Building with the iCalendar standard, it's time to extract schedule information from a database and build calendars on the fly.
Last month, we continued our look at the iCalendar standard, which makes it possible for programs to exchange calendar and appointment information. As we saw, an iCalendar file contains one or more events and tasks. If we make the file available via an HTTP server such as Apache, we can distribute it to anyone with an iCalendar-compatible program, such as Mozilla's Sunbird. As we saw last month, we can go one step further than this, generating an iCalendar file dynamically, using a CGI program.
Although the programs I presented and discussed last month might be useful in a limited context, it should be clear to any Web developer that keeping the date and time information inside of a program would be foolish, to say the least.
One of the best ways to keep track of such data is in a relational database such as PostgreSQL. A relational database allows you to ensure that the data you have entered is valid and provides you with fast, flexible access to some or all of the data it contains. Moreover, by storing the calendar information inside of a database, you can create multiple versions of the same calendar file, using the same source.
This month, we look at a simple example of a Web-based program that takes calendar information from a relational database and uses it to generate an iCalendar data file, which then can be imported into iCalendar-compliant programs, such as Mozilla's Sunbird.
If we are going to store our calendar information in a relational database, we need to define at least one table. This is because everything in a relational database—often including configuration and status information—is stored in a two-dimensional table, in which the columns define individual fields, and each row contains one record. For example, here is how we might define a simple table of events in PostgreSQL:
CREATE TABLE Events ( event_id SERIAL NOT NULL, event_summary TEXT NOT NULL CHECK (event_summary <> ''), event_location TEXT NOT NULL CHECK (event_location <> ''), event_start TIMESTAMP NOT NULL, event_end TIMESTAMP NOT NULL, event_timestamp TIMESTAMP NOT NULL DEFAULT NOW(), PRIMARY KEY(event_id) );
The above table contains six columns. The first, event_id, is defined to be of type SERIAL. If we don't explicitly provide a value for event_id when adding a row to the table, PostgreSQL retrieves a new integer value automatically, up to a maximum of 231. PostgreSQL allows you to set a larger ceiling to allow the sequence to wrap around to 1, or both; see the documentation for more details.
The event_id column uniquely identifies rows in our table, and we tell the database this by marking it as a PRIMARY KEY. This not only tells other database programmers which column will be used for retrieving records, but it ensures that values are unique and that the column is indexed as well.
Another automatically populated column is event_timestamp. From the definition, it might appear as though we can (and will) set event_timestamp to an explicit value, with the current time providing a default as necessary. But whenever I define a column in this way, it implies that I never expect to set a value explicitly for this column. Rather, I am interested in letting PostgreSQL set the column's value with the current date and time.
Notice how the event_summary and event_location columns are both defined to be of type TEXT (that is, infinite-length text fields), while event_start, event_end and event_timestamp are all of type TIMESTAMP, the SQL-standard way of saying date and time.
All of the columns in this table are defined to be NOT NULL, meaning that they may not be assigned SQL's undefined value of NULL. NULL is distinct from true and false, which can make it a bit tricky for newcomers to understand. However, if you think of NULL as representing an unknown or undefined value, it might become clearer. As useful as NULLs can be in distinguishing between false and unknown values, it's usually a good idea to cut down on them as much as possible. Indeed, the advice that I have long heard, and repeated to others, is that you should define columns to be NOT NULL by default, opening them up to NULL values as the situation requires.
Finally, notice how our two text columns (event_summary and event_location) are defined both as NOT NULL and with an integrity check that ensures we enter something other than an empty string. Whether this combination of constraints is appropriate depends on your database needs. You might want to think about whether you want to allow NULL values at all and also if you want to allow empty strings for the summary and location columns.
Although this simple definition is meant to serve as an example, consider how much better it would be if we were to have a separate Locations table, with a location_id and location_name, and then replace the textual event_location column with a location_id. This would have the advantage of standardizing location names, which would lead to fewer inconsistencies. It also would allow us to search for all of the events taking place in a particular location.
Once we are done defining the table, we add some indexes to our table. Each index ensures that data will be retrieved from the table more quickly than usual, at the expense of additional time for each INSERT. Here are the definitions:
CREATE INDEX event_location_idx ON Events(event_location); CREATE INDEX event_start_idx ON Events(event_start); CREATE INDEX event_end_idx ON Events(event_end);
Now that we have a defined table and indexes, we can start to populate our database table with some events. We can, as always, INSERT new events into our table with the following syntax:
INSERT INTO Events (event_summary, event_location, event_start, event_end) VALUES ('Ides of March', 'Everywhere', '2005-March-15 00:00', '2005-March-15 23:59:59')
As you can see, the above INSERT statement names only four of the six columns defined in Events. When we check our new row, we find the following:
atf=# select * from events; -[ RECORD 1 ]---+--------------------------- event_id | 1 event_summary | Ides of March event_location | Everywhere event_start | 2005-03-15 00:00:00 event_end | 2005-03-15 23:59:59 event_timestamp | 2005-04-04 01:20:15.575032
As you can see, event_id (which we defined to be of type SERIAL) has automatically received a value of 1. Furthermore, event_timestamp has been set with the date and time at which we executed the query.
It's easy to imagine how we could invoke this INSERT statement with a Web-based program using CGI or a more advanced system, such as mod_perl or Zope. Indeed, we really don't have to think much about how the data has arrived in the database, particularly if we have set appropriate constraints on our data. We can assume that whatever resides in the database is reliable, and that the server has rejected any entries that would violate our rules.
Now that we have some activities in our database table, we can retrieve them into a CGI program. That program then produces output in iCalendar format, allowing iCalendar clients to retrieve its data. Listing 1 contains the program, which is a modified version of last month's dynamic-calendar.py program. As I mentioned last month, I wrote this program in Python in no small part because of the relative dearth of modules to create iCalendar-format files. Fortunately, there is such a module for Python, and I have taken advantage of that fact in this program.
As you can see in Listing 1, the program is fairly straightforward. After importing a number of modules, we create a calendar object and insert the iCalendar-mandated fields indicating the source of the calendar.
We then connect to a PostgreSQL server, which is presumed to be on the local computer. Although several database adaptors exist in Python for PostgreSQL access, I have long used psycopg, which is both fast and stable. To connect to PostgreSQL with psycopg, we use the following syntax:
db_connection = psycopg.connect ('dbname=atf user=reuven')
The above indicates that the database name is atf and the user name is reuven. You also might need to specify the server and a password as additional arguments, especially if you are working on a production system.
Once we have connected to the database, we get a cursor, which allows us to submit queries and get their results:
db_cursor = db_connection.cursor()
With a cursor in hand, we now can send our SQL query to the database, using Python's triple-quote functionality to make our SQL more readable. Now we retrieve our results. If we were expecting to retrieve dozens or hundreds of rows, we probably would want to get them one at a time, or perhaps in batches. But I know that this calendar will contain only a few events, so I use the fetchall() method to get them in one large sequence:
result_rows = db_crsor.fetchall()
Each element of result_rows is a row from our PostgreSQL database. We thus iterate (in a for loop) over the rows, retrieving the different elements that appear.
For the most part, this is pretty straightforward. However, things get a bit tricky when we are working with dates and times—important elements of any calendar of events! The problem is that psycopg uses the open-source mxDateTime module from eGenix.com, which makes working with dates extremely easy. But mxm's iCalendar module uses Python's datetime module, which is different. We thus need to retrieve each of the dates (for the event's starting time, ending time and stamp), turn them from an instance of mxDateTime into a datetime-compatible tuple, use that tuple to create an instance of datetime and then pass that to event.add, using the three calls starting with:
event.add('dtstart', datetime(tzinfo=UTC(), event.add('dtend', datetime(tzinfo=UTC(), *row.tuple()[0:5]))
The second argument to datetime() in the above three rows of code does exactly what we said. It retrieves one column from the returned row and turns it into a tuple. We then take a slice of the sequence (with Python's convenient [0:5] notation) to grab a subset of the items returned by tuple().
But we can't pass datetime() a sequence; rather, it is expecting a number of individual elements. In other words, datetime() wants several numbers, not a reference or pointer to a list of numbers. We turn the tuple into its individual elements with Python's * operator. Finally, sharp-eyed readers will notice that we have passed the tzinfo argument before the individual elements of the tuple; this is because Python requires that we pass named arguments before the * operator.
Sure enough, the result of invoking db-calendar.py is a fully iCalendar-compliant file, suitable for importing into Sunbird or any other calendar program. Moreover, simply by modifying the contents of our Events database table, we can ensure that everyone who subscribes to our calendar gets the latest version.
We can go one step further than this, modifying db-calendar.py such that it includes only certain events in its result. For example, perhaps the calendar needs to contain only events in the future; there is no need to clutter someone's calendar (and bandwidth) with events from the past. By adding a simple WHERE clause to our SQL query, we easily can remove all of the events from the past.
More intriguing is the possibility of supporting different groups and access levels to a calendar. HTTP supports authentication with user names and passwords, and although Sunbird doesn't support such protections at the present time, I would expect it (and other programs) to do so in the future. Given that a CGI program easily can determine the user name of the person making an authenticated HTTP request, it's not too far-fetched to say that db-calendar.py could produce different output for different users, depending on a set of assigned permissions or roles.
Finally, although we have focused on iCalendar-format output for the last few months, there isn't any reason why we can turn only the contents of the database into an iCalendar file. Indeed, it's quite possible that we would want to display our events database in plain-old HTML, as well as in iCalendar. Once again, it's easy to see how we could do that using HTML tables—demonstrating once again that relational databases make it easy to display a set of data in a number of different ways.
This month, we have seen how to use a database to store event information that eventually will be transformed into an iCalendar-compliant file. Using a database makes us not only more confident that stored data is valid, but it allows us to create dynamically generated files quickly and easily that are suitable for use in programs that use the iCalendar format.
Resources for this article: /article/8263.