π Quora Search Scraper helps you extract answers, questions, and author data from Quora search results. π Perfect for market research, lead gen, and content insightsβfast, reliable, and easy to use. π Get actionable data in minutes!
ποΈ timeFilter discovery fallback β if the full DIRECT β DATACENTER β
RESIDENTIAL (+retries) proxy ladder is exhausted with zero Quora URLs found
while a recency window (timeFilter != all_time) is active, search_question_urls
now makes one final discovery pass with DuckDuckGo's df date-range dropped
before giving up. A narrow df bucket can legitimately starve keyword
discovery for some query/window combinations even when nothing is actually
being blocked. This does NOT weaken the freshness guarantee: the existing
post-fetch creationTime age filter in main.py still discards any row
outside the requested window β widening only gives that filter more
candidates to check. Root-caused via a live run (machine learning +
past_year + trackNewQuestions) that returned 0 rows after exhausting
the ladder, while the same query/window isolated independently (without
the narrow df pre-filter) succeeded.
Superset of the base Quora Search Scraper. All base inputs, outputs, per-section
views, the DIRECT β DATACENTER β RESIDENTIAL proxy ladder and PPE row_result
billing are preserved. New on top:
β° timeFilter (all_time/past_day/past_week/past_month/past_year)
β DuckDuckGo df date-range at discovery and a post-fetch creationTime
age filter. No past_hour (DuckDuckGo's finest bucket is a day).
ποΈ Absolute dates β new created_at (ISO) + age_days columns from
creationTime, plus an is_fresh flag against the window. Question freshness
falls back to its newest answer's date.
π·οΈ topicsFilter β keep only questions tagged with the chosen Quora topics.
