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If athlete_list is not empty, the number of athletes will be displayed by the {{ athlete_ list|length }} variable. As you can see, the if tag can take an optional {% else %} clause that will be displayed if the test fails. if tags may use and, or, or not to test a number of variables or to negate a given variable: {% if athlete_list and coach_list %} Both athletes and coaches are available. {% endif %} {% if not athlete_list %} There are no athletes. {% endif %} {% if athlete_list or coach_list %} There are some athletes or some coaches. {% endif %} {% if not athlete_list or coach_list %} There are no athletes or there are some coaches (OK, so writing English translations of Boolean logic sounds stupid; it's not our fault). {% endif %} {% if athlete_list and not coach_list %} There are some athletes and absolutely no coaches. {% endif %} if tags don t allow and and or clauses within the same tag, because the order of logic would be ambiguous. For example, this is invalid: {% if athlete_list and coach_list or cheerleader_list %} If you need to combine and and or to do advanced logic, just use nested if tags, for example: {% if athlete_list %} {% if coach_list or cheerleader_list %} We have athletes, and either coaches or cheerleaders! {% endif %} {% endif %} Multiple uses of the same logical operator are fine, as long as you use the same operator. For example, this is valid: {% if athlete_list or coach_list or parent_list or teacher_list %}



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Third normal form (3NF) extends the concept of functional dependence to full functional dependence. Essentially, this means that all nonkey columns in a table are uniquely identified by the whole, not just part of, the primary key. For example, if you revised our hypothetical 1NF managers-employees table to have three columns (managername, employeeid, and employeename) instead of two, and you defined the composite primary key as managername + employeeid, the table would be in 2NF (since employeename, the nonkey column, is dependent on the primary key), but it wouldn t be in 3NF since employeename is uniquely identified by part of the primary key (employeeid). Creating a separate table for employees and removing employeename from managers-employees would put the table into 3NF. Note that even though this table is now normalized to 3NF, the database design is still not as normalized as it should be. Creating another table for managers, using an ID shorter than the manager s name, though not required for normalization here, is definitely a better approach that would probably be advisable for a real-world database. Database design (even of small databases) is an art more than a science, and applying normalization wisely is always important. On the other hand, normalization inherently increases the number of tables and therefore the number of operations (called joins) required to retrieve data. Denormalizing one or more tables, by intentionally providing redundant data to reduce the number or complexity of joins to get quicker query response times, may be necessary. With either normalization or denormalization, the goal is to control redundancy so that the database design adequately (and ideally, optimally) supports the actual use of the database.





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Checks if a value has changed from the last iteration of a loop. The ifchanged block tag is used within a loop. It has two possible uses: It checks its own rendered contents against its previous state and displays the content only if it has changed. For example, this displays a list of days, only displaying the month if it changes: <h1>Archive for {{ year }}</h1> {% for date in days %} {% ifchanged %}<h3>{{ date|date:"F" }}</h3>{% endifchanged %} <a href="{{ date|date:"M/d"|lower }}/">{{ date|date:"j" }}</a> {% endfor %} If given a variable, it checks whether that variable has changed: {% for date in days %} {% ifchanged date.date %} {{ date.date }} {% endifchanged %} {% ifchanged date.hour date.date %} {{ date.hour }} {% endifchanged %} {% endfor %} The preceding shows the date every time it changes, but it only shows the hour if both the hour and the date have changed.

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In this chapter you furthered your understanding of relational databases, particularly how data in tables represents relationships between tables. Among the things we covered were: How to create and drop tables The different types of relationships between tables What primary keys and foreign keys are What entity and referential integrity mean and how they are defined and enforced What normalization and denormalization mean In the next chapter we ll revisit SQL queries and experiment with more advanced query facilities, including how to combine data from multiple tables.

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