Sort Dataset Items

root = true

[*]
indent_style = space
indent_size = 4
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
end_of_line = lf

{
    "extends": "@apify"
}

# This file tells Git which files shouldn't be added to source control

.idea
node_modules

# First, specify the base Docker image. You can read more about
# the available images at https://sdk.apify.com/docs/guides/docker-images
# You can also use any other image from Docker Hub.
FROM apify/actor-node:16

# Second, copy just package.json and package-lock.json since it should be
# the only file that affects "npm install" in the next step, to speed up the build
COPY package*.json ./

# Install NPM packages, skip optional and development dependencies to
# keep the image small. Avoid logging too much and print the dependency
# tree for debugging
RUN npm --quiet set progress=false \
 && npm install --only=prod --no-optional \
 && echo "Installed NPM packages:" \
 && (npm list --only=prod --no-optional --all || true) \
 && echo "Node.js version:" \
 && node --version \
 && echo "NPM version:" \
 && npm --version

# Next, copy the remaining files and directories with the source code.
# Since we do this after NPM install, quick build will be really fast
# for most source file changes.
COPY . ./

# Optionally, specify how to launch the source code of your actor.
# By default, Apify's base Docker images define the CMD instruction
# that runs the Node.js source code using the command specified
# in the "scripts.start" section of the package.json file.
# In short, the instruction looks something like this:
#
# CMD npm start

{
    "title": "Input schema for the apify_project actor.",
    "type": "object",
    "schemaVersion": 1,
    "properties": {
        "datasetId": {
            "title": "Dataset Id",
            "type": "string",
            "description": "Dataset Id of dataset to sort. You don't need to provide this if you use a webhook.",
            "editor": "textfield"
        }
    },
    "required": []
}

{
    "env": { "npm_config_loglevel": "silent" }
}

1const Apify = require('apify');
2
3const transformFunction = (items) => {
4    items.sort((a, b) => {
5        return a.index - b.index;
6    })
7    return items;
8}
9
10Apify.main(async () => {
11    // Get input of the actor (here only for demonstration purposes).
12    const input = await Apify.getInput();
13    console.log('Input:');
14    console.dir(input);
15
16    let {
17        // either called from webhook or directly
18        resource,
19        datasetId
20    } = input;
21
22    if (resource) {
23        datasetId = resource.defaultDatasetId;
24    }
25
26    const actorInput = {
27        datasetIds: [datasetId],
28        preDedupTransformFunction: transformFunction,
29    };
30
31    await Apify.metamorph(
32        'lukaskrivka/dedup-datasets',
33        actorInput,
34    )
35});

{
    "name": "project-empty",
    "version": "0.0.1",
    "description": "This is a boilerplate of an Apify actor.",
    "dependencies": {
        "apify": "^2.0.7"
    },
    "devDependencies": {
        "@apify/eslint-config": "^0.1.3",
        "eslint": "^7.0.0"
    },
    "scripts": {
        "start": "node main.js",
        "lint": "./node_modules/.bin/eslint ./src --ext .js,.jsx",
        "lint:fix": "./node_modules/.bin/eslint ./src --ext .js,.jsx --fix",
        "test": "echo \"Error: oops, the actor has no tests yet, sad!\" && exit 1"
    },
    "author": "It's not you it's me",
    "license": "ISC"
}