The implementation uses the Qwant API (https://api.qwant.com/v3). The API is
undocumented but can be reverse engineered by reading the network log of
https://www.qwant.com/ queries.
This implementation is used by different qwant engines in the settings.yml::
- name: qwant
categories: general
...
- name: qwant news
categories: news
...
- name: qwant images
categories: images
...
- name: qwant videos
categories: videos
...
Signed-off-by: Markus Heiser <markus.heiser@darmarit.de>
The old xpath configuration for google scholar did not work and is replaced by a
python implementation.
Signed-off-by: Markus Heiser <markus.heiser@darmarit.de>
To get meaningfull diffs, the json file has to be sorted. Before applying any
further content patch, the json file needs a inital sort (without changing any
content).
Sorted by::
import sys, json
with open('engines_languages.json') as f:
j = json.load(f)
with open('engines_languages.json', 'w') as f:
json.dump(j, f, indent=2, sort_keys=True)
Signed-off-by: Markus Heiser <markus.heiser@darmarit.de>
Instead of a single line with 500000 characters use nicely formatted JSON.
Sort the lists in engine_languages.py so when updating it is possible to
more easily see the differences (search engines do change the order their
languages are listed in)
Add match_language function in utils to match any user given
language code with a list of engine's supported languages.
Also add language_aliases dict on each engine to translate
standard language codes into the custom codes used by the engine.
languages.py can change, so users may query on a language that is not
on the list anymore, even if it is still recognized by a few engines.
also made no and nb the same because they seem to return the same,
though most engines will only support one or the other.
