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callable) If the attribute exists and is callable we can return it to the caller; otherwise, we return None to signify that the function isn t available If hundreds of les were being processed (eg, due to using ** in the C:\windows directory), we don t want to go through the lookup process for every module for every le So immediately after de ning the get_function() function, we add an attribute to the function, a dictionary called cache (In general, Python allows us to add arbitrary attributes to arbitrary objects) The rst time that get_function() is called the cache dictionary is empty, so the dictget() call will return None But each time a suitable function is found it is put in the dictionary with a 2-tuple of the module and function name used as the key and the function itself as the value So the second and all subsequent times a particular function is requested the function is immediately returned from the cache and no attribute lookup takes place at all The technique used for caching the get_function() s return value for a given set of arguments is called memoizing It can be used for any function that has no side effects (does not change any global variables), and that always returns the same result for the same (immutable) arguments Since the code required to create and manage a cache for each memoized function is the same, it is an ideal candidate for a function decorator, and several @memoize decorator recipes are given in the Python Cookbook, in codeactivestatecom/recipes/langs/python/ However, module objects are mutable, so some off-the-shelf memoizer decorators wouldn t work with our get_function() function as it stands An easy solution would be to use each module s __name__ string rather than the module itself as the rst part of the key tuple Doing dynamic module imports is easy, and so is executing arbitrary Python code using the exec() function This can be very convenient, for example, allowing us to store code in a database However, we have no control over what imported or exec()uted code will do Recall that in addition to variables, functions, and classes, modules can also contain code that is executed when it is imported if the code came from an untrusted source it might do something unpleasant How to address this depends on circumstances, although it may not be an issue at all in some environments, or for personal projects.

c# upc-a reader

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LDAPConnectionsetReferrals( ldREFERRALS, new Boolean( true ) ); LDAPConstraintssetReferrals( true ); If the connection has the referral option set to true, or constraints are supplied with the referral option enabled, then the client code doing LDAP operations will never see a referral exception The highlighted sections of the previous examples can be eliminated If a referral is encountered during the execution of the operation, the SDK will make a new temporary connection to the referred-to server if necessary and continue the operation there The hopLimit parameter of the constraints, or the REFERRALS_HOP_LIMIT option of the connection, determines how many links to follow on a referral before giving up The default limit is 10 The default behavior on automatic referral following is not to authenticate (that is, to use an anonymous connection) to the referred-to server To supply credentials for the referred-to connection, you must implement the LDAPRebind interface and supply an instance of the implementation to LDAPConstraintssetRebindProc or to LDAPConnectionsetOption( LDAPConnectionREFERRALS_REBIND_PROC ) The interface speci es a single method getRebindAuthentication to provide credentials, using a host name and port as input parameters It is common to supply the same credentials to the referred-to server as were used to authenticate to the original server, as in the following example:

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// Illegal self-reference!! @interface SelfRef { SelfRef value(); }

It is often useful to have one or more small helper functions inside another function Python allows this without formality we simply de ne the functions we need inside the de nition of an existing function Such functions are often called nested functions or local functions We already saw examples of these in 7

The following annotation type declaration de nes an annotation type with several elements:

protected void setDefaultReferralCredentials( LDAPConnection conn ) { final LDAPConnection m_conn = conn; LDAPRebind rebind = new LDAPRebind() { public LDAPRebindAuth getRebindAuthentication( String host, int port ) { return new LDAPRebindAuth( m_conngetAuthenticationDN(), m_conngetAuthenticationPassword() ); } }; LDAPSearchConstraints cons = conngetSearchConstraints(); conssetReferrals( true ); conssetRebindProc( rebind ); connsetSearchConstraints( cons ); }

A slightly more sophisticated get_function() that has better handling of modules without the required functionality is in the magic-numberspy program alongside the version shown here

// Normal annotation type declaration with several elements /** * Describes the "request-for-enhancement" (RFE) * that led to the presence of * the annotated API element

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One common use case for local functions is when we want to use recursion In these cases, the enclosing function is called, sets things up, and then makes the rst call to a local recursive function Recursive functions (or methods) are ones that call themselves Structurally, all directly recursive functions can be seen as having two cases: the base case and the recursive case The base case is used to stop the recursion Recursive functions can be computationally expensive because for every recursive call another stack frame is used; however, some algorithms are most naturally expressed using recursion Most Python implementations have a xed limit to how many recursive calls can be made The limit is returned by sysgetrecursionlimit() and can be changed by syssetrecursionlimit(), although increasing the limit is most often a sign that the algorithm being used is inappropriate or that the implementation has a bug The classic example of a recursive function is one that is used to calculate factorials For example, factorial(5) will calculate 5! and return 120, that is, 1 2 3 4 5:

The method extracts the credentials from an authenticated connection and stores them for use on referrals When LDAPRebindProcgetRebindAuthentication is called by the SDK, an LDAPRebindAuth object is instantiated using the stored credentials

*/ public @interface RequestForEnhancement { int id(); // Unique ID number associated with RFE String synopsis(); // Synopsis of RFE String engineer(); // Name of engineer who implemented RFE String date(); // Date RFE was implemented }

def factorial(x): if x <= 1: return 1 return x * factorial(x - 1)

The following annotation type declaration de nes an annotation type with no elements, termed a marker annotation type:

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