What is a symbol code? I am a physicist learning a bit of information theory.

I have encountered a term ("symbol codes") on Wikipedia, and cannot find what it means:


  Source coding theorem for symbol codes
  
  Let $\Sigma_1,\Sigma_2$ denote two finite alphabets and let $\Sigma_1^*$ and $\Sigma_2^*$ denote the set of all finite words over those alphabets (respectively).
  
  Suppose that $X$ is a random variable taking values in $\Sigma_1$, and let $f$ be a uniquely decodable code from $\Sigma_1^*$ to $\Sigma_2^*$, where $|\Sigma_2| = a$. Let $S$ denote the random variable given by the length of the codeword $f(X)$.
  
  If $f$ is optimal in the sense that it has the minimal expected word length for $X$, then (Shannon 1948): $$ \frac{H(X)}{\log_2 a} \leq \mathbb{E}[S] &lt; \frac{H(X)}{\log_2 a} + 1, $$ where $\mathbb{E}$ denotes the expected value operator.


Please let me know what does symbol code mean.
"Symbol Codes" means codes that work over a (finite) alphabet with an arbitrary size. Many times people focus only on binary codes, and Shannon Thm says that the minimal code length of some random variable $X$ is between $H(X)$ and $H(X)+1$ bits.

But what if, instead of bits, you use trits, or symbols from a larger alphabet of size, say, $a$?  Then, the length of $X$'s coding needs to be adjusted since every symbol of the codeword now "contains"  $\log_2 a$ bits.
Then, the wikipedia page says, the minimal code length will be 
between $H(x)/\log_2(a)$ and $H(x)/\log_2(a)+1$ symbols. 

Multiply the equation by $\log_2 a$ to convert into information bits:
the codeword will have $S$ symbols, hence $S\log_2 a$ bits, and this amount, by Shannon's coding theorem, can be minimized so that it is almost $H(X)$ (maybe up to one additional symbol, i.e., additional $\log_2 a$ bits).