shapeshifter package¶
Submodules¶
shapeshifter.shapeshifter module¶
-
class
shapeshifter.shapeshifter.
ShapeShifter
(file_path, file_type=None)¶ Bases:
object
Creates a ShapeShifter object, which represents a file to be transformed.
Parameters: - file_path (str) – Name of a file path to read and perform operations on.
- file_type (str) – Name of the type of file that is being read.
-
export_filter_results
(out_file_path, out_file_type=None, filters=None, columns=[], transpose=False, include_all_columns=False, gzip_results=False, index='Sample')¶ Filters and then exports data to a file.
Parameters: - out_file_path (str) – Name of the file that results will be saved to.
- out_file_type (str, default None) – Name of the file format results will be saved to. If None, the type will be inferred from the file path.
- filters (str, default None) – Query or filter to apply to the data set written in Python logic.
- columns (list of str, default []) – Names of columns to include in the output. If blank and no filter is specified, all columns will be included.
- transpose (bool, default False) – If True, index and columns will be transposed in the output file.
- include_all_columns (bool, default False) – Indicates whether to include all columns in the output. If True, overrides columnList.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
Returns: None
-
export_query_results
(out_file_path, out_file_type=None, columns=[], continuous_queries=[], discrete_queries=[], transpose=False, include_all_columns=False, gzip_results=False)¶ Filters and exports data to a file. Similar to export_filter_results, but takes filters in the form of ContinuousQuery and DiscreteQuery objects, and has slightly less flexible functionality
Parameters: - out_file_path (str) – Name of the file that results will be saved to.
- out_file_type (str, default None) – Name of the file format results will be saved to. If None, the type will be inferred from the file path.
- columns (list of str, default []) – Names of columns to include in the output. If blank and no filter is specified, all columns will be included.
- continuous_queries (list of ContinuousQuery.) – Objects representing queries on a column of continuous data.
- discrete_queries (list of DiscreteQuery) – Objects representing queries on a column of discrete data.
- transpose (bool, default False) – If True, index and columns will be transposed in the output file.
- include_all_columns (bool, default False) – Indicates whether to include all columns in the output. If True, overrides columnList.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
Returns: None
-
get_all_columns_info
()¶ Retrieves the column name, data type, and all unique values from every column in a file.
Returns: Name, data type (continuous/discrete), and unique values from every column. Return type: dictionary where key: column name and value:ColumnInfo object containing the column name, data type (continuous/discrete), and unique values from all columns
-
get_column_info
(columnName: str, sizeLimit: int = None)¶ Retrieves a specified column’s name, data type, and all its unique values from a file.
Parameters: - columnName (str) – The name of the column about which information is being obtained.
- sizeLimit (int) – limits the number of unique values returned to be no more than this number.
Returns: Name, data type (continuous/discrete), and unique values from specified column
Return type: ColumnInfo object
-
get_column_names
() → list¶ Retrieves all column names from a dataset stored in a parquet file :type parquetFilePath: string :param parquetFilePath: filepath to a parquet file to be examined
Returns: All column names Return type: list
-
get_filtered_samples
(continuous_queries, discrete_queries)¶
-
merge_files
(file_list, out_file_path, out_file_type=None, gzip_results=False, on=None, how='inner')¶ Merges multiple ShapeShifter-compatible files into a single file.
Parameters: - file_list (list of str) – File paths representing files that will be merged with the file in this ShapeShifter object.
- out_file_path (str) – File path where the output of merging the files will be stored.
- out_file_type (str, default None) – Name of the file format that results will be saved to. If None, the type will be inferred from the file path.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
- on (str, default None) – Column or index level names to join on. These must be found in all files. If on is None and not merging on indexes then this defaults to the intersection of the columns in all.
Returns: None
-
peek
(numRows=10, numCols=10)¶ Takes a look at the first few rows and columns of a parquet file and returns a Pandas DataFrame corresponding to the number of requested rows and columns
Parameters: - numRows (int, default 10) – the number of rows the returned Pandas DataFrame will contain.
- numCols (int, default 10) – the number of columns the returned Pandas DataFrame will contain.
Returns: The first numRows and numCols in the given parquet file
Return type: Pandas DataFrame
-
peek_by_column_names
(listOfColumnNames, numRows=10, indexCol='Sample')¶ Takes a look at a portion of the file by showing only the requested columns.
Parameters: - listOfColumnNames (list of str) – Names of columns that will be given in the output.
- numRows (int, default 10) – The number of rows that will be shown with the requested columns in the output.
- indexCol (str, default 'Sample') – Name of the column that will be the index column in the DataFrame.
Returns: Pandas DataFrame with only the requested columns and number of rows.
Module contents¶
-
class
shapeshifter.
ShapeShifter
(file_path, file_type=None)¶ Bases:
object
Creates a ShapeShifter object, which represents a file to be transformed.
Parameters: - file_path (str) – Name of a file path to read and perform operations on.
- file_type (str) – Name of the type of file that is being read.
-
export_filter_results
(out_file_path, out_file_type=None, filters=None, columns=[], transpose=False, include_all_columns=False, gzip_results=False, index='Sample')¶ Filters and then exports data to a file.
Parameters: - out_file_path (str) – Name of the file that results will be saved to.
- out_file_type (str, default None) – Name of the file format results will be saved to. If None, the type will be inferred from the file path.
- filters (str, default None) – Query or filter to apply to the data set written in Python logic.
- columns (list of str, default []) – Names of columns to include in the output. If blank and no filter is specified, all columns will be included.
- transpose (bool, default False) – If True, index and columns will be transposed in the output file.
- include_all_columns (bool, default False) – Indicates whether to include all columns in the output. If True, overrides columnList.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
Returns: None
-
export_query_results
(out_file_path, out_file_type=None, columns=[], continuous_queries=[], discrete_queries=[], transpose=False, include_all_columns=False, gzip_results=False)¶ Filters and exports data to a file. Similar to export_filter_results, but takes filters in the form of ContinuousQuery and DiscreteQuery objects, and has slightly less flexible functionality
Parameters: - out_file_path (str) – Name of the file that results will be saved to.
- out_file_type (str, default None) – Name of the file format results will be saved to. If None, the type will be inferred from the file path.
- columns (list of str, default []) – Names of columns to include in the output. If blank and no filter is specified, all columns will be included.
- continuous_queries (list of ContinuousQuery.) – Objects representing queries on a column of continuous data.
- discrete_queries (list of DiscreteQuery) – Objects representing queries on a column of discrete data.
- transpose (bool, default False) – If True, index and columns will be transposed in the output file.
- include_all_columns (bool, default False) – Indicates whether to include all columns in the output. If True, overrides columnList.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
Returns: None
-
get_all_columns_info
()¶ Retrieves the column name, data type, and all unique values from every column in a file.
Returns: Name, data type (continuous/discrete), and unique values from every column. Return type: dictionary where key: column name and value:ColumnInfo object containing the column name, data type (continuous/discrete), and unique values from all columns
-
get_column_info
(columnName: str, sizeLimit: int = None)¶ Retrieves a specified column’s name, data type, and all its unique values from a file.
Parameters: - columnName (str) – The name of the column about which information is being obtained.
- sizeLimit (int) – limits the number of unique values returned to be no more than this number.
Returns: Name, data type (continuous/discrete), and unique values from specified column
Return type: ColumnInfo object
-
get_column_names
() → list¶ Retrieves all column names from a dataset stored in a parquet file :type parquetFilePath: string :param parquetFilePath: filepath to a parquet file to be examined
Returns: All column names Return type: list
-
get_filtered_samples
(continuous_queries, discrete_queries)¶
-
merge_files
(file_list, out_file_path, out_file_type=None, gzip_results=False, on=None, how='inner')¶ Merges multiple ShapeShifter-compatible files into a single file.
Parameters: - file_list (list of str) – File paths representing files that will be merged with the file in this ShapeShifter object.
- out_file_path (str) – File path where the output of merging the files will be stored.
- out_file_type (str, default None) – Name of the file format that results will be saved to. If None, the type will be inferred from the file path.
- gzip_results (bool, default False) – Indicates whether the resulting file will be gzipped.
- on (str, default None) – Column or index level names to join on. These must be found in all files. If on is None and not merging on indexes then this defaults to the intersection of the columns in all.
Returns: None
-
peek
(numRows=10, numCols=10)¶ Takes a look at the first few rows and columns of a parquet file and returns a Pandas DataFrame corresponding to the number of requested rows and columns
Parameters: - numRows (int, default 10) – the number of rows the returned Pandas DataFrame will contain.
- numCols (int, default 10) – the number of columns the returned Pandas DataFrame will contain.
Returns: The first numRows and numCols in the given parquet file
Return type: Pandas DataFrame
-
peek_by_column_names
(listOfColumnNames, numRows=10, indexCol='Sample')¶ Takes a look at a portion of the file by showing only the requested columns.
Parameters: - listOfColumnNames (list of str) – Names of columns that will be given in the output.
- numRows (int, default 10) – The number of rows that will be shown with the requested columns in the output.
- indexCol (str, default 'Sample') – Name of the column that will be the index column in the DataFrame.
Returns: Pandas DataFrame with only the requested columns and number of rows.


dev* 2018
Yeah, old joke...
Recursion in computer science is a method of solving a problem where the solution depends on solutions to smaller instances of the same problem (as opposed to iteration). The approach can be applied to many types of problems, and recursion is one of the central ideas of computer science. |
🤔 |
int factorial(int n) {
int res = 1;
for (int i=1; i<=n; i++) {
res = res * i;
}
return res;
}
With mutation included, as iteration often does.
Standard response of functional languages: recursion!
factorial 0 = 1
factorial n = n * factorial (n-1)
Maybe elegant but there's a problem...
It's not tail recursive -> will blow up stack usage
(define (length lst)
(cond
[(empty? lst) 0]
[else (+ 1 (length lst))]))
But there’s a bug not easily seen!
This is in Scheme, so is this a...
•_•)
( •_•)>⌐■-■
(⌐■_■)
... Recursion Scheme?
Recursion is dangerous!
Do we really need recursion?
factorial n = foldr (*) 1 [1..n]
No recursion to be seen! But what is this “fold” thing?
more Haskell factorials: https://www.willamette.edu/~fruehr/haskell/evolution.html
Can we “package” all kinds of recursion?
Could we even have a usable programming language without any kind of explicit recursive calls?
 No need to make this, but as an example...
data MyListF elem rest = NilF | ConsF elem rest deriving Functor
type List t = Fix (MyListF t)
nil = Fix NilF -- make an empty list
cons x xs = Fix (ConsF x xs) -- cons a value in front of a list
-- our "algorithm" to sum list elements would be just:
sumAlg = \case
NilF -> 0 -- sum of an empty list is 0
ConsF x xs -> x + xs -- add the current value to others
-- execute our algorithm by giving it to some library function
exampleSum = doStuff sumAlg
-- > exampleSum (cons 4 $ cons 12 $ cons 7 nil) -- [4, 12, 7]
-- 23
-- This general library function still needs explicit recursion
doStuff alg = unfix >>> -- unwrap from the Fix point
fmap (doStuff alg) -- apply algorithm recursively
>>> alg -- apply to the final value
-- "alg" was not an abreviation of "algorithm", but of "Algebra"
type Algebra f a = f a -> a
-- Complete implementation for 'sum' would thus be the
-- following (using recursion-schemes library), which neatly
-- contains only the algorithmic part without any recursion
sum :: [Int] -> Int
sum = cata $ \case
Nil -> 0
Cons x xs -> x + xs
Sum is just a regular fold, so the famous fold is just one of the recursion schemes, namely catamorphism!
-- Stream of natural numbers
data StreamF r = StreamF Natural r deriving Functor
type NatStream = Fix StreamF
-- our "algorithm" to create numbers would be
naturalsCoalg n = StreamF n (n + 1) -- for each n, next is n+1
-- same as before, seed value zero
exampleNats = doStuff naturalsCoalg 0
-- unfortunately in this example our numbers are our NatStream,
-- but we can convert it to a Haskell list with a catamorphism
exampleNaturals = cata (\case StreamF x xs -> x:xs) exampleNats
-- > take 4 exampleNaturals
-- [0,1,2,3]
-- Dual of catamorphism:
-- 1) arrows are reversed
-- 2) wrap instead of unwrap
doStuff coalg = Fix <<< fmap (doStuff coalg) <<< coalg
-- "coalg" is called a "Coalgebra"
type Coalgebra f a = a -> f a
-- Complete implementation using recursion-schemes library:
naturals :: [Natural]
naturals = ana (\n -> Cons n (n + 1)) 0
So, generating an infinite stream is just one of the recursion schemes, namely anamorphism!
in Data.Tuple.Extra
or Control.Arrow
or Control.Category.Cartesian
-- for functions:
(&&&) :: (a -> b) -> (a -> c) -> a -> (b, c)
-- for any category:
(&&&) :: a b c -> a b c' -> a b (c, c')
"split a value to two different paths”
-- Natural numbers as Peano
data NatF r = ZeroF | SuccF r deriving Functor
type Nat = Fix NatF
zero = Fix ZeroF
succ = Fix . SuccF
factorialAlg = \case
ZeroF -> 1
SuccF (cur, r) -> (toNat cur + 1) * r
-- unfortunately our example numbers are Peano, but we
-- can use catamorphism to transform to regular numbers
where toNat = cata $ \case
ZeroF -> 0
SuccF n -> n + 1
exampleFactorial = doStuff factorialAlg
-- > exampleFactorial (succ (succ (succ zero))) -- 3
-- 6
doStuff alg = unfix >>> fmap (id &&& doStuff alg) >>> alg
-- here "alg" is called an "RAlgebra"
type RAlgebra f a = f (Fix f, a) -> a
-- Complete implementation using recursion-schemes library:
factorial :: Natural -> Natural
factorial = para $ \case
Nothing -> 1
Just (n, r) -> (n+1) * r
Thus, catamorphism with access to the current input value is called a paramorphism!
dual for fan out
in Control.Arrow
or Control.Category.Cartesian
(|||) :: a b d -> a c d -> a (Either b c) d
“split a valut to one of two different paths”
rangeCoalg to = \case
n | n == to -> ConsF n (Left nil)
n -> ConsF n (Right (n + 1))
exampleRange_ from to = doStuff (rangeCoalg to) from
-- have to convert our List type to the Haskell list again...
exampleRange from to = cata (\case
NilF -> []
ConsF x xs -> x:xs
) (exampleRange_ from to)
-- > exampleRange 0 4
-- [0,1,2,3,4]
doStuff coalg = Fix <<< fmap (id ||| doStuff coalg) <<< coalg
-- here "coalg" is called an "RCoalgebra":
type RCoalgebra f a = a -> f (Either (Fix f) a)
-- Complete implementation using recursion-schemes library:
range :: Int -> Int -> [Int]
range from to = flip apo from $ \case
n | n == to -> Cons n (Left [])
n -> Cons n (Right (n + 1))
That is: anamorphism terminating at some chosen point, is called an apomorphism!
Free Monad:
data Free f a = Pure a | Free (f (Free f a))
Cofree Comonad:
data Cofree f a = a :< (f (Cofree f a))
Kind of minimal way to provide monadic or comonadic structure
Sometimes we need access to the previous values
-- using Cofree Comonad here to bring comonadic structure...
fibonacciAlg ZeroF = 0
fibonacciAlg (SuccF (_ :< ZeroF)) = 1
fibonacciAlg (SuccF (a :< SuccF (b :< _))) = a + b
exampleFibonacci = doStuff fibonacciAlg
-- > exampleFibonacci (succ (succ (succ zero))) -- 3
-- 2
doStuff alg = f >>> (\(x :< _) -> x)
where f = unfix >>> fmap f >>> (alg &&& id) >>> uncurry (:<)
-- here "alg" is called a "CVAlgebra"
type CVAlgebra f a = f (Cofree f a) -> a
-- Complete implementation using recursion-schemes library:
fibonacci :: Natural -> Natural
fibonacci = histo $ \case
Nothing -> 0
Just (_ :< Nothing) -> 1
Just (a :< Just (b :< _)) -> a + b
Paramorphism providing the whole history instead of the current value is called a histomorphism!
Apomorphism let us terminate once, but now we need to terminate multiple times with a value (word)
capitalizeWordsCoalg "" = NilF
capitalizeWordsCoalg str = let
ws = words str
(first,rest) = (head ws, tail ws)
capitalized = toUpper (head first) : tail first
in ConsF capitalized (Pure $ unwords rest)
exampleCapitalizeWords_ = doStuff capitalizeWordsCoalg
exampleCapitalizeWords str = unwords $ cata (\case
NilF -> []
ConsF x xs -> x:xs
) (exampleCapitalizeWords_ str)
-- > exampleCapitalizeWords "foo bar"
-- "Foo Bar"
doStuff coalg = Fix <<< fmap worker <<< coalg
where worker (Pure a) = doStuff coalg a
worker (Free a) = Fix (fmap worker a)
-- here "coalg" is called a "CVCoalgebra":
type CVCoalgebra f a = a -> f (Free f a)
-- Complete implementation using recursion-schemes library:
capitalizeWords :: String -> String
capitalizeWords = unwords . futu (\case
"" -> Nil
str -> let ws = words str
(first,rest) = (head ws, tail ws)
capitalized = toUpper (head first) : tail first
in Cons capitalized (Pure $ unwords rest))
Whereas histomorphism extended paramorphism to the whole history, futumorphism extends apomorphism to the whole future!
-- filtering of a List-functor with a predicate function
filter _ Nil = Nil
filter pred x@(Cons h _)
| pred h = x
| otherwise = Nil
takeWhile :: (a -> Bool) -> [a] -> [a]
takeWhile pred = prepro (filter pred) $ \case
Nil -> []
(Cons x xs) -> x:xs
Prepromorphism is like a catamorphism but executes a natural transformation before the actual stuff
With Apomorphism we could terminate the recursion, but it would be nicer if we could work on infinite streams and cap them with an external function.
-- use whatever generator function
generate f n = Cons n (f n)
-- now both filtering and stream generation are nicely separated from recursion
range :: (Num a, Ord a) => a -> a -> [a]
range from to = postpro (filter (<= to)) (generate (+1)) from
Postpromorphism is like an anamorphism but executes a natural transformation after the actual stuff
Many times a problem involves multiple recursions.
For example: Merge sort
using ana + cata is called a hylomorphism
hylo :: Functor f => Algebra f b -> Coalgebra f a -> a -> b
hylo alg coalg = ana coalg >>> cata alg
Can be implemented without actually invoking cata or ana.
Also it seems that the compiler can optimize away all our imaginary structure used to define Algebra and Coalgebra! *
* http://fho.f12n.de/posts/2014-05-07-dont-fear-the-cat.html
One can also combine Futumorphism + Histomorphism:
chrono :: Functor f => CVAlgebra f b -> CVCoalgebra f a -> a -> b
chrono cvalg cvcoalg = futu cvcoalg >>> histo cvalg
Sometimes we need to short circuit our hylomorphism during construction
elgot :: Functor f => Algebra f b -> (a -> Either b (f a)) -> a -> b
or during destruction
coelgot :: Functor f => ((a, f b) -> b) -> Coalgebra f a -> a -> b
Sorting algorithms tend to be different combinations of specific recursion patterns.
Many (if not all?) sorting algorithms can be defined elegantly with suitable recursion schemes.
| merge-sort | hylomorfismi |
| quick-sort | hylomorfismi |
| insertion-sort | apomorfismi |
| selection-sort | paramorphism |
| data | finite |
| codata | infinite |
Different algebras deal with data. They provide recursion.
Different coalgebras deal with codata. They provide corecursion.
Some functions are total for data but not for codata (e.g. length).
Some functions are total for codata but not for data (e.g. head).
In a total language (not Haskell!) the difference is important, since all functions must always terminate and never fail.
If our language separated data and codata,
could we have safe recursion for data and safe corecursion for codata?!?
| catamorphism | “romauttaminen” | type Algebra f a = f a -> a |
| anamorphism | “hajauttaminen” | type Coalgebra f a = a -> f a |
| paramorphism | “liittäminen” | type RAlgebra f a = f (Fix f, a) -> a |
| apomorphism | “erottaminen” | type RCoalgebra f a = a -> f (Either (Fix f) a) |
| histomorphism | “historia” | type CVAlgebra f a = f (Cofree f a) -> a |
| futumorphism | “tulevaisuus” | type CVCoalgebra f a = a -> f (Free f a) |
| prepromorphism | “esikäsittely” | |
| postpromorphism | “jälkikäsittely” | |
| hylomorphism | “hajauttaminen + romauttaminen” | |
| chronomorphism | “tulevaisuus + historia” |
zygomorphism, dynamorphism, codynamorphism, elgot algebra, elgot coalgebra, metamorphism, synchromorphism, exomorphism, mutumorphism, ...
https://github.com/sellout/recursion-scheme-talk/blob/master/cheat%20sheet.pdf
Remember to learn
a category theoretical thing
every year ;)
Thank you!


But, it has some elements that can change state trough user input!
When you navigate trough different views their previous state,
as well as scroll position - will be preserved.
Try it out. Enter some values and navigate around...
name:
email:
Select of frameworks:
Checkbox of frameworks:
Ember
Angular2
AngularJS
Vue
Inferno
Preact
React
View location:
/app/views/templates/state-view.html
"/keep-state": { view: "text!views/templates/state-view.html", data: { title: "Plain text view - state handling", category: "templates" } }


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After weeks of anticipation, I've finally arrived in Cleveland, Ohio, ready to start my new job at the NASA Glenn Research Center.
What will I be doing? Great question.
My project for the next sixteen weeks centers around a system called Computer Automatic Virtual Environment (CAVE). For all you Star Trek fans, it seems directly inspired by the renowned Holodeck. CAVE features four to six 4K screens forming a small room (hence - CAVE!) in which the user immerses him or herself into a fully virtual environment! The Glenn Research Center programs two categories of simulations for CAVE: explanatory (informing the public about NASA) and exploratory (researching space and other exciting fields).
While I don't know my specific assignments yet, my first day on the job is sure to be filled with objectives, training, and space puns. Follow and learn with me as I fulfill every nerd's dream, and check back frequently for updates on my internship, life at NASA, and the world of virtual reality!


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Specialization: Volumetric Lighting in DirectX11


Braiding The Blockchain
Transcript By: Bryan Bishop
Tags: Miners
Category: Conference
Braiding the blockchain
Bob McElrath (bsm117532)
slides: https://scalingbitcoin.org/hongkong2015/presentations/DAY2/2_breaking_the_chain_1_mcelrath.pdf
video: https://www.youtube.com/watch?v=fst1IK_mrng&feature=youtu.be&t=2h17m20s
I work for SolidX in New York. I am here to tell you about some modifications to the blockchain. All the things we heard yesterday about the block size, come down to the existence of orphans. The reason why we have these problems are orphans. These are consequences of physics and resources. This is not a fundamental property in Bitcoin. ((Transcripter’s note: basically, only sharding can make local bandwidth less of an issue. Block size limit is not only for the orphan rate.))
An orphan is when two miners don’t know about the existence of other blocks. Someone cannot propagate their block fast enough. Any time you have multiple writers, Bitcoin has no locks. No matter what we do with IBLT or weak blocks, we will still have this problem. We don’t have to deprive a miner from profit.
What if the orphan block has no double spending? What if it contains a duplicate transaction? It’s not a double-spend. It’s a spend of the same UTXO. It’s not a problem if we see the same thing twice. If this new block contains no conflicting transactions and, why not just call it a sibling instead of an orphan? We can allow a miner to be paid for this sibling block.
We have two chaintips, we don’t know which one to follow, some miner in the future needs to tie them together and make a single changetip, to indicate that there’s no conflict. The miner will assert that there is no transaction conflict in the entire subset of all the blocks. If you want to get rid of orphans, blocks must have multiple parents. Let’s say there was a double-spend in this new block, then this forms a new chaintip, we have to evaluate the amount of work in B and C, and pick which one to work on top of. When there is a double spend, we must pick one.
A block can have multiple parents. This adds lots of complexity. This is a directed acyclic graph. That’s the name of the data structure. What if we just take blocks and we throw them out as fast as we can, let them have multiple parents, could we make sense of this mess? Can we evaluate the amount of work? Can we track changetips in a DAG chain? In many ways, it’s a linked list data structure. You cannot add something to the end of the tip with another person adding at the same time. So let’s move to a more complex data structure.
The consequences of this linked list blockchain model includes orphan risk. DAG allows blocks with multiple parents. Blocks have parents. There are nodes and edges. Edges have direction. Points from children to parents. All of the links only go one way, that’s what directed means. There are no cycles. This is cryptographically impossible to do cycles here. If we break the hash function, we have other problems. It’s not a line, it’s a graph.
DAGs can be partially-ordered in linear time. I can order the success of transactions in linear time. We have to make one more transaction relative to a general DAG. I am going to call this a braid.
I have drawn a graph at the top. A braid is a directed acyclic graph with none of the red links up there. Each block can have multiple parents. A block cannot name its own grandparent as its parent. So no incest. Mommy and grandpa can’t have babies because that’s gross. I am going to call the analog of a Bitcoin block something called a “bead”. This is not a blockchain, so new data structure names. A sibling is a bead that cannot be partial ordered relative to their pairs. And incest is a parent that is simultaneously an ancestor of another parent. I cannot name anything back to the genesis block as a parent. I can already order the DAG using the parent information itself. Adding information about a grandparent doesn’t add any new information that I didn’t already have.
This is not a straight DAG, it’s a slight restriction on a DAG. I am going to add an incentive. I am going to explicitly incentivize quickly transmitting blocks. Satoshi with Bitcoin did the opposite with the blockchain data structure. He slowed this down because of the problem of people simultaneously transmitting blocks. I am going to remove block time altogether. The GHOST paper adds another way to make blocks faster, by taking into account work in another block. GHOST blocks can contain double spends. If I am an attacker and trying to make a double-spend, I can mitigate my losses on the double-side of things. I require parents must not contain conflicting transactions, just like Bitcoin but unlike GHOST.
Per node, the bead time and block time and bead target difficulty and size are all decided per node. I am assuming this data structure is a smaller faster layer below Bitcoin, and we are going to checkpoint this data structure into blocks in order to have compatibility with old bitcoind nodes. There are many ways to get this into Bitcoin. I am not going to go into detail about this or the p2p layer. That’s your job, not mine. This is a longer-term project than some of the other proposals you have heard so far.
Finally, I am going to publish these beads ex post facto just like Bitcoin does. Bitcoin-ng in a more traditional computer science way they elect a leader which dictates which transactions come next, but if I can find the leader hten I can ddos the leader.
Here’s a slightly more complex example of what happens when you have a fork. Suppose you have beads that have a double-spend between each other. Miners are going to have to choose which bead to work on. You cannot use both of those as parents. So you have to evaluate which one has more work. A consequence of the no grandparent rule (no incest), the graphs have no triangles, a triangle is explicitly naming a grandparent. These graphs have four-sided figures or higher because of that.
The beads that we mine on top of have to reference only one side of the double-spend. We have to take the subset of beads that point back to either A or B and we have to evaluate the amount of work in this subset. We have to evaluate how much work was done in that sub DAG in that sub group of transactions.
That’s the basic structure. Okay, so how do you incentivize miners? You can’t do what you do in Bitcoin. One of the consequences of Bitcoin is that, you have this rule that you can’t spend a coinbase transaction per 100 blocks. This is about making the UTXO set too large in the event of reorg. Because of the size of the earth and people do generate these siblings, then how do you cdecide who to allocate coins to until you can see both of the siblings? Instead of not allowing people to spend coins in, and letting miners create the coinbase, don’t let them. We should calculate the coinbase 100 blocks later, rather than calculating it first and not being able to spend it.
The consensus of this system, the changetip, is caused by the profit-maximizing behavior of the miners. This is what causes the whole thing to work. We need to think whether we have the consensus model right. Otherwise you will have a selfish-mining attack. I am going to propose something in a couple slides. Let’s all do some analysis in the coming days and coming years and figure out if we have the right thing with this braid.
Miners are going ot individually choose the target. The only limiting factor is CPU and bandwidth. Signatures is CPU-bound, and network is bandwidth-bound. I am going to define two quantities here. One is sibling. The sibling is an analog to Bitcoin orphans. It’s a bead that cannot be ordered to come before or after my own bead, using only the DAG’s partial order. The time is across the horizontal axis. Siblings are defined per braid tip. You don’t care about siblings with double-spends. Siblings must not have conflicting transactions. They must have a single set of UTXOs. Siblings may contain duplicate transactions. We could use IBLT, but we’re likely to have blocks with identical transactions, so we will allow that. Each sibling can be weighted a work-weighted fraction of the transaction fee. If you have two siblings and each are at the same difficulty then evenly split the transaction fee.
There is also a cohort difficulty. Cohort is group of people about the same age, like classmates in school. It’s the work of other miners in the same mining period. It’s all of the beads between my youngest parent and oldest child. I want to look at the youngest parent, in other words, miners in this model would have to retarget their mining often, and look at the latest bead that they have seen. If a miner sits for an hour and mines on the same thing, this does not create a fast network. If we want to look at the oldest child, which says someone else came along and put more transactions on it, then a miner should publish a bead quickly in order to get miners to mine on top of it quickly. So maybe the miner was trying to steal fees by becoming everyone’s sibling. We are going to disincentivize this by this quantity, or the children arrive late because of withheld blocks. The cohort difficulty will incentivize fast block transmission.
Here is a diagram of what this looks like. This is a sub-braid. On the left hand side we have A. And then a group of beads here. Siblings are relative to a particular bead. So I am asking what are the siblings of B? If any of G or B or D, eqriqieqrklewqlekqrfasdkfa… you can imagine taking B and G and D, and moving them horizontally and you can’t tell which one came first which is why they are siblings.
The youngest parent to B is C, the oldest child is F, only one parent one child in this example, but everyone in that subset there which is D and E and B, which is included in its cohort. For a quiz, think to yourself, what are the siblings of G and the cohort of G, anyone want to shout it out? Siblings of G are C, D, E, F and B. Siblings of D are B and G. Its cohort is B and D.
Here is my proposed miner incentive formula. This is a graph. There are many ways to redefine interesting quantities on this graph that we could explicitly incentivize or disincentivize. The first term is transaction fees, the other one is reward. Proportional to difficulty, the quantity di n the denominator is cohort difficulty, cohort is a better word I renamed it. I am summing over transactions that are in among my siblings.
Rather than having 25 BTC, I could mine at 1/2 difficulty and get 1/2 BTC twice as often. This is probably valuable to smaller miners. The difficulty-weighted split of fees, bigger miners get more money than smaller miners. This causes us to incentivize and optimize the p2p topology to quickly propagate blocks. We are explicitly incentivizing the work between the youngest parent and oldest child, so we want to transmit thing quickly. The p2p topology in bitcoin is quite random right now, and could be optimized.
This means that smaller miners could mine without joining funds. I am pulling p2pool (( http://p2pool.in/ )) into bitcoin itself. Optimizing the p2p topology makes censorship much more easy. Bitcoin has a linear, you just add up in each one, this is simplistic. Which braid has more work?
Getting rid of orphans forces the braid structure. Transaction volume is limited by bandwidth and CPU. Confirmation time can be much faster, we can throw out blocks as fast as possible, and we can do it as much as we can propagate blocks, which is limited by the size of the planet. We don’t have to solve the NP-complete traveling salesman problem. Miner income can become much more smooth and more predictable. There are many ways to insert this into Bitcoin, and I am sure we will discuss this in the future. Smaller miners don’t have huge pools, which is miner decentralization.
Q: You say miners can choose their own difficulty. Is there a limit on not doing empty blocks? It comes to mind that they can produce infinite difficulty blocks and mess with the network.
A: How to get this into bitcoin is a good question. Should there be a minimum difficulty floor is what you are asking?
Q: Many low-difficulty empty blocks would be a problem.
A: Possibly. I have not done that explicitly yet.
Q: Selfish mining?
A: Selfish mining happens because of orphans. It doesn’t work here. ((Er, there are orphans. And there are incentives about not including transactions.))
Q: Orphan risk?
A: Yes, you have branches.
Q: What is the difference?
A: Fees are split evenly. There’s no difference. Each miner has to choose which one to mine on. Satoshi’s analysis baout 51% is correct for this, but not for bitcoin due to selfish mining.
Q: Am I right to say, I should mine an …
A: Why?
Q: Because there can’t be any…
A: If you want to get some transaction fees, …
Q: ..
A: It would be zero. No split.
Q: …
A: The reaosn why consensus works in Bitcoin is because miners are forced to choose which branch to take.   That choice is very important. We have to force miners to pick one.
Q: Conflicting transactions?
A: Someone could publish a whole bunch of conflicting transactions? And lots of new changetips? Someone can do that in bitcoin too. The only one that matters are the ones that get mined. We could switch to a model where we get rid of p2p relay, and we mine everything. Throwing out transactions for free is not a problem. Only when they get mined, then I have to evaluate which one is what. It’s an attack, but it’s also an attack in Bitcoin. It’s not something new.
Q: If there is a split or fork or orphan, how do you pick which of the two braids to mine?
A: Miner utilization is 100%. Miner utilization goes down if there are double-spends. We want miners to choose. That’s their job. Their job is to pick one, and create a chain of consensus.


Congratulations. You have won {{ newItemsData.length }} Spin. 1">Congratulations. You have won {{ newItemsData.length }} Spins. Please proceed to the Spinner page to use your spins to earn points.


Model Name:
FLL Robot 2015 - Builderdude35
Number of Bricks: 181
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| 4 x | 4494222 | WEDGE-BELT WHEEL Ø24 - Medium Stone Grey |
| 2 x | 4568006 | MOTORCYCLE RIM Ø 75 - Dark Stone Grey |
| 2 x | 4567999 | MOTORCYCLE TYRE Ø 94.2 - Black |
| 10 x | 6024581 | CABLE 250 MM - Black,Transparent |
| 2 x | 6008919 | MS, EV3, SENSOR, COLOUR - White,Bright Red,Black,Medium Blue,Medium Stone Grey |
| 1 x | 6008577 | SMALL MOTOR - White,Bright Red,Medium Stone Grey,Silver Metallic |
| 2 x | 6057952 | MS 2013 ENGINE - White,Bright Red,Medium Stone Grey |
| 1 x | 6009996 | MS-EV3, P-BRICK - White,Transparent,Medium Stone Grey,Dark Stone Grey,Silver Metallic |
| 2 x | 4142822 | TECHNIC 3M BEAM - Black |
| 2 x | 4142135 | TECHNIC 5M BEAM - Black |
| 2 x | 4495935 | TECHNIC 7M BEAM - Black |
| 2 x | 4645732 | TECHNIC 9M BEAM - Black |
| 1 x | 4562805 | TECHNIC 11M BEAM - Bright Red |
| 2 x | 4542573 | TECHNIC 15M BEAM - Black |
| 4 x | 4142823 | TECHNIC ANG. BEAM 3X5 90 DEG. - Black |
| 2 x | 4111998 | DOUBLE ANGULAR BEAM 3X7 45° - Black |
| 4 x | 4239601 | 1/2 BUSH - Bright Yellow |
| 5 x | 4142865 | 2M CROSS AXLE W. GROOVE - Bright Red |
| 1 x | 4211375 | BALL W. CROSS AXLE - Medium Stone Grey |
| 42 x | 4121715 | CONNECTOR PEG W. FRICTION - Black |
| 6 x | 4211815 | CROSS AXLE 3M - Medium Stone Grey |
| 2 x | 4227155 | BUSH FOR CROSS AXLE - Bright Red |
| 6 x | 4184169 | BALL WITH FRICTION SNAP - Black |
| 17 x | 4206482 | CONN.BUSH W.FRIC./CROSSALE - Bright Blue |
| 16 x | 4514553 | CONNECTOR PEG W. FRICTION 3M - Bright Blue |
| 1 x | 4514554 | 3M CONNECTOR PEG - Brick Yellow |
| 2 x | 4513174 | CROSS AXLE, EXTENSION, 2M - Bright Red |
| 2 x | 4254606 | ANGLE ELEMENT, 0 DEGREES [1] - Bright Red |
| 1 x | 4211639 | CROSS AXLE 5M - Medium Stone Grey |
| 3 x | 4188298 | CROSS BLOCK 90° - Bright Red |
| 2 x | 4211758 | HUB Ø11,2 X 7,84 - Medium Stone Grey |
| 2 x | 6006140 | BEAM 1X2 W/CROSS AND HOLE - Black |
| 2 x | 4211865 | 2M FRIC. SNAP W/CROSS HOLE - Medium Stone Grey |
| 1 x | 4211805 | CROSS AXLE 7M - Medium Stone Grey |
| 4 x | 4128598 | DOUBLE CROSS BLOCK - Bright Red |
| 4 x | 4234429 | ANGLE ELEMENT, 180 DEGREES [2] - Bright Red |
| 7 x | 4175442 | CROSS BLOCK 3M - Bright Red |
| 1 x | 4535768 | CROSS AXLE 9M - Medium Stone Grey |
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| 2 x | 4640536 | GEAR WHEEL Z16 - Medium Stone Grey |


You get the API token on todoist.com in the settings under Integration.
API-Key
Minimize log events
Every run creates log entries. Writing log events can be opted out here.


var Type = require('type-of-is');
var Type = require('type-of-is');
var Route = require('./Route');
var NotFound = require('./NotFound');
function Router (routes) {
this._routes = [];
this._not_found = null;
this._not_found_path = '/404';
if (arguments.length === 1) {
this.addRoutes(routes);
}
}
Regular expression for matching HTTP verb prefix in routes
var _METHOD_PREFIX_REGEXP = /^(GET|HEAD|POST|UPDATE|DELETE) /;
Add a single route
Router.prototype.addRoute = function addRoute (route_name, route_pattern) {
if (arguments.length !== 2) {
throw new TypeError('addRoute expects two arguments: (route_name, route_pattern)');
}
var routes = {};
routes[route_name] = route_pattern;
this.addRoutes(routes);
};
Add multiple routes. Routes can be specified as plain string or as object with pattern and method attributes
Router.prototype.addRoutes = function addRoutes (routes) {
if (arguments.length !== 1) {
throw new TypeError('addRoutes expects argument with { routename1 : routepattern 1, ...}');
}
for (var route_name in routes) {
if (!routes.hasOwnProperty(route_name)) {
continue;
}
var route = routes[route_name];
var pattern;
var method;
if (Type(route, String)) {
pattern = route;
method = null;
check for a HTTP verb prefix
var method_prefix = pattern.match(_METHOD_PREFIX_REGEXP);
if (method_prefix) {
pattern = pattern.slice(method_prefix[0].length);
method = method_prefix[1];
}
} else if (Type(route, Object) && route.hasOwnProperty('pattern')) {
pattern = route.pattern;
method = ('method' in route) ? route.method : null;
} else {
throw new TypeError('Route pattern must be String or Object with pattern property');
}
route = new Route({
pattern : pattern,
method : method,
name : route_name
});
this._routes.push(route);
}
};
Find a route by its name
Router.prototype.route = function route (name) {
var num_routes = this._routes.length;
Look through the routes for a route with matching name
for (var i = 0; i < num_routes; i++) {
var route = this._routes[i];
if (route.name === name) {
return route;
}
}
return null;
};
Optionally register a function to be called when no route is matched by handle
Router.prototype.notFound = function notFound (not_found) {
this._not_found = not_found;
};
Optionally set the path that is returned in the NotFound route. This is only set when a route-based match fails, for path-based matches, the specified path is used.
Router.prototype.notFoundPath = function notFoundPath (path) {
this._not_found_path = path;
}
Process incoming request and augment request object with route
This function can be called directly when using basic http, and also invoked by connect middleware.
Router.prototype.handle = function (req, res, next) {
req.route = this.match({
path : req.url,
method : req.method
});
call the not found handler if its been set
if (req.route.notFound() && this._not_found) {
return this._not_found(req, res, next);
}
Connect looks for a function named “handle” that is expected to call next when done processing. Next is not needed when calling handle directly
if (!!next) {
next();
}
};
Checks whether there is a route matching the passed path or route data. If there is a match, it returns a MatchedRoute otherwise returns NotFound.
Router.prototype.match = function match (args) {
for (var i = 0; i < this._routes.length; i++) {
var route = this._routes[i];
var matched_route = route.match(args);
if (matched_route) {
return matched_route;
}
}
if a route arg was passed and it didn’t match anything then there’s no way to construct a path so set it to _not_found_path, which defaults to /404 and can be set via notFoundPath
var path;
if ('path' in args) {
get just the path of path
path = '/' + args.path.split('/').slice(3).join('/')
} else {
path = this._not_found_path;
}
var not_found = new NotFound(path);
return not_found;
};
module.exports = Router;


--- layout: default title: joshvito.com description: 'Josh Vito, Front End Web Developer, Artist, and all around great guy.' ---
This site is under construction, you will be directed to my LinkedIn CV shortly.
Example projects and portfolio available per request.


litepixel.js
Litepixel.js is a 2D GPU accelerated game's library based in litegl.js .
Some of the main features are:
- Do not generate garbage.
- Optimized for rendering thousand of sprites.
- Box2D physics (using emscripten version)
- PostFX
Download
You can download the full source code from GitHub, or use just the library using this link litepixel.js (compressed version)
Usage
Include the script
<script src="js/litepixel.js"></script>
Examples
Documentation
Click here to read the documentation, it is automatically generated using yui, and can be located in the doc folder.
Check also the gl-matrix documentation to a better understanding of how to operate with matrices and vectors.


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Kui Jia
✉, 1
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Code
[GitHub]
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Paper
[CVF]
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We propose a novel adversarial learning method termed Discriminative Adversarial Domain Adaptation (DADA). Based on an integrated category and domain classifier, DADA has a novel adversarial objective that encourages a mutually inhibitory relation between category and domain predictions for any input instance. Except for the traditional closed set domain adaptation, we also extend DADA for extremely challenging problem settings of partial and open set domain adaptation. |
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Given labeled instances on a source domain and unlabeled ones on a target domain, unsupervised domain adaptation aims to learn a task classifier that can well classify target instances. Recent advances rely on domain-adversarial training of deep networks to learn domain-invariant features. However, due to an issue of mode collapse induced by the separate design of task and domain classifiers, these methods are limited in aligning the joint distributions of feature and category across domains. To overcome it, we propose a novel adversarial learning method termed Discriminative Adversarial Domain Adaptation (DADA). Based on an integrated category and domain classifier, DADA has a novel adversarial objective that encourages a mutually inhibitory relation between category and domain predictions for any input instance. We show that under practical conditions, it defines a minimax game that can promote the joint distribution alignment. Except for the traditional closed set domain adaptation, we also extend DADA for extremely challenging problem settings of partial and open set domain adaptation. Experiments show the efficacy of our proposed methods and we achieve the new state of the art for all the three settings on benchmark datasets. |
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To establish a direct interaction between category and domain predictions for any source instance, we propose a novel source discriminative adversarial loss that is inspired by the principle of binary cross-entropy loss and tailored to the design of the integrated classifier. Changes of category and domain predictions when minimizing and maximizing the proposed source discriminative adversarial loss in the two cases. To achieve the joint distribution alignment, the explicit interplay between category and domain predictions for any target instance should also be created. We propose a target discriminative adversarial loss based on the design of the integrated classifier. It uses conditional category probabilities to weight the domain predictions. |
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Partial domain adaptation is a more realistic setting, where the target label space is subsumed by the source one. We extend DADA for partial domain adaptation by using a reliable category-level weighting mechanism. |
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Open set domain adaptation is a very challenging setting, where the source label space is subsumed by the target one. We extend DADA for open set domain adaptation by training the classifier to classify all target instances as the unknown category with a small probability q, which can achieve a balance between domain adaptation and outlier rejection. |
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Our proposed DADA can formally better bound the expected target error than existing domain adaptation methods, which aim to measure and minimize the F-distance or the D-distance. The FH-distance can be upper bounded by the optimal solution of DADA. |
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R1: Ablation Study In the following table, we can observe that DANN improves over No Adaptation, its result is much worse than DANN-CA, verifying the efficacy of the design of the integrated classifier. DADA (w/o em + w/o td) improves over DANN-CA and DADA (w/o em) improves over DADA (w/o em + w/o td), showing the efficacy of our proposed discriminative adversarial learning. |
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R2: Quantitative Comparison The following figure shows that our proposed DADA gives the predicted probability on the true category of any target instance a better chance to approach 1, meaning that target instances are more likely to be correctly classified by DADA, i.e., a better category-level domain alignment. Average probability on the true category over all target instances by task classifiers of different methods. |
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R3: Feature Visualization The following figure shows qualitative improvements of these methods at aligning features across data domains, i.e., the distribution of target samples (red) changes from the scattered state of DANN to multiple category-wise clusters of DADA, which are aligned with source samples (blue) of corresponding categories. |
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(a) No Adaptation |
(b) DANN |
(c) DANN-CA |
(d) DADA |
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The t-SNE visualization of feature alignment between the source (blue) and target (red) domains. |
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R4: An In-Depth Analysis of Our Training Scheme
"Rate of Source Instances Failing to Satisfy Condition" declines to a very low value in an oscillatory manner,
showing the efficacy of this training scheme in keeping the condition satisfied.
(a) MNIST→USPS (Nalter = 32) (b) USPS→MNIST (Nalter = 32) |
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R5: Comparison with SOTA Our proposed DADA outperforms existing methods, testifying the efficacy of DADA in aligning the joint distributions of feature and category across domains. Our proposed DADA consistently achieves a good result on different adaptation settings, showing its excellent robustness. Results for closed set domain adaptation on Office-31 based on ResNet-50. Results for closed set domain adaptation on Syn2Real-C based on ResNet-101. Results for closed set domain adaptation on Digits based on LeNet. |
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R1: Effects of the Number of Target Categories The following figure shows that our proposed DADA-P performs much better than DANN in all settings. It is noteworthy that the relative performance improvement becomes larger when the number of target categories decreases, testifying the superiority of our methods in reducing the influence of negative transfer. Thus, given a source domain, our methods can perform much better when applied to the target domain with unknown number of categories. |
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R2: Effects of the Number of Outlier Source Categories The following figure shows that our proposed DADA-P significantly outperforms DANN in all settings. Particularly, the relative performance improvement is larger when the number of source categories is larger, demonstrating that our methods are more robust to the number of outlier source categories. Thus, for a given target task, our methods can have a much better performance when utilizing different source tasks. |
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R3: Comparison with SOTA Our proposed DADA-P substantially outperforms all comparative methods, showing the effectiveness of DADA-P on reducing the negative influence of source outliers while promoting the joint distribution alignment in the shared label space. Results for partial domain adaptation on Syn2Real-C based on ResNet-50. Results for partial domain adaptation on Office-31 based on ResNet-50. Results for partial domain adaptation on Office-31 based on AlexNet. Results for partial domain adaptation on Office-Home based on ResNet-50. Results for partial domain adaptation on ImageNet-Caltech based on ResNet-50. |
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R1: Effects of the Small Probability As the small probability q increases, accuracies of OS and OS* decrease and the accuracy of Unknown increases, which means that the target instances are more likely classified as the unknown category. When q = 0, the objective of the feature extractor is to align the whole source domain and the whole target domain, resulting in the misclassification of all unknown target instances as the known categories. To make a trade-off, we empirically set q = 0.1 for all open set adaptation settings. |
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R2: Comparison with SOTA Our proposed DADA-O outperforms all comparative methods in both evaluation metrics of Known and Mean, showing the efficacy of DADA-O in both aligning joint distributions of the known instances and identifying the unknown target instances. Results for open set domain adaptation on Syn2Real-O based on ResNet-152. Results for open set domain adaptation on Office-31 based on AlexNet. |
@inproceedings{tang2020discriminative,
title={Discriminative adversarial domain adaptation},
author={Tang, Hui and Jia, Kui},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={34},
number={04},
pages={5940--5947},
year={2020}
}
Based on a template by Keyan Chen.


[[${user.firstName}]] [[${user.lastName}]]
Staff
Owner
Developer
User Name[[${user.userName}]]
User Name
[[${user.email}]]
Address
[[${user.address}]]
Contact
[[${user.phone}]]
Staff
Owner
Developer
User Name[[${user.userName}]]
[[${user.email}]]
[[${user.address}]]
[[${user.phone}]]


Hugo-smorg is a theme for Hugo, a fast and flexible static site engine written in Go.
This theme incorporates Bulma, a capable and easy to use responsive CSS framework and Bulmaswatch theme customizations for Bulma.
Visit github.com/solutionroute/hugo-smorg to grab or fork this theme.


I remember that, growing up, I didn’t have too many memories with my grandma. Living in different cities, I’d only see her every few months. But I remember one thing so vividly: my grandmother’s cooking. There was never a day when I thought that it wasn’t the best thing I’d ever tasted in my life. Every time I’d go to see her, it was like I was visiting a new world of flavors. She really opened my eyes to all the amazing things the world had to offer. So when I found this old diary of all of her recipes, I knew what I wanted to do. I wanted everyone else to enjoy food the way I had been able to as a kid. I hope these delicious, homely recipes will be able to bring a smile to your faces, something you can remember fondly like I do.


Our knives are the most prized possession of our esteemed kitchen. We hold them very highly in our modus operandi and there are specific practices that one should follow when interacting with them. Namely:
Finally, we are racist towards our knives as all these practices are about coloured knives. We don’t care about our generic gold and silver knives.
The guardian of the operations around knives is Flo.
We have a wide range of pans, which, in order to take care of, and because they are anti-stick pans, we should not use the harsh green side of the sponge on the inside side of the pans.
In addition, we do not put them inside the dish washing machine (or any washing machine actually).
We clean our revered house every week and we are very meticulous in keeping it clean every time we interact with any room or piece of furniture. We keep our cleaning rota at nutcroft.com and one can also subscribe for email updates every Monday 8am exactly.
The common-for-all weekly house cleaning tasks are:
In addition to these we also have the toilets which are cleaned by the people that share them.
How could we not have a special relationship with the past, present, and future of urban transportation? The best, coolest, most efficient, most environmentally friendly, most human friendly, sum positive means of transportation is highly regarded in the Nutcroft Foundation. We have resident expert bicycle knowledge that we share amongst us, as well as, all the necessary tools to fix and maintain one’s bicycle.
We welcome all Nutcroft residents to bring their guests, though due to corona we have established that one should inform the Foundation beforehand.
The process for long term guests (more than 1-2 weeks) is open to discussion.
We have a high quality fully automated dish washing machine that we use daily. Some things can’t go inside such as the coloured knives and the pans.
We also have two clothes washing machines. The one on the ground floor is currently facing some issues and may not start if angry. The one in the kitchen is super friendly though, starts immediately on the touch of a button.
We have a state of the art vacuum cleaner which we call Hoover, or just H. The official residing place of H is in the living room while H can sometimes be found hanging around outside the kitchen.
H has many functions and we keep learning new ones as time passes and we interact more.
H has recently had an illness in which filters were lost and fans got infiltrated by dust. Thankfully we fitted H with new filters as soon as possible.
The guardian of the Hoover is Karen.
We grow fruit and vegetable in the garden. There is also a newly built fire pit which we plan to use in the winter in case the heating breaks down.
We love bins (we have 8 in total) but we are also racist towards them. We have 4 of them in the kitchen. Namely:
For the compost, you can find more information on what is compostable in the flyer on the tall fridge.
The Southwark Council collects some of our garbage every Thursday. Depending on the week it may collect either brown + blue or brown + black. One can find the annual schedule on the tall fridge.
Every Wednesday night, the resident in charge of bins makes sure that the appropriate garbage has been put out and the appropriately coloured bins are outside of our front porch.
Finally, we have the big compost in the garden, which we put the small compost’s contents.
How could we be true revolutionaries if we didn’t consume one of the most ancient and dangerous substances? Alcohol, and specifically beer and mezcal are the two official drinks of the Nutcroft Foundation. While we love those timelessly, we continuously try new ones to broaden our horizons.
We hold multi-annual Nutcroft conferences which denote milestones in our society’s journey throughout time. Due to corona we had to cut back on those but we do have the next one scheduled for July 11th.
The holy process of Nutcroft is our house meetings. We used to hold them every one or two weeks, but due to corona times, we now hold ad-hoc meetings.
The meetings take place in the kitchen, sitting around the holy table. Every meeting has a moderator and a meeting notes author.
The moderator's job is to control who talks so that there is equality amongst everybody in talking and hearing time. In order to do this efficiently, and without talking, we have adopted some signs to convey our thoughts in a muted fasion. Specifically:
The moderator closely watches everybody and when somebody makes a response, they make a mental note and give permission to talk to the person who spoke the least, or however else they choose to balance the discussion.
The meetings notes author's job is to capture what has been said in the meeting so that we can refer to it later. It is a job of utmost importance as the meeting notes will be the truth that will help us solidify our decisions. Ideally, everybody should read the meeting notes after the meeting and sign off on them.
It is unavoidable to have disagreements between the mates of the house at some point. Thus it is important to have a high quality process of solving them.
Our process is as follows. The person who has the disagreement talks with the person that they disagree with. In case this fails, then the person who has the disagreement approaches a third person and all three together try to solve the issue at hand. If this process also fails, then the person who has the disagreement raises the issue on a house meeting (or asks for one if there aren't any scheduled).
It is important to externalize our disagreements as the person on the other side might not be aware of the issue they might cause, while also it might be easier for them to rectify than assumed.
We try to reach consensus in all the decisions we make. The basis of that is a common goal we all share: high quality co-living.


PLACE VENDOME
Written and Directed by Nicole Garcia
Plan B NR 117 min. Subtitles
There are great pleasures to this silkily adult thriller set in the murky world of precious stones, and none is greater, silkier, or more adult that the presence of the great Catherine Deneuve. As beautiful in her late fifties as she was in her early twenties, Ms. Deneuve has long since justified the Best Actress awards she won as a newcomer in The Umbrellas of Cherbourg (1964).
She's never been better than she is here as Marianne Malivert, the dipsomaniac wife (and before too long, widow) of the head of one of the great jewelry firms of Paris's famed Place Vendome. When we first meet her, she's virtually a full-time resident of a private alcohol clinic. But the sudden death of her husband (Bernard Fresson) shakes her out of it, and re-armed with her former expertise as a diamond specialist and in possession of a cache of stolen gems he showed her before he drove his car into a truck, she penetrates the dark and dangerous shadows of the diamond trade, from De Beers in London to the burrows of Antwerp in an effort to secure her future.
Actress-turned-writer/director Nicole Garcia keeps the mind churning by gradually revealing knots and tangles as she spools out her story. There are multiple links between many of the characters, of both a professional and a romantic character, but we only discover them bit by bit. There is a determined rejection of consistency, that hobgoblin of little minds; instead Garcia challenges us with shifting attitudes and character traits. Marianne is a drunk; when she sobers up, she can still slip without falling apart. Her feelings toward the beautiful Nathalie (Emmanuelle Seignier) range unapologetically from hostility to empathy. Strong performances from Jacques Dutronc and Jean-Pierre Bacri as a couple of the men in her life draw the twisted skein of this story tighter. "Love means getting lied to and betrayed," Marianne muses, and mendacity and betrayal in love and business are at the heart of this often difficult but always rewarding film noir.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


Suzanne Jackson names and shames Instagram account after receiving cruel message
The vile troll told her she "should be shot"
by Kendra BeckerSuzanne Jackson has named and shamed an Instagram account, after receiving a cruel message from them.

Suzanne then shared a screenshot of the message on her Instagram Story, revealing she received the DM from @daniel.kenna21 – which turned out to be a fake account.
The SOSU by SJ founder was flooded with supportive messages after sharing the troll’s nasty DM.
Taking to her Instagram Story today, Sue told her 276k followers: “Lots of people are messaging me about that message last night, but it really doesn’t bother me.”
“That’s just light compared to what you would receive some days.”
“Obviously sometimes comments can be really hurtful, but that one last night was just… I was like, ok, little piggy went to the market, oink oink,” she joked.


Tea is the answer to everything, in life, and in this free visual novel
by Tom SykesHere's a free visual novel where you run a booze-free tavern, situated on the border between the human and demon realms. As human or demon customers come inside, you have to prepare each an appropriate cup of tea. A brew that will, for example, calm them down, or give them an infusion of energy, depending on the particular ingredients it's made from.
A Tavern For Tea is a handsomely drawn visual novel, where the talking is punctuated every so often by a tea-making minigame. In order to continue the story, you'll need to a) listen to what the customer has asked for, and b) pick the right three ingredients to chuck in the tea pot. That might sound easy, but the rules for brewing aren't explained as well as they could be (it helps to know that you can use the same ingredient more than once).
Still, this is a sweet game about sorting out people's problems, using the primary tool in the British arsenal: a nice cup of tea. None of the ingredients is 'milk', or even 'chocolate hobnobs', but I can forgive that. Maybe. Just about.
For more great free experiences, check out our roundup of the best free PC games.


scriptingbundle:metadata
Full name:
org.apache.sling:scriptingbundle-maven-plugin:0.2.2:metadata
Description:
The metadata goal will generate two Maven project
properties, namely
org.apache.sling.scriptingbundle.maven.plugin.Require-Capability
and
org.apache.sling.scriptingbundle.maven.plugin.Provide-Capability
which can be used to generate the corresponding OSGi bundle headers
for bundles providing scripts executable by a
ScriptEngine.
Attributes:
- Requires a Maven project to be executed.
- Binds by default to the lifecycle phase: prepare-package.
Optional Parameters
| Name |
Type |
Since |
Description |
| <excludes> |
String[] |
0.2.0 |
Allows defining a list of excluded files and folders or patterns to
filter which files should be excluded in the analysis for
generating capabilities.
The following list provides the default excluded files and
patterns:
- Miscellaneous typical temporary files
- **/*~, **/#*#, **/.#*, **/%*%, **/._*
- CVS
- **/CVS, **/CVS/**, **/.cvsignore
- Subversion
- **/.svn, **/.svn/**
- Bazaar
- **/.bzr, **/.bzr/**
- Mac
- **/.DS_Store
- Mercurial
- **/.hg, **/.hg/**
- git
- **/.git, **/.git/**
User property is: scriptingbundle.excludes.
|
| <includes> |
String[] |
0.2.0 |
Allows defining a list of included files and folders or patterns to
filter which files should be included in the analysis for
generating capabilities. By default all files are included. Default value is: **. User property is: scriptingbundle.includes.
|
| <scriptEngineMappings> |
Map |
0.2.0 |
Allows overriding the default extension to script engine mapping,
in order to correctly generate the
sling.resourceType;scriptEngine
Provide-Capability attribute value. When configuring
this mapping, please make sure to use the script extension as the
key and one of the Script Engine's name (obtained from
ScriptEngineFactory.getNames()) as the value.
The following list represents the default extension to Script
Engine mapping:
- ftl
- freemarker
- gst
- gstring
- html
- htl
- java
- java
- esp, ecma
- rhino
- jsp, jspf, jspx
- jsp
|
| <searchPaths> |
Set |
0.2.0 |
Allows overriding the default search paths (/apps and
/libs). When scripts are organised in folders which
follow the search path structure, the Mojo will generate two
resource types for each resource type folder. For example:
src/main/scripts/apps/org/apache/sling/example/example.html
will generate the following two resource types
org/apache/sling/example
/apps/org/apache/sling/example
However, the following script
src/main/scripts/org/apache/sling/example/example.html
will generate only one resource type
User property is: scriptingbundle.searchPaths.
|
| <sourceDirectories> |
Set |
0.2.0 |
Defines where this goal will look for scripts in the project. By
default the src/main/scripts and
src/main/resources/javax.script folders will be
considered. User property is: scriptingbundle.sourceDirectories.
|
Parameter Details
Allows defining a list of excluded files and folders or patterns to
filter which files should be excluded in the analysis for
generating capabilities.
The following list provides the default excluded files and
patterns:
- Miscellaneous typical temporary files
- **/*~, **/#*#, **/.#*, **/%*%, **/._*
- CVS
- **/CVS, **/CVS/**, **/.cvsignore
- Subversion
- **/.svn, **/.svn/**
- Bazaar
- **/.bzr, **/.bzr/**
- Mac
- **/.DS_Store
- Mercurial
- **/.hg, **/.hg/**
- git
- **/.git, **/.git/**
- Type: java.lang.String[]
- Since: 0.2.0
- Required: No
- User Property: scriptingbundle.excludes
Allows defining a list of included files and folders or patterns to
filter which files should be included in the analysis for
generating capabilities. By default all files are included.
- Type: java.lang.String[]
- Since: 0.2.0
- Required: No
- User Property: scriptingbundle.includes
- Default: **
Allows overriding the default extension to script engine mapping,
in order to correctly generate the
sling.resourceType;scriptEngine
Provide-Capability attribute value. When configuring
this mapping, please make sure to use the script extension as the
key and one of the Script Engine's name (obtained from
ScriptEngineFactory.getNames()) as the value.
The following list represents the default extension to Script
Engine mapping:
- ftl
- freemarker
- gst
- gstring
- html
- htl
- java
- java
- esp, ecma
- rhino
- jsp, jspf, jspx
- jsp
- Type: java.util.Map
- Since: 0.2.0
- Required: No
Allows overriding the default search paths (
/apps and
/libs). When scripts are organised in folders which
follow the search path structure, the Mojo will generate two
resource types for each resource type folder. For example:
src/main/scripts/apps/org/apache/sling/example/example.html
will generate the following two resource types
org/apache/sling/example
/apps/org/apache/sling/example
However, the following script
src/main/scripts/org/apache/sling/example/example.html
will generate only one resource type
- Type: java.util.Set
- Since: 0.2.0
- Required: No
- User Property: scriptingbundle.searchPaths
Defines where this goal will look for scripts in the project. By
default the src/main/scripts and
src/main/resources/javax.script folders will be
considered.
- Type: java.util.Set
- Since: 0.2.0
- Required: No
- User Property: scriptingbundle.sourceDirectories


You are about to deploy the environment configuration.
After this action you will not be able to edit the environment setup.


val metric: TextMetric
The metric that has been used to calculate the heuristic values
metric - The metric that has been used to calculate the heuristic values
metric


NavyBay
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?The
University
of
Texas
at
Arlington
Nama
jamaicense
L.
John
D.
Bacon
1984
PLANTS
OF
BAHAMA
ISLANDS
Nama
jamaicensis
L.
Crooked
Island:
in
open
gravelly
soil
on
hills
just
northeast
of
Cabbage
Hill.
Flowers
white.
February
22,
1975
D.
S.
Correll
44477
Herbarium
FAIRCHILD
TROPICAL
GARDEN
01498419
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Fri Feb 23, 2007
There is no denying that the iPod has become part of our popular culture. What started as a neat toy for Mac users blossomed into a fashion craze for young urban hipsters. These cool urbanites identified each other not with secret handshakes but by the white ear-buds that had become the icon for “coolness”. The rise of the iPod sub-culture has a grassroots foundation in the heart of the thriving metropolis - on gritty city streets, on crowded subway trains and in public places. The iPod fad proliferated in cities like New York, where people walk everywhere. Those little white ear-buds also started popping up everywhere and the iPod caught on like wildfire.  Auto manufacturers have heeded their cries - most new cars being put on the market today are iPod ready.
But with Apple pushing for dominant shares in every market, they are in danger of alienating their core group of users. Those street-smart iPod evangelists who started the whole viral marketing thing won’t think twice about ditching the pod for the next cool gadget that comes along (with the exception of hardcore Mac users, whose loyalty borders on stubbornness). Why?
The reason is simple - everybody has one.
There is no longer anything separating the cool from the uncool, the hip from the square, the geek from the flavour of the week. The line between urban chic and the vast hinterland outside of the urban centre has been eradicated. Now the straight-laced banker can bop to his iPod tunes in his BMW while he commutes to the city from the burbs. Now farmer Joe can till his field while listening to some twanging country and western on his nano. Does that sound like the kind of scene an urban hipster wants to be part of?


- canDelete() - Method in class rs.raf.storage.spec.auth.Privilege
-
- canRead() - Method in class rs.raf.storage.spec.auth.Privilege
-
- canWrite() - Method in class rs.raf.storage.spec.auth.Privilege
-
- checkDelete(User, File) - Method in class rs.raf.storage.spec.auth.Authorizer
-
Check if provided user can delete provided file.
- checkManage(User, Storage) - Method in class rs.raf.storage.spec.auth.Authorizer
-
Check if provided user can manage other users from provided file.
- checkRead(User, File) - Method in class rs.raf.storage.spec.auth.Authorizer
-
Check if provided user can read from provided file.
- checkWrite(User, File) - Method in class rs.raf.storage.spec.auth.Authorizer
-
Check if provided user can write to provided file.
- clear() - Method in class rs.raf.storage.spec.core.Metadata
-
Clears metadata.
- connect(String, String, User) - Method in class rs.raf.storage.spec.core.Storage
-
Template method for connecting currently active user to storage
represented by unique id that located on path.
- copy(Directory) - Method in class rs.raf.storage.spec.core.Directory
-
- copy(Directory) - Method in class rs.raf.storage.spec.core.File
-
Template method for copying abstract file from and to real storage.
- Criteria - Class in rs.raf.storage.spec.search
-
Holds search query and type of search.
- Criteria(CriteriaType, String) - Constructor for class rs.raf.storage.spec.search.Criteria
-
One and only contructor that accepts search query adn type of search.
- CriteriaNameContains - Class in rs.raf.storage.spec.search
-
Search criteria that check if file name contains search query.
- CriteriaNameContains() - Constructor for class rs.raf.storage.spec.search.CriteriaNameContains
-
- CriteriaNameEndsWith - Class in rs.raf.storage.spec.search
-
Search criteria that check if file name ends with search query.
- CriteriaNameEndsWith() - Constructor for class rs.raf.storage.spec.search.CriteriaNameEndsWith
-
- CriteriaNameEquals - Class in rs.raf.storage.spec.search
-
Search criteria that check if file name is equal to search query.
- CriteriaNameEquals() - Constructor for class rs.raf.storage.spec.search.CriteriaNameEquals
-
- CriteriaNameStartsWith - Class in rs.raf.storage.spec.search
-
Search criteria that check if file name starts with search query.
- CriteriaNameStartsWith() - Constructor for class rs.raf.storage.spec.search.CriteriaNameStartsWith
-
- CriteriaType - Enum in rs.raf.storage.spec.search
-
Search criteria that check if file name contains search query.
- CriteriaVisitor - Interface in rs.raf.storage.spec.search
-


The Shiba Inu is the smallest of the six original and distinct spitz breeds of dog from Japan. A small, agile dog that copes very well with mountainous terrain, the Shiba Inu was originally bred for hunting.
{{folder.updated | date}}
{{note.updated | date}}
|
|
|


abaaso is a modern, lightweight Enterprise class RESTful JavaScript application framework.
All standards compliant browsers and platforms such as Desktops, Tablets, Smartphones, Google TV, and more!
If you're having problems, use the support forum at CodersClan.
Copyright (c) 2013 Jason Mulligan Licensed under the BSD-3 license.
abaaso
abaaso is a modern, lightweight Enterprise class RESTful JavaScript application framework.
What is Supported?
All standards compliant browsers and platforms such as Desktops, Tablets, Smartphones, Google TV, and more!
Features
Support
If you're having problems, use the support forum at CodersClan.
License
Copyright (c) 2013 Jason Mulligan
Licensed under the BSD-3 license.


|
Egyptian Islamic Jihadaka al-JihadEgypt has been home to rabble-rousers and troublemakers since the days of Moses.But while Moses had frogs, boils, locusts and baby-killing angels at his disposal, Egyptian Islamic Jihad only has guns, knives and explosives to work with. They've made the most of their tools. EIJ is perhaps the most overtly successful terrorist operation in history. An offshoot of the Muslim Brotherhood, EIJ splintered off in the early 1970s as a student-oriented rebellion against the right-wing military dictatorship run by former Nazi spy Anwar Sadat. The members of Egyptian Islamic Jihad are Sunni Islamic fundamentalists who want to overthrow Egypt's secular government and replace it with a Taliban-style theocracy. Affiliated groups include Gama'a al-Islamiyah (aka Jamaat al-Islamiyya) al-Jihad. By paying lip service to nonviolence, the Muslim Brotherhood began to push for mainstream political acceptance, while EIJ acted as its "covert-overt" militant arm, along with several other groups. Although the Brotherhood denied any tie to the actions of EIJ and groups like al-Jihad, journalists and the Egyptian government believe the Brotherhood calls the shots when it comes to terrorist attacks in Egypt. And there have been an awful lot of terrorist attacks in Egypt. Egyptian Islamic Jihad and other domestic groups have distinguished themselves in both ambition and sheer bloodiness. In 1981, EIJ and other affiliated groups changed the course of Middle Eastern history by assassinating Sadat, who had been attempting to negotiate peace with Israel. Sadat's assassins were connected to the Brotherhood, EIJ and Gama'a al-Islamiyah, via radical Sheikh Omar Abdel Rahman, a blind cleric who doubles as "spiritual leader" for both groups. "The Blind Sheikh," who was later tied to the 1993 World Trade Center bombing, reputedly pronounced a fatwa approving the assassination. (He was suspected of a similar role in the WTC attack.) Abdel-Rahman stood trial alongside the Sadat triggermen, but he was acquitted. Ayman Al-Zawahiri, a former doctor, also served hard time for allegedly playing a part in Sadat's assassinations (along with thousands of others arrested almost indiscriminately by the Egyptian government). In the mid-1980s, Zawahiri took over EIJ. A member of the ultraviolent Al Takfir Wal Hijra sect, Zawahiri led Egyptian Islamic Jihad to new levels of global accomplishment. Shortly after Zawahiri took the reins, EIJ went international. A handful of Egyptian terrorists came to the U.S. and created sleeper cells which were eventually tied back to Egyptian Islamic Jihad and the still young al Qaeda. One member of this group, Ali Mohammed, even joined the U.S. Special Forces, where he served as a sergeant. Another, Mahmud Abouhalima, moved to New York City and joined the NRA. El Sayyid Nosair, an Egyptian militant associated with the cell, shot and killed a right-wing rabbi named Meir Kahane in 1990. The advance team moved to key locations and began setting up networks for moving money and weapons around the U.S. and overseas. The U.S. government looked the other way while this was happening, since the team's efforts were largely directed toward fighting the Soviet Union in Afghanistan, where the CIA was running a proxy war on behalf of the U.S. using a volunteer army made up of Islamic extremists. At some point, EIJ became formally consolidated with al Qaeda, after Zawahiri and Osama bin Laden became close friends and theological sparring partners. The conventional wisdom holds that this happened around 1998, but there is a substantial body of evidence to suggest it happened much earlier. Al Qaeda and Egyptian Islamic Jihad operatives cooperated extensively to pull off the 1993 WTC attack, in which Ramzi Yousef worked closely with followers of the blind sheikh in Brooklyn. In 1995, Zawahiri came to the U.S. for a fundraising visit. While in California, he stayed with Ali Mohammed, who by then had become bin Laden's chief of security. Regardless of exactly when the alliance formally took place, Egyptian Islamic Jihad is today considered to be a regional adjunct of al Qaeda, a branch office in Egypt, much like Jemaah Islamiah in Southeast Asia. Zawahiri himself is now considered to be the No. 2 figure in al Qaeda, after bin Laden. In most meaningful respects, he's probably more like the No. 1 figure in al Qaeda, although bin Laden is the visible outer head of the organization. Despite its status as a satellite to al Qaeda, Egyptian Islamic Jihad is far from irrelevant, however. Before hooking up with al Qaeda, EIJ mostly targeted political leaders and military figures, rather than random civilians. The group has tried to assassinate Egyptian president Hosni Mubarek on more than one occasion, including at least one effort directly tied to al Qaeda. EIJ has also tried to kill various lesser officials in the Egyptian government. But since the mid 1990s, the organization has increasingly focused its attention overseas and its efforts have been largely indistinguishable from those of al Qaeda. It may not be so much Egyptian any more, but the Islamic Jihad goes on... and on... and on... After Zawahiri, probably the most famous member of Egyptian Islamic Jihad is Mohammed Atta, who flew an airplane into the World Trade Center on September 11. EIJ is also believed to be responsible for the 1998 bombing of U.S. embassies in Kenya and Tanzania, an attack which led to the historic "U.S. vs. bin Laden," the criminal case that first brought bin Laden's name out of the shadows and into the headlines. Zawahiri's pal Ali Mohammed was a key suspect in this case, and he cut a plea deal in which he provided information in exchange for a sentence which is still under seal. His current whereabouts are one of the great "national security" secrets of the day...
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{% extends "layout.html" %} {% from "items.html" import render_items %} {% block title %} {{country.label}} {% endblock %} {% block description %} Information on projects, organisations and datasets in {{country.label}} related to government spending, budgets and revenue. {% endblock %} {% block content %}


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Privacy PolicyThis Privacy Policy is for Top-Law-Schools.com ("TLS") which is owned by Top Law Schools LLC ("us", "our", "we"), a limited liability company organized under the laws of the State of Florida. This Privacy Policy can be found at http://www.top-law-schools.com/privacy.html as well as within the Terms of Service found at http://www.top-law-schools.com/terms.html which were last updated on February 13, 2014. We reserve the right to modify this privacy policy, and the most up-to-date version can be found through the above links. In this privacy policy we describe the information we collect, how we use that information, and details about who we share information with. Email address: In order to register to submit content to TLS you need to provide us with an email address. We send you a verification email to verify that the email address you provided belongs to you. We use your email address to provide you with the option of receiving notifications to give you a better experience when using the TLS forums or TLS wiki. We do not sell or rent your email address to any third party. If we ever decide to send you promotional emails, we will provide a clear way for you to opt-in or opt-out of receiving promotional emails. IP addresses: Your IP address can reveal information about your location because it can reveal information about the location of the Internet Service Provider you use to access the Internet. We collect your IP address when you submit content to TLS, and we use this information to help prevent undesirable users, such as spammers, from posting content on TLS. With every forum registration we query the stopforumspam.com database to see if the registering IP address has been used in the past by spammers. Also, to help us prevent undesirable users from posting content on TLS, we share your IP address(es) with the moderators with the requirement that moderators agree not to disclose information such as IP address without an appropriate reason, such as a moderator being required to do so by law. Server logs: With each page view our server automatically collects standard log file information such as your IP address, browser type, operating system, the referring web page, pages visited, and search terms. We use this information to manage the server that hosts TLS. Cookies: Like most websites, some parts of our website use cookies, which are small data files that are stored on your computer when you visit a website. We use cookies to provide a better user experience such as by remembering which forum and wiki user account you browser is logged into. You have options to manage cookies. For example, you can set your browser to refuse all cookies or to indicate when a cookie is being sent. You can also delete cookies. However, please keep in mind that some aspects of TLS and other websites may not function properly without cookies enabled. There may also be third-party cookies sent while you are using TLS which are discussed in the "third-party embed codes" section below. Third-party embed codes: On TLS we have embedded code from various third parties such as Google Adsense, Google Double Click for Publishers, Google Analytics, and Amazon Associates. The purpose of us placing third-party code on TLS is to serve relevant advertisements to our visitors and to help us understand how our visitors as a whole use TLS. With the third-party embed codes placed on TLS these third parties can do things such as collect information directly from you like your IP address, send/recognize cookies and anonymous identifiers to/from your device, access device specific information, and use a cookie that collects anonymous traffic data. This enables the third parties to do things such as show you advertisements while on TLS based on previous visits you may have made to other websites. Email correspondence: Your email correspondence with us is kept private. However, for email correspondence related to forum bans and other forum related issues, such as a feature request, we may share certain applicable portions of your email within a private forum to seek the advice and input of the moderators. Private message feature: The content of your private messages is designed to only be shared with your intended recipient. However, we reserve the right to investigate private messages sent by certain individuals to prevent abuse of the private messaging system. Private messages are not shared with the moderators unless the sender or recipient uses the feature to report a private message. Anonymous post feature: The content of your anonymous posts is shared with the public but the identity of the user who submitted the post is kept hidden from the public. However, this author identity information is made known to the moderators for the purpose of preventing abuse of the anonymous post feature.  However, associations between wiki and forum accounts are made known to the moderators for the purposes of preventing undesirable users from posting content on TLS. Forced disclosure: The private information we gather from you may be disclosed to judicial or other government agencies subject to warrants, subpoenas, or other governmental orders. Public information: Unless specifically mentioned above, all other information you submit to TLS is public information. Once the information becomes public it may no longer be possible for you to remove it. In the past we have helped some people who made the mistake of publicly revealing too much information about themselves, but we have also declined requests to scrub public information from TLS, so please consider carefully the future consequences of all content you submit to TLS. How to contact us: In the footer of almost every page on this site, including this page, is a link to our contact page which provides information on how to contact us. Our mailing address is: Top Law Schools LLC, 2637 E Atlantic Blvd #21442, Pompano Beach, FL 33062. Other information: We implement a variety of security measures to maintain the safety of your personal information. However, like many websites, TLS uses the standard http protocol and not secure https protocol, which means there is no SSL encryption on the information you send to and receive from TLS. |
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A data type definition language for YAML, JSON, CSV and more.
SchemaType is designed to be easy for people to work with. Easy to read and easy to write, but also easy to use, fork, extend, publish, share and maintain. The SchemaType syntax is YAML based combined with a nice, compact DSL. Schemas can be published and referenced from source control such as GitHub.
SchemaType even lets you create and maintain schemas automatically. By looking analyzing existing data, SchemaType can generate new schemas or make suggestions for improvemnt on existing ones.
How SchemaType Works →SchemaType definitions are meant to be published and reused. Even the most core types are no different from types you make yourself. If a schema is close to what you want, reference it as a base and add the extra properties. If there is a bug in a core schema, fork it, fix it, use the fork, submit a patch or pull request.
SchemaType makes using and maintaining schema information work the same as using and maintaining source code. Schemas act like OO classes; they support subclassing, inheritance, polymorphism etc.
SchemaType Examples →Think about it... The more specifically you define data, the less code you need to write. Schemas can not only validate data, they can generate all sorts of functionality that would otherwise need to be done by hand. SchemaType aims to make a future where all data is defined and can be reasoned on precisely (both by people and by computers).
Every schema and type defined by SchemaType is (expands to) an immutable URL reference. This makes your schemas themselves be immutable and therefore trustable by others.
SchemaType Usage →Quick-start Instructions
$ npm install schematype
$ schematype --help
$ schematype generate -i my.yaml -o my.stp
$ schematype validate -s my.stp my.yaml
YAML is valid ✓


The list below shows all of the nodes currently connected to the cluster. There is no master/woker or master/slave relationship between any of the nodes. They are all peers, and all auto-discover the state of the cluster periodically. Killing a node causes all nodes to be updated with the current state of the cluster. Likewise, starting a new node does the same.
To kill a node on the cluster, click its ID. It will be killed immediately, and within a few seconds, the list should update itself accordingly. To add a new node to the cluster, click the button.


Classes
The following classes are available globally.
-
Overview:
The Action Logger class sends messages to the Xcode console and / or a file or a NSTextView object (very new!!!). The messages are processed accordingly before they are issued. If the Xcode Plugin XcodeColors is installed, the messages in the Xcode console are displayed in color. The aim of the development was to implement a very easy-to-use method that can be generated with the reports to track program run during software testing. On the other hand has been achieved that through a variety of options, the class can also be used for any other protocol tasks. See two example outputs
general description:
A message line consists of individually assembled components:
{Date+Time}▫[{LogLevel}]▫[{Filename}:{LineNumber}]▫{Functionname}▫:▫{Messagetext}
Components are enclosed in {}, ▫ means space
By default, all components are selected. Each of these components can be turned off (not the message text).
Use:
The use of Action Logger class in your project is very simple:
Drag the file ActionLoggerComplete.swift file from Finder directly in Xcode project. in AppDelegate.swift immediately after the imports, insert the following:
// Get a reference to defaultLoggerlet log = ActionLogger.defaultLogger ()
Once the Action Logger class is referenced once, a default logger is automatically created. The default logger specifies the Xcode Debug Console.
The logger log can now be used in all other .swift files in your project.
log.verbose("this message is generated in ViewController") ActionLogger.info("here is an info for you")
As the above example shows, it’s even easier: all outputs can also be done via class methods. Step 2 of this procedure could also be left out! If you will use the class methods used internally also the default logger automatically generated.
See moreDeclaration
Swift
public class ActionLogger : CustomDebugStringConvertible
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- A standard log destination that outputs log details to the console
Declaration
Swift
public class ActionLogConsoleDestination : ActionLogDestinationProtocol, CustomDebugStringConvertible
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- A standard log destination that outputs log details to a file
Declaration
Swift
public class ActionLogFileDestination : ActionLogDestinationProtocol, CustomDebugStringConvertible
-
- A log destination that outputs log details to a NSTextView
Declaration
Swift
public class ActionLogTextViewDestination : ActionLogDestinationProtocol, CustomDebugStringConvertible


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