{"id":25776,"date":"2023-02-25T19:22:50","date_gmt":"2023-02-25T13:52:50","guid":{"rendered":"http:\/\/www.pythonpool.com\/?p=25776"},"modified":"2026-07-14T19:49:30","modified_gmt":"2026-07-14T14:19:30","slug":"filter-lambda-python","status":"publish","type":"post","link":"https:\/\/www.pythonpool.com\/filter-lambda-python\/","title":{"rendered":"Python filter() With lambda: Examples, Rules, and Better Alternatives"},"content":{"rendered":"<p><strong>Quick answer:<\/strong> filter(function, iterable) returns a lazy iterator containing the items for which function returns a truthy value. A lambda can express a short predicate, but a list comprehension is often clearer when the condition is simple and the result should be a new list.<\/p>\n<figure class=\"pythonpool-article-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/filter-lambda-python-b099.png\" alt=\"Python Pool infographic showing an iterable passed through filter and lambda to produce matching values\" width=\"1536\" height=\"1024\" loading=\"lazy\" decoding=\"async\"><figcaption>filter() keeps values whose predicate is truthy; convert the lazy result only when a concrete list or other collection is needed.<\/figcaption><\/figure>\n<p>Python <code>filter()<\/code> selects items from an iterable by applying a test function to each item. The official <a href=\"https:\/\/docs.python.org\/3\/library\/functions.html#filter\">Python <code>filter()<\/code> documentation<\/a> defines it as an iterator over the elements for which the function is true. A <a href=\"https:\/\/docs.python.org\/3\/reference\/expressions.html#lambda\">lambda expression<\/a> is one compact way to write that test function.<\/p>\n<p>The basic pattern is <code>filter(function, iterable)<\/code>. The result is an iterator, not a list. Convert it with <code>list()<\/code> only when you actually need all matching items in memory.<\/p>\n<p>Use <code>filter()<\/code> when the code reads clearly as \u201ckeep items matching this predicate.\u201d Use a list comprehension when the condition is easier to read inline. Both approaches are normal Python; the better choice is the one that makes the filtering rule obvious.<\/p>\n<p>Lambdas are best for short expressions. If the test needs several steps, logging, exception handling, or a useful name, write a regular function with <code>def<\/code>.<\/p>\n<p>The most important detail is that <code>filter()<\/code> keeps items based on truthiness. The predicate does not have to return the literal value <code>True<\/code>; any truthy result keeps the item, and any falsey result removes it.<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #990303;color:#990303\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #990303;color:#990303\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Filter_Even_Numbers_With_Lambda\" >Filter Even Numbers With Lambda<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Filter_Strings_By_Length\" >Filter Strings By Length<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Use_None_To_Remove_Falsey_Items\" >Use None To Remove Falsey Items<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Use_A_Named_Function_For_Reuse\" >Use A Named Function For Reuse<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Compare_filter_With_A_List_Comprehension\" >Compare filter With A List Comprehension<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Chain_Filter_With_Other_Iterables\" >Chain Filter With Other Iterables<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Read_The_Function_Signature\" >Read The Function Signature<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Remember_Laziness\" >Remember Laziness<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Handle_None_As_A_Predicate\" >Handle None As A Predicate<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Compare_A_Comprehension\" >Compare A Comprehension<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Avoid_Hidden_Side_Effects\" >Avoid Hidden Side Effects<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Test_Empty_And_Mixed_Inputs\" >Test Empty And Mixed Inputs<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Frequently_Asked_Questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#What_does_filter_do_in_Python\" >What does filter() do in Python?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#How_do_I_use_filter_with_lambda\" >How do I use filter() with lambda?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Why_is_filter_not_showing_a_list\" >Why is filter() not showing a list?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.pythonpool.com\/filter-lambda-python\/#Is_a_list_comprehension_clearer_than_filter_with_lambda\" >Is a list comprehension clearer than filter() with lambda?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Filter_Even_Numbers_With_Lambda\"><\/span>Filter Even Numbers With Lambda<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>This example keeps only even numbers. The lambda receives each number and returns <code>True<\/code> for values that should stay in the result.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">numbers = [1, 2, 3, 4, 5, 6]\n\neven_numbers = filter(lambda number: number % 2 == 0, numbers)\n\nprint(list(even_numbers))\n<\/code><\/pre>\n<\/div>\n<p>The call to <code>list()<\/code> is only for display. In a pipeline, you can pass the filter object to another function that accepts any iterable.<\/p>\n<p>This matters with large data sources because <code>filter()<\/code> produces values lazily. It does not build the whole output until something consumes it.<\/p>\n<p>If you print the filter object itself, you will see an iterator representation rather than the kept values. Convert it to a list for debugging, or loop over it directly.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Filter_Strings_By_Length\"><\/span>Filter Strings By Length<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Lambdas work well for simple string checks. This example keeps names with at least five characters.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">names = [\"Ada\", \"Grace\", \"Linus\", \"Guido\", \"Edsger\"]\n\nlong_names = filter(lambda name: len(name) &gt;= 5, names)\n\nprint(list(long_names))\n<\/code><\/pre>\n<\/div>\n<p>The predicate should return a truthy or falsey value. Returning a comparison, as shown here, keeps the intent direct.<\/p>\n<p>If the rule becomes more complicated, name it. A named predicate improves tracebacks, reuse, and testability.<\/p>\n<p><!-- Python Pool visual layout repair 2026-07-13 --><\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/filter-lambda-iterable-b134.png\" alt=\"Python Pool infographic showing filter values, iterator, predicate, and None\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Input iterable: Filter values, iterator, predicate, and None.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Use_None_To_Remove_Falsey_Items\"><\/span>Use None To Remove Falsey Items<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>If the first argument is <code>None<\/code>, Python uses an identity test and removes falsey items such as empty strings, zero, <code>False<\/code>, and <code>None<\/code>.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">raw_items = [\"python\", \"\", None, \"filter\", 0, \"lambda\"]\n\nclean_items = filter(None, raw_items)\n\nprint(list(clean_items))\n<\/code><\/pre>\n<\/div>\n<p>This is compact, but it removes every falsey value. Do not use it when <code>0<\/code> or <code>False<\/code> is valid data that should be preserved.<\/p>\n<p>When the cleanup rule is specific, write it explicitly so future readers can see exactly what is being removed.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Use_A_Named_Function_For_Reuse\"><\/span>Use A Named Function For Reuse<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A named function is clearer when the predicate has business meaning. It also makes the same rule easy to test.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">def is_active_user(user):\n    return user[\"active\"] and user[\"login_count\"] &gt; 0\n\nusers = [\n    {\"name\": \"Maya\", \"active\": True, \"login_count\": 4},\n    {\"name\": \"Noor\", \"active\": False, \"login_count\": 8},\n    {\"name\": \"Luis\", \"active\": True, \"login_count\": 0},\n]\n\nactive_users = filter(is_active_user, users)\n\nprint([user[\"name\"] for user in active_users])\n<\/code><\/pre>\n<\/div>\n<p>The function name documents the filtering goal. The body documents the details of the rule.<\/p>\n<p>This style is usually better than a long lambda, especially in shared code or tutorials where readers need to understand the condition quickly.<\/p>\n<p>Named predicates are also easier to unit test. You can test <code>is_active_user()<\/code> with a few small dictionaries before using it in a filtering pipeline.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Compare_filter_With_A_List_Comprehension\"><\/span>Compare filter With A List Comprehension<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The Python docs note that <code>filter(function, iterable)<\/code> is equivalent to a generator expression when the function is not <code>None<\/code>. A list comprehension is often the clearest option when you want a list immediately.<\/p>\n<p>A comprehension can also transform the items it keeps. The <a href=\"https:\/\/www.pythonpool.com\/python-list-comprehension-if-else\/\">list comprehension if\/else syntax guide<\/a> separates a trailing filter from a leading conditional expression and shows how to combine them safely.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">numbers = [3, 8, 11, 14, 17]\n\nwith_filter = list(filter(lambda number: number &gt; 10, numbers))\nwith_comprehension = [number for number in numbers if number &gt; 10]\n\nprint(with_filter)\nprint(with_comprehension)\n<\/code><\/pre>\n<\/div>\n<p>Both results are the same. The comprehension avoids a small lambda and can be easier to scan.<\/p>\n<p>Choose <code>filter()<\/code> when a reusable predicate already exists, when you want a lazy iterator, or when the pipeline style reads better. Choose a comprehension when the rule is short and the output should be a list.<\/p>\n<p>For beginners, the comprehension often feels more direct because the condition appears beside the loop. For iterator-heavy code, <code>filter()<\/code> can keep each step focused.<\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/filter-lambda-lambda-b134.png\" alt=\"Python Pool infographic showing a lambda argument, expression, truthiness, and return value\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Lambda: A lambda argument, expression, truthiness, and return value.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Chain_Filter_With_Other_Iterables\"><\/span>Chain Filter With Other Iterables<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Because <code>filter()<\/code> returns an iterator, it can be chained with other iterable tools. This example filters first, then transforms the kept values.<\/p>\n<div class=\"pythonpool-code-scroll\" style=\"max-width:100%;overflow-x:auto;-webkit-overflow-scrolling:touch;\">\n<pre><code class=\"language-python\">scores = [54, 91, 76, 88, 43, 99]\n\npassing_scores = filter(lambda score: score &gt;= 60, scores)\nlabels = map(lambda score: f\"pass:{score}\", passing_scores)\n\nprint(list(labels))\n<\/code><\/pre>\n<\/div>\n<p>This pattern is useful for streaming-style processing, but do not over-chain simple logic. If a comprehension is clearer, use it. For related iterator transformations, see the <a href=\"https:\/\/www.pythonpool.com\/python-map-function\/\">Python map guide<\/a>, and for text cleanup before filtering, see the <a href=\"https:\/\/www.pythonpool.com\/what-does-split-do-in-python\/\">Python split guide<\/a>.<\/p>\n<p>The practical rule is simple: keep lambdas short, convert the filter object only when needed, and use a named predicate when the condition matters enough to explain.<\/p>\n<p>Also remember that a filter object is consumed as you iterate over it. If you need to reuse the result multiple times, store a list or recreate the filter from the original data.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Read_The_Function_Signature\"><\/span>Read The Function Signature<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The first argument receives one item and returns a truth value; the second is the iterable. Passing the arguments in the wrong order or returning a transformed value instead of a predicate changes the result.<\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/filter-lambda-filter-b134.png\" alt=\"Python Pool infographic showing lazy filter output, list conversion, consumption, and result\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Filter result: Lazy filter output, list conversion, consumption, and result.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Remember_Laziness\"><\/span>Remember Laziness<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>In Python 3, filter returns an iterator. It is consumed once, so convert it to list when a reusable snapshot is required, or iterate directly when streaming values is preferable.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Handle_None_As_A_Predicate\"><\/span>Handle None As A Predicate<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>filter(None, iterable) keeps truthy items and removes falsey values such as 0, empty strings, and None. Use an explicit lambda or function when falsey values are valid data that should be retained.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Compare_A_Comprehension\"><\/span>Compare A Comprehension<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>A comprehension such as [value for value in values if value > 0] puts the output and condition in one readable expression. filter is useful when the predicate is already a named function or a lazy pipeline is desired.<\/p>\n<figure class=\"pythonpool-article-visual pythonpool-supporting-visual\"><img src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2026\/07\/filter-lambda-check-b134.png\" alt=\"Python Pool infographic testing empty input, exceptions, readability, comprehensions, and output\" width=\"1536\" height=\"1054\" loading=\"lazy\" decoding=\"async\"><figcaption>Filter checks: Empty input, exceptions, readability, comprehensions, and output.<\/figcaption><\/figure>\n<h2><span class=\"ez-toc-section\" id=\"Avoid_Hidden_Side_Effects\"><\/span>Avoid Hidden Side Effects<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Predicates should normally inspect an item and return a result. Side effects make lazy evaluation surprising because the function runs only when the iterator is consumed, not when filter is created.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Test_Empty_And_Mixed_Inputs\"><\/span>Test Empty And Mixed Inputs<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Test empty iterables, strings, generators, falsey values, and predicates that return non-Boolean truthy objects. Verify whether the caller expects an iterator or a concrete collection.<\/p>\n<p>The <a href=\"https:\/\/docs.python.org\/3\/library\/functions.html#filter\">official filter documentation<\/a> defines the lazy iterator behavior. Related Python Pool references include <a href=\"2\">lists<\/a> and <a href=\"https:\/\/www.pythonpool.com\/python-testing-framework\/\">tests<\/a>.<\/p>\n<p>For related collection patterns, compare <a href=\"2\">list comprehensions<\/a>, <a href=\"https:\/\/www.pythonpool.com\/python-foreach\/\">iteration<\/a>, and <a href=\"https:\/\/www.pythonpool.com\/python-testing-framework\/\">predicate tests<\/a> when choosing filter or lambda.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions\"><\/span>Frequently Asked Questions<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"What_does_filter_do_in_Python\"><\/span>What does filter() do in Python?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>filter() returns an iterator containing values for which its function returns a truthy result.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"How_do_I_use_filter_with_lambda\"><\/span>How do I use filter() with lambda?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Pass a lambda that accepts one item and returns a Boolean-like result, followed by the iterable to test.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Why_is_filter_not_showing_a_list\"><\/span>Why is filter() not showing a list?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In Python 3, filter() is lazy and returns an iterator; wrap it in list() or iterate over it when you need to consume the values.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Is_a_list_comprehension_clearer_than_filter_with_lambda\"><\/span>Is a list comprehension clearer than filter() with lambda?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Often yes for simple conditions, because the condition is visible next to the output expression; choose the form that makes the predicate easiest to review.<\/p>\n<p><script 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because the condition is visible next to the output expression; choose the form that makes the predicate easiest to review.\"}}]}<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Learn how Python filter() works with lambda, iterable values, truth tests, list conversion, generator behavior, and clearer comprehensions.<\/p>\n","protected":false},"author":35,"featured_media":33436,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[15],"tags":[],"class_list":["post-25776","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tutorials","infinite-scroll-item"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.1 (Yoast SEO v28.0) - 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