like" queries), filter by tag, filter by date, filter by content type (entries vs blogmarks vs quotation) and any combination of the above. Some example searches:</p><ul><li><a href="https://simonwillison.net/search/?q=postgresql">All content matching "postgresql"</a></li><li><a href="https://simonwillison.net/search/?q=django&type=quotation">Just quotations matching "django"</a></li><li><a href="https://simonwillison.net/search/?q=python+javascript&tag=mozilla&year=2007">All content matching "python" and "javascript" with the tag "mozilla" posted in 2007</a></li></ul><p>It also provides facet counts, so you can tell how many results you will get back before you apply one of these filters - and get a general feeling for the shape of the corpus as you navigate it.</p>')

Results:

|                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        to_tsvector |
|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| '2007':70 'ad':3 'also':72 'appli':89 'back':86 'blog':10 'blogmark':38 'combin':43 'content':34,51,59 'corpus':104 'count':75 'date':31 'django':57 'engin':7 'entri':36 'exampl':48 'facet':5,74 'feel':98 'filter':26,29,32,93 'general':97 'get':85,95 'javascript':63 'like':24 'mani':81 'match':52,56,60 'mozilla':67 'navig':107 'one':90 'post':68 'postgresql':13,53 'power':11 'proper':19 'provid':73 'python':61 'queri':25 'quotat':40,55 'regular':16 'result':82 'search':6,18,20,49 'shape':101 'sql':23 'support':15 'tag':28,66 'tell':79 'text':17 'type':35 've':2 'vs':37,39 |

Query 2:

SELECT to_tsvector('I''ve added a faceted search engine to this blog, powered by PostgreSQL. It supports regular text search (proper search, not just SQL"like" queries), filter by tag, filter by date, filter by content type (entries vs blogmarks vs quotation) and any combination of the above. Some example searches:All content matching "postgresql"Just quotations matching "django"All content matching "python" and "javascript" with the tag "mozilla" posted in 2007It also provides facet counts, so you can tell how many results you will get back before you apply one of these filters - and get a general feeling for the shape of the corpus as you navigate it.')

Results:

|                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          to_tsvector |
|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| '2007it':70 'ad':3 'also':71 'appli':88 'back':85 'blog':10 'blogmark':38 'combin':43 'content':34,51,59 'corpus':103 'count':74 'date':31 'django':57 'engin':7 'entri':36 'exampl':48 'facet':5,73 'feel':97 'filter':26,29,32,92 'general':96 'get':84,94 'javascript':63 'like':24 'mani':80 'match':52,56,60 'mozilla':67 'navig':106 'one':89 'post':68 'postgresql':13,53 'power':11 'proper':19 'provid':72 'python':61 'queri':25 'quotat':40,55 'regular':16 'result':81 'search':6,18,20,49 'shape':100 'sql':23 'support':15 'tag':28,66 'tell':78 'text':17 'type':35 've':2 'vs':37,39 |

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