Fps Counter Download
Donnell Simon
A ChainMap class is provided for quickly linking a number of mappingsso they can be treated as a single unit. It is often much faster than creatinga new dictionary and running multiple update() calls.
A ChainMap groups multiple dicts or other mappings together tocreate a single, updateable view. If no maps are specified, a single emptydictionary is provided so that a new chain always has at least one mapping.
A user updateable list of mappings. The list is ordered fromfirst-searched to last-searched. It is the only stored state and canbe modified to change which mappings are searched. The list shouldalways contain at least one mapping.
Returns a new ChainMap containing a new map followed byall of the maps in the current instance. If m is specified,it becomes the new map at the front of the list of mappings; if notspecified, an empty dict is used, so that a call to d.new_child()is equivalent to: ChainMap(, *d.maps). If any keyword argumentsare specified, they update passed map or new empty dict. This methodis used for creating subcontexts that can be updated without alteringvalues in any of the parent mappings.
Property returning a new ChainMap containing all of the maps inthe current instance except the first one. This is useful for skippingthe first map in the search. Use cases are similar to those for thenonlocal keyword used in nested scopes. The use cases also parallel those for the built-insuper() function. A reference to d.parents is equivalent to:ChainMap(*d.maps[1:]).
The ChainMap class only makes updates (writes and deletions) to thefirst mapping in the chain while lookups will search the full chain. However,if deep writes and deletions are desired, it is easy to make a subclass thatupdates keys found deeper in the chain:
A Counter is a dict subclass for counting hashable objects.It is a collection where elements are stored as dictionary keysand their counts are stored as dictionary values. Counts are allowed to beany integer value including zero or negative counts. The Counterclass is similar to bags or multisets in other languages.
Changed in version 3.7: As a dict subclass, Counterinherited the capability to remember insertion order. Math operationson Counter objects also preserve order. Results are orderedaccording to when an element is first encountered in the left operandand then by the order encountered in the right operand.
Return a list of the n most common elements and their counts from themost common to the least. If n is omitted or None,most_common() returns all elements in the counter.Elements with equal counts are ordered in the order first encountered:
Elements are counted from an iterable or added-in from anothermapping (or counter). Like dict.update() but adds countsinstead of replacing them. Also, the iterable is expected to be asequence of elements, not a sequence of (key, value) pairs.
Several mathematical operations are provided for combining Counterobjects to produce multisets (counters that have counts greater than zero).Addition and subtraction combine counters by adding or subtracting the countsof corresponding elements. Intersection and union return the minimum andmaximum of corresponding counts. Equality and inclusion comparecorresponding counts. Each operation can accept inputs with signedcounts, but the output will exclude results with counts of zero or less.
Counters were primarily designed to work with positive integers to representrunning counts; however, care was taken to not unnecessarily preclude usecases needing other types or negative values. To help with those use cases,this section documents the minimum range and type restrictions.
The Counter class itself is a dictionary subclass with norestrictions on its keys and values. The values are intended to be numbersrepresenting counts, but you could store anything in the value field.
For in-place operations such as c[key] += 1, the value type need onlysupport addition and subtraction. So fractions, floats, and decimals wouldwork and negative values are supported. The same is also true forupdate() and subtract() which allow negative and zero valuesfor both inputs and outputs.
The multiset methods are designed only for use cases with positive values.The inputs may be negative or zero, but only outputs with positive valuesare created. There are no type restrictions, but the value type needs tosupport addition, subtraction, and comparison.
Though list objects support similar operations, they are optimized forfast fixed-length operations and incur O(n) memory movement costs forpop(0) and insert(0, v) operations which change both the size andposition of the underlying data representation.
If maxlen is not specified or is None, deques may grow to anarbitrary length. Otherwise, the deque is bounded to the specified maximumlength. Once a bounded length deque is full, when new items are added, acorresponding number of items are discarded from the opposite end. Boundedlength deques provide functionality similar to the tail filter inUnix. They are also useful for tracking transactions and other pools of datawhere only the most recent activity is of interest.
In addition to the above, deques support iteration, pickling, len(d),reversed(d), copy.copy(d), copy.deepcopy(d), membership testing withthe in operator, and subscript references such as d[0] to accessthe first element. Indexed access is O(1) at both ends but slows to O(n) inthe middle. For fast random access, use lists instead.
A round-robin scheduler can be implemented withinput iterators stored in a deque. Values are yielded from the activeiterator in position zero. If that iterator is exhausted, it can be removedwith popleft(); otherwise, it can be cycled back to the end withthe rotate() method:
To implement deque slicing, use a similar approach applyingrotate() to bring a target element to the left side of the deque. Removeold entries with popleft(), add new entries with extend(), and thenreverse the rotation.With minor variations on that approach, it is easy to implement Forth stylestack manipulations such as dup, drop, swap, over, pick,rot, and roll.
Return a new dictionary-like object. defaultdict is a subclass of thebuilt-in dict class. It overrides one method and adds one writableinstance variable. The remaining functionality is the same as for thedict class and is not documented here.
The first argument provides the initial value for the default_factoryattribute; it defaults to None. All remaining arguments are treated the sameas if they were passed to the dict constructor, including keywordarguments.
When each key is encountered for the first time, it is not already in themapping; so an entry is automatically created using the default_factoryfunction which returns an empty list. The list.append()operation then attaches the value to the new list. When keys are encounteredagain, the look-up proceeds normally (returning the list for that key) and thelist.append() operation adds another value to the list. This technique issimpler and faster than an equivalent technique using dict.setdefault():
When a letter is first encountered, it is missing from the mapping, so thedefault_factory function calls int() to supply a default count ofzero. The increment operation then builds up the count for each letter.
The function int() which always returns zero is just a special case ofconstant functions. A faster and more flexible way to create constant functionsis to use a lambda function which can supply any constant value (not justzero):
Named tuples assign meaning to each position in a tuple and allow for more readable,self-documenting code. They can be used wherever regular tuples are used, andthey add the ability to access fields by name instead of position index.
Returns a new tuple subclass named typename. The new subclass is used tocreate tuple-like objects that have fields accessible by attribute lookup aswell as being indexable and iterable. Instances of the subclass also have ahelpful docstring (with typename and field_names) and a helpful __repr__()method which lists the tuple contents in a name=value format.
Any valid Python identifier may be used for a fieldname except for namesstarting with an underscore. Valid identifiers consist of letters, digits,and underscores but do not start with a digit or underscore and cannot bea keyword such as class, for, return, global, pass,or raise.
If rename is true, invalid fieldnames are automatically replacedwith positional names. For example, ['abc', 'def', 'ghi', 'abc'] isconverted to ['abc', '_1', 'ghi', '_3'], eliminating the keyworddef and the duplicate fieldname abc.
defaults can be None or an iterable of default values.Since fields with a default value must come after any fields without adefault, the defaults are applied to the rightmost parameters. Forexample, if the fieldnames are ['x', 'y', 'z'] and the defaults are(1, 2), then x will be a required argument, y will default to1, and z will default to 2.
In addition to the methods inherited from tuples, named tuples supportthree additional methods and two attributes. To prevent conflicts withfield names, the method and attribute names start with an underscore.
Changed in version 3.8: Returns a regular dict instead of an OrderedDict.As of Python 3.7, regular dicts are guaranteed to be ordered. If theextra features of OrderedDict are required, the suggestedremediation is to cast the result to the desired type:OrderedDict(nt._asdict()).
Ordered dictionaries are just like regular dictionaries but have some extracapabilities relating to ordering operations. They have become lessimportant now that the built-in dict class gained the abilityto remember insertion order (this new behavior became guaranteed inPython 3.7).
Move an existing key to either end of an ordered dictionary. The itemis moved to the right end if last is true (the default) or to thebeginning if last is false. Raises KeyError if the key doesnot exist:
Equality tests between OrderedDict objects are order-sensitiveand are implemented as list(od1.items())==list(od2.items()).Equality tests between OrderedDict objects and otherMapping objects are order-insensitive like regulardictionaries. This allows OrderedDict objects to be substitutedanywhere a regular dictionary is used.
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