Class: Puma::Configuration
| Relationships & Source Files | |
| Namespace Children | |
|
Classes:
| |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Instance Chain:
self,
ConfigDefault
|
|
| Inherits: | Object |
| Defined in: | lib/puma/configuration.rb |
Overview
The main configuration class of ::Puma
.
It can be initialized with a set of “user” options and “default” options. Defaults will be merged with #puma_default_options.
This class works together with 2 main other classes the UserFileDefaultOptions
which stores configuration options in order so the precedence is that user set configuration wins over “file” based configuration wins over “default” configuration. These configurations are set via the DSL
class. This class powers the ::Puma
config file syntax and does double duty as a configuration DSL
used by the CLI
and ::Puma
rack handler.
It also handles loading plugins.
> Note: :port
and :host
are not valid keys. By they time they make it to the
configuration options they are expected to be incorporated into a `:binds` key.
Under the hood the DSL maps `port` and `host` calls to `:binds`
config = Configuration.new({}) do |user_config, file_config, default_config|
user_config.port 3003
end
config.load
puts config.options[:port]
# => 3003
It is expected that #load is called on the configuration instance after setting config. This method expands any values in config_file
and puts them into the correct configuration option hash.
Once all configuration is complete it is expected that #clamp will be called on the instance. This will expand any procs stored under “default” values. This is done because an environment variable may have been modified while loading configuration files.
Constant Summary
ConfigDefault
- Included
DefaultRackup, DefaultTCPHost, DefaultTCPPort, DefaultWorkerShutdownTimeout, DefaultWorkerTimeout
Class Method Summary
Instance Attribute Summary
-
#app_configured? ⇒ Boolean
readonly
Indicate if there is a properly configured app.
- #options readonly
- #plugins readonly
Instance Method Summary
-
#app
Load the specified rackup file, pull options from the rackup file, and set @app.
-
#clamp
Call once all configuration (included from rackup files) is loaded to flesh out any defaults.
- #config_files
- #configure
-
#environment
Return which environment we’re running in.
- #environment_str
- #flatten
- #flatten!
- #initialize_copy(other)
- #load
- #load_plugin(name)
- #puma_default_options
- #rackup
- #run_hooks(key, arg)
- #infer_tag private
- #load_rackup private
-
#rack_builder
private
Load and use the normal
Rack
builder if we can, otherwise fallback to our minimal version.
Constructor Details
.new(user_options = {}, default_options = {}, &block) ⇒ Configuration
# File 'lib/puma/configuration.rb', line 131
def initialize(={}, = {}, &block) = self. .merge( ) @options = UserFileDefaultOptions.new(, ) @plugins = PluginLoader.new @user_dsl =<EMAIL_ADDRESS>self) @file_dsl =<EMAIL_ADDRESS>self) @default_dsl =<EMAIL_ADDRESS>self) if block configure(&block) end end
Class Method Details
.random_token (private)
[ GitHub ]# File 'lib/puma/configuration.rb', line 334
def self.random_token begin require 'openssl' rescue LoadError end count = 16 bytes = nil if defined? OpenSSL::Random bytes = OpenSSL::Random.random_bytes(count) elsif File.exist?("/dev/urandom") File.open('/dev/urandom') { |f| bytes = f.read(count) } end if bytes token = "".dup bytes.each_byte { |b| token << b.to_s(16) } else token = (0..count).to_a.map { rand(255).to_s(16) }.join end return token end
.temp_path
[ GitHub ]# File 'lib/puma/configuration.rb', line 282
def self.temp_path require 'tmpdir' t = (Time.now.to_f * 1000).to_i "#{Dir.tmpdir}/puma-status-#{t}-#{$$}" end
Instance Attribute Details
#app_configured? ⇒ Boolean
(readonly)
Indicate if there is a properly configured app
#options (readonly)
[ GitHub ]# File 'lib/puma/configuration.rb', line 145
attr_reader :, :plugins
#plugins (readonly)
[ GitHub ]# File 'lib/puma/configuration.rb', line 145
attr_reader :, :plugins
Instance Method Details
#app
Load the specified rackup file, pull options from the rackup file, and set @app.
# File 'lib/puma/configuration.rb', line 245
def app found = [:app] || load_rackup if @options[:mode] == :tcp require 'puma/tcp_logger' logger = @options[:logger] quiet = !@options[:log_requests] return TCPLogger.new(logger, found, quiet) end if @options[:log_requests] require 'puma/commonlogger' logger = @options[:logger] found = CommonLogger.new(found, logger) end ConfigMiddleware.new(self, found) end
#clamp
Call once all configuration (included from rackup files) is loaded to flesh out any defaults
# File 'lib/puma/configuration.rb', line 215
def clamp @options.finalize_values end
#config_files
[ GitHub ]# File 'lib/puma/configuration.rb', line 200
def config_files files = @options.all_of(:config_files) return [] if files == ['-'] return files if files.any? first_default_file = %W(config/puma/#{environment_str}.rb config/puma.rb).find do |f| File.exist?(f) end [first_default_file] end
#configure
[ GitHub ]# File 'lib/puma/configuration.rb', line 147
def configure yield @user_dsl, @file_dsl, @default_dsl ensure @user_dsl._offer_plugins @file_dsl._offer_plugins @default_dsl._offer_plugins end
#environment
Return which environment we’re running in
# File 'lib/puma/configuration.rb', line 266
def environment @options[:environment] end
#environment_str
[ GitHub ]# File 'lib/puma/configuration.rb', line 270
def environment_str environment.respond_to?(:call) ? environment.call : environment end
#flatten
[ GitHub ]# File 'lib/puma/configuration.rb', line 161
def flatten dup.flatten! end
#flatten!
[ GitHub ]# File 'lib/puma/configuration.rb', line 165
def flatten! @options = @options.flatten self end
#infer_tag (private)
[ GitHub ]# File 'lib/puma/configuration.rb', line 291
def infer_tag File.basename(Dir.getwd) end
#initialize_copy(other)
[ GitHub ]# File 'lib/puma/configuration.rb', line 155
def initialize_copy(other) @conf = nil @cli_options = nil @options = @options.dup end
#load
[ GitHub ]# File 'lib/puma/configuration.rb', line 194
def load config_files.each { |config_file| @file_dsl._load_from(config_file) } @options end
#load_plugin(name)
[ GitHub ]# File 'lib/puma/configuration.rb', line 274
def load_plugin(name) @plugins.create name end
#load_rackup (private)
[ GitHub ]# File 'lib/puma/configuration.rb', line 318
def load_rackup raise "Missing rackup file '#{rackup}'" unless File.exist?(rackup) rack_app, = rack_builder.parse_file(rackup) @options. .merge!( ) config_ru_binds = [] .each do |k, v| config_ru_binds << v if k.to_s.start_with?("bind") end @options. [:binds] = config_ru_binds unless config_ru_binds.empty? rack_app end
#puma_default_options
[ GitHub ]# File 'lib/puma/configuration.rb', line 170
def { :min_threads => 0, :max_threads => 16, :log_requests => false, :debug => false, :binds => ["tcp://#{DefaultTCPHost}:#{DefaultTCPPort}"], :workers => 0, :daemon => false, :mode => :http, :worker_timeout => DefaultWorkerTimeout, :worker_boot_timeout => DefaultWorkerTimeout, :worker_shutdown_timeout => DefaultWorkerShutdownTimeout, :remote_address => :socket, :tag => method(:infer_tag), :environment => -> { ENV['RACK_ENV'] || "development" }, :rackup => DefaultRackup, :logger => STDOUT, :persistent_timeout => Const::PERSISTENT_TIMEOUT, :first_data_timeout => Const::FIRST_DATA_TIMEOUT, :raise_exception_on_sigterm => true } end
#rack_builder (private)
Load and use the normal Rack
builder if we can, otherwise fallback to our minimal version.
# File 'lib/puma/configuration.rb', line 297
def rack_builder # Load bundler now if we can so that we can pickup rack from # a Gemfile if ENV.key? 'PUMA_BUNDLER_PRUNED' begin require 'bundler/setup' rescue LoadError end end begin require 'rack' require 'rack/builder' rescue LoadError # ok, use builtin version return Puma::Rack::Builder else return ::Rack::Builder end end
#rackup
[ GitHub ]# File 'lib/puma/configuration.rb', line 238
def rackup @options[:rackup] end
#run_hooks(key, arg)
[ GitHub ]# File 'lib/puma/configuration.rb', line 278
def run_hooks(key, arg) @options.all_of(key).each { |b| b.call arg } end


ICASA ontologies for integrated description of agricultural field experiments and production
Core Ontology
(Management Info)
Variables Ontology
(Measured Data)
Variables and Units


Created by Hakim El Hattab / @hakimel
reveal.js enables you to create beautiful interactive slide decks using HTML. This presentation will show you examples of what it can do.
Presentations look great on touch devices, like mobile phones and tablets. Simply swipe through your slides.
Hit the next arrow...
... to step through ...
... a fragmented slide.
There's different types of fragments, like:
grow
shrink
roll-in
fade-out
current-visible
highlight-red
highlight-blue
Set data-background="#dddddd"
on a slide to change the background color. All CSS color formats are supported.

Different background transitions are available via the backgroundTransition option. This one's called "convex".
Reveal.configure({ backgroundTransition: 'convex' })
You can override background transitions per-slide.

function linkify( selector ) {
if( supports3DTransforms ) {
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for( var i = 0, len = nodes.length; i < len; i++ ) {
var node = nodes[i];
if( !node.className ) {
node.className += ' roll';
}
}
}
}
Code syntax highlighting courtesy of highlight.js.
| Item | Value | Quantity |
|---|---|---|
| Apples | $1 | 7 |
| Lemonade | $2 | 18 |
| Bread | $3 | 2 |
These guys come in two forms, inline:
“The nice thing about standards is that there are so many to choose from”
and block:
“For years there has been a theory that millions of monkeys typing at random on millions of typewriters would reproduce the entire works of Shakespeare. The Internet has proven this theory to be untrue.”
Press B or . on your keyboard to pause the presentation. This is helpful when you're on stage and want to take distracting slides off the screen.


Hi everyone,
My energy consultant recommended using the openenergy equipment for house monitoring so I am just starting to look into it, whats involved, what I would need etc. and thought someone might be able to help.
So we are mid way through the construction of what will be a certified passivhaus. We are building a house with detached garage and planning to install PV panels on both roofs to approx. 11kW array. We are having a 3 phase supply which will feed into the garage, one phase will run the garage with a 4kW array and the other two phases will go to the house running 2 x 3.5kW arrays. Obviously these phases will run lighting, sockets etc. also.
I would like to be able to monitor electricity generated, usage and the amount exported. Also thinking out loud, I would like to monitor temperature/humidity upstairs and downstairs (possibly individual rooms), external temperature/humidity, slab temperature in a few places (if possible), MVHR inlet/outlet temps, plant room temp (under the stairs cupboard!), ASHP temp/usage,
If someone could point me in the right direction as to what I would need for this that would be great! At this stage I just want to make sure I have enough sockets in the right places before we start plastering although it seems most of these units are battery operated.
Thanks
Ben
Re: Passivhaus new build - help needed!
It certainly sounds do-able.
At a minimum, it look as if you wil want 3 × emonTx, one per phase, each will give you the true nett power on that phase and you'll have 2 high power and one low power current inputs left over, one you will use for the P.V> and the remaining two can be used for individual circuits. Each will need a socket on the phase you are measuring the voltage of.
You can add a handful of emonTH's (battery powered) for the individual rooms. If your garage emonTx is near an outside north-facing wall, you can add an external temperature sensor to that, otherwise it's another emonTH but it need a ventilated and weatherproof enclosure.
For the other temperatures, if they are reasonably close to an emonTx, you can add many temperature sensors to each.
To record and make all of this available, you'll probably want an emonPi (which can replace one of the emonTx's if it only uses two current inputs), but that will need a second socket for its 5 V power as well as the one for the a.c. measurement. If you don't want to replace an emonTx, then a plain Raspberry Pi and the RFM69Pi radio and the software will do the job (and that needs a 5 V supply too).
The main thing to think about at this point is the wiring you'll need - for temperature sensors in particular and maybe Ethernet connections to your router, if WiFi isn't viable. The emonBase (the emonPi or RPi) needs to be within radio range of all the emonTH's and emonTx's. If you have foil-backed insulation, that could be a major problem and we'd need to think of wires rather than radio, and that would be a nightmare once construction is finished.


Story
My story has not even started yet, but still.
-
November 2003
Humble Beginning
Don't think I was able to design back then. I mean, first one have to learn how to walk, right?
-
August 2009
Art School
After moving to Thailand I was going to after-school art classes.
-
May 2013
Getting the hang of it
My little sister was born and I started practicing every week at the school.
-
November 2015
Expansion
My dad made me this website for my birthday. Keeping fingers crossed.
-
Coming
soon


Convert an IPFS URL (starting ipfs://) to a gateway URL (starting https://) that can be used in a webpage. If the passed URL is not an IPFS URL it is returned as a new URL object with no further changes.
An IPFS URL e.g. ipfs://bafy.../path
An IPFS gateway URL e.g. https://dweb.link/ipfs/bafy.../path
Generated using TypeDoc
A client library for the https://nft.storage/ service. It provides a convenient interface for working with the Raw HTTP API from a web browser or Node.js and comes bundled with TS for out-of-the box type inference and better IntelliSense.


Read and write XES Files to create event log objects used by the 'bupaR' framework. XES (Extensible Event Stream) is the 'IEEE' standard for storing and sharing event data (see <http://standards.ieee.org/findstds/standard/1849-2016.html> for more info).
| Version: | 0.2.2 |
| Depends: | R (≥ 3.0.0) |
| Imports: | bupaR, dplyr, XML, xml2, data.table, tidyr, purrr, stringr, lubridate |
| Suggests: | knitr, rmarkdown |
| Published: | 2017-12-04 |
| Author: | Gert Janssenswillen [aut, cre], Benoît Depaire [ctb] |
| Maintainer: | Gert Janssenswillen <gert.janssenswillen at uhasselt.be> |
| License: | MIT + file LICENSE |
| URL: | http://www.bupar.net |
| NeedsCompilation: | no |
| CRAN checks: | xesreadR results |
| Reference manual: | xesreadR.pdf |
| Vignettes: |
xesreadR |
| Package source: | xesreadR_0.2.2.tar.gz |
| Windows binaries: | r-devel: xesreadR_0.2.2.zip, r-release: xesreadR_0.2.2.zip, r-oldrel: xesreadR_0.2.2.zip |
| OS X binaries: | r-release: xesreadR_0.2.2.tgz, r-oldrel: xesreadR_0.2.2.tgz |
| Old sources: | xesreadR archive |
Please use the canonical form https://CRAN.R-project.org/package=xesreadR to link to this page.


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Class: Connection
| Defined in: | src/connection.coffee |
Overview
Connection object to a datasource. @see {NodeJDBC#config} Queries and methods are executed using a connection object.
Instance Method Summary
- # (void) setAutoCommit(autoCommit) Set the auto-commit mode of the connection
- # (Statement) createStatement() Create a statement for executing SQL queries.
- # (PreparedStatement) prepareStatement(sql) Creates a PreparedStatement for executing SQL statements with or without parameter binding.
- # (CallableStatement) prepareCall(call) Creates a CallableStatement object for calling database stored procedures.
- # (void) commit() Persists the changes to the datasource from the last commit.
- # (void) rollback() Ignore all the changes since last commit and release locks on the given datastore.
- # (void) close() Closes the connection to the given datasource.
- # (boolean) isClosed() Checks if the connection is closed
- # (void) isValid(timeout) Checks is connection is still valid
Constructor Details
#
(void)
constructor(connection)
constructor method
Instance Method Details
#
(void)
setAutoCommit(autoCommit)
Set the auto-commit mode of the connection
#
(Statement)
createStatement()
Create a statement for executing SQL queries.
SQL statements with no parameters can be executed by using Statement object. @example statement.executeQuery('SELECT COL_NAME FROM MY_TABLE')
If the sql statement is to be executed many times or with binding parameters
Connection#prepareStatement should be used instead
#
(PreparedStatement)
prepareStatement(sql)
Creates a PreparedStatement for executing SQL statements with or without parameter binding. This is designed for precompilation optimization. If the driver supports precompilation option then given sql statement will be passed to datasource for precompilation once when this method is called. If precompilation is not supported then the SQL statement will be passed when the PreparedStatement object is executed.
#
(CallableStatement)
prepareCall(call)
Creates a CallableStatement object for calling database stored procedures.
#
(void)
commit()
Persists the changes to the datasource from the last commit. This method throws exception if the auto-commit mode is on.
#
(void)
rollback()
Ignore all the changes since last commit and release locks on the given datastore. This method throws exception if the auto-commit mode is on.
#
(void)
close()
Closes the connection to the given datasource.
#
(boolean)
isClosed()
Checks if the connection is closed
#
(void)
isValid(timeout)
Checks is connection is still valid


history
Click on the button to push items to the history. Then, navigate with the 'back' and 'forward' buttons of your browser. See the result in the section below
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| Package | Description |
|---|---|
| org.jclouds.fujitsu.fgcp.compute.functions | |
| org.jclouds.fujitsu.fgcp.compute.strategy | |
| org.jclouds.fujitsu.fgcp.domain |
Licensed to jclouds, Inc.
|
| org.jclouds.fujitsu.fgcp.services | |
| org.jclouds.fujitsu.fgcp.xml.internal |
Licensed to jclouds, Inc.
|
| Class and Description |
|---|
| CPU
Describes the virtual CPU of a server.
|
| Disk
Describes a disk as part of the description of hardware represented by a
virtual server.
|
| DiskImage
Represents a disk image with pre-installed OS and/or software.
|
| ServerType
Describes the hardware of a virtual server.
|
| VServer
Represents a virtual server.
|
| VServerStatus
Possible statuses of a virtual server.
|
| VServerWithVNICs |
| Class and Description |
|---|
| DiskImage
Represents a disk image with pre-installed OS and/or software.
|
| PublicIP
Represents a public IP address.
|
| ServerType
Describes the hardware of a virtual server.
|
| VServer
Represents a virtual server.
|
| VServerStatus
Possible statuses of a virtual server.
|
| VServerWithVNICs |
| Class and Description |
|---|
| BuiltinServer
Represents a built-in server, also called extended function module (EFM),
such as a firewall or load balancer (SLB).
|
| BuiltinServer.BuiltinServerType |
| BuiltinServerConfiguration
Possible statuses of a built-in server, also called extended function module
(EFM), such as a firewall or load balancer (SLB).
|
| BuiltinServerStatus
Possible statuses of a built-in server, also called extended function module
(EFM), such as a firewall or load balancer (SLB).
|
| Cause
Represents a load balancer (SLB) log entry.
|
| CPU
Describes the virtual CPU of a server.
|
| Direction
Grouping of firewall rules pertaining to a particular direction in network
traffic, e.g.
|
| Disk
Describes a disk as part of the description of hardware represented by a
virtual server.
|
| DiskImage
Represents a disk image with pre-installed OS and/or software.
|
| DiskImage.Builder |
| ErrorStatistics
Holds statistics of errors reported by a load balancer (SLB).
|
| Firewall
Represents a firewall (FW).
|
| Group
Describes attributes of a software load balancer's (SLB) configuration.
|
| Image
Holds information on the system disk image of a virtual server, including the
OS and software pre-installed on it.
|
| IntermediateCACert
Describes an intermediate CA certificate for use with a load balancer (SLB).
|
| LoadStatistics
Holds statistics of the load on a load balancer (SLB).
|
| Memory
Represents the memory of a virtual server.
|
| NAT
Holds the network address translation rules of a firewall.
|
| PerformanceInfo
Holds the statistics of a virtual server.
|
| Period
Describes the period over which error statistics of a load balancer (SLB) are
kept.
|
| Policy
Describes a firewall rule in detail.
|
| Product
Represents a product for which usage information can be queried.
|
| PublicIP
Represents a public IP address.
|
| PublicIP.Version |
| PublicIPStatus
Possible statuses of a public IP address.
|
| Rule
Represents a network address translation or network address port translation
rule.
|
| ServerCert
Describes a server certificate for use with a load balancer (SLB).
|
| ServerType
Describes the hardware of a virtual server.
|
| SLB
Represents a software load balancer.
|
| Software
Represents the software installed on a disk.
|
| Target
Describes the target server of a load balancer.
|
| VDisk
Represents attachable storage in the form of a virtual disk.
|
| VDiskStatus
Possible statuses of an attachable virtual disk.
|
| VNet
Represents a virtual network.
|
| VNIC
Represents a virtual network interface card (NIC).
|
| VServer
Represents a virtual server.
|
| VServerStatus
Possible statuses of a virtual server.
|
| VServerWithDetails
Represents a virtual server with virtual storage and NICs.
|
| VServerWithVNICs |
| VSystem
Represents a virtual system.
|
| VSystemStatus
Possible statuses of a virtual system.
|
| Class and Description |
|---|
| AddressRange
Describes the address range pool in a contract used for allocating private IP
address network segments for virtual systems.
|
| BuiltinServer
Represents a built-in server, also called extended function module (EFM),
such as a firewall or load balancer (SLB).
|
| BuiltinServerBackup
Holds information on a backup of a built-in server, such as a firewall or
load balancer (SLB).
|
| BuiltinServerConfiguration
Possible statuses of a built-in server, also called extended function module
(EFM), such as a firewall or load balancer (SLB).
|
| BuiltinServerStatus
Possible statuses of a built-in server, also called extended function module
(EFM), such as a firewall or load balancer (SLB).
|
| DiskImage
Represents a disk image with pre-installed OS and/or software.
|
| EventLog
Represents an entry in the event log.
|
| Information
Holds information relating to the FGCP service.
|
| PerformanceInfo
Holds the statistics of a virtual server.
|
| PublicIP
Represents a public IP address.
|
| PublicIPStatus
Possible statuses of a public IP address.
|
| Rule
Represents a network address translation or network address port translation
rule.
|
| ServerType
Describes the hardware of a virtual server.
|
| UsageInfo
Describes the usage by a virtual system.
|
| VDisk
Represents attachable storage in the form of a virtual disk.
|
| VDiskStatus
Possible statuses of an attachable virtual disk.
|
| VServer
Represents a virtual server.
|
| VServerStatus
Possible statuses of a virtual server.
|
| VServerWithDetails
Represents a virtual server with virtual storage and NICs.
|
| VSystem
Represents a virtual system.
|
| VSystemDescriptor
Describes a virtual system template.
|
| VSystemStatus
Possible statuses of a virtual system.
|
| VSystemWithDetails
Represents a virtual system with servers, additional storage, public IP
addresses and networks.
|
| Class and Description |
|---|
| AddressRange
Describes the address range pool in a contract used for allocating private IP
address network segments for virtual systems.
|
| BuiltinServer
Represents a built-in server, also called extended function module (EFM),
such as a firewall or load balancer (SLB).
|
| BuiltinServerBackup
Holds information on a backup of a built-in server, such as a firewall or
load balancer (SLB).
|
| DiskImage
Represents a disk image with pre-installed OS and/or software.
|
| EventLog
Represents an entry in the event log.
|
| PerformanceInfo
Holds the statistics of a virtual server.
|
| PublicIP
Represents a public IP address.
|
| ServerType
Describes the hardware of a virtual server.
|
| VDisk
Represents attachable storage in the form of a virtual disk.
|
| VServer
Represents a virtual server.
|
| VSystem
Represents a virtual system.
|
Copyright © 2009-2013 jclouds. All Rights Reserved.


Young people have their say on climate change at Dail na nOg sitting
A total of 68 young people from 31 Comhairle na nOg groups debated the chosen theme of climate action as part of the Dail 100 commemorations
by irishmirror.ieIreland's young people have had their say on climate change at a sitting of Dail na nOg.
Amy White from Wexford is shown taking part in one of the voting sessions at the youth parliament with her fellow members looking on.
A total of 68 young people from 31 Comhairle na nOg groups debated the chosen theme of climate action as part of the Dail 100 commemorations.
They agreed a two-year programme of work focusing on how young people in Ireland can take action to tackle climate change.
How to follow the Irish Mirror on social media
You can like our main Facebook page here.
Our Irish Mirror Sports page - which brings you all your Irish and UK sports news - can be found here.
You can also check out our Irish Mirror GAA sports page.
The Irish Mirror Twitter account is @IrishMirror while our sports account is @MirrorSportIE.
Our Instagram account can be found here.


M.A.M.R. Muthiah elected Madras Race Club chairman
M.A.M.R Muthiah was elected chairman and senior steward of the Madras Race Club (MRC)on Thursday by the 12-member committee of management that was elected at the annual general meeting of the club held here on Wednesday. Ramesh Rangarajan was elected chairman of the Board of Appeal.
Committee of Management: M.A.M.R. Muthiah (chairman), Arun Alagappan, Chaduranga Kanthraj Urs, T. Dhevanathan Yadav, K. Kaliyaperumal, SP Lakshmanan, A.C. Muthiah, Paul Antony, Rm. Ramaswamy, Ramesh Rangarajan, M. Ravi and K. Shashabindu Das.
Stewards: M.A.M.R. Muthiah (senior steward), Arun Alagappan, Chaduranga Kanthraj Urs, T. Dhevanathan Yadav, Paul Antony and K. Shashabindu Das.
Board of Appeal: Ramesh Rangarajan (chairman), K. Kaliyaperumal, F.R.A. Nathan, Rajendra Mootha and Rm. Ramaswamy.


|
Drake
|
Namespaces | |
| test | |
Functions | |
| void | CallPythonInit (const std::string &filename) |
Initializes CallPython for a given file. More... | |
| template<typename... Types> | |
| PythonRemoteVariable | CallPython (const std::string &function_name, Types... args) |
| Calls a Python client with a given function and arguments, returning a handle to the result. More... | |
| template<typename... Types> | |
| PythonRemoteVariable | ToPythonTuple (Types... args) |
| Creates a tuple in Python. More... | |
| template<typename... Types> | |
| PythonRemoteVariable | ToPythonKwargs (Types... args) |
| Creates a keyword-argument list to be unpacked. More... | |
| std::string | GetRpcPipeTempDirectory () |
| Returns a directory location suitable for temporary files for the call_* clients and libraries. More... | |
| PythonRemoteVariable drake::common::CallPython | ( | const std::string & | function_name, |
| Types... | args | ||
| ) |
Calls a Python client with a given function and arguments, returning a handle to the result.
For example uses, see call_python_test.cc
.
| void drake::common::CallPythonInit | ( | const std::string & | filename | ) |
Initializes CallPython
for a given file.
If this function is not called, then the filename defaults to /tmp/python_rpc
.
| std::runtime_error | If either this function or CallPython have already been called. |
| std::string drake::common::GetRpcPipeTempDirectory | ( | ) |
Returns a directory location suitable for temporary files for the call_* clients and libraries.
| std::runtime_error | If the path referred to by TEST_TMPDIR or /tmp does not exist or is not a directory. |
| PythonRemoteVariable drake::common::ToPythonKwargs | ( | Types... | args | ) |
Creates a keyword-argument list to be unpacked.
| args | Argument list in the form of (key1, value1, key2, value2, ...). |
| PythonRemoteVariable drake::common::ToPythonTuple | ( | Types... | args | ) |
Creates a tuple in Python.


Head Blacksmith Ferris:
Why are you still here? You must hurry and take the
Hammer of Maestro Reorin
back to its original owner! There is no time to lose!


How do I pay for your services?
Click on the "buy now" button to access the checkout page and login to your paypal account. If you do not have a paypal account, click the "create an account" or
the "pay with debit or credit card" button (depending on what your device may show you) and fill in the form using the information on your credit/debit card.
(N.B. The checkout page reflects the price for the services rendered in United States Dollars because it is the currency used by PayPal)
How long should I expect to wait for the completion of my purchased service?
Due to the high volumes of orders we recieve, your business' website or advertising campaign will be complete within 5-7 days.
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Our services are availiable online to everyone around the world.


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hey there
enter your date of birth and age
First name:
Last name:
Age:
mercury
venus
earth
mars
jupiter


HTML elements are positioned static by default. Static positioned elements are not affected by the top,bottom, left and right properties. An element with position:static is not positioned in any special way, it is always positioned accordinglyto the normal flow of the page.


TFrameViewer component
procedure Load(const SRC: String);
The Load method is used to initiate loading of an HTML document when using one of the OnBufferRequest, OnFileRequest, OnStreamRequest, or OnStringsRequest event handlers. SRC is the identifier of the document to be loaded. This method causes an immediate call to the appropriate event handler.
See also:


Someone knocks on the door of your overly spacious apartment. It's an Old Friend from childhood, or an old college roommate — someone you knew long ago but lost touch. Maybe he just stopped to say hi, or maybe he needs to bunk down at your place, or maybe he wants to share a holiday with you. He may be more wild and crazy than you. You may be reluctant to join his hijinks at first, but now that he's around, you start joining in.
This can be the premise of a work or a series. Think The Odd Couple or Supernatural.
If the Old Friend messing with your life isn't part of the premise, then Status Quo Is God will eventually have your friend leave, or you give him the boot. You will likely be unhappy; there's more than even odds he will be, too. The visit of the Old Friend will leave you wondering how little he's changed and how much you have. Or, on occasion, vice versa.
Toxic Friend Influence is when this friendship is really bad for you; expect An Aesop about leaving the past behind you, often with the main character recalling that this is why they lost touch in the first place.
In sufficiently recent works, the Old Friend is likely to be a New-Age Retro Hippie.
Compare Beleaguered Childhood Friend. Not to be confused with I Want You to Meet an Old Friend of Mine, but can overlap. Contrast Old Flame Fizzle, discovering that the friendship (instead of the love) is gone.
Examples:
- Parodied on Sayonara, Zetsubou-Sensei with a character in love with all things old-fashioned who claims to be an old friend of the title character's. It turns out that they were friends for just one day in elementary school; it's a Japanese pun.
- In chapter 112 UQ Holder!, Touta's adoptive mother takes him to meet some of her old school friends (aka the cast of Mahou Sensei Negima!).
- In Asteroid in Love, this is the forty-first chapter's premise. Specifically, Mai reunited with her elementary-school era friend Keiko, who brought Mai into maps in the first place. At Present Day, however, Keiko sees that as an Embarrassing Hobby and has a poor opinion on Mai's continued interest in this. Sayuri tries to recouncile the two.
- It turns out Crystal and Lunker were Childhood Friends in Retail'. Notably, she's the only one of Grumbel's employees allowed to call him by his real name of Mel.
- A darker example occurs in The Third Man — the main character, Holly Martins, goes to post-WWII Vienna to meet up with an old friend, who ends up having become a child-killing criminal, and whose actions turn Holly from a jovial and semi-innocent guy into a severely depressed one.
- In Kiss Kiss Bang Bang, Harry is reunited with childhood friend/crush Harmony at a Christmas party. True to this trope, her appearance heralds a whole lot of trouble for Harry.
- The Banger Sisters has Goldie Hawn arriving to bust straitlaced farmer groupie friend Susan Sarandon out of a rut she didn't know she was in.
- Rude Awakening, a 1989 film starring Cheech Marin and Eric Roberts as two former radicals who have been hiding out in the jungles of Central America from the government, returning to the US to discover that their friends have sold out.
- In Dan Abnett's Gaunt's Ghosts novel Blood Pact, an old friend of Gaunt's from school is a major character — although it is inverted, with Gaunt turning his life upside down.
- The setup for P. G. Wodehouse's Love Among the Chickens.
- In The Hitchhiker's Guide to the Galaxy, this is basically the role that wild and crazy quasi-hippie Zaphod plays to his ever-so-slightly more down-to-Earth "semi-cousin" Ford.
- Gandalf in both The Hobbit and The Lord of the Rings drops by the protagonist's house and gets him into an adventure.
- Game of Thrones:
- Ned Stark to King Robert, stemming from the two of them growing up as foster brothers.
- Howland Reed is also an old friend of Ned Stark's. Unusually, he is also The Ghost and only introduced after Ned's death.
- Scrubs uses this a lot:
- J.D. and Turk's old college buddy Spence, played by Ryan Reynolds, comes to visit. They envy Spence because he gets paid more money, works fewer hours, and gets to drink in his time off. His whole purpose in the episode is to take them out and encourage them to party like the old days; they drink while on call and then have to deal with the consequences.
- Spence even gets a What the Hell, Hero? moment when they tell him about the verbal thrashing they went through from Cox the next day.
Spence: You didn't tell me you were on call... Hey, you know, I have a presentation to give tomorrow. Ask me if I want to go out drinking tonight.Turk and J.D.: (sheepish murmuring)Spence: No. I have a presentation. - Turk's brother Kevin turns up, constantly trying to be a bundle of fun and energy to mask up his unhappiness with his divorce. He drags Turk out with him, making Turk realize that he needs to make time for his brother, even if his wackiness is annoying, because Kevin needs the emotional support. Doing so, however, causes problems in Turk's relationship with his girlfriend Carla, so actually Turk would have been better off saying no to Kevin.
- J.D.'s older brother Dan shows up in several episodes. His lack of maturity and responsibility in comparison to his younger brother is highlighted in a variety of ways, though each brother usually ends up learning something from the other by the end of each of Dan's appearances.
- Elliot's sorority sister Melody comes to visit. She still acts as wild as she did when the two were in college together, and this is contrasted with how much Elliot feels she has changed over the years.
- J.D. and Turk's old college buddy Spence, played by Ryan Reynolds, comes to visit. They envy Spence because he gets paid more money, works fewer hours, and gets to drink in his time off. His whole purpose in the episode is to take them out and encourage them to party like the old days; they drink while on call and then have to deal with the consequences.
- Friends has "Gandalf" (because he's the Party Wizard) who is never seen but is described as exactly having this effect. When he fails to get into town for a planned weekend of fun, the guys try to replicate the results without him and find they can't because they've grown up and their tastes have changed.
- Green Acres used this trope when Lisa had relatives visit. In one episode, her mother came and the entire town turned out to welcome her.
- One episode of How I Met Your Mother is dedicated to the phenomenon of "Revertigo", whereby meeting an old friend temporarily turns you into the kind of person you were when you knew them.
- Done repeatedly on all the CSI series. Usually one offs, but Sam Braun recurred and was revealed as Catherine's dad.
- Mike Franks played this role at times on NCIS, usually turning up in time to bring a case to Gibbs's attention.
- In The Legend of Zelda: Majora's Mask, Kafei hides himself in the backroom of his old friend who owns the Curiosity Shop while searching for the Sun's Mask. The Curiosity Shop owner apparently knew Kafei when the latter was just a kid and is predictably shocked to see his friend looking like a kid once again. The typical character dynamic is inverted, however, in that Kafei is the straitlaced one compared to the Curiosity Shop owner.
- A thoroughly benign example appears in Dragon Age: Inquisition. It's actually a subversion in that Baron Desjardins is an Old Friend not of anyone in the actual game, but of Josephine's father; she reaches out to him to take control of Suledin Keep once the Inquisition liberates it. The usual character dynamic is absent in that the Baron is a good-hearted and responsible man who is happy to be of service.
- In an episode of Daria, Jake and Helen's old hippie friends come stay with them for a weekend. The friends are still living the hippie lifestyles, and at first Jake and Helen try to rekindle with their hippie roots. But eventually their friends reveal how weary they are of the hippie life and instead decide to adopt a more modern lifestyle.
- Inverted and subverted in the Five-Episode Pilot of Chip 'n Dale: Rescue Rangers. Inverted in that Monterey Jack is the Old Friend of Geegaw Hackwrench, who brings Chip and Dale to drop in unannounced at Geegaw's home and enlist his help on the case they're investigating. Subverted when it's revealed that he disappeared sometime prior to the series, leaving his daughter Gadget to join the hijinks—and the cast—instead.
- My Little Pony: Friendship Is Magic: In "Griffon the Brush Off", Rainbow Dash's old friend Gilda (a griffon she met at Junior Speedster Flight Camp) comes to Ponyville to visit. When she's not hanging out with Rainbow, Gilda displays a mean streak: she steals an apple from a produce stand, scares Granny Smith, and bullies Fluttershy until she bursts into tears and runs away. When Pinkie Pie tries to turn the situation around by throwing a welcome party for Gilda, the griffon lashes out at the other ponies, calling them dweebs and insulting Pinkie as "Queen Lame-o", and tries to get Rainbow to leave the party with her. Disgusted with Gilda's rude and selfish behavior, Rainbow tells her to go find some "new cool friends someplace else", and Gilda storms out, ending the friendship.
- However, four seasons later, both Rainbow Dash and Gilda make amends with the help of Pinkie Pie and a friendship problem to rebuild Griffonstone.


{% extends "soc/base.html" %} {% comment %} Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. {% endcomment %} {% block body %} {% block instructions %} Ranking details for student. {% endblock %}
| Task | Organization | Date completed | |
|---|---|---|---|
| {{ task.title }} | {{ task.scope.name }} | {{ task.closed_on }} | {{ task.points }} |
| Total |   |   | {{ total }} |


PubNub Chess Club
Click on a user name in the Online Users list and challenge them to a match.
Find Match
You are
Online Users
Lobby Chat
Send Message


Team
Doug
Manager
ID: 1
Email:
<EMAIL_ADDRESS>Office Number: 123
Jack
Engineer
ID: 2
Email:
<EMAIL_ADDRESS>Github:
git
Tracy
Intern
ID: 3
Email:
<EMAIL_ADDRESS>School: here


Sorting
One common task for computers is to sort data. For example, people might want to see all their files on a computer sorted by size. Since sorting is a simple problem with many different possible solutions, it is often used to introduce the study of algorithms.
Insertion Sort
These challenges will cover Insertion Sort, a simple and intuitive sorting algorithm. We will first start with an already sorted list.
Insert element into sorted list
Given a sorted list with an unsorted number $e$ in the rightmost cell, can you write some simple code to insert $e$ into the array so that it remains sorted?
Print the array every time a value is shifted in the array until the array is fully sorted. The goal of this challenge is to follow the correct order of insertion sort.
Guideline: You can copy the value of $e$ to a variable and consider its cell "empty". Since this leaves an extra cell empty on the right, you can shift everything over until $V$ can be inserted. This will create a duplicate of each value, but when you reach the right spot, you can replace it with $e$.
Input Format
There will be two lines of input:
Output Format
On each line, output the entire array every time an item is shifted in it.
Constraints
$1 \le Size \le 1000$
$-10000 \le e \le 10000, e ∈ Arr$
Sample Input
5
2 4 6 8 3
Sample Output
2 4 6 8 8
2 4 6 6 8
2 4 4 6 8
2 3 4 6 8
Explanation
$3$ is removed from the end of the array.
In the $1$st line $8 > 3$, so $8$ is shifted one cell to the right.
In the $2$nd line $6 > 3$, so $6$ is shifted one cell to the right.
In the $3$rd line $4 > 3$, so $4$ is shifted one cell to the right.
In the $4$th line $2 < 3$, so $3$ is placed at position $2$.
Task
Complete the method insertionSort which takes in one parameter:
Next Challenge
In the next Challenge, we will complete the insertion sort itself!


A simple shared array implementation using Mutex locks and RMA one-sided communication.
More...
|
| template<typename T > |
| Shared< T > | MEL::SharedCreate (const int len, const int rank, const int size, const int root, const Comm &comm) |
| | Create a MEL::Shared array across a comm world. More...
|
| |
| template<typename T > |
| Shared< T > | MEL::SharedCreate (const int len, const int root, const Comm &comm) |
| | Create a MEL::Shared array across a comm world. More...
|
| |
| template<typename T > |
| void | MEL::SharedFree (Shared< T > &shared) |
| | Free a MEL::Shared array. More...
|
| |
| template<typename T > |
| bool | MEL::SharedTest (const Shared< T > &shared) |
| | Test if the shared array is currently locked. More...
|
| |
| template<typename T > |
| void | MEL::SharedLock_noget (Shared< T > &shared) |
| | Get the lock on the shared array without synchronizing the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedLock_noget (Shared< T > &shared, const int start, const int end) |
| | Get the lock on the shared array without synchronizing the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedLock (Shared< T > &shared) |
| | Get the lock on the shared array and synchronize the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedLock (Shared< T > &shared, const int start, const int end) |
| | Get the lock on the shared array and synchronize the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedUnlock_noput (Shared< T > &shared) |
| | Release the lock on the shared array without synchronizing the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedUnlock_noput (Shared< T > &shared, const int start, const int end) |
| | Release the lock on the shared array without synchronizing the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedUnlock (Shared< T > &shared) |
| | Release the lock on the shared array and synchronize the data. More...
|
| |
| template<typename T > |
| void | MEL::SharedUnlock (Shared< T > &shared, const int start, const int end) |
| | Release the lock on the shared array and synchronize the data. More...
|
| |
A simple shared array implementation using Mutex locks and RMA one-sided communication.
template<typename T >
| Shared<T> MEL::SharedCreate |
( |
const int |
len, |
|
|
const int |
rank, |
|
|
const int |
size, |
|
|
const int |
root, |
|
|
const Comm & |
comm |
|
) |
| |
|
inline |
Create a MEL::Shared array across a comm world.
- Parameters
-
| [in] | len | The number of elements to allocate |
| [in] | rank | The rank of the calling process |
| [in] | size | The size of the comm world |
| [in] | root | The rank of the process who will own the shared array |
| [in] | comm | The comm world to share the array across |
template<typename T >
| Shared<T> MEL::SharedCreate |
( |
const int |
len, |
|
|
const int |
root, |
|
|
const Comm & |
comm |
|
) |
| |
|
inline |
Create a MEL::Shared array across a comm world.
- Parameters
-
| [in] | len | The number of elements to allocate |
| [in] | root | The rank of the process who will own the shared array |
| [in] | comm | The comm world to share the array across |
template<typename T >
| void MEL::SharedFree |
( |
Shared< T > & |
shared | ) |
|
|
inline |
Free a MEL::Shared array.
- Parameters
-
| [in] | shared | The shared array to free |
template<typename T >
| bool MEL::SharedTest |
( |
const Shared< T > & |
shared | ) |
|
|
inline |
Test if the shared array is currently locked.
- Parameters
-
| [in] | shared | The shared array to test |
template<typename T >
| void MEL::SharedLock_noget |
( |
Shared< T > & |
shared | ) |
|
|
inline |
Get the lock on the shared array without synchronizing the data.
Useful for if you only intend to write to the array
- Parameters
-
| [in] | shared | The shared array to lock |
template<typename T >
| void MEL::SharedLock_noget |
( |
Shared< T > & |
shared, |
|
|
const int |
start, |
|
|
const int |
end |
|
) |
| |
|
inline |
Get the lock on the shared array without synchronizing the data.
Useful for if you only intend to write to the array
- Parameters
-
| [in] | shared | The shared array to lock |
| [in] | start | The start index to lock |
| [in] | end | The end index to lock |
template<typename T >
| void MEL::SharedLock |
( |
Shared< T > & |
shared | ) |
|
|
inline |
Get the lock on the shared array and synchronize the data.
- Parameters
-
| [in] | shared | The shared array to lock |
template<typename T >
| void MEL::SharedLock |
( |
Shared< T > & |
shared, |
|
|
const int |
start, |
|
|
const int |
end |
|
) |
| |
|
inline |
Get the lock on the shared array and synchronize the data.
- Parameters
-
| [in] | shared | The shared array to lock |
| [in] | start | The start index to lock |
| [in] | end | The end index to lock |
template<typename T >
| void MEL::SharedUnlock_noput |
( |
Shared< T > & |
shared | ) |
|
|
inline |
Release the lock on the shared array without synchronizing the data.
Useful for if you only read from the array
- Parameters
-
| [in] | shared | The shared array to unlock |
template<typename T >
| void MEL::SharedUnlock_noput |
( |
Shared< T > & |
shared, |
|
|
const int |
start, |
|
|
const int |
end |
|
) |
| |
|
inline |
Release the lock on the shared array without synchronizing the data.
Useful for if you only read from the array
- Parameters
-
| [in] | shared | The shared array to unlock |
| [in] | start | The start index to unlock |
| [in] | end | The end index to unlock |
template<typename T >
| void MEL::SharedUnlock |
( |
Shared< T > & |
shared | ) |
|
|
inline |
Release the lock on the shared array and synchronize the data.
- Parameters
-
| [in] | shared | The shared array to unlock |
template<typename T >
| void MEL::SharedUnlock |
( |
Shared< T > & |
shared, |
|
|
const int |
start, |
|
|
const int |
end |
|
) |
| |
|
inline |
Release the lock on the shared array and synchronize the data.
- Parameters
-
| [in] | shared | The shared array to unlock |
| [in] | start | The start index to unlock |
| [in] | end | The end index to unlock |


The Akan people of Ghana frequently name their children after the day of the week they were born and the order in which they were born. These "day names" have further meanings concerning the soul and character of the person. Middle names have considerably more variety and can refer to their birth order, twin status, or an ancestor's middle name.
This naming tradition is shared throughout West Africa and the African diaspora. During the 18th–19th centuries, enslaved people in the Caribbean from the region that is modern-day Ghana were referred to as Coromantees. Many of the leaders of enslaved people’s rebellions had "day names" including Cuffy, Cuffee or Kofi, Cudjoe or Kojo, Quao or Quaw, and Quamina or Kwame/Kwamina.
Most Ghanaians have at least one name from this system, even if they also have an English or Christian name. Notable figures with day names include Ghana's first president Kwame Nkrumah and former United Nations Secretary-General Kofi Annan.
In the official orthography of the Twi language, the Ashanti versions of these names as spoken in Kumasi are as follows. The diacritics on á a̍ à represent high, mid, and low tone (tone does not need to be marked on every vowel), while the diacritic on a̩ is used for vowel harmony and can be ignored. (Diacritics are frequently dropped in any case.) Variants of the names are used in other languages, or may represent different transliteration schemes. The variants mostly consist of different affixes (in Ashanti, kwa- or ko- for men and a- plus -a or -wa for women). For example, among the Fante, the prefixes are kwe- and e-, respectively. Akan d̩wo is pronounced something like English Joe, but there do appear to be two sets of names for those born on Monday.
There are also special names for elder and younger twins. The second twin to be born is considered the elder as they were mature enough to help their sibling out first. (The definition above must be a regional concept because in Cape Coast, heart of Fanti land, the elder twin is the one who comes out first, the second twin is considered the younger one. Therefore, The older twin would be Kakra; the younger twin would be Payin.)The word Payin means older/elder. Kakra is short for Kakraba which means little/younger one. The definition/description below for the meaning of younger and an elder are backwards or vice versa.
For more information about Akan Names click here.


Appointment to be cancelled:
Decemeber 27, 2016 1:00PM
Treatment X
Employee Name
If you cancel this appointment you may be charged
Reason For Cancellation:
Cancel


https://shameed.github.io/ecpl-image-viewer/
Angular4 library for image viewer in a popup
Install through npm:
npm install --save ecpl-image-viewer
Then include in your apps module:
import { NgModule } from '@angular/core';
import { EcplImageViewerModule } from 'ecpl-image-viewer';
@NgModule({
imports: [
EcplImageViewerModule.forRoot()
]
})
export class MyModule {}
Finally use in one of your apps components:
import { Component } from '@angular/core';
@Component({
template: '<hello-world></hello-world>'
})
export class MyComponent {}
You may also find it useful to view the demo source.
<script src="node_modules/ecpl-image-viewer/bundles/ecpl-image-viewer.umd.js"></script>
<script>
// everything is exported ecplImageViewer namespace
</script>
All documentation is auto-generated from the source via compodoc and can be viewed here: https://shameed.github.io/ecpl-image-viewer/docs/
npm install
while current directory is this repoRun npm start
to start a development server on port 8000 with auto reload + tests.
Run npm test
to run tests once or npm run test:watch
to continually run tests.
npm run release
MIT


## Software Engineering Project ### Presentation Marco Prosdocimi - Enrico Ruggiano - Giacomo Vercesi
--- # Concept -- ## What is Travlendar+ * Calendar application functionality * Map application which could calculate a best path -- ## Main functionalities * basic calendar function (add/update/delete events) * way to calculate best path * time/geographical data support (using Standards) * ... -- ## Other Specific function * preference system * notification support * specific event * ... -- ## A lot of work to do! -- ## Simplicity So the idea was to develop it as simple as possible. Simplicity is main key value of our project. -- ## Simplicity **Simplicity** => Maintanability => Good Teamwork => Better Result
--- # Architecture --
-- ## Client * Thin * Simple * Cross platform -- ## RestFull
-- ## Server Side
-- ## Optimal Path * RESTful Api * Computes the best routes and the mode of transportations for the given trip * closely cooperates with the scraper module -- ## User Data and Transport DBs * Used for storing persistent data --- # UI -- Particular attenction on the Graphics aspects of the client application to have the best result as possible. Best UI graphics is the key of success in software market.
-- **immediate Design** and **an every day application**. * Material Design guidelines.
-- Same graphical layout on every type of different clients => Usability Personal User page and secondary and optional user data => High Customizability --
--
--- # Implementation -- # Docker
-- #### Docker features: * Scalability * Reproducibility * Application Isolation * Network Simulation * Platform-independent build process -- ### Docker in Travlendar * All the components use a different container * Network-based interaction * Extremely simple to isolate and firewall individual components --- # Frontend -- Travlendar was projected to be easy, simple, UI friendly, client-server application and cross-platforming. Nowday's fashion using Html, Css And Javascript to handle frontend.
-- ## And this helped a lot! -- ## Cross-Platforming * Electron: desktop app * Cordova: android/ios/mobile
-- ## Javascript Comunity vast library and API support. * FullCalendar API. * OpenLayers v3 API. * Material Design lite. -- ## JQuery JQuery we could implement Event-Based design paradigm.
-- ## How it Works Html documents are the static layout page which works like a reactive gui. When user permorms some particular actions, Jquery triggers execution of javascript code.
-- ## Javascript Code The tasks of javascript frontend code are only two: * modify the layout, changing some html attribute or creating a new child element for example. * start an Ajax calls to the endpoint server to perform a GET or a POST HTTP request
-- ## CSS * adjust html layout * blink or fade animation * make responsive the html.
-- ## Other Javascript Pro * simple write code * dinamical type system. * readability * rarely are exceeded the 100 lines of code --- # Backend -- ## Python * Dynamically type system * Interpreted but efficent * Very easy to use * Vast collection of libraries
-- ### Python and RethinkDb
-- ### Python and Json
-- ## Flask Is a micro web framework API enpoint
-- ```python @app.route('/registration', methods=['POST']) def registration_api(): user = flask.request.get_json() response = registration(user) return response ``` -- ## JsonSchema * Check and validate JSON Post request ```python def registration(json): scheme = load(open("resource/registration.json")) validate(json, scheme) ``` -- #### registration.json ```json { "type" : "object", "properties": { "first_name": {"type": "string"}, "last_name": {"type": "string"}, "email": {"type": "string"}, "password": {"type": "string"} }, "required":["first_name", "last_name", "email", "password"], "additionalProperties": false } ``` --- # RethinkDB -- ### RethinkDB * document-oriented database * natively works with json * multilingual bindings --- # OptimalRoute and Valhalla -- ### Valhalla * OpenStreetMap routing engine * REST Api * Supports car, foot and bike routing -- ### OptimalRoute * 'glue' between routing data/engines * REST Api * Closely interacts with the scraper component via the Transport DB * Lightweight Plugin System --- # Testing Frontend --
It was not simple!
-- ## Standard Ways * QUnit library
-- ## Test Automation test Automation technique, which is great and widely used for web application * Selenium API -- ## Selenium * is possible to create a 'Marionette' * a 'Marionette' is an artificial user with a programmated navigation behaviour *Perform test to verify the expected update of html after ajax call or jquery modification*.
-- ## Test Java Suit * Selenium Api supported it * jUnit and other usefull java testing libriaries * starting a sistematic test simply executing a jar file
-- ## Html Log
--- # Testing Backend -- ## python test unittest framework -- ```python @classmethod def setUpClass(cls): # code # the tests need login def setUp(self): # code def tearDown(self): # code @classmethod def tearDownClass(cls): # code ``` --- # Other Test -- ## Jmeter * Test Restfull Api
-- * Perform Post or Get Request * Make an assertion of the response * Suppose the back end work correctly


Honzi
/
Personal Bests
/RuneScape
Version
Status
Old School RuneScape
Hardcore Ironman
RuneScape 3
Quit


Building Materials
Greyboxing, building cities, and updates
March 8, 2023
Hobbitses! This week I've had the pleasure to begin building other parts of Middle-earth, and my personal favorite the City of Kings: Minas Tirith! While again most of the work is greyboxes, the first result is very impressive may I say!
But wait! There is more!
I also updated the world map with region names and models of monuments and fortresses, making navigation a bit easier. Unless you know the map of Middle-Earth by heart... And I also made a few tweeks to the main menu scene. Mostly, it's color and scale changes, but the scene is coming together. Water shaders are in the pipelines!
The City of Kings!
Second floor of Minas Tirith. That gate is almost 20 meters high!
Top-floor of Minas Tirith. There is a small corridor leading to the floor below.
The Argonath and a good book. Working on adding some water shaders, just waiting for James Cameron to answer all my prayers! ಠ_ಠ
World map with Region names. Had to remove the flight mechanics, since they are now bugged! ¯\_(ツ)_/¯ Working on fixing that though!
Greyboxing Moria
Exploring the halls of Moria
February 28, 2023
Hobbitses! I've been busy with building up a simple greybox level for Moria. Most of the layout is just for exploration and the purpose of this exercise is essentially to get a feel for the size and scale of what a level could look like. The main gist of it goes as follow:
1. You begin in a vast open area, maybe do some looting and BAM! Balrog appears (outta nowhere)!
2. You run through Moria fighting a bit of evil, goblins, and trolls on the way. Nasty business.
3. You arrive at the stairs and run down to a main open area. Could be a good spot to engage in some combat. More enemies appear.
4. You escape all the enemies and arrive at the bridge of Khazad-dûm.
5. You have a final confrontation with the Balrog; maybe break the bridge and escape?
Designing a level based on a structured adventure as this is quite the challenge. Not only is the process of laying out the room tedious, it is also challenging to follow the prelaid narrative.
We all know how this is supposed to go: Balrog appears, fellowship runs away to bridge, Gandalf stays behind (making space...), and the fellowship escapes.
This poses a problem: suppose you have picked a character, say you play as Boromir. After the bridge, you still have to escape the goblins and end the level on the other side of Moria, i.e. escape the mountain, and travel on to Lothlorien.
However, say you pick Gandalf. Now you have a similar gameflow, but, once you get to the bridge, you fight off with the Balrog.
1. Then you fall.
2. Then you keep fighting him mid-air.
3. And then through fire and water.
4. From the darkest pit of Moria to its highest point, Durin's tower, above Moria upon the peak of Zirakzigil.
Now that's a challenge.
But while I figure that out, feel free to enjoy some videos and pictures below. The whole Zirakzigil thing is a bit overkill right now. :) Last but not least, Unity's built in Probuilder is very handy to quickly generate level geometry and makes it super easy to adjust and change things on the fly, so kudos to the wizards at Unity!
The lighting is awful. It looks okay on my monitor, but once in VR, the scene is very dark. I'll have to find a good lighting solution. Right now, it gets the job done.
Complete walkthrough of the level.
Added a little Gandalf for scale. He's very laid back.
The bridge is only 2 meters across, but the Balrog is bigger. Also, yes, I fell on purpose.
Shadow and Flame
Introducing Durin's Bane
February 16, 2023
Well... this is fun. New website (had to refresh a few things), and of course news! For those who don't know, I'm fumbling around a little VR project codenamed "Blue Harvest" built using the Unity3D engine. Recently I started working on particles and what better exemple for particles then the one and only Durin's Bane!
 I decided to use the Unity VFX-graph to generate the particle systems, since it has the skinned mesh property. This allows you to spawn particles along the vertices of an animated mesh. The fire particles are also using a flipbook animated texture, creating a feeling of very dynamic fire and the particles fire spawn from both his head and wings.
Last but not least, the Balrog is described as a creature of shadow and flames. Using the same techniques, I added a smoke particle system to the skinnedMesh, to get that sense of fiery hell.
There is still some polish to be done! I'm thinking, sparks, heat distortion, fiery flaming sword of fire, but I'm amazed by the initial result! Check out some work in progress screenshot below!
The bloom is more intense then I thought!
Integrating the Balrog in a greybox room of Moria. Feeling the heat. Now how do I fight him?
Fly you fools!
Prototyping flight mechanics
February 16, 2023
This is the answer to the old age question: "Why don't you just fly into Mordor on the back of an Eagle?"
Well... turns out flying is hard! Not only in order to not induce motion sickness, but also in order to provide easy controls.
In order to do this, I've decided to build a flight rig. Essentially, the player rig is being pulled by the flying object (in this case the bird). The flight direction is determined by the position of the player hand, acting as the aim point. This way the player can just intuitively point and aim at a direction, and the bird flies toward that direction.
First steps in flight: getting the animation and player in position. Saddle on!
Once you get the hang of it, it's actually fun! But how do I adjust the flight speed? There is work to be done!


| Opcode/Instruction | Op/En | 64/32-bit Mode | CPUID Feature Flag | Description |
|---|---|---|---|---|
| F2 0F F0 /r LDDQU xmm1, mem | RM | V/V | SSE3 | Load unaligned data from mem and return double quadword in xmm1. |
| VEX.128.F2.0F.WIG F0 /r VLDDQU xmm1, m128 | RM | V/V | AVX | Load unaligned packed integer values from mem to xmm1. |
| VEX.256.F2.0F.WIG F0 /r VLDDQU ymm1, m256 | RM | V/V | AVX | Load unaligned packed integer values from mem to ymm1. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| RM | ModRM:reg (w) | ModRM:r/m (r) | NA | NA |
The instruction is functionally similar to (V)MOVDQU ymm/xmm, m256/m128 for loading from memory. That is: 32/16 bytes of data starting at an address specified by the source memory operand (second operand) are fetched from memory and placed in a destination register (first operand). The source operand need not be aligned on a 32/16-byte boundary. Up to 64/32 bytes may be loaded from memory; this is implementation dependent.
This instruction may improve performance relative to (V)MOVDQU if the source operand crosses a cache line boundary. In situations that require the data loaded by (V)LDDQU be modified and stored to the same location, use (V)MOVDQU or (V)MOVDQA instead of (V)LDDQU. To move a double quadword to or from memory locations that are known to be aligned on 16-byte boundaries, use the (V)MOVDQA instruction.
In 64-bit mode, use of the REX.R prefix permits this instruction to access additional registers (XMM8-XMM15).
Note: In VEX-encoded versions, VEX.vvvv is reserved and must be 1111b otherwise instructions will #UD.
DEST[127:0] ← SRC[127:0] DEST[MAXVL-1:128] (Unmodified)
DEST[127:0] ← SRC[127:0] DEST[MAXVL-1:128] ← 0
DEST[255:0] ← SRC[255:0]
LDDQU: __m128i _mm_lddqu_si128 (__m128i * p);
VLDDQU: __m256i _mm256_lddqu_si256 (__m256i * p);
None
See Exceptions Type 4;
Note treatment of #AC varies.


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--- layout: post title: Learning feature vector tagline: " for words" permalink: /machine-learning/neural-network/feature-vector-for-words.html categories: [machine learning, neural networks] tags: [feature vector,] ---
Christopher = Penelope Margaret = Arthur Andrew = Christine Victoria = James Colin Charlotte Roberto = Maria Gina = Emilio Alfonso Jennifer = Charles Pierro = Francesca Lucia = Marco Sophia Angela = Tomaso
• Make a set of propositions using the 12 relationships:
– son, daughter, nephew, niece, father, mother, uncle, aunt
– brother, sister, husband, wife
• (colin has-father james)
• (colin has-mother victoria)
• (james has-wife victoria) this follows from the two above
• (charlotte has-brother colin)
• (victoria has-brother arthur)
• (charlotte has-uncle arthur) this follows from the above
• Given a large set of triples that come from some family trees, figure out the regularities.
– The obvious way to express the regularities is as symbolic rules (x has-mother y) & (y has-husband z) => (x has-father z)
• Finding the symbolic rules involves a difficult search through a very large discrete space of possibilities.
• Can a neural network capture the same knowledge by searching through a continuous space of weights?
local encoding of person 2 output distributed encoding of person 2 units that learn to predict features of the output from features of the inputs distributed encoding of person 1 local encoding of person 1 distributed encoding of relationship inputs local encoding of relationshipChristopher = Penelope Margaret = Arthur Andrew = Christine Victoria = James Colin Charlotte Jennifer = Charles
• The six hidden units in the bottleneck connected to the input representation of person 1 learn to represent features of people that are useful for predicting the answer.
– Nationality, generation, branch of the family tree.
• These features are only useful if the other bottlenecks use similar representations and the central layer learns how features predict other features. For example: Input person is of generation 3 and relationship requires answer to be one generation up implies Output person is of generation 2
• Train the network on all but 4 of the triples that can be made using the 12 relationships
– It needs to sweep through the training set many times adjusting the weights slightly each time.
• Then test it on the 4 held-out cases.
– It gets about 3/4 correct.
– This is good for a 24-way choice.
– On much bigger datasets we can train on a much smaller fraction of the data.
• Suppose we have a database of millions of relational facts of the form (A R B).
– We could train a net to discover feature vector representations of the terms that allow the third term to be predicted from the first two.
– Then we could use the trained net to find very unlikely triples. These are good candidates for errors in the database.
• Instead of predicting the third term, we could use all three terms as input and predict the probability that the fact is correct.
– To train such a net we need a good source of false facts.
• There has been a long debate in cognitive science between two rival theories of what it means to have a concept: The feature theory : A concept is a set of semantic features.
– This is good for explaining similarities between concepts.
– Its convenient: a concept is a vector of feature activities. The structuralist theory: The meaning of a concept lies in its relationships to other concepts.
– So conceptual knowledge is best expressed as a relational graph.
– Minsky used the limitations of perceptrons as evidence against feature vectors and in favor of relational graph representations.
• These two theories need not be rivals. A neural net can use vectors of semantic features to implement a relational graph.
– In the neural network that learns family trees, no explicit inference is required to arrive at the intuitively obvious consequences of the facts that have been explicitly learned.
– The net can “intuit” the answer in a forward pass.
• We may use explicit rules for conscious, deliberate reasoning, but we do a lot of commonsense, analogical reasoning by just “seeing” the answer with no conscious intervening steps.
– Even when we are using explicit rules, we need to just see which rules to apply.
• The obvious way to implement a relational graph in a neural net is to treat a neuron as a node in the graph and a connection as a binary relationship. But this “localist” method will not work:
– We need many different types of relationship and the connections in a neural net do not have discrete labels.
– We need ternary relationships as well as binary ones. e.g. A is between B and C.
• The right way to implement relational knowledge in a neural net is still an open issue.
– But many neurons are probably used for each concept and each neuron is probably involved in many concepts. This is called a “distributed representation”.
• The squared error measure has some drawbacks:
– If the desired output is 1 and the actual output is 0.00000001 there is almost no gradient for a logistic unit to fix up the error.
– If we are trying to assign probabilities to mutually exclusive class labels, we know that the outputs should sum to 1, but we are depriving the network of this knowledge.
• Is there a different cost function that works better?
– Yes: Force the outputs to represent a probability distribution across discrete alternatives.
The output units in a softmax group use a non-local non-linearity: y i z i softmax group this is called the “logit” y i = e z i ∑ e z j j∈group ∂y i = y i ( 1 − y i ) ∂z i
• The right cost function is the negative log probability of the right answer.
• C has a very big gradient when the target value is 1 and the output is almost zero.
– A value of 0.000001 is much better than 0.000000001
– The steepness of dC/dy exactly balances the flatness of dy/dz
\(C = -\displaystyle \sum_{j} target_j \log y_j\)
\(\frac {\partial C}{\partial z_i} = \displaystyle \sum_j \frac {\partial C}{\partial y_j} \frac {\partial y_i}{\partial z_j} = y_j - t_j\)
• We cannot identify phonemes perfectly in noisy speech
– The acoustic input is often ambiguous: there are several different words that fit the acoustic signal equally well.
• People use their understanding of the meaning of the utterance to hear the right words.
– We do this unconsciously when we wreck a nice beach.
– We are very good at it.
• This means speech recognizers have to know which words are likely to come next and which are not.
– Fortunately, words can be predicted quite well without full understanding.
•
• Take a huge amount of text and count the frequencies of all triples of words. Use these frequencies to make bets on the relative probabilities of words given the previous two words:
\(\frac{p(w_3 = c | w_2 = b, w_1 = a)}{p(w_3 = d | w_2 = b, w_1 = a)} = \frac{count(abc)}{count(abd)}\)
• Until very recently this was the state-of-the-art.
– We cannot use a much bigger context because there are too many possibilities to store and the counts would mostly be zero.
– We have to “back-off” to digrams when the count for a trigram is too small.
• The probability is not zero just because the count is zero!
• Suppose we have seen the sentence “the cat got squashed in the garden on friday”
• This should help us predict words in the sentence “the dog got flattened in the yard on monday”
• A trigram model does not understand the similarities between
– cat/dog squashed/flattened garden/yard friday/monday
• To overcome this limitation, we need to use the semantic and syntactic features of previous words to predict the features of the next word.
– Using a feature representation also allows a context that contains many more previous words (e.g. 10).
“ softmax” units (one per possible next word) skip-layer connections units that learn to predict the output word from features of the input words learned distributed encoding of word t-2 table look-up index of word at t-2 learned distributed encoding of word t-1 table look-up index of word at t-1
• Each unit in the last hidden layer has 100,000 outgoing weights.
– So we cannot afford to have many hidden units.
• Unless we have a huge number of training cases.
– We could make the last hidden layer small, but then its hard to get the 100,000 probabilities right.
• The small probabilities are often relevant.
• Is there a better way to deal with such a large number of outputs?Neural Networks for Machine Learning Lecture 4e
of possible outputs in neuro-probabilistic language models Geoffrey
Hinton with Nitish Srivastava Kevin Swersky of possible outputs in neuro-probabilistic language models
Try all candidate next words one at a time. logit score for the candidate word This allows the learned feature vector representation to be used for the candidate word. hidden units that discover good or bad combinations of features learned distributed encoding of word t-2 table look-up index of word at t-2 learned distributed encoding of word t-1 table look-up index of word at t-1 learned distributed encoding of candidate table look-up index of candidate
• After computing the logit score for each candidate word, use all of the logits in a softmax to get word probabilities.
• The difference between the word probabilities and their target probabilities gives cross-entropy error derivatives.
– The derivatives try to raise the score of the correct candidate and lower the scores of its high-scoring rivals.
• We can save a lot of time if we only use a small set of candidates suggested by some other kind of predictor.
– For example, we could use the neural net to revise the probabilities of the words that the trigram model thinks are likely.
path through a tree (Minih and Hinton, 2009)
• Arrange all the words in a binary tree with words as the leaves.
• Use the previous context to generate a “prediction vector”, v.
– Compare v with a learned vector, u, at each node of the tree.
– Apply the logistic function to the scalar product of u and v to predict the probabilities of taking the two branches of the tree.
– So during learning, we only need to consider the nodes on the correct path. This is an exponential win: log(N) instead of N.
– For each of these nodes, we know the correct branch and we know the current probability of taking it so we can get derivatives for learning both the prediction vector v and that node vector u.
• Unfortunately, it is still slow at test time.
(Collobert and Weston, 2008) Learn to judge if a word fits the 5 word context on either side of it. right or random? Train on ~600 million examples. Use for many different NLP tasks. units that learn to predict the output from features of the input words word code word code word code word code word at t-2 word at t-1 word at t or random word word at t+1 word code word at t+2
• We can get an idea of the quality of the learned feature vectors by displaying them in a 2-D map.
– Display very similar vectors very close to each other.
– Use a multi-scale method called “t-sne” that also displays similar clusters near each other.
• The learned feature vectors capture lots of subtle semantic distinctions, just by looking at strings of words.
– No extra supervision is required.
– The information is all in the contexts that the word is used in.
– Consider “She scrommed him with the frying pan.”


The Hundred-Year Language
Here. Paul gets a bit wordy, but I really like the idea that most of the concepts we use in our programming languages are optimizations. How much simpler would programming be if we could do away with things like the artificial distinction between arrays and strings?


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Lorem ipsum dolor sit amet, consectetur adipisicing elit. Molestias, consequuntur iure commodi omnis at pariatur quis hic mollitia impedit error.


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Polls are weighted to ensure that they are representative but this weighting can be
subjective.
Change the weighting and see how the margins change!
Surveys only capture a sample of the population, so we know that the result probably
won’t exactly match the “true” result that we would get if we surveyed everyone in the
population or that we would expect to see on election day.
Without adjustment, surveys tend to over represent people who are easier to reach and
underrepresent those types of people who are harder to reach. In order to make the
results more representative we weight the data so that it matches the population – based
on a number of demographic measures. Weighting is a crucial step for avoiding biased
results, but it also has the effect of making the margin of error larger. Using US
Census data and voting history, we can get a rough sense of the proportions of gender,
race, age, and political/voting history we would expect to see in our sample.
We can either weight data based off of the most recent census (the default) or exit
polling.
{% include checkbox.html id="census-overall" text="Weight data based off demographics.
(Traditional weights)" classes="option census-data"%}
{% include checkbox.html id="gender" text="Gender"
classes="subOption census-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="race" text="Race" classes="subOption census-data weight"
parentClasses="pl-4"%}
{% include checkbox.html id="education" text="Education"
classes="subOption census-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="income" text="Income"
classes="subOption census-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="age" text="Age" classes="subOption census-data weight"
parentClasses="pl-4"%}
{% include checkbox.html id="loc_county" text="Location (county)"
classes="subOption census-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="past-vote-overall" text="Weight data based off past voting
history.
(Traditional weights)" classes="option past-vote-data"%}
{% include checkbox.html id="vote2016" text="2016 Presidential Election
Vote" classes="subOption past-vote-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="vote2020" text="2020 Presidential Election
Vote" classes="subOption past-vote-data weight" parentClasses="pl-4"%}
{% include checkbox.html id="experimental-overall" text="Weight data based off more
experimental factors" classes="option experimental-data weight" checked=false%}
{% include checkbox.html id="gss_trust" text="General social trust-- adjust for people who
trust strangers more being more likely to take surveys" classes="subOption
experimental-data weight" parentClasses="pl-4" checked=false%}
{% include checkbox.html id="gss_bible" text="Adjust for views on the bible"
classes="subOption experimental-data weight" parentClasses="pl-4" checked=false%}
{% include checkbox.html id="gss_spanking" text="Adjust for views spanking children, a proxy
for income and many social views." classes="subOption experimental-data weight"
parentClasses="pl-4" checked=false%}
{% include checkbox.html id="social_fb" text="Adjust for facebook usage." classes="subOption
experimental-data weight" parentClasses="pl-4" checked=false%}
To create a view of what will happen on election day, it is important to only sample
those who vote. However, many people ineligible to vote and eligible voters who end up
deciding not to vote still show up in our survey sample. To resolve this, we create a
probabilistic likely voter model and weigh our results accordingly.
Our likely voter model is based on the Perry-Gallup index outlined in Pew 2016.
We give respondents "points" that estimate how likely we think they are to vote. More
points means we think they're more likely to vote.
How many points to give respondents who...
{% include slider.html text="turned out in 2020"
id="turnout2020" min="0.01" max="2" defaultValue="0.5" step="0.001" %}
{% include slider.html text="said they already voted"
id="alreadyVoted" min="0.01" max="2" defaultValue="1" step="0.001" %}
{% include slider.html text="said they were \"very likely\" to vote"
id="veryLikely" min="0.01" max="2" defaultValue="1" step="0.001" %}
{% include slider.html text="said they were \"likely\" to vote"
id="likely" min="0.01" max="2" defaultValue="0.7" step="0.001" %}
{% include slider.html text="said they were \"somewhat likely\" to vote"
id="somewhatLikely" min="0.01" max="2" defaultValue="0.4" step="0.001" %}
{% include slider.html text="said they were \"neither likely nor unlikely\" to vote"
id="neitherLikelyNorUnlikely" min="0.01" max="2" defaultValue="0.2" step="0.001" %}
{% include slider.html text="said they were \"somewhat unlikely\" to vote"
id="somewhatUnlikely" min="0.01" max="2" defaultValue="0.1" step="0.001" %}
{% include slider.html text="said they were \"unlikely\" to vote"
id="unlikely" min="0.01" max="2" defaultValue="0.05" step="0.001" %}


pg_resetwal — reset the write-ahead log and other control information of a PostgreSQL database cluster
pg_resetwal
[ --force
| -f
] [ --dry-run
| -n
] [option
...] [ --pgdata
| -D
] datadir
pg_resetwal
clears the write-ahead log (WAL) and
optionally resets some other control information stored in the
pg_control
file. This function is sometimes needed
if these files have become corrupted. It should be used only as a
last resort, when the server will not start due to such corruption.
After running this command, it should be possible to start the server,
but bear in mind that the database might contain inconsistent data due to
partially-committed transactions. You should immediately dump your data,
run initdb
, and reload. After reload, check for
inconsistencies and repair as needed.
This utility can only be run by the user who installed the server, because
it requires read/write access to the data directory.
For safety reasons, you must specify the data directory on the command line.
pg_resetwal
does not use the environment variable
PGDATA
.
If pg_resetwal
complains that it cannot determine
valid data for pg_control
, you can force it to proceed anyway
by specifying the -f
(force) option. In this case plausible
values will be substituted for the missing data. Most of the fields can be
expected to match, but manual assistance might be needed for the next OID,
next transaction ID and epoch, next multitransaction ID and offset, and
WAL starting location fields. These fields can be set using the options
discussed below. If you are not able to determine correct values for all
these fields, -f
can still be used, but
the recovered database must be treated with even more suspicion than
usual: an immediate dump and reload is imperative. Do not
execute any data-modifying operations in the database before you dump,
as any such action is likely to make the corruption worse.
-f
--force
Force pg_resetwal
to proceed even if it cannot determine
valid data for pg_control
, as explained above.
-n
--dry-run
The -n
/--dry-run
option instructs
pg_resetwal
to print the values reconstructed from
pg_control
and values about to be changed, and then exit
without modifying anything. This is mainly a debugging tool, but can be
useful as a sanity check before allowing pg_resetwal
to proceed for real.
-V
--version
Display version information, then exit.
-?
--help
Show help, then exit.
The following options are only needed when
pg_resetwal
is unable to determine appropriate values
by reading pg_control
. Safe values can be determined as
described below. For values that take numeric arguments, hexadecimal
values can be specified by using the prefix 0x
.
-c xid
,xid
--commit-timestamp-ids=xid
,xid
Manually set the oldest and newest transaction IDs for which the commit time can be retrieved.
A safe value for the oldest transaction ID for which the commit time can
be retrieved (first part) can be determined by looking
for the numerically smallest file name in the directory
pg_commit_ts
under the data directory. Conversely, a safe
value for the newest transaction ID for which the commit time can be
retrieved (second part) can be determined by looking for the numerically
greatest file name in the same directory. The file names are in
hexadecimal.
-e xid_epoch
--epoch=xid_epoch
Manually set the next transaction ID's epoch.
The transaction ID epoch is not actually stored anywhere in the database
except in the field that is set by pg_resetwal
,
so any value will work so far as the database itself is concerned.
You might need to adjust this value to ensure that replication
systems such as Slony-I and
Skytools work correctly —
if so, an appropriate value should be obtainable from the state of
the downstream replicated database.
-l walfile
--next-wal-file=walfile
Manually set the WAL starting location by specifying the name of the next WAL segment file.
The name of next WAL segment file should be
larger than any WAL segment file name currently existing in
the directory pg_wal
under the data directory.
These names are also in hexadecimal and have three parts. The first
part is the “timeline ID” and should usually be kept
the same.
For example, if<PHONE_NUMBER>0000320000004A
is the
largest entry in pg_wal
, use -l<PHONE_NUMBER>0000320000004B
or higher.
Note that when using nondefault WAL segment sizes, the numbers in the WAL file names are different from the LSNs that are reported by system functions and system views. This option takes a WAL file name, not an LSN.
pg_resetwal
itself looks at the files in
pg_wal
and chooses a default -l
setting
beyond the last existing file name. Therefore, manual adjustment of
-l
should only be needed if you are aware of WAL segment
files that are not currently present in pg_wal
, such as
entries in an offline archive; or if the contents of
pg_wal
have been lost entirely.
-m mxid
,mxid
--multixact-ids=mxid
,mxid
Manually set the next and oldest multitransaction ID.
A safe value for the next multitransaction ID (first part) can be
determined by looking for the numerically largest file name in the
directory pg_multixact/offsets
under the data directory,
adding one, and then multiplying by 65536 (0x10000). Conversely, a safe
value for the oldest multitransaction ID (second part of
-m
) can be determined by looking for the numerically smallest
file name in the same directory and multiplying by 65536. The file
names are in hexadecimal, so the easiest way to do this is to specify
the option value in hexadecimal and append four zeroes.
-o oid
--next-oid=oid
Manually set the next OID.
There is no comparably easy way to determine a next OID that's beyond the largest one in the database, but fortunately it is not critical to get the next-OID setting right.
-O mxoff
--multixact-offset=mxoff
Manually set the next multitransaction offset.
A safe value can be determined by looking for the numerically largest
file name in the directory pg_multixact/members
under the
data directory, adding one, and then multiplying by 52352 (0xCC80).
The file names are in hexadecimal. There is no simple recipe such as
the ones for other options of appending zeroes.
--wal-segsize=wal_segment_size
Set the new WAL segment size, in megabytes. The value must be set to a power of 2 between 1 and 1024 (megabytes). See the same option of initdb for more information.
While pg_resetwal
will set the WAL starting address
beyond the latest existing WAL segment file, some segment size changes
can cause previous WAL file names to be reused. It is recommended to
use -l
together with this option to manually set the
WAL starting address if WAL file name overlap will cause problems with
your archiving strategy.
-x xid
--next-transaction-id=xid
Manually set the next transaction ID.
A safe value can be determined by looking for the numerically largest
file name in the directory pg_xact
under the data directory,
adding one,
and then multiplying by 1048576 (0x100000). Note that the file names are in
hexadecimal. It is usually easiest to specify the option value in
hexadecimal too. For example, if 0011
is the largest entry
in pg_xact
, -x 0x1200000
will work (five
trailing zeroes provide the proper multiplier).
PG_COLOR
Specifies whether to use color in diagnostic messages. Possible values
are always
, auto
and
never
.
This command must not be used when the server is
running. pg_resetwal
will refuse to start up if
it finds a server lock file in the data directory. If the
server crashed then a lock file might have been left
behind; in that case you can remove the lock file to allow
pg_resetwal
to run. But before you do
so, make doubly certain that there is no server process still alive.
pg_resetwal
works only with servers of the same
major version.


Make data cleansing fun again with Pandas
04:00 PM - 04:25 PM on July 16, 2016, Room CR6Joe Hooper
- Audience level:
- novice
- Watch:
- https://www.youtube.com/watch?v=3lT1HKvwjRU
Description
This talk will provide a fast-paced introduction to cleansing text data with Python. We'll cover specific Pandas tools as well as strategies for managing the cleansing processes. Topics include: slicing/splitting/joining, transforming text, working with missing values, supplementing with additional sources, and dealing with duplicates.
Abstract
Cleaning data isn't everyone's favorite task, but Python can ease the pain. Whether you are preparing data to migrate into a database driven application or for analysis and visualization, a strong data cleansing toolkit will save you time and improve the quality of your work. With the tools and strategies covered in this talk, you'll be a data cleansing powerhouse in no time.
Planned topics include: Making effective use of Pandas features to slice, split, and join data to support data cleansing Text value transformations using conditional logic, mappings, and regular expressions Filling and supplementing missing values Merging data sources and dealing with unmatched rows Dealing with duplicates: criteria-based deduplication, merging duplicates, and handling conflicts