "codemirror": "^5.65.18",
-    "codemirror-editor-vue3": "^2.8.0",
-    "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": "^2.35.2",
-    "promise-worker": "^2.0.1",
-    "react": "^16.14.0",
-    "react-chart-editor": "^0.46.1",
-    "react-dom": "^16.14.0",
-    "sql.js": "file:./lib/sql-js",
-    "tiny-emitter": "^2.1.0",
-    "veaury": "^2.5.1",
-    "vue": "^3.5.11",
-    "vue-final-modal": "^4.5.5",
-    "vue-multiselect": "^3.0.0-beta.3",
-    "vue-router": "^4.4.5",
-    "vuejs-paginate-next": "^1.0.2",
-    "vuex": "^4.1.0"
-  },
-  "devDependencies": {
-    "@babel/core": "^7.25.7",
-    "@vitejs/plugin-vue": "^5.2.1",
-    "@vue/eslint-config-standard": "^8.0.1",
-    "@vue/test-utils": "^2.4.6",
-    "chai": "^4.1.2",
-    "chai-as-promised": "^8.0.1",
-    "eslint": "^8.57.1",
-    "eslint-config-prettier": "^10.1.1",
-    "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": "^9.28.0",
-    "flush-promises": "^1.0.2",
-    "karma": "^6.4.4",
-    "karma-coverage": "^2.2.1",
-    "karma-coverage-istanbul-reporter": "^3.0.3",
-    "karma-firefox-launcher": "^2.1.3",
-    "karma-mocha": "^1.3.0",
-    "karma-spec-reporter": "^0.0.36",
-    "karma-vite": "^1.0.5",
-    "mocha": "^5.2.0",
-    "prettier": "3.5.3",
-    "process": "^0.11.10",
-    "url-loader": "^4.1.1",
-    "vite": "^5.4.14",
-    "vite-plugin-istanbul": "^5.0.0",
-    "vite-plugin-node-polyfills": "^0.23.0",
-    "vite-plugin-pwa": "^0.21.1",
-    "vite-plugin-static-copy": "^2.2.0",
-    "vue-cli-plugin-ui-karma": "^0.2.5"
-  },
-  "overrides": {
-    "karma-vite": {
-      "vite-plugin-istanbul": "$vite-plugin-istanbul"
-    }
-  }
-}

public/inquiries.json

@@ -1 +0,0 @@
-[]

public/manifest.webmanifest

@@ -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"
-}

sidebar.json

@@ -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/"
+			]
+		}
+	]
+}]

src/App.vue

@@ -1,95 +0,0 @@
-<template>
-  <div id="app">
-    <router-view />
-  </div>
-</template>
-
-<script>
-import storedInquiries from '@/lib/storedInquiries'
-
-export default {
-  computed: {
-    inquiries() {
-      return this.$store.state.inquiries
-    }
-  },
-  watch: {
-    inquiries: {
-      deep: true,
-      handler() {
-        storedInquiries.updateStorage(this.inquiries)
-      }
-    }
-  },
-  created() {
-    this.$store.commit('setInquiries', storedInquiries.getStoredInquiries())
-    addEventListener('storage', event => {
-      if (event.key === storedInquiries.myInquiriesKey) {
-        this.$store.commit('setInquiries', storedInquiries.getStoredInquiries())
-      }
-    })
-  }
-}
-</script>
-
-<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,
-.dialog,
-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>