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locals().update(dictionary) doesn't add all the variables

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I think, one of the reasons for that is that whether a variable is global or local is defined during the function compilation, so that in:

def func():
   locals()['val'] = 1
print val

Suggestion : 2

The locals() method returns a dictionary with all the local variables and symbols for the current program. ,The locals() method returns the dictionary of the current local symbol table.,A Local Symbol table stores all the information related to the program's local scope (within the class or a method). We can access this symbol table with the locals() method.,In the above example, we have changed the value of the present variable inside a function localsPresent using the locals() method.

Example

print(locals())

Output

{
   'In': ['', 'locals()'],
   'Out': {},
   '_': '',
   '__': '',
   '___': '',
   '__builtin__': ,
   '__builtins__': ,
   '__name__': '__main__',
   '_dh': ['/home/repl'],
   '_i': '',
   '_i1': 'locals()',
   '_ih': ['', 'locals()'],
   '_ii': '',
   '_iii': '',
   '_oh': {},
   '_sh': ,
   'exit': ,
   'get_ipython': > ,
   'quit':
}

Example

print(locals())

Output

{
   'In': ['', 'locals()'],
   'Out': {},
   '_': '',
   '__': '',
   '___': '',
   '__builtin__': ,
   '__builtins__': ,
   '__name__': '__main__',
   '_dh': ['/home/repl'],
   '_i': '',
   '_i1': 'locals()',
   '_ih': ['', 'locals()'],
   '_ii': '',
   '_iii': '',
   '_oh': {},
   '_sh': ,
   'exit': ,
   'get_ipython': > ,
   'quit':
}

The syntax of the locals() method is:

locals()

Example 2: locals() to change values

def localsPresent():
   present = True
print(present)
locals()['present'] = False;
print(present)

localsPresent()

Suggestion : 3

Local variables that are used within interfaces can refresh their values under a variety of conditions. When a variable is refreshed, the value of that variable is recalculated and the variable is updated with the latest value.,Variables that depend on a specific field within another variable (for example, local variables, rule inputs, etc.) will only refresh when that field is updated, rather than the entire variable.,When defining the value of a local variable, you may use other types of variables. This includes process variables, rule inputs, and other local variables that were previously defined.,Local variables are defined in the a!localVariables function. You can define both the name and the value of the local variable, then use those variables in the last parameter of the function:

1._
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5
a!localVariables(
   local!a: 1,
   local!b: 2,
   local!a + local!b
)
2._
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2
3
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5
3._
a!localVariables(
   local!a: 1,
   local!b: 2,
   local!a + local!b
)
1
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5
a!localVariables(
   local!a: 1,
   local!b: 2,
   local!a + local!b
)
1._
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a!localVariables(
   local!input,
   a!textField(
      label: "Input",
      value: local!input,
      saveInto: local!input
   )
)
2._
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3._
a!localVariables(
   local!input,
   a!textField(
      label: "Input",
      value: local!input,
      saveInto: local!input
   )
)
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a!localVariables(
   local!input,
   a!textField(
      label: "Input",
      value: local!input,
      saveInto: local!input
   )
)

Suggestion : 4

Why do lambdas defined in a loop with different values all return the same result?,What are the rules for local and global variables in Python?,In Python, variables that are only referenced inside a function are implicitly global. If a variable is assigned a value anywhere within the function’s body, it’s assumed to be a local unless explicitly declared as global.,In order to avoid this, you need to save the values in variables local to the lambdas, so that they don’t rely on the value of the global x:

>>> x = 10 >>>
   def bar():
   ...print(x) >>>
   bar()
10
>>> x = 10 >>>
   def foo():
   ...print(x)
   ...x += 1
>>> foo()
Traceback(most recent call last):
   ...
   UnboundLocalError: local variable 'x'
referenced before assignment
>>> x = 10 >>>
   def foobar():
   ...global x
   ...print(x)
   ...x += 1 >>>
   foobar()
10
>>> print(x)
11
>>> def foo():
   ...x = 10
   ...def bar():
   ...nonlocal x
   ...print(x)
   ...x += 1
   ...bar()
   ...print(x) >>>
   foo()
10
11

Suggestion : 5

For large phone books, the difference between the O(1) lookup of the dictionary and the O(n) time for linear search over the list (or, at best, the O(log n) with the bisect module) is quite substantial.,Doing a lookup on a dictionary is fast; however, doing it unnecessarily will slow down your code, just as any extraneous lines will. One area where this surfaces is in Python’s namespace management, which heavily uses dictionaries to do its lookups.,This allows us to create entries in a set or dictionary indexed by the properties of the Point object as opposed to the memory address of the instantiated object:,Create a script that times the performance of the list-bisect method versus a dictionary for finding a number in a phone book. How does the timing scale as the size of the phone book grows?

def find_phonenumber(phonebook, name):
   for n, p in phonebook:
   if n == name:
   return p
return None

phonebook = [
   ("John Doe", "555-555-5555"),
   ("Albert Einstein", "212-555-5555"),
]
print "John Doe's phone number is", find_phonenumber(phonebook, "John Doe")
phonebook = {
   "John Doe": "555-555-5555",
   "Albert Einstein": "212-555-5555",
}
print "John Doe's phone number is", phonebook["John Doe"]
def list_unique_names(phonebook):
   unique_names = []
for name, phonenumber in phonebook: #
first_name, last_name = name.split(" ", 1)
for unique in unique_names: #
if unique == first_name:
   break
else:
   unique_names.append(first_name)
return len(unique_names)

def set_unique_names(phonebook):
   unique_names = set()
for name, phonenumber in phonebook: #
first_name, last_name = name.split(" ", 1)
unique_names.add(first_name) #
return len(unique_names)

phonebook = [
   ("John Doe", "555-555-5555"),
   ("Albert Einstein", "212-555-5555"),
   ("John Murphey", "202-555-5555"),
   ("Albert Rutherford", "647-555-5555"),
   ("Elaine Bodian", "301-555-5555"),
]

print "Number of unique names from set method:", set_unique_names(phonebook)
print "Number of unique names from list method:", list_unique_names(phonebook)
def index_sequence(key, mask = 0b111, PERTURB_SHIFT = 5):
   perturb = hash(key) #
i = perturb & mask
yield i
while True:
   i = ((i << 2) + i + perturb + 1)
perturb >>= PERTURB_SHIFT
yield i & mask
class City(str):
   def __hash__(self):
   return ord(self[0])

# We create a dictionary where we assign arbitrary values to cities
data = {
   City("Rome"): 4,
   City("San Francisco"): 3,
   City("New York"): 5,
   City("Barcelona"): 2,
}

By default, the smallest size of a dictionary or set is 8 (that is, if you are only storing three values, Python will still allocate eight elements). On resize, the number of buckets increases by 4x until we reach 50,000 elements, after which the size is increased by 2x. This gives the following possible sizes:

8, 32, 128, 512, 2048, 8192, 32768, 131072, 262144, ...

Suggestion : 6

Let's digress from HTML processing for a minute and talk about how Python handles variables. Python has two built-in functions, locals and globals, which provide dictionary-based access to local and global variables. ,local namespace - specific to the current function or class method. If the function defines a local variable x, or has an argument x, Python will use this and stop searching. ,built-in namespace - global to all modules. As a last resort, Python will assume that x is the name of built-in function or variable. ,global namespace - specific to the current module. If the module has defined a variable, function, or class called x, Python will use that and stop searching. 

    def unknown_starttag(self, tag, attrs):
       strattrs = "".join([' %s="%s"' % (key, value) for key, value in attrs])
    self.pieces.append("<%(tag)s%(strattrs)s>" % locals())
Python
from __future__
import nested_scopes

Example 8.10. Introducing locals

>>> def foo(arg):
   ...x = 1
   ...print locals()
   ...
   >>>
   foo(7) {
      'arg': 7,
      'x': 1
   } >>>
   foo('bar') {
      'arg': 'bar',
      'x': 1
   }

Look at the following block of code at the bottom of BaseHTMLProcessor.py: 

if __name__ == "__main__":
   for k, v in globals().items():
   print k, "=", v

Now running the script from the command line gives this output (note that your output may be slightly different, depending on your platform and where you installed Python): 

c: \docbook\ dip\ py > python BaseHTMLProcessor.py
c:\docbook\dip\py> python BaseHTMLProcessor.py
SGMLParser = sgmllib.SGMLParser
htmlentitydefs = <module 'htmlentitydefs' from 'C:\Python23\lib\htmlentitydefs.py'>
   BaseHTMLProcessor = __main__.BaseHTMLProcessor
   __name__ = __main__
   ... rest of output omitted for brevity...

Example 8.12. locals is read-only, globals is not 

def foo(arg):
   x = 1
print locals()
locals()["x"] = 2
print "x=", x

z = 7
print "z=", z
foo(3)
globals()["z"] = 8
print "z=", z


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