style: do not use three dots in incomplete examples

Author: honzajavorek

sources/academy/webscraping/scraping_basics_javascript2/11_scraping_variants.md

@@ -72,8 +72,6 @@ These elements aren't visible to regular visitors. They're there just in case Ja
 Using our knowledge of Beautiful Soup, we can locate the options and extract the data we need:
 
 ```py
-...
-
 listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales"
 listing_soup = download(listing_url)
 
@@ -89,8 +87,6 @@ for product in listing_soup.select(".product-item"):
     else:
         item["variant_name"] = None
         data.append(item)
-
-...
 ```
 
 The CSS selector `.product-form__option.no-js` matches elements with both `product-form__option` and `no-js` classes. Then we're using the [descendant combinator](https://developer.mozilla.org/en-US/docs/Web/CSS/Descendant_combinator) to match all `option` elements somewhere inside the `.product-form__option.no-js` wrapper.

sources/academy/webscraping/scraping_basics_javascript2/12_framework.md

@@ -534,7 +534,6 @@ If you export the dataset as JSON, it should look something like this:
 To scrape IMDb data, you'll need to construct a `Request` object with the appropriate search URL for each movie title. The following code snippet gives you an idea of how to do this:
 
 ```py
-...
 from urllib.parse import quote_plus
 
 async def main():
@@ -550,7 +549,6 @@ async def main():
         await context.add_requests(requests)
 
     ...
-...
 ```
 
 When navigating to the first search result, you might find it helpful to know that `context.enqueue_links()` accepts a `limit` keyword argument, letting you specify the max number of HTTP requests to enqueue.

sources/academy/webscraping/scraping_basics_python/11_scraping_variants.md

@@ -71,8 +71,6 @@ These elements aren't visible to regular visitors. They're there just in case Ja
 Using our knowledge of Beautiful Soup, we can locate the options and extract the data we need:
 
 ```py
-...
-
 listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales"
 listing_soup = download(listing_url)
 
@@ -88,8 +86,6 @@ for product in listing_soup.select(".product-item"):
     else:
         item["variant_name"] = None
         data.append(item)
-
-...
 ```
 
 The CSS selector `.product-form__option.no-js` matches elements with both `product-form__option` and `no-js` classes. Then we're using the [descendant combinator](https://developer.mozilla.org/en-US/docs/Web/CSS/Descendant_combinator) to match all `option` elements somewhere inside the `.product-form__option.no-js` wrapper.

sources/academy/webscraping/scraping_basics_python/12_framework.md

@@ -533,7 +533,6 @@ If you export the dataset as JSON, it should look something like this:
 To scrape IMDb data, you'll need to construct a `Request` object with the appropriate search URL for each movie title. The following code snippet gives you an idea of how to do this:
 
 ```py
-...
 from urllib.parse import quote_plus
 
 async def main():
@@ -549,7 +548,6 @@ async def main():
         await context.add_requests(requests)
 
     ...
-...
 ```
 
 When navigating to the first search result, you might find it helpful to know that `context.enqueue_links()` accepts a `limit` keyword argument, letting you specify the max number of HTTP requests to enqueue.