{"ok": true, "database": "tils", "table": "til", "rows": [{"path": "django_filter-by-comma-separated-values.md", "topic": "django", "title": "Filter by comma-separated values in the Django admin", "url": "https://github.com/simonw/til/blob/main/django/filter-by-comma-separated-values.md", "body": "I have a text column which contains comma-separated values - inherited from an older database schema.\n\nI should refactor this into a many-to-many field (or maybe even a PostgreSQL array field), but I haven't done that yet. And I wanted to be able to filter by those values in the Django admin.\n\nSince I'm using PostgreSQL, I decided to figure out how to do this using the PostgreSQL `regexp_split_to_array()` function.\n\nThere are two necessary SQL queries here: one to figure out all of the unique distinct values that are represented across all of those comma-separated lists, and one to filter for rows that include a specific value.\n\nHere's what I came up with for the first:\n\n```sql\nselect distinct unnest(\n  regexp_split_to_array(my_column, ',\\s*')\n) from my_table\n```\nThis uses `unnest()`, see [this TIL](https://til.simonwillison.net/postgresql/unnest-csv).\n\nFor filtering down to rows that contain a specific value in their comma-separated list, I figured out this:\n\n```sql\nselect\n  *\nfrom\n  my_table\nwhere\n  array_position(\n    regexp_split_to_array(\n      my_column, ',\\s*'\n    ),\n    'MyValue'\n  ) is not null\n```\nThat second one, translated into the Django ORM, looks like this:\n```python\nfrom django.contrib.postgres.fields import ArrayField\nfrom django.db.models import F, IntegerField, TextField, Value\nfrom django.db.models.expressions import Func\n\nqueryset.annotate(\n    value_array_position=Func(\n        Func(\n            F(my_column),\n            Value(\",\\\\s*\"),\n            function=\"regexp_split_to_array\",\n            output_field=ArrayField(TextField()),\n        ),\n        Value(my_value),\n        function=\"array_position\",\n        output_field=IntegerField()\n    )\n).filter(value_array_position__isnull=False)\n```\nI didn't bother figuring out the ORM equivalent of that first `unnest()` SQL.\n\nHere's the reusable admin filter factory I came up with using these:\n\n```python\nfrom django.contrib.admin import SimpleListFilter\nfrom django.contrib.postgres.fields import ArrayField\nfrom django.db import connection\nfrom django.db.models import F, TextField, Value\nfrom django.db.models.expressions import Func\n\n\ndef make_csv_filter(filter_title, filter_parameter_name, table, column):\n    class CommaSeparatedValuesFilter(SimpleListFilter):\n        title = filter_title\n        parameter_name = filter_parameter_name\n\n        def lookups(self, request, model_admin):\n            sql = \"\"\"\n                select distinct unnest(\n                    regexp_split_to_array({}, ',\\\\s*')\n                ) from {}\n            \"\"\".format(\n                column, table\n            )\n            with connection.cursor() as cursor:\n                cursor.execute(sql)\n                values = [r[0] for r in cursor.fetchall() if r[0]]\n            return zip(values, values)\n\n        def queryset(self, request, queryset):\n            value = self.value()\n            if not value:\n                return queryset\n            else:\n                return queryset.annotate(\n                    value_array_position=Func(\n                        Func(\n                            F(column),\n                            Value(\",\\\\s*\"),\n                            function=\"regexp_split_to_array\",\n                            output_field=ArrayField(TextField()),\n                        ),\n                        Value(value),\n                        function=\"array_position\",\n                        output_field=IntegerField()\n                    )\n                ).filter(value_array_position__isnull=False)\n\n    return CommaSeparatedValuesFilter\n```\nThen you use it in a `ModelAdmin` subclass like this:\n```python\n@admin.register(Reporter)\nclass ReporterAdmin(admin.ModelAdmin):\n    list_filter = (\n        make_csv_filter(\n            filter_title=\"Roles\",\n            filter_parameter_name=\"role\",\n            table=\"reporter\",\n            column=\"role_names\",\n        ),\n    )\n```", "html": "<p>I have a text column which contains comma-separated values - inherited from an older database schema.</p>\n<p>I should refactor this into a many-to-many field (or maybe even a PostgreSQL array field), but I haven't done that yet. And I wanted to be able to filter by those values in the Django admin.</p>\n<p>Since I'm using PostgreSQL, I decided to figure out how to do this using the PostgreSQL <code>regexp_split_to_array()</code> function.</p>\n<p>There are two necessary SQL queries here: one to figure out all of the unique distinct values that are represented across all of those comma-separated lists, and one to filter for rows that include a specific value.</p>\n<p>Here's what I came up with for the first:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select distinct</span> unnest(\n  regexp_split_to_array(my_column, <span class=\"pl-s\"><span class=\"pl-pds\">'</span>,<span class=\"pl-cce\">\\s</span>*<span class=\"pl-pds\">'</span></span>)\n) <span class=\"pl-k\">from</span> my_table</pre></div>\n<p>This uses <code>unnest()</code>, see <a href=\"https://til.simonwillison.net/postgresql/unnest-csv\" rel=\"nofollow\">this TIL</a>.</p>\n<p>For filtering down to rows that contain a specific value in their comma-separated list, I figured out this:</p>\n<div class=\"highlight highlight-source-sql\"><pre><span class=\"pl-k\">select</span>\n  <span class=\"pl-k\">*</span>\n<span class=\"pl-k\">from</span>\n  my_table\n<span class=\"pl-k\">where</span>\n  array_position(\n    regexp_split_to_array(\n      my_column, <span class=\"pl-s\"><span class=\"pl-pds\">'</span>,<span class=\"pl-cce\">\\s</span>*<span class=\"pl-pds\">'</span></span>\n    ),\n    <span class=\"pl-s\"><span class=\"pl-pds\">'</span>MyValue<span class=\"pl-pds\">'</span></span>\n  ) <span class=\"pl-k\">is not null</span></pre></div>\n<p>That second one, translated into the Django ORM, looks like this:</p>\n<div class=\"highlight highlight-source-python\"><pre><span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">contrib</span>.<span class=\"pl-s1\">postgres</span>.<span class=\"pl-s1\">fields</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">ArrayField</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">db</span>.<span class=\"pl-s1\">models</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">F</span>, <span class=\"pl-v\">IntegerField</span>, <span class=\"pl-v\">TextField</span>, <span class=\"pl-v\">Value</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">db</span>.<span class=\"pl-s1\">models</span>.<span class=\"pl-s1\">expressions</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">Func</span>\n\n<span class=\"pl-s1\">queryset</span>.<span class=\"pl-en\">annotate</span>(\n    <span class=\"pl-s1\">value_array_position</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">Func</span>(\n        <span class=\"pl-v\">Func</span>(\n            <span class=\"pl-v\">F</span>(<span class=\"pl-s1\">my_column</span>),\n            <span class=\"pl-v\">Value</span>(<span class=\"pl-s\">\",<span class=\"pl-cce\">\\\\</span>s*\"</span>),\n            <span class=\"pl-s1\">function</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"regexp_split_to_array\"</span>,\n            <span class=\"pl-s1\">output_field</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">ArrayField</span>(<span class=\"pl-v\">TextField</span>()),\n        ),\n        <span class=\"pl-v\">Value</span>(<span class=\"pl-s1\">my_value</span>),\n        <span class=\"pl-s1\">function</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"array_position\"</span>,\n        <span class=\"pl-s1\">output_field</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">IntegerField</span>()\n    )\n).<span class=\"pl-en\">filter</span>(<span class=\"pl-s1\">value_array_position__isnull</span><span class=\"pl-c1\">=</span><span class=\"pl-c1\">False</span>)</pre></div>\n<p>I didn't bother figuring out the ORM equivalent of that first <code>unnest()</code> SQL.</p>\n<p>Here's the reusable admin filter factory I came up with using these:</p>\n<div class=\"highlight highlight-source-python\"><pre><span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">contrib</span>.<span class=\"pl-s1\">admin</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">SimpleListFilter</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">contrib</span>.<span class=\"pl-s1\">postgres</span>.<span class=\"pl-s1\">fields</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">ArrayField</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">db</span> <span class=\"pl-k\">import</span> <span class=\"pl-s1\">connection</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">db</span>.<span class=\"pl-s1\">models</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">F</span>, <span class=\"pl-v\">TextField</span>, <span class=\"pl-v\">Value</span>\n<span class=\"pl-k\">from</span> <span class=\"pl-s1\">django</span>.<span class=\"pl-s1\">db</span>.<span class=\"pl-s1\">models</span>.<span class=\"pl-s1\">expressions</span> <span class=\"pl-k\">import</span> <span class=\"pl-v\">Func</span>\n\n\n<span class=\"pl-k\">def</span> <span class=\"pl-en\">make_csv_filter</span>(<span class=\"pl-s1\">filter_title</span>, <span class=\"pl-s1\">filter_parameter_name</span>, <span class=\"pl-s1\">table</span>, <span class=\"pl-s1\">column</span>):\n    <span class=\"pl-k\">class</span> <span class=\"pl-v\">CommaSeparatedValuesFilter</span>(<span class=\"pl-v\">SimpleListFilter</span>):\n        <span class=\"pl-s1\">title</span> <span class=\"pl-c1\">=</span> <span class=\"pl-s1\">filter_title</span>\n        <span class=\"pl-s1\">parameter_name</span> <span class=\"pl-c1\">=</span> <span class=\"pl-s1\">filter_parameter_name</span>\n\n        <span class=\"pl-k\">def</span> <span class=\"pl-en\">lookups</span>(<span class=\"pl-s1\">self</span>, <span class=\"pl-s1\">request</span>, <span class=\"pl-s1\">model_admin</span>):\n            <span class=\"pl-s1\">sql</span> <span class=\"pl-c1\">=</span> <span class=\"pl-s\">\"\"\"</span>\n<span class=\"pl-s\">                select distinct unnest(</span>\n<span class=\"pl-s\">                    regexp_split_to_array({}, ',<span class=\"pl-cce\">\\\\</span>s*')</span>\n<span class=\"pl-s\">                ) from {}</span>\n<span class=\"pl-s\">            \"\"\"</span>.<span class=\"pl-en\">format</span>(\n                <span class=\"pl-s1\">column</span>, <span class=\"pl-s1\">table</span>\n            )\n            <span class=\"pl-k\">with</span> <span class=\"pl-s1\">connection</span>.<span class=\"pl-en\">cursor</span>() <span class=\"pl-k\">as</span> <span class=\"pl-s1\">cursor</span>:\n                <span class=\"pl-s1\">cursor</span>.<span class=\"pl-en\">execute</span>(<span class=\"pl-s1\">sql</span>)\n                <span class=\"pl-s1\">values</span> <span class=\"pl-c1\">=</span> [<span class=\"pl-s1\">r</span>[<span class=\"pl-c1\">0</span>] <span class=\"pl-k\">for</span> <span class=\"pl-s1\">r</span> <span class=\"pl-c1\">in</span> <span class=\"pl-s1\">cursor</span>.<span class=\"pl-en\">fetchall</span>() <span class=\"pl-k\">if</span> <span class=\"pl-s1\">r</span>[<span class=\"pl-c1\">0</span>]]\n            <span class=\"pl-k\">return</span> <span class=\"pl-en\">zip</span>(<span class=\"pl-s1\">values</span>, <span class=\"pl-s1\">values</span>)\n\n        <span class=\"pl-k\">def</span> <span class=\"pl-en\">queryset</span>(<span class=\"pl-s1\">self</span>, <span class=\"pl-s1\">request</span>, <span class=\"pl-s1\">queryset</span>):\n            <span class=\"pl-s1\">value</span> <span class=\"pl-c1\">=</span> <span class=\"pl-s1\">self</span>.<span class=\"pl-en\">value</span>()\n            <span class=\"pl-k\">if</span> <span class=\"pl-c1\">not</span> <span class=\"pl-s1\">value</span>:\n                <span class=\"pl-k\">return</span> <span class=\"pl-s1\">queryset</span>\n            <span class=\"pl-k\">else</span>:\n                <span class=\"pl-k\">return</span> <span class=\"pl-s1\">queryset</span>.<span class=\"pl-en\">annotate</span>(\n                    <span class=\"pl-s1\">value_array_position</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">Func</span>(\n                        <span class=\"pl-v\">Func</span>(\n                            <span class=\"pl-v\">F</span>(<span class=\"pl-s1\">column</span>),\n                            <span class=\"pl-v\">Value</span>(<span class=\"pl-s\">\",<span class=\"pl-cce\">\\\\</span>s*\"</span>),\n                            <span class=\"pl-s1\">function</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"regexp_split_to_array\"</span>,\n                            <span class=\"pl-s1\">output_field</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">ArrayField</span>(<span class=\"pl-v\">TextField</span>()),\n                        ),\n                        <span class=\"pl-v\">Value</span>(<span class=\"pl-s1\">value</span>),\n                        <span class=\"pl-s1\">function</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"array_position\"</span>,\n                        <span class=\"pl-s1\">output_field</span><span class=\"pl-c1\">=</span><span class=\"pl-v\">IntegerField</span>()\n                    )\n                ).<span class=\"pl-en\">filter</span>(<span class=\"pl-s1\">value_array_position__isnull</span><span class=\"pl-c1\">=</span><span class=\"pl-c1\">False</span>)\n\n    <span class=\"pl-k\">return</span> <span class=\"pl-v\">CommaSeparatedValuesFilter</span></pre></div>\n<p>Then you use it in a <code>ModelAdmin</code> subclass like this:</p>\n<div class=\"highlight highlight-source-python\"><pre><span class=\"pl-en\">@<span class=\"pl-s1\">admin</span>.<span class=\"pl-en\">register</span>(<span class=\"pl-v\">Reporter</span>)</span>\n<span class=\"pl-k\">class</span> <span class=\"pl-v\">ReporterAdmin</span>(<span class=\"pl-s1\">admin</span>.<span class=\"pl-v\">ModelAdmin</span>):\n    <span class=\"pl-s1\">list_filter</span> <span class=\"pl-c1\">=</span> (\n        <span class=\"pl-en\">make_csv_filter</span>(\n            <span class=\"pl-s1\">filter_title</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"Roles\"</span>,\n            <span class=\"pl-s1\">filter_parameter_name</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"role\"</span>,\n            <span class=\"pl-s1\">table</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"reporter\"</span>,\n            <span class=\"pl-s1\">column</span><span class=\"pl-c1\">=</span><span class=\"pl-s\">\"role_names\"</span>,\n        ),\n    )</pre></div>\n", "shot": {"$base64": true, "encoded": 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"}, "created": "2021-04-21T09:31:55-07:00", "created_utc": "2021-04-21T16:31:55+00:00", "updated": "2021-04-28T16:23:10-07:00", "updated_utc": "2021-04-28T23:23:10+00:00", "shot_hash": "b908bf07608a7730778650f861b6fb75", "slug": "filter-by-comma-separated-values"}], "primary_keys": ["path"], "primary_key_values": ["django_filter-by-comma-separated-values.md"], "query_ms": 2.0844989994657226, "truncated": false}