Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

section on your website which should be the same on every single page, such as a footer block. You could hard-code your footer into the template, but it would be nicer to be able to manage it through the CMS static placeholders from a template, you can reuse them later. So let’s add a footer to all our pages. Since we want our footer on every single page, we should add it to our base template (mysite/templates/base {% load djangocms_alias_tags %} {% block content %} <footer> {% static_alias 'footer' %} footer> {% endblock content %} Save the template and return to your

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader

Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results useful to create nested loaders. Imagine you’re extracting details from a footer of a page that looks something like: Example: <footer> Like Us Us footer> Without nested loaders, you need to specify the full xpath (or css) for each value that you wish to extract. Example: loader = ItemLoader(item=Item()) # load stuff not in the footer loader