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create-docker-container
Add a Docker container to a Datagrok package with Dockerfile and config
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Add a Docker container to a Datagrok package with Dockerfile and config
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Use whenever you need the Datagrok browser to actually execute JavaScript — adding viewers, filtering, modifying the view, or returning a result widget to the chat. Open this skill before calling the datagrok_exec tool.
Filter rows of a Datagrok DataFrame inside a datagrok-exec block through the Filters panel — by range, equals/contains/in-set, multi-value, boolean, free-text row expressions, or substructure (SMILES / SMARTS / molblock). Also covers clearing, inverting, the show-only-filtered vs destructive-drop split, and the filter event lifecycle (onRowsFiltering / onFilterChanged / onRowsFiltered). Use whenever the user says "filter", "show only", "hide rows where", "narrow to subset", "find rows that", "contains", "substructure search", "categorical filter", "range filter", "invert", "clear the filter", "clear filters", "drop rows", or asks for the filtered subset as a new table. Does NOT cover selection (separate skill) or generic DataFrame cloning (datagrok-df-and-columns).
Add a calculated, formula-based column to a dataframe inside a datagrok-exec block. Use whenever the user asks to compute, derive, add, or create a new column from existing columns — LipE, ratios, log/round, heavy atom count, any expression in the Datagrok formula DSL. Replaces hand-written addNewFloat/addNewInt + for-loop with a single formula-attached column that recomputes when source columns change.
Find, describe, add, remove, rename, clone, or set metadata on columns of a Datagrok DataFrame inside a datagrok-exec block. Use whenever the user asks to locate "the X column", summarize a column, add a typed/empty/values-filled/virtual column, set semantic type / units / format / friendly name, apply linear or categorical or conditional color coding, drop or rename columns, or copy a DataFrame. Covers everything in DataFrame.columns and Column.meta — but not row filtering/selection (datagrok-filtering, datagrok-selection) and not formula-only columns (datagrok-calc-column).
Sort, hide, show, reorder, resize, pin, format, and color-code columns in a Datagrok TableView grid from a datagrok-exec block. Use whenever the user asks to sort by a column (any direction), multi-sort, hide / show / reorder / pin / resize columns, freeze the first N columns, change number-format display, color-code cells (defaults and grid-only tint here; full per-type reference in datagrok-df-and-columns), set row height, or reset the grid back to defaults. Distinct from datagrok-df-and-columns (which owns column-level data metadata like semType, units, friendlyName, and is also where canonical color-coding lives) and from datagrok-viewers (which owns scatter plot / histogram / etc.). Does NOT cover filtering (`datagrok-filtering`), selection (`datagrok-selection`), custom cell renderer authoring (`create-cell-renderer`), saving / restoring layouts, or grid event handlers.
Add a viewer, configure a viewer, change viewer options, find viewer, close viewer, view a scatter plot, bar chart, histogram, line chart, box plot, pie chart, heat map, correlation plot, 3D scatter, trellis, density plot, statistics, on a Datagrok TableView inside a datagrok-exec block. Use whenever the user asks to plot, chart, visualize, show a graph, draw a distribution, color by a column, swap a viewer's axis, toggle a legend / regression line / log scale, replace one viewer with another, close every chart, reset the view to just the grid, or find an existing viewer by type. Plugin viewers like "Chem space", "sequence space", "activity cliffs" are NOT viewer types — they're registered functions — route those to `grok.functions.call`. Does NOT cover filtering (separate skill `datagrok-filtering`), selection (`datagrok-selection`), grid cell rendering (`datagrok-grid-customization`), layout save/restore, or custom-viewer authoring.
| name | create-docker-container |
| description | Add a Docker container to a Datagrok package with Dockerfile and config |
| when-to-use | When user asks to add a Docker container, create a Dockerfile, or add server-side processing |
| effort | medium |
Help the user add a Docker container to their Datagrok package so it can be built, deployed, and accessed via the platform.
/create-docker-container [package-name]
Follow these steps to create a Docker container for a Datagrok package:
Create a dockerfiles/ folder inside the package root and add a Dockerfile there.
EXPOSE $PORT (only one EXPOSE is allowed).Example structure:
packages/MyPackage/
dockerfiles/
Dockerfile
container.json (optional)
src/
package.json
Place container.json in the same directory as the Dockerfile. If omitted, defaults are used.
{
"cpu": 1.5,
"gpu": 1,
"memory": 2048,
"on_demand": true,
"shutdown_timeout": 60,
"storage": 25,
"env": {
"CONN": "#{x.Package:Entity}",
"LOGIN": "login"
}
}
Configuration properties and defaults:
| Property | Type | Default | Description |
|---|---|---|---|
| cpu | Double | 0.25 | CPU cores allocated |
| gpu | Integer | 0 | GPU devices reserved |
| memory | Integer | 512 | RAM in megabytes |
| on_demand | Boolean | false | Start container only on first request |
| shutdown_timeout | Integer | null | Idle minutes before auto-shutdown |
| storage | Integer | 21 | Disk storage in gigabytes |
| shm_size | Integer | 64 | Shared memory in megabytes |
| env | Object | Environment variables passed to the container |
For env values, use #{x.Package:Entity} to pass a JSON-serialized entity from a package namespace. Credentials are only passed for connections within the same package.
Get the container ID and use fetchProxy to call the container's HTTP server:
const containerId = (await grok.dapi.docker.dockerContainers.filter('my-container').first()).id;
const params = {
method: 'POST',
headers: {'Accept': 'application/json', 'Content-Type': 'application/json'},
body: JSON.stringify(payload),
};
const response: Response = await grok.dapi.docker.dockerContainers.fetchProxy(containerId, '/endpoint', params);
const result = await response.json();
The params object follows the standard RequestInit interface.
const ws: WebSocket = await grok.dapi.docker.dockerContainers.webSocketProxy(container.id, '/ws');
ws.send('Hello');
ws.addEventListener('message', (event: MessageEvent) => {
console.log(event.data);
});
setTimeout(() => ws.close(), 3000);
webpack
grok publish dev
A return code of 0 indicates successful deployment. After publishing, Datagrok queues the image for building automatically.
In Datagrok, go to Platform -> Dockers to view containers and images. Status indicators:
Right-click a card to start/stop containers or rebuild images. Check logs via the Property pane.
dockerfiles/ directory, Dockerfile, and optionally container.json.fetchProxy.webSocketProxy.EXPOSE port is allowed in the Dockerfile.grok-spawner must be running in the same environment.