# Dockerfile contains instructions how to build a Docker image that
# will contain all the code and configuration needed to run your actor.
# For a full Dockerfile reference,
# see https://docs.docker.com/engine/reference/builder/

# First, specify the base Docker image. Apify provides the following
# base images for your convenience:
# apify/actor-node-basic (Node.js 10 on Alpine Linux, small and fast)
# apify/actor-node-chrome (Node.js 10 + Chrome on Debian)
# apify/actor-node-chrome-xvfb (Node.js 10 + Chrome + Xvfb on Debian)
# For more information, see https://apify.com/docs/actor#base-images
# Note that you can use any other image from Docker Hub.
FROM apify/actor-node-chrome

# Second, copy just package.json since it should be the only file
# that affects NPM install in the next step
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 \
 &amp;&amp; npm install --only=prod --no-optional \
 &amp;&amp; echo "Installed NPM packages:" \
 &amp;&amp; npm list \
 &amp;&amp; echo "Node.js version:" \
 &amp;&amp; node --version \
 &amp;&amp; echo "NPM version:" \
 &amp;&amp; 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 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

Dockerfile

{
 "title": "Article text extractor input",
 "description": "",
 "type": "object",
 "schemaVersion": 1,
 "properties": {
 "url": {
 "title": "Article URL",
 "type": "string",
 "description": "Fill the article URL, from which you want to extract data.",
 "prefill": "https://www.bbc.com/news/world-asia-china-48659073",
 "editor": "textfield"
 }
 },
 "required": ["url"]
}

INPUT_SCHEMA.json

Simply extracts article text and other meta info from given url. 
Uses https://github.com/ageitgey/node-unfluff which is a NodeJS implementation of https://github.com/grangier/python-goose.
Check out also [lukaskrivka/article-extractor-smart](https://apify.com/lukaskrivka/article-extractor-smart).

Output get's saved into a default key-value store under the `OUTPUT` key. HTML of the given page is stored under the `page.html` key.

Example output:

```json
{
 "title": "Sánchez no logra extender su poder territorial pese al triunfo del 26-M",
 "softTitle": "Sánchez no logra extender su poder territorial pese al triunfo del 26-M",
 "date": "16/06/2019 22:03",
 "author": [
 "Madrid"
 ],
 "publisher": "La Vanguardia",
 "copyright": "La Vanguardia Ediciones Todos los derechos reservados",
 "favicon": "https://www.lavanguardia.com/rsc/images/ico/favicon.ico",
 "description": "El PSOE ganó el pasado 26 de mayo las elecciones municipales y autonómicas de manera 'clara y rotunda', según celebró el propio Pedro Sánchez aquella misma noche. Aunque la victoria socialista se tiñó...",
 "lang": "es",
 "canonicalLink": "https://www.lavanguardia.com/politica/20190617/462906149711/psoe-pedro-sanchez-elecciones-26m-alcaldias-gobiernos-espana.html",
 "tags": [],
 "image": "https://www.lavanguardia.com/r/GODO/LV/p6/WebSite/2019/06/17/Recortada/20190614-636961455890161857_20190614215051428-kvhE-U462903686315FDE-992x558@LaVanguardia-Web.jpg",
 "videos": [],
 "links": [],
 "text": "..."
}
```

README.md

main.js

{
 "name": "my-actor",
 "version": "0.0.1",
 "dependencies": {
 "apify": "^0.14.15",
 "request-promise": "latest",
 "unfluff": "latest"
 },
 "scripts": {
 "start": "node main.js"
 },
 "author": "Me!"
}

package.json

# Dockerfile contains instructions how to build a Docker image that
# will contain all the code and configuration needed to run your actor.
# For a full Dockerfile reference,
# see https://docs.docker.com/engine/reference/builder/

# First, specify the base Docker image. Apify provides the following
# base images for your convenience:
#  apify/actor-node-basic (Node.js 10 on Alpine Linux, small and fast)
#  apify/actor-node-chrome (Node.js 10 + Chrome on Debian)
#  apify/actor-node-chrome-xvfb (Node.js 10 + Chrome + Xvfb on Debian)
# For more information, see https://apify.com/docs/actor#base-images
# Note that you can use any other image from Docker Hub.
FROM apify/actor-node-chrome

# Second, copy just package.json since it should be the only file
# that affects NPM install in the next step
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 \
 && 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 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


Fill the article URL, from which you want to extract data.

Article URL

Article text extractor input

Simply extracts article text and other meta info from given url. 
Uses https://github.com/ageitgey/node-unfluff which is a NodeJS implementation of https://github.com/grangier/python-goose.
Check out also [lukaskrivka/article-extractor-smart](https://apify.com/lukaskrivka/article-extractor-smart).

Output get's saved into a default key-value store under the `OUTPUT` key. HTML of the given page is stored under the `page.html` key.

Example output:

```json
{
  "title": "Sánchez no logra extender su poder territorial pese al triunfo del 26-M",
  "softTitle": "Sánchez no logra extender su poder territorial pese al triunfo del 26-M",
  "date": "16/06/2019 22:03",
  "author": [
    "Madrid"
  ],
  "publisher": "La Vanguardia",
  "copyright": "La Vanguardia Ediciones Todos los derechos reservados",
  "favicon": "https://www.lavanguardia.com/rsc/images/ico/favicon.ico",
  "description": "El PSOE ganó el pasado 26 de mayo las elecciones municipales y autonómicas de manera 'clara y rotunda', según celebró el propio Pedro Sánchez aquella misma noche. Aunque la victoria socialista se tiñó...",
  "lang": "es",
  "canonicalLink": "https://www.lavanguardia.com/politica/20190617/462906149711/psoe-pedro-sanchez-elecciones-26m-alcaldias-gobiernos-espana.html",
  "tags": [],
  "image": "https://www.lavanguardia.com/r/GODO/LV/p6/WebSite/2019/06/17/Recortada/20190614-636961455890161857_20190614215051428-kvhE-U462903686315FDE-992x558@LaVanguardia-Web.jpg",
  "videos": [],
  "links": [],
  "text": "..."
}
```

my-actor

Simply extracts article texts and other meta info from the given URL. Uses https://github.com/ageitgey/node-unfluff which is a NodeJS implementation of https://github.com/grangier/python-goose.

Article Text Extractor

Where next?