In 2006, Nick Galbreath was VP of Engineering at Right Media, responsible for both the Development and Operations departments for an online advertising platform that displayed and served over ten billion impressions daily.
Galbreath described the competitive landscape they operated in:
In our business, ad inventory levels were extremely dynamic, so we needed to respond to market conditions within minutes. This meant that Development had to be able to quickly make code changes and get them into production as soon as possible, otherwise we would lose to faster competitors. We found that having a separate group for testing, and even deployment, was simply too slow. We had to integrate all these functions into one group, with shared responsibilities and goals. Believe it or not, our biggest challenge was getting developers to overcome their fear of deploying their own code!
There is an interesting irony here: Dev often complains about Ops being afraid to deploy code. But in this case, when given the power to deploy their own code, developers became just as afraid to perform code deployments.
The fear of deploying code that was shared by both Dev and Ops at Right Media is not unusual. However, Galbreath observed that providing faster and more frequent feedback to engineers performing deployments (whether Dev or Ops), as well as reducing the batch size of their work, created safety and then confidence.
After observing many teams go through this transformation, Galbreath describes their progression as follows:
We start with no one in Dev or Ops being willing to push the “deploy code” button that we’ve built that automates the entire code deployment process, because of the paralyzing fear of being the first person to potentially bring all of the production systems down. Eventually, when someone is brave enough to volunteer to push their code into production, inevitably, due to incorrect assumptions or production subtleties that weren’t fully appreciated, the first production deployment doesn’t go smoothly—and because we don’t have enough production telemetry, we only find out about the problems when customers tell us.
To fix the problem, our team urgently fixes the code and pushes it into production, but this time with more production telemetry added to our applications and environment. This way, we can actually confirm that our fix restored service correctly, and we’ll be able to detect this type of problem before a customer tells us next time.
Later, more developers start to push their own code into production. And because we’re working in a complex system, we’ll still probably break something in production, but this time we’ll be able to quickly see what functionality broke, and quickly decide whether to roll back or fix-forward, resolving the problem. This is a huge victory for the entire team and everyone celebrates—we’re now on a roll.
However, the team wants to improve the outcomes of their deployments, so developers proactively get more peer reviews of their code changes (described in chapter 18), and everyone helps each other write better automated tests so we can find errors before deployment. And because everyone now knows that the smaller our production changes, the fewer problems we will have, developers start checking ever-smaller increments of code more frequently into the deployment pipeline, ensuring that their change is working successfully in production before moving to their next change.
We are now deploying code more frequently than ever, and service stability is better than ever too. We have re-discovered that the secret to smooth and continuous flow is making small, frequent changes that anyone can inspect and easily understand.
Galbreath observes that the above progression benefits everyone, including Development, Operations, and Infosec. “As the person who is also responsible for security, it’s reassuring to know that we can deploy fixes into production quickly, because changes are going into production throughout the entire day. Furthermore, it always amazes me how interested every engineer becomes in security when you find problems in their code that they are responsible for and that they can quickly fix themselves.”
The Right Media story shows that it is not enough to merely automate the deployment process—we must also integrate the monitoring of production telemetry into our deployment work, as well as establish the cultural norms that everyone is equally responsible for the health of the entire value stream.
In this chapter, we create the feedback mechanisms that enable us to improve the health of the value stream at every stage of the service life cycle, from product design through development and deployment and into operation and eventually retirement. By doing this, we ensure that our services are “production ready,” even at the earliest stages of the project, as well as integrating the learnings from each release and production problem into our future work, resulting in better safety and productivity for everyone.
In this step, we ensure that we are actively monitoring our production telemetry when anyone performs a production deployment, as was illustrated in the Right Media story. This allows whoever is doing the deployment, be it Dev or Ops, to quickly determine whether features are operating as designed after the new release is running in production. After all, we should never consider our code deployment or production change to be done until it is operating as designed in the production environment.
We do this by actively monitoring the metrics associated with our feature during our deployment to ensure we haven’t inadvertently broken our service—or worse, that we broke another service. If our change breaks or impairs any functionality, we quickly work to restore service, bringing in whoever else is required to diagnose and fix the issue.†
As described in Part III, our goal is to catch errors in our deployment pipeline before they get into production. However, there will still be errors that we don’t detect, and we rely on production telemetry to quickly restore service. We may choose to turn off broken features with feature toggles (which is often the easiest and least risky option since it involves no deployments to production), or fix forward (i.e., make code changes to fix the defect, which are then pushed into production through the deployment pipeline), or roll back (e.g., switch back to the previous release by using feature toggles or by taking broken servers out of rotation using the blue-green or canary release patterns, etc.)
Although fixing forward can often be dangerous, it can be extremely safe when we have automated testing and fast deployment processes, and sufficient telemetry that allows us to quickly confirm whether everything is functioning correctly in production.
Figure 37 shows a deployment of PHP code change at Etsy that generated a spike in PHP runtime warnings—in this case, the developer quickly noticed the problem within minutes, and generated a fix and deployed it into production, resolving the issue in less than ten minutes.
Because production deployments are one of the top causes of production issues, each deployment and change event is overlaid onto our metric graphs to ensure that everyone in the value stream is aware of relevant activity, enabling better communication and coordination, as well as faster detection and recovery.
Even when our production deployments and releases go flawlessly, in any complex service we will still have unexpected problems, such as incidents and outages that happen at inopportune times (every night at 2 a.m.). Left unfixed, these can cause recurring problems and suffering for Ops engineers downstream, especially when these problems are not made visible to the upstream engineers responsible for creating the problem.
Even if the problem results in a defect being assigned to the feature team, it may be prioritized below the delivery of new features. The problem may keep recurring for weeks, months, or even years, causing continual chaos and disruption in Operations. This is an example of how upstream work centers can locally optimize for themselves but actually degrade performance for the entire value stream.
To prevent this from happening, we will have everyone in the value stream share the downstream responsibilities of handling operational incidents. We can do this by putting developers, development managers, and architects on pager rotation, just as Pedro Canahuati, Facebook Director of Production Engineering, did in 2009. This ensures everyone in the value stream gets visceral feedback on any upstream architectural and coding decisions they make.
By doing this, Operations doesn’t struggle, isolated and alone with code-related production issues; instead, everyone is helping find the proper balance between fixing production defects and developing new functionality, regardless of where we reside in the value stream. As Patrick Lightbody, SVP of Product Management at New Relic, observed in 2011, “We found that when we woke up developers at 2 a.m., defects were fixed faster than ever.”
One side effect of this practice is that it helps Development management see that business goals are not achieved simply because features have been marked as “done.” Instead, the feature is only done when it is performing as designed in production, without causing excessive escalations or unplanned work for either Development or Operations.‡
This practice is equally applicable for market-oriented teams, responsible for both developing the feature and running it in production, and for functionally-oriented teams. As Arup Chakrabarti, Operations Engineering Manager at PagerDuty, observed during a 2014 presentation, “It’s becoming less and less common for companies to have dedicated on-call teams; instead, everyone who touches production code and environments is expected to be reachable in the event of downtime.”
Regardless of how we’ve organized our teams, the underlying principles remain the same: when developers get feedback on how their applications perform in production, which includes fixing it when it breaks, they become closer to the customer, this creates a buy-in that everyone in the value stream benefits from.
One of the most powerful techniques in interaction and user experience design (UX) is contextual inquiry. This is when the product team watches a customer use the application in their natural environment, often working at their desk. Doing so often uncovers startling ways that customers struggle with the application, such as requiring scores of clicks to perform simple tasks in their daily work, cutting and pasting text from multiple screens, or writing down notes on paper. All of these are examples of compensatory behaviors and workarounds for usability issues.
The most common reaction for developers after participating in a customer observation is dismay, often stating “how awful it was seeing the many ways we have been inflicting pain on our customers.” These customer observations almost always result in significant learning and a fervent desire to improve the situation for the customer.
Our goal is to use this same technique to observe how our work affects our internal customers. Developers should follow their work downstream, so they can see how downstream work centers must interact with their product to get it running into production.§
Developers want to follow their work downstream—by seeing customer difficulties firsthand, they make better and more informed decisions in their daily work.
By doing this, we create feedback on the non-functional aspects of our code—all the elements that are not related to the customer-facing feature—and identify ways that we can improve deployability, manageability, operability, and so on.
UX observation often has a powerful impact on the observers. When describing his first customer observation, Gene Kim, the founder and CTO at Tripwire for thirteen years and co-author of this book, said:
One of the worst moments of my professional career was in 2006 when I spent an entire morning watching one of our customers use our product. I was watching him perform an operation that we expected customers to do weekly, and, to our extreme horror, we discovered that it required sixty-three clicks. This person kept apologizing, saying things like, “Sorry, there’s probably a better way to do this.”
Unfortunately, there wasn’t a better way to do that operation. Another customer described how initial product setup took 1,300 steps. Suddenly, I understood why the job of managing our product was always assigned to the newest engineer on the team—no one wanted the job of running our product. That was one of the reasons I helped create the UX practice at my company, to help atone for the pain we were inflicting on our customers.
UX observation enables the creation of quality at the source and results in far greater empathy for fellow team members in the value stream. Ideally, UX observation helps us as we create codified non-functional requirements to add to our shared backlog of work, eventually allowing us to proactively integrate them into every service we build, which is an important part of creating a DevOps work culture.¶
Even when Developers are writing and running their code in production-like environments in their daily work, Operations may still experience disastrous production releases because it is the first time we actually see how our code behaves during a release and under true production conditions. This result occurs because operational learnings often occur too late in the software life cycle.
Left unaddressed, the result is often production software that is difficult to operate. As an anonymous Ops engineer once said, “In our group, most system administrators lasted only six months. Things were always breaking in production, the hours were insane, and application deployments were painful beyond belief—the worst part was pairing the application server clusters, which would take us six hours. During each moment, we all felt like the developers personally hated us.”
This can be an outcome of not having enough Ops engineers to support all the product teams and the services we already have in production, which can happen in both functionally- and market-oriented teams.
One potential countermeasure is to do what Google does, which is have Development groups self-manage their services in production before they become eligible for a centralized Ops group to manage. By having developers be responsible for deployment and production support, we are far more likely to have a smooth transition to Operations.**
To prevent the possibility of problematic, self-managed services going into production and creating organizational risk, we may define launch requirements that must be met in order for services to interact with real customers and be exposed to real production traffic. Furthermore, to help the product teams, Ops engineers should act as consultants to help them make their services production-ready.
By creating launch guidance, we help ensure that every product team benefits from the cumulative and collective experience of the entire organization, especially Operations. Launch guidance and requirements will likely include the following:
Superficially, these requirements may appear similar to traditional production checklists we have used in the past. However, the key differences are we require effective monitoring to be in place, deployments to be reliable and deterministic, and an architecture that supports fast and frequent deployments.
If any deficiencies are found during the review, the assigned Ops engineer should help the feature team resolve the issues or even help re-engineer the service if necessary, so that it can be easily deployed and managed in production.
At this time, we may also want to learn whether this service is subject to any regulatory compliance objectives or if it is likely to be in the future:
This information helps ensure that we effectively manage not only the technical risks associated with this service, but also any potential security and compliance risks. It also provides essential input into the design of the production control environment.
By integrating operability requirements into the earliest stages of the development process and having Development initially self-manage their own applications and services, the process of transitioning new services into production becomes smoother, becoming far easier and more predictable to complete. However, for services already in production, we need a different mechanism to ensure that Operations is never stuck with an unsupportable service in production. This is especially relevant for functionally-oriented Operations organizations.
In this step, we may create a service handback mechanism—in other words, when a production service becomes sufficiently fragile, Operations has the ability to return production support responsibility back to Development.
When a service goes back into a developer-managed state, the role of Operations shifts from production support to consultation, helping the team make the service production-ready.
This mechanism serves as our pressure escape valve, ensuring that we never put Operations in a situation where they are trapped into managing a fragile service while an ever-increasing amount of technical debt buries them and amplifies a local problem into a global problem. This mechanism also helps ensure that Operations has enough capacity to work on improvement work and preventive projects.
The hand-back remains a long-standing practice at Google and is perhaps one of the best demonstrations of the mutual respect between Dev and Ops engineers. By doing this, Development is able to quickly generate new services, with Ops engineers joining the team when the services become strategically important to the company and, in rare cases, handing them back when they become too troublesome to manage in production.†† The following case study of Site Reliability Engineering at Google describes how the Hand-off Readiness Review and Launch Readiness Review processes evolved, and the benefits that resulted.
Case Study
The Launch and Hand-off Readiness Review at Google (2010)
One of the many surprising facts about Google is that they have a functional orientation for their Ops engineers, who are referred to as “Site Reliability Engineers” (SRE), a term coined by Ben Treynor Sloss in 2004.‡‡ That year, Treynor Sloss started off with a staff of seven SREs that grew to over 1,200 SREs by 2014. As Treynor Sloss said, “If Google ever goes down, it’s my fault.” Treynor Sloss has resisted creating a single sentence definition of what SREs are, but, he once described SREs as “what happens when a software engineer is tasked with what used to be called operations.”
Every SRE reports to Treynor Sloss’s organization to help ensure consistency of quality of staffing and hiring, and they are embedded into product teams across Google (which also provide their funding). However, SREs are still so scarce they are assigned only to the product teams that have the highest importance to the company or those that must comply with regulatory requirements. Furthermore, those services must have low operational burden. Products that don’t meet the necessary criteria remain in a developer-managed state.
Even when new products become important enough to the company to warrant being assigned an SRE, developers still must have self-managed their service in production for at least six months before it becomes eligible to have an SRE assigned to the team.
To help ensure that these self-managed product teams can still benefit from the collective experience of the SRE organization, Google created two sets of safety checks for two critical stages of releasing new services called the Launch Readiness Review and the Hand-Off Readiness Review (LRR and HRR, respectively).
The LRR must be performed and signed off on before any new Google service is made publicly available to customers and receives live production traffic, while the HRR is performed when the service is transitioned to an Ops-managed state, usually months after the LRR. The LRR and HRR checklists are similar, but the HRR is far more stringent and has higher acceptance standards, while the LRR is self-reported by the product teams.
Any product team going through an LRR or HRR has an SRE assigned to them to help them understand the requirements and to help them achieve those requirements. The LRR and HRR launch checklists have evolved over time so every team can benefit from the collective experiences of all previous launches, whether successful or unsuccessful. Tom Limoncelli noted during his “SRE@Google: Thousands of DevOps Since 2004” presentation in 2012, “Every time we do a launch, we learn something. There will always be some people who are less experienced than others doing releases and launches. The LRR and HRR checklists are a way to create that organizational memory.”
Requiring product teams to self-manage their own services in production forces Development to walk in the shoes of Ops, but guided by the LRR and HRR, which not only makes service transition easier and more predictable, but also helps create empathy between upstream and downstream work centers.
Limoncelli noted, “In the best case, product teams have been using the LRR checklist as a guideline, working on fulfilling it in parallel with developing their service, and reaching out to SREs to get help when they need it.”
Furthermore, Limoncelli observed, “The teams that have the fastest HRR production approval are the ones that worked with SREs earliest, from the early design stages up until launch. And the great thing is, it’s always easy to get an SRE to volunteer to help with your project. Every SRE sees value in giving advice to project teams early, and will likely volunteer a few hours or days to do just that.”
The practice of SREs helping product teams early is an important cultural norm that is continually reinforced at Google. Limoncelli explained, “Helping product teams is a long-term investment that will pay off many months later when it comes time to launch. It is a form of ‘good citizenship’ and ‘community service’ that is valued, it is routinely considered when evaluating engineers for SRE promotions.”
In this chapter, we discussed the feedback mechanisms that enable us to improve our service at every stage of our daily work, whether it is deploying changes into production, fixing code when things go wrong and engineers are paged, having developers follow their work downstream, creating non-functional requirements that help development teams write more production-ready code, or even handing problematic services back to be self-managed by Development.
By creating these feedback loops, we make production deployments safer, increase the production readiness of code created by Development, and help create a better working relationship between Development and Operations by reinforcing shared goals, responsibilities, and empathy.
In the next chapter, we explore how telemetry can enable hypothesis-driven development and A/B testing to perform experiments that help us achieve our organizational goals and win in the marketplace.


Java is a programming language created by James Gosling from Sun Microsystems in 1991. The target of Java is to write a program once and then run this on multiple operating systems.
Java >>Data abstraction is the process of hiding certain details and showing only essential information. Abstraction can be achieved with either abstract classes or interfaces.
Abstraction >>An interface in java is a blueprint of a class. It has static constants and abstract methods. The interface in java is a mechanism to achieve abstraction. There can be only abstract methods in the Java interface.
Interface >>Abstract class and interface both are used to achieve abstraction where we can declare the abstract methods. But there are many differences between abstract class and interface.
Interface vs Abstraction >>


Reference Manual ¶
To learn how to use HoloViews, we recommend that people start with the Tutorials , and then use the online help features from within IPython Notebook to learn more. Each option should have corresponding tab-completion and help provided, and this is usually enough to determine how to use the HoloViews components.
Even so, for a truly comprehensive reference to every object in HoloViews, we provide this reference manual. The reference manual is generated directly from documentation and declarations in the source code, and is thus often much more verbose than necessary, because many little-used yet often-duplicated methods are listed for each class. Still, the reference for a given component does provide a comprehensive listing of all attributes and methods, inherited or otherwise, which is can be difficult to obtain from the source code directly.
Module Structure ¶
An overview of all modules within all subpackages of HoloViews.
HoloViews subpackages ¶
- core
- Base classes implementing the core data structures of HoloViews.
- element
- Elements that form the basis of more complex visualizations.
- operation
- Operations applied to transform existing Elements or other data structures.
- plotting
- Matplotlib-based implementations of plotting for each component type.
- ipython
- Interface to IPython notebook, including magics and display hooks.
- interface
- Interfaces to optional external libraries (e.g. Pandas and Seaborn), as well as collecting and collating data from an external source.
- testing
- TestComparison classes to compare different component objects.


{% extends 'layout-bsa.html' %}
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Do you get money from any of these? - LIS training - NHSBSA
{% endblock %}
{% block outerContent %}
{% endblock %}
{% block content %}
Get a refund
Which of these NHS costs do you want to claim a refund for?


Runs the provided fitting command, and blocks until it
completes. Saves the output to a temporary file, and upon
completion moves it to a new directory according to whether the
fitting run completed successfully.
Find the best-fitting template parameters for each band/channel of
a particular event at a particular station. Store the template
parameters in the database.


Index to search against
dns
dns
another
another4
another
another
another4
another
Search
Notify me by email
From
To
Success
success... link
Failed
error... link
Success
success... link
Failed
error... link
Success
success... link
Failed
error... link
Success
success... link
Failed
error... link


|
| UMI3DHandPose | Clone () |
| | To make a clone of the current handpose thats registered to the ressouce manager More...
|
| |
| void | UnRegistered () |
| | To Diregister the HandposeFrom The embodiment manager at run time More...
|
| |
| virtual LoadEntity | GetLoadEntity (HashSet< UMI3DUser > users=null) |
| | Ask the clients to load the entity. - Parameters
-
| users | Target clients user set. |
- Returns
- The operation to send to makes clients load the entity
More...
|
| |
| DeleteEntity | GetDeleteEntity (HashSet< UMI3DUser > users=null) |
| | Ask the clients to delete the entity. - Parameters
-
| users | Target clients user set. |
- Returns
- The operation to send to makes clients delete the entity
More...
|
| |
| ulong | Id () |
| | UMI3D Id of an entity. Null id is 0
Ids are set between 1 and 18,446,744,073,709,551,615.
Actualy between 1 and 9,223,372,036,854,775,807 due to the serializer not sutporting unsigned values. - Returns
More...
|
| |
| IEntity | ToEntityDto (UMI3DUser user) |
| | Convert the entity to a DTO. - Parameters
-
- Returns
- Entity as a DTO
More...
|
| |
| Bytable | ToBytes (UMI3DUser user) |
| | Convert the entity to a list of bytes as a bytable. - Parameters
-
- Returns
- return a couple (size,func) with size as the required size more the baseSize given, and func a method taking a byte array in which the data should be written, a position at which it should be written, a base size. This method return the updated position (position + required size) and the (required size + base size); The byte array given should be at least of size position + required size;
Used in networking with bytes. More...
|
| |
| UMI3DHandPoseDto | ToDto () |
| |
| bool | LoadOnConnection (UMI3DUser user) |
| | Condition to be loaded on connection. More...
|
| |
| bool | AddConnectionFilter (UMI3DUserFilter filter) |
| | Add a filtering condition from the user filtering. More...
|
| |
| bool | RemoveConnectionFilter (UMI3DUserFilter filter) |
| | Remove a filtering condition from the user filtering. More...
|
| |
| LoadEntity | GetLoadEntity (HashSet< UMI3DUser > users=null) |
| | Ask the clients to load the entity. More...
|
| |
| DeleteEntity | GetDeleteEntity (HashSet< UMI3DUser > users=null) |
| | Ask the clients to delete the entity. More...
|
| |
| IEntity | ToEntityDto (UMI3DUser user) |
| | Convert the entity to a DTO. More...
|
| |
| Bytable | ToBytes (UMI3DUser user) |
| | Convert the entity to a list of bytes as a bytable. More...
|
| |
| bool | LoadOnConnection (UMI3DUser user) |
| | Condition to be loaded on connection. More...
|
| |
| bool | AddConnectionFilter (UMI3DUserFilter filter) |
| | Add a filtering condition from the user filtering. More...
|
| |
| bool | RemoveConnectionFilter (UMI3DUserFilter filter) |
| | Remove a filtering condition from the user filtering. More...
|
| |
| ulong | Id () |
| | UMI3D Id of an entity. More...
|
| |
UMI3D hand pose.
A hand pose description is composed of the position and rotation of hand and the position and rotation of every phalanx of the hand.
See HandDescription and HandAnimation.
| ulong umi3d.edk.userCapture.UMI3DHandPose.Id |
( |
| ) |
|
UMI3D Id of an entity. Null id is 0
Ids are set between 1 and 18,446,744,073,709,551,615.
Actualy between 1 and 9,223,372,036,854,775,807 due to the serializer not sutporting unsigned values.
- Returns
Implements umi3d.edk.UMI3DEntity.


Platforms Known to Work Might Work, Untested Not Expected to Work
Concepts / Configuration Global Settings Dependency Rules: Disallowed Configurations
Listener and Controller Listener Controller
gaggled is a process manager focused on inter-process dependencies within a system with an eye to developing cluster-level process management later (with equivalent semantics for process dependency). It is currently in development and bug reports are welcome at https://github.com/ZenFire/gaggled if you find anything wrong. Reports of working/not working status on various platforms are also welcomed and encouraged.
To build gaggled, you must create a build directory, run cmake, and use make to build. How to use the rpm build setup and how to install are to be covered later. Watch this space.
mkdir build
cmake ..
make -j4
You may be clever enough to just use gaggled right after building, but you're advised for security reasons to read this entire document, at the very least the Caveats section.
gaggled has been tested on a few platforms, and is expected to work on all relatively recent Linux distributions.
The section labelled gaggled
contains several settings, all of which are optional. The section itself is optional.
killwait
: milliseconds to wait after sending SIGTERM to shut down a process before assuming it won't die and using SIGKILL. Default: 10000.startwait
: milliseconds to defer trying to start a program again after an instance where gaggled noted that the program's dependencies were not yet satisfied. Default: 100.tick
: the event loop timer: how long to sleep after an event loop in which no events were processed. Default: 10.path
: to prepend to $PATH for searching for programs. Do not end with a : unless you want to add the current directory to the search path. Optional.env
: an optional environment section. Overlays over the global environment that gaggled was run in.eventurl
: a ZeroMQ URL to bind to, to publish up/down events to.controlurl
: a ZeroMQ URL to bind to, to process control and state-dump requests from.A program is a settings section. It can have any arbitrary title, which is the name of the program.
command
: for instance, /usr/bin/sleep
. If it contains no slashes, [path:]$PATH will be searched for the command.argv
: for instance, 8h
. Defaults to empty.env
: config section, overlays the list of assignments onto gaggled's env for the program.respawn
: true
if it should be restarted if it dies. This defaults to true
.enabled
: true
if it should be started, false
if it's disabled. Defaults to true
.depends
section under the program section they are dependencies of. The name of a dependency section is the name of the program the dependency is on
.
delay
: the program will not start until on
has been running for delay
milliseconds. Defaults to 0
. Negative numbers or numbers over<PHONE_NUMBER> result in undefined behaviour.propagate
: if on
restarts, of
should restart as well. Stop is initiated as soon as possible after on
dies. Starts as a result of this feature will obey delay
. Defaults to false
. Of course, if on
has respawn
turned off, of
will not get started as on
won't come back up.Some examples of gaggled config files are in the contrib/ directory.
There are some dependency configurations that are valid syntax, you may not express in the configuration of gaggled. Doing so will result in gaggled failing to run or configest.
enabled
program on a non-enabled
program.of
-> on
), so it's possible to have a dependency set like (a -> b), (b -> c), (a -> c) which is not considered a cycle. If you have one, then the programs in it would never start.During gaggled shutdown and in other scenarios, sometimes a program must be shut down. This will work the same way init does it: use SIGTERM
, if the process does not die within 10 seconds, SIGKILL
will be sent.
-c
$FILE will use a specific config file. This argument is required.-t
will check dependency rules and existence of all programs but not start gaggled-h
to display help instead of running.There are two utility programs included with gaggled.
The program gaggled_listener will connect to a gaggled instance that is configured with the eventurl
option and display incoming program state changes messages as needed. Use the -h option for help.
The program gaggled_controller will connect to a gaggled instance that is configured with the controlurl
option and print program state, shut down programs, or start them up. Use the -h
option for help.
eventurl
or controlurl
, transport restrictions such as firewalls and binding to localhost are the the only restriction on status information and up/down commands being interchanged.startwait
or tick
(compared to delay
etc) can result in confusing behaviour (things taking longer to start or be recognized as stopped than expected)EX_NOPERM
, EX_DATAERR
, EX_NOINPUT
, or EX_UNAVAILABLE
(defined in sysexits.h for your system) may result in gaggled logging a specific type of execution failure that may not be accurate.


{% extends 'base.html' %} {% block content %}
Someone somewhere made a mistake, because page you were pointed to, does not exists.
Back to home page


--- layout: post title: The “Pull Effect” – What is it, and why do Enterprises CIOs want it… date: '2012-01-17T14:12:43-08:00' tags: tumblr_url: http://alexhwilliams.tumblr.com/post/16024965351/the-pull-effect-what-is-it-and-why-do-enterprises ---
http://bit.ly/A3wuzA


# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# 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.
"""
Sensitivity analysis implementations for learning rate on Modules against loss funcs.
"""
from typing import Any, Callable, List, Tuple, Union
from torch import Tensor
from torch.nn import Module
from torch.optim.optimizer import Optimizer
from torch.utils.data import DataLoader
from sparseml.optim import LRLossSensitivityAnalysis
from sparseml.pytorch.utils import (
DEFAULT_LOSS_KEY,
LossWrapper,
ModuleRunFuncs,
ModuleRunResults,
ModuleTrainer,
PyTorchLogger,
infinite_data_loader,
set_optim_learning_rate,
)
__all__ = ["default_exponential_check_lrs", "lr_loss_sensitivity"]
[docs]def default_exponential_check_lrs(
init_lr: float = 1e-6, final_lr: float = 0.5, lr_mult: float = 1.1
) -> Tuple[float, ...]:
"""
Get the default learning rates to check between init_lr and final_lr.
:param init_lr: the initial learning rate in the returned list
:param final_lr: the final learning rate in the returned list
:param lr_mult: the multiplier increase for each step between
init_lr and final_lr
:return: the list of created lrs that increase exponentially between
init_lr and final_lr according to lr_mult
"""
check_lrs = [init_lr] # type: List[float]
while check_lrs[-1] < final_lr:
check_lrs.append(check_lrs[-1] * lr_mult)
check_lrs.append(final_lr)
return tuple(check_lrs)
def _sensitivity_callback(
check_lrs: Union[List[float], Tuple[float, ...]],
steps_per_measurement: int,
optim: Optimizer,
analysis: LRLossSensitivityAnalysis,
loss_key: str,
) -> Tuple[Callable, Callable]:
measurement_steps = 0
check_index = -1
lr_results = None
def complete_lr():
nonlocal measurement_steps
nonlocal check_index
nonlocal lr_results
if measurement_steps > 0 and check_index >= 0 and check_index < len(check_lrs):
lr_res = [res.item() for res in lr_results.result_list_tensor(loss_key)]
analysis.add_result(check_lrs[check_index], lr_res)
measurement_steps = 0
check_index += 1
lr_results = ModuleRunResults()
if check_index < len(check_lrs):
set_optim_learning_rate(optim, check_lrs[check_index])
complete_lr() # initial to set the lr
def batch_end(
epoch: int,
step: int,
batch_size: int,
data: Any,
pred: Any,
losses: Any,
):
nonlocal measurement_steps
measurement_steps += 1
if measurement_steps >= steps_per_measurement:
complete_lr()
lr_results.append(losses, batch_size)
def completed():
complete_lr() # make sure we didn't miss any
return batch_end, completed
[docs]def lr_loss_sensitivity(
module: Module,
data: DataLoader,
loss: Union[LossWrapper, Callable[[Any, Any], Tensor]],
optim: Optimizer,
device: str,
steps_per_measurement: int,
check_lrs: Union[List[float], Tuple[float, ...]] = default_exponential_check_lrs(),
loss_key: str = DEFAULT_LOSS_KEY,
trainer_run_funcs: ModuleRunFuncs = None,
trainer_loggers: List[PyTorchLogger] = None,
show_progress: bool = True,
) -> LRLossSensitivityAnalysis:
"""
Implementation for handling running sensitivity analysis for
learning rates on modules.
:param module: the module to run the learning rate sensitivity analysis over,
it is expected to already be on the correct device
:param data: the data to run through the module for calculating
the sensitivity analysis
:param loss: the loss function to use for the sensitivity analysis
:param optim: the optimizer to run the sensitivity analysis with
:param device: the device to run the analysis on; ex: cpu, cuda.
module must already be on that device, this is used to place then data
on that same device.
:param steps_per_measurement: the number of batches to run through for
the analysis at each LR
:param check_lrs: the learning rates to check for analysis
(will sort them small to large before running)
:param loss_key: the key for the loss function to track in the returned dict
:param trainer_run_funcs: override functions for ModuleTrainer class
:param trainer_loggers: loggers to log data to while running the analysis
:param show_progress: track progress of the runs if True
:return: a list of tuples containing the analyzed learning rate at 0
and the ModuleRunResults in 1, ModuleRunResults being a collection
of all the batch results run through the module at that LR
"""
analysis = LRLossSensitivityAnalysis()
trainer = ModuleTrainer(
module,
device,
loss,
optim,
loggers=trainer_loggers,
log_summary=False,
log_steps=max(1, round(steps_per_measurement / 10)),
)
batch_end, completed = _sensitivity_callback(
check_lrs, steps_per_measurement, optim, analysis, loss_key
)
batch_end_hook = trainer.run_hooks.register_batch_end_hook(batch_end)
if trainer_run_funcs is not None:
trainer.run_funcs.copy(trainer_run_funcs)
data_loader = infinite_data_loader(data)
trainer.run(
data_loader,
desc="LR Analysis",
show_progress=show_progress,
track_results=False,
max_steps=steps_per_measurement * len(check_lrs),
)
completed()
batch_end_hook.remove()
return analysis


--- title: "About" layout: "about" url: "/about/" summary: "about" draft: False publishDate: "2020-01-01" hideMeta: True authors: - Emlyn Graham ---
Welcome to my website!
I’ve set this site up to learn about Hugo and RMarkdown, but I hope to start making use of it as a learning aide, for my interests and generally for my writing.
My current professional interests involve facilitating science and its application through good public policy. I also try to keep an ear to the ground in the world of physics, which I hope to rejoin for a PhD eventually. In my spare time I enjoy cooking (currently lots of Adam Liaw recipes), and satisfy my inner musician through playing the cello and singing in a choir.
I am currently a Graduate working in policy and public administration for the Commonwealth of Australia in Canberra.


--- layout: post esbma_id: unknown title: Don't use ReactiveUI date: 2017-01-24 12:00:00 ---
This blog post says the opposite of its lazy and deliberately provocative title. I have become a huge fan of ReactiveUI. I just want to ramble about the path I took to get here.
I first heard about ReactiveUI at a conference presentation by Paul Betts. I think it was at Xamarin Evolve. Mostly I remember feeling dumb. He said a lot of things that I didn't understand.
I went to that session without much real experience in Model-View-ViewModel (MVVM) development. Conceptually, I understood the idea of a ViewModel. But Paul mostly talked about how ReactiveUI avoids certain problems. And since I had not experienced those problems, his words didn't sink in.
Each time one of my kids was approaching adolescence, I sat down and explained the risks associated with certain choices. Laws and moral judgements aside, the simple fact is that many choices involve risks, and I thought it would be helpful to pass along that bit of information.
And in each case, my child said, "Thanks Dad", and proceeded to always make wise and low-risk choices from that point on.
Well, actually, no.
Teenagers simply do not learn that way. They process risk very differently from people who are more mature.  The adolescent will immediately begin driving too fast, and, in all likelihood, will not get ticket. This is how teenagers realize they are smarter than their parents.
Tangent #1: It is almost certainly a good thing that young people are more brave. It would be Very Bad if everybody started out with the same level of risk aversion as the average 65-year-old. Go watch the "Tapestry" episode of Star Trek TNG.
Tangent #2: I really should claim no expertise in parenting, but if somebody forced me to write a book on parenting a teenager, I would say this: Let your kid suffer from their own choices. That said, it is worth the effort to try and help them avoid the really bad mistakes, the ones with consequences that last for decades. But they do have to learn to make their own choices. Realize this as early as you can. The path to frustration starts with making everything all about you.
My metaphor has many problems. For starters, Paul Betts is not my Dad.
Also, the element of adolescent rebellion was not present. I didn't hear Paul's wisdom and run in the opposite direction because of my deep need to separate my identity from his. In fact, I started devouring everything I could find on MVVM and IObservable. I really wanted to understand what he was saying.
But the metaphor works in one significant way: Like a teenager, I had to learn by doing. Nobody's words made much of a difference. None of that reading helped me become a a user of ReactiveUI. I went down another path.
Actually, I went down several other paths.
I observe that most developers want content that explains how to get something done. "If your objective is to do X, then do the following steps." The most popular books and articles tend to follow this pattern. Questions of this form are the ones that do well on StackOverflow.
But this is almost never what I want.
I much prefer content that explains how things work. Once I understand that, I can figure out the steps myself.
When I am developing software, I always, ALWAYS do better when I understand what is going on "under hood", when I can see through the leaky abstractions.
And as I mentioned, I am apparently in the very small minority on this. If 90% of the world disagrees with me, does that put me in the top 10% ? Or does it mean my approach is somehow defective? Modesty aside, my history contains enough successes to allow me some confidence in believing that my approach is better.
I also observe that my approach is just a different spelling for the old adage, "Give a man a fish and you feed him for a day. Teach a man to fish and he eats for a lifetime."
If you tell a software developer what to type and where to click, you can help them complete today's task. But if you instead teach them how things work, they will be able to apply that understanding on other days too.
Hmmm. I'm talking myself into this. I don't know why most people prefer shallow recipes, but I really do think deep understanding is better.
Still, I like to stay open-minded about things. I've got a lot of failures too.
The truth is that my approach has tradeoffs. The need to understand everything tends to slow me down during the early stages. I usually gain some of that back in the fourth quarter of the game, where deeper understanding is often helpful in diagnosing tricky problems.
But again, in the decision making around software development, absolutes are rare. I'll admit that sometimes a simple set of steps without depth are exactly what is needed.
I don't know. Maybe. I've read the docs plenty. They don't seem bad to me. I also see nothing there that makes me want to defend them as the best docs ever.
Suppose that I regret not choosing ReactiveUI sooner. Further suppose that I wanted to blame somebody else for my choices. I guess I could find something to complain about. But I also don't tend to find that criticizing somebody else's work is helpful.
And remember, I started this journey sitting in front of an audience, listening to Paul Betts, and feeling dumb. To be clear, in that kind of context, I *like* feeling dumb. It's an opporunity to learn.
I guess I don't really know. But I'm pretty sure that nothing has made me appreciate ReactiveUI more than the suffering that comes from not using it.
And that remark isn't very helpful, is it? I'd like to try and do better. Let's see...
"Son, it's just basic statistics. If you're going to always drive 15 MPH over the speed limit, you will eventually get caught. Suppose you roll the dice 20 times in a row without getting a 12. You still might get a 12 on the next roll, right?"
Oh, wait, wrong topic. Let me try again.
In some software development situations, like mobile apps, if you take a step back and look at the forest instead of the trees, you will see that most of your code is reacting to something that changed.
There are lots of tools you can use to approach this kind of app. You can use C# events and callbacks and switch statements and delegates and lambdas and observables and notifications and bindings and more.
For simple apps, none of these approaches are much better than any other. But as your app gets more complicated, some approaches cope more gracefully than others.
Most cars drive pretty smooth at 30 MPH. But at 75 MPH, some vehicles are still giving a smooth ride, while others are shaking.
Let's try a conceptual example or two. Suppose you have a button, and you want something to happen when the user presses that button. This is pretty simple. All reasonable solutions to this problem are about the same.
On the other hand, let's say you have a list of items. The items in that list come from a SQL query. That query has 4 inputs, each of which comes from a UI control. Every time one of those controls changes its value, the query needs to be re-run and the list needs to be updated. A couple of those controls need to be disabled under certain circumstances.
These UI elements have a complicated relationship. We still have plenty of choices in how to express that relationship in code, but this situation is complicated enough that we start to see differences between those approaches. Some of the ones that worked out really well in the simple case seem kinda tedious for this case.
If my driveway has half an inch of snow, all methods of clearing it are about the same. But if my driveway has 15 inches of snow, a shovel is decidedly inferior to a tractor.
Why do I like ReactiveUI? Because I have found that it copes gracefully as the situation gets more complicated.
Why is this? Much of the credit goes to the "reactive" foundation on which ReactiveUI is built. Reactive Extensions. Rx. IObservable. These building blocks are particularly adept at expressing the relationship between a group of things that are changing. ReactiveUI adds another layer (or two) on top of these things to make that expressiveness more convenient when implementing user interfaces.
To be honest, I fudged a little bit when I said that all solutions are roughly equivalent when the problem is simple. That's not quite true. For simple situations, I'd have to admit that ReactiveUI might be a little worse. There is a learning curve.
If I am writing a grocery list, I could use a word processor, but a pencil and paper is actually simpler. But if I am writing a novel, the word processor is the clear winner.
I'm claiming that the effort to learn Rx and ReactiveUI is worth the trouble. My claim is based on this notion that ReactiveUI shines as complexity increases, but also on my belief that most people underestimate the complexity of their app.
If you disagreed with me above when I said that "most of your code is reacting to something that changed", you might be underestimating the complexity of your app. It is in fact very common to start implementing under the assumption that something will not change and then later realize that you need notifications or events. Or an observable.
Would the paragraphs above have changed my course earlier?
I don't know. Probably not.
I didn't start this believing that I could write the best ReactiveUI advocacy ever. Looking at it now, I can't believe I wrote it with no code in it. The canonical ReactiveUI evangelism pamphlet has gotta have WhenAnyValue() in it somewhere.
I just think it's interesting that despite my best efforts, I was unable to really understand the benefits of ReactiveUI until I tried using its alternatives. My current project is late. If I had chosen ReactiveUI earlier, maybe it would be, er, less late? There are questions here worth asking.
But am I 100% certain that it is always better to spare yourself the learning experience of using less effective approaches? No.
Can I credibly claim that everyone should choose ReactiveUI in every situation? Certainly not.
Maybe all I can say is that I am currently having a great experience with ReactiveUI.

But you should have known that when you saw the cheesy title.


jscodeshift
jscodeshift is a toolkit for running codemods over multiple JS files. It provides:
- A runner, which executes the provided transform for each file passed to it. It also outputs a summary of how many files have (not) been transformed.
- A wrapper around recast, providing a different API. Recast is an AST-to-AST transform tool and also tries to preserve the style of original code as much as possible.
Install
Get jscodeshift from npm:
$ npm install -g jscodeshift
This will install the runner as jscodeshift
.
Usage (CLI)
The CLI provides the following options:
$ jscodeshift --help
Usage: jscodeshift <path>... [options]
path Files or directory to transform
Options:
-t FILE, --transform FILE Path to the transform file. Can be either a local path or url [./transform.js]
-c, --cpus (all by default) Determines the number of processes started.
-v, --verbose Show more information about the transform process [0]
-d, --dry Dry run (no changes are made to files)
-p, --print Print output, useful for development
--babel Apply Babel to transform files [true]
--extensions File extensions the transform file should be applied to [js]
--ignore-pattern Ignore files that match a provided glob expression
--ignore-config FILE Ignore files if they match patterns sourced from a configuration file (e.g., a .gitignore)
--run-in-band Run serially in the current process [false]
-s, --silent No output [false]
--parser The parser to use for parsing your source files (babel | babylon | flow) [babel]
--version print version and exit
This passes the source of all passed through the transform module specified
with -t
or --transform
(defaults to transform.js
in the current
directory). The next section explains the structure of the transform module.
Transform module
The transform is simply a module that exports a function of the form:
module.exports = function(fileInfo, api, options) {
// transform `fileInfo.source` here
// ...
// return changed source
return source;
};
Arguments
fileInfo
Holds information about the currently processed file.
| Property | Description |
|---|---|
| path | File path |
| source | File content |
api
This object exposes the jscodeshift
library and helper functions from the
runner.
| Property | Description |
|---|---|
| jscodeshift | A reference to the jscodeshift library |
| stats | A function to collect statistics during --dry runs |
jscodeshift
is a reference to the wrapper around recast and provides a
jQuery-like API to navigate and transform the AST. Here is a quick example,
a more detailed description can be found below.
/**
* This replaces every occurrence of variable "foo".
*/
module.exports = function(fileInfo, api) {
return api.jscodeshift(fileInfo.source)
.findVariableDeclarators('foo')
.renameTo('bar')
.toSource();
}
Note: This API is exposed for convenience, but you don't have to use it. You can use any tool to modify the source.
stats
is a function that only works when the --dry
options is set. It accepts
a string, and will simply count how often it was called with that value.
At the end, the CLI will report those values. This can be useful while developing the transform, e.g. to find out how often a certain construct appears in the source(s).
options
Contains all options that have been passed to runner. This allows you to pass additional options to the transform. For example, if the CLI is called with
$ jscodeshift -t myTransforms fileA fileB --foo=bar
options
would contain {foo: 'bar'}
. jscodeshift uses nomnom to parse
command line options.
Return value
The return value of the function determines the status of the transformation:
- If a string is returned and it is different from passed source, the transform is considered to be successful.
- If a string is returned but it's the same as the source, the transform is considered to be unsuccessful.
- If nothing is returned, the file is not supposed to be transformed (which is ok).
The CLI provides a summary of the transformation at the end. You can get more
detailed information by setting the -v
option to 1
or 2
.
You can collect even more stats via the stats
function as explained above.
Parser
The transform can let jscodeshift know with which parser to parse the source files (and features like templates).
To do that, the transform module can export parser
, which can either be one
of the strings "babel"
, "babylon"
, or "flow"
, or it can be a parser
object that is compatible with recast.
For example:
module.exports.parser = 'flow'; // use the flow parser
// or
module.exports.parser = {
parse: function(source) {
// return estree compatible AST
},
};
Example output
$ jscodeshift -t myTransform.js src
Processing 10 files...
Spawning 2 workers with 5 files each...
All workers done.
Results: 0 errors 2 unmodified 3 skipped 5 ok
The jscodeshift API
As already mentioned, jscodeshift also provides a wrapper around recast. In order to properly use the jscodeshift API, one has to understand the basic building blocks of recast (and ASTs) as well.
Core Concepts
AST nodes
An AST node is a plain JavaScript object with a specific set of fields, in
accordance with the Mozilla Parser API. The primary way to identify nodes
is via their type
.
For example, string literals are represented via Literal
nodes, which
have the structure
// "foo"
{
type: 'Literal',
value: 'foo',
raw: '"foo"'
}
It's OK to not know the structure of every AST node type. The (esprima) AST explorer is an online tool to inspect the AST for a given piece of JS code.
Path objects
Recast itself relies heavily on ast-types which defines methods to traverse the AST, access node fields and build new nodes. ast-types wraps every AST node into a path object. Paths contain meta-information and helper methods to process AST nodes.
For example, the child-parent relationship between two nodes is not explicitly
defined. Given a plain AST node, it is not possible to traverse the tree up.
Given a path object however, the parent can be traversed to via path.parent
.
For more information about the path object API, please have a look at ast-types.
Builders
To make creating AST nodes a bit simpler and "safer", ast-types defines a couple
of builder methods, which are also exposed on jscodeshift
.
For example, the following creates an AST equivalent to foo(bar)
:
// inside a module transform
var j = jscodeshift;
// foo(bar);
var ast = j.callExpression(
j.identifier('foo'),
[j.identifier('bar')]
);
The signature of each builder function is best learned by having a look at the definition files.
Collections and Traversal
In order to transform the AST, you have to traverse it and find the nodes that need to be changed. jscodeshift is built around the idea of collections of paths and thus provides a different way of processing an AST than recast or ast-types.
A collection has methods to process the nodes inside a collection, often resulting in a new collection. This results in a fluent interface, which can make the transform more readable.
Collections are "typed" which means that the type of a collection is the
"lowest" type all AST nodes in the collection have in common. That means you
cannot call a method for a FunctionExpression
collection on an Identifier
collection.
Here is an example of how one would find/traverse all Identifier
nodes with
jscodeshift and with recast:
// recast
var ast = recast.parse(src);
recast.visit(ast, {
visitIdentifier: function(path) {
// do something with path
return false;
}
});
// jscodeshift
jscodeshift(src)
.find(jscodeshift.Identifier)
.forEach(function(path) {
// do something with path
});
To learn about the provided methods, have a look at the Collection.js and its extensions.
Extensibility
jscodeshift provides an API to extend collections. By moving common operators into helper functions (which can be stored separately in other modules), a transform can be made more readable.
There are two types of extensions: generic extensions and type-specific extensions. Generic extensions are applicable to all collections. As such, they typically don't access specific node data, but rather traverse the AST from the nodes in the collection. Type-specific extensions work only on specific node types and are not callable on differently typed collections.
Examples
// Adding a method to all Identifiers
jscodeshift.registerMethods({
logNames: function() {
return this.forEach(function(path) {
console.log(path.node.name);
});
}
}, jscodeshift.Identifier);
// Adding a method to all collections
jscodeshift.registerMethods({
findIdentifiers: function() {
return this.find(jscodeshift.Identifier);
}
});
jscodeshift(ast).findIdentifiers().logNames();
jscodeshift(ast).logNames(); // error, unless `ast` only consists of Identifier nodes
Passing options to recast
You may want to change some of the output settings (like setting '
instead of "
).
This can be done by passing config options to recast.
.toSource({quote: 'single'}); // sets strings to use single quotes in transformed code.
You can also pass options to recast's parse
method by passing an object to
jscodeshift as second argument:
jscodeshift(source, {...})
More on config options here
Unit Testing
jscodeshift comes with a simple utility to allow easy unit testing with Jest, without having to write a lot of boilerplate code. This utility makes some assumptions in order to reduce the amount of configuration required:
- The test is located in a subdirectory under the directory the transform itself is located in (eg.
__tests__
) - Test fixtures are located in a
__testfixtures__
directory
This results in a directory structure like this:
/MyTransform.js
/__tests__/MyTransform-test.js
/__testfixtures__/MyTransform.input.js
/__testfixtures__/MyTransform.output.js
To define a test, use defineTest
or defineInlineTest
from the testUtils
module. A simple example is bundled in the sample directory.
defineTest
jest.autoMockOff();
const defineTest = require('jscodeshift/dist/testUtils').defineTest;
defineTest(__dirname, 'MyTransform');
An alternate fixture filename can be provided as the fourth argument to defineTest
. This also means that multiple test fixtures can be provided:
defineTest(__dirname, 'MyTransform', null, 'FirstFixture');
defineTest(__dirname, 'MyTransform', null, 'SecondFixture');
This will run two tests: One for __testfixtures__/FirstFixture.input.js
and one for __testfixtures__/SecondFixture.input.js
defineInlineTest
const transform = require('../myTransform');
defineInlineTest(transform, {}, 'input', 'expected output', 'test name (optional)');
Example Codemods
- react-codemod - React codemod scripts to update React APIs.
- js-codemod - Codemod scripts to transform code to next generation JS.
- js-transforms - Some documented codemod experiments to help you learn.
Recipes
Support
- Discord - #codemod on Reactiflux


FILM TITLE: LA BUENA ESTRELLA (LUCKY STAR) DIRECTOR: RICARDO FRANCO COUNTRY: SPAIN 1997 CINEMATOGRAPHY: Tote Trenas MUSIC: Eva Gancedo CAST: Antonio Resines, Maribel Verdu, Jordi Molla, Elvira Minguez, Ramon Barea, Clara Sanchiz SUPER FEATURES: Story should hold you.
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
(Seen at the 22nd Portland International Film Festival in Portland, Oregon)
It is good that when seeing this film, we finally get the impression that Spanish film makers can do much more than just a farce, or a satire, or some sort of surrealistic picture that defies description. Might make one think that all Spaniards are crazy. Well, we don't really care for all those Kleenex fantasies, either. If anything, LA BUENA ESTRELLA, is a film with some sort of normalcy, in the human spirit that we can actually believe and come to grips with. The question is, will the film also do it?.
Well, yes it does. Then again, it doesn't, as it makes the film appear to close to us, and too human for us to be able to buy into it. We've seen hundreds of these stories, few of them do we discuss, and many of them were literary works that we consider them best discussed in class rooms, rather than accept that our own neighbors may be living a similar life. Reality is always so far away for us to accept and live with. But the sad thing about the film is that it makes women look stupid and secondary to many male wishes and desires, which is simply not true, or a valid point in these modern times. There maybe many of us old fashioned ones, but modern day Spain is not too far off the rest of us all.
Rafael, owns a meat market, and there he has been able to make a living. On a fateful day, he is driving home and finds someone being attacked. Actually she is not being attacked, she is being molested by her boyfriend.  He takes Marina to the Hospital and then home, where he proceeds to offer her shelter. She is pregnant. Simple enough. However, it appears that Marina has been forced to into prostitution, or equivalent so that she could make some money for herself and the boyfriend. As it turns out, the boyfriend gets himself in jail for a few years, which helps things. Marina has settled in with Rafael, and her daughter is growing. Unfortunately, Rafael has had a childhood accident that has prevented him from becoming a full man, and this may eat apart at Marina's fiber. As the film wears on, she can never let go of her boyfriend.
He gets out of jail with his pride intact. And eventually finds his way to Rafael's house where Marina has been. And Rafael, being the good Samaritan that he is,lets him in.  She is still in love with Dani. Rafael may be her family now, but there is one unresolved thing that she has not been able to deal with.
She leaves, she returns. He leaves, he returns. Dani leaves, he returns. The triangle is in full bloom. Rafael does not know what to do. Marina says that Dani will leave sooner or later as he always has. An opportunity arises to get Dani out of the house. But this only gets Dani in jail again, and this time his pride is broken. And it kills him. And in the end, it also has killed Marina.
Actually, this reviewer hates these stories.  But, this opinion fails on one thing. It does not take in consideration the human spirit and the way that we are. A little animal, and a lot human. The film right off the bat, gives us that impression, unfortunately, it is badly juxtaposed to the story and unnecessary. Is this a comment about us all being animals just because Rafael is a butcher? That we have no sense or care about people and relationships like a butcher would have for a piece of meat? Rafael is certainly well defined in this area, even if the part of him that could easily make him an "animal" is no longer operational. But if the film were to make that point a little further in the end, a Butcher truck would have driven by in the background and made it clear that the animals are dead, and the humans have lived on. Maybe this would have offended many of us. As it is it ends in a respectful manner, and a rather positive one considering the situation. Rafael is too human and too caring, and will raise the two daughters and take care of them.
Acting is what this film is really about, at least for three characters. Maribel Verdu (La Belle Epoque, Amantes), is really good, as the emotionally frail Marina. Antonio Resines is really fine, subdued way too much but still very fine. A nice contrast. And Jordi Molla (the Flower of My Secret, Jamon Jamon) is over the top, and crazy, as his character really is. His manhood is not measured in his love, or in his ability to provide for the one woman that he can not let go of. And all three of them could have really done this film in at any moment were it not for the caring sequences that maintain the story going. It never blows its cool, and it manages to solve things, never "animalizes" the situation. The characters have their desire to contend with and even Rafael tries to outdo Dani, but the love Marina has for him has less to do with that, and she reminds him of that.
But what is really fine in this film is the ending sequences, that are excellently directed and filmed. When Rafael goes to visit Dani in jail, the way it is photographed is magnificent and the expressions couldn't be more perfect. Total juxtaposition. Basically two broken men, differently so, yet they have something so much in common, which has to end in some sort of sad resolution. However, that resolution is not a resolution but an end.
A very nice film, acting and directing wise. A love triangle that has a fateful resolution, but not in a negative way. The offsprings will be well taken care of.
4 of 5 GIBLOONS Reviewed by Pedro Sena, Copyright (c) Pedro Sena 1999. All Rights Reserved.
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.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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Edit file, by writing html codes, and commit changes.
Change the username and then create a new pull request
Add an image to the web page
Create a new list
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Create a style to the page


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|
The People Next Door
by Christine A. Corcos
The people upstairs all practice
ballet./Their living room is a bowling alley./Their bedroom is
full of conducted tours/Their radio is louder than yours./They
celebrate the weekends all the week. When they take a shower,
your ceilings leak/They try to get their parties to mix/By supplying
their guests with Pogo sticks/And when their orgy at last abates/They
go to the bathroom on roller skates/I might love the people upstairs
wondrous/If instead of above us, they just lived under us.
Ogden Nash, I Wouldn't Have Missed It: Selected Poems of Ogden
Nash (1971).
In this age of terrorism and
uncertainty, we surely must rely more than ever on our neighbors,
yet we are more than ever unlikely to know them, or know much
about them. The fear of the stranger is never more potent than
when that stranger is someone in one's own home town, someone
who should share one's values and dreams, on whom one should
be able to rely in times of need and whom one should also expect
to assist when necessary. We expect to know our neighbors if
we live in small towns or intimate communities in large cities,
but we expect not to know them if we live in anonymous high-rises.
Indeed, we so prize our privacy that we resist those who attempt
to make friends. They could be well meaning but nosy, but they
could also be serial killers. People disappear daily, and their
neighbors tell police, "We didn't know much about her. She
kept to herself. One day we just didn't see her anymore."
Kitty Genovese's lonely, terrifying death on a New York street
in 1964, within earshot of neighbors who did nothing, not even
call the police, and dramatized in the 1975 film Death Scream,
symbolized our turn toward willful ignorance. Someone we thought
we knew is taken away in handcuffs, and the obligatory interviews
on the six o'clock news reveal, "He was such a good boy!
Always went to church! Always visited his mother!"
Not surprisingly, Hollywood has explored our strange relationship
with our neighbors in numerous films and television shows, to
the point that certain neighbor personas are now archetypal,
if not clichéd, as are the legal issues that involve neighbors.
The phrase "good fences make good neighbors" has a
great deal of truth, and not just because those fences protect
our children from falling into our neighbors' pools. From the
classic fifties comedy Dennis the Menace to the nineties
hit Family Matters television series highlight the long-suffering
neighbor who must deal with a destructive and nosy child. I
Love Lucy had faithful neighbors who were also close friends,
as did the Jackie Gleason vehicle The Honeymooners. The
popular sitcom Home Improvement features a neighbor with
all the answers. Comedies about neighborhoods are perennially
popular with viewers. They create a friendly, reliable world
that does not necessarily reflect our own, but that we yearn
for, a world that seems secure, and predictable, and to a great
extent desirable.
Series like American Gothic, on the other hand, remind
us that the smallest, friendliest seeming town hides secrets.
Like Shirley Jackson's short story "The Lottery",
shows like American Gothic give us the permanent creeps:
we suspect that somewhere in this country, there really is a
town where evil has overtaken good. Isn't that what Stephen King
keeps telling us? In particular, the small Southern or mid-Western
town comes in for its share of suspicion. My Cousin Vinny
(1992) derived much of its humor from the juxtaposition of New
York and Southern culture, and New York didn't always win out.
Fred Gwynne's bewilderment at Joe Pesci's pronunciation of "two
youths" is worth the price of the film. And as Judge Haller,
Gwynne teaches Lawyer Gambini (Pesci) some rules about courtroom
decorum he'll never forget. But Southern towns aren't always
so amusing: In the Heat of the Night (1967) is the archetypal
example of the clash between prejudice and honor, a story in
which a local policeman must decide to arrest his neighbor, a
fellow officer, in the interests of justice.
The notion that our neighbors have things to hide is a popular
theme in Hollywood. In Fright Night, a teenager begins
to believe that his new neighbors are vampires and he carries
out numerous investigations (also known as trespasses) in order
to prove himself right. Teenagers with time on their hands, usually
during summer vacation, are notorious for investigating empty
houses and bothering retired people, the local "witch"
and anybody who doesn't fit in. For years, movies had obligatory
scenes in which children bothered the town eccentrics, sometimes
played for laughs as in Meet Me in St. Louis (1944), and
sometimes not, as in To Kill a Mockingbird (1962).
In some movies, the adults take matters into their own hands
once they take the children seriously as in the Tom Hanks comedy
The 'Burbs, when they begin to suspect that their new
neighbors are up to no good, especially since the former occupants
of the house vanished without a trace, as does one of their present
neighbors. The vigilante justice that is a major part of these
"Neighborhood Watch" investigations indicates that
we have little faith in the ability of the police to investigate
our suspicions, even if we can convince the folks in blue to
take them at face value. We know from countless courtroom dramas
that the police cannot intervene until a crime has been committed,
by which time it is normally too late. Indeed, the theme of many
movies of the week as well as Hollywood blockbusters such as
What Lies Beneath (2000), is precisely that the police
are legally impotent, and that we must protect ourselves, because
the people we expect to protect us (the police, the district
attorneys, and the judges) simply cannot do so. That's what the
NRA keeps telling us, anyway.  Because he cannot convince the authorities that this
is so, he decides to deal with the man himself, a theme that
we see taken seriously in such films as Death and the Maiden
(1994) and The Execution (1985). In Rear Window
(1954), the granddaddy of all nosy neighbor flicks, the immobilized
James Stewart details the cool and beautiful Grace Kelly to do
his leg work (literally) when he suspects his neighbor of a murder.
If only Hitchcock had known how often his theme was to be reused
over the next decades ("But, Mom, I know our new neighbors
are up to something!" "Now, mind your own business,
Timmy, and do your homework." Organ music swelling up in
the background. Ominous sounds of digging. Weird laughter. Small
pets disappearing suddenly in the night.)
Hollywood particularly loves the Nazis Among Us theme, and not
just because it may actually be true. The movies that gave us
Nazis in patrician New England in The Stranger (1946)
also gave us Nazis in Manhattan in Marathon Man (1976),
Music Box (1989), Descending Angel (1990), Death
and the Maiden and The Execution, all war crimes films
made more believable because of the real life trials of John
Demjanjuk, Adolph Eichmann, and Klaus Barbie. Except for Music
Box, all of these films require the intervention of laypersons
to bring the wrongdoer to justice, or to make a decision not
to do so. Although lawyers play parts in some of these films,
most notably Death and the Maiden and The Execution,
in few do they have the heroic role. Indeed, the lawyers in the
latter three films seem to most non-lawyers to act in contravention
of justice, to prevent evildoers from being brought to account,
to protect the evil neighbors, rather than to root them out.
Nazis (and later Communists) are only one of the hidden threats
that may face us in our neighborhoods. The neighbor as serial
killer threat has recently emerged as a favorite, particularly
since FBI profilers have impressed upon us that serial killers
are not easily recognizable loonies. In fact, they are usually
the boy (or girl) next door. Mark Harmon was cast against type
as Ted Bundy in The Deliberate Stranger (1986), perhaps
the U. S.'s most notorious serial killer, but Bundy himself was
a handsome, charming man. Harmon also played a serial killer
in the 1991 remake of the Hitchcock thriller Shadow of a Doubt,
in which he is arguably even more creepy than Joseph Cotton in
the original (1943) version. The very neighborliness of the serial
killer is what allows many of them to blend into the ordinariness
of everyday life, coupled with our increasing unwillingness to
get involved, our genuine lack of knowledge about those around
us, indeed our very uncertainty about what constitutes "normality."
In these days of unusual religious views, differing dress codes,
a reluctance to exchange even the most perfunctory greetings
on the street, is it any wonder that many of us refuse to ask
the most basic questions about our neighbors' daily or nocturnal
habits? Innocent questions might be seen as harassment. Who needs
confrontation? Anyone might have a concealed weapon, and might
be willing to use it. And fear breeds more fear.
Meanwhile, "normal" people go unchallenged, even when
we have some sneaking doubts about whether their behavior is
in fact entirely normal, until one day, we hear that the nice
man next door, the deacon of the church, has been arrested for
possession of child pornography, or the vice president of the
bank has been hauled in for sexual harassment, or the helpful
home economics teacher has been convicted of raping a fourteen
year old boy. These people live in our neighborhood? Yes, and
they've begun to reproduce-cineamatically speaking. After a rash
of serial killer movies-The Killer Next Door (2001); Through
the Eyes of a Killer (1992)(Richard Dean Anderson is a carpenter
who builds himself a secret passageway so he can spy on his client/victim),
we had a rash of female sexual predator conspiracy to murder
movies (Stay the Night (1992); To Die For (1995);
Murder in New Hampshire (1991); Seduced By Madness
(1996)). We've had female serial killer movies (Black Widow
Murders (1993); Wife, Mother, Murderer (1991); Overkill
(1992) and Monster (2003), both about Aileen Wuornos).
With the possible exception of Wuornos, none of the real life
people depicted was necessarily identifiable as dangerous to
the average person. Just your average normal, daily dog walking,
Saturday night beer drinking, Sunday church going, weekly lawn
cutting, annual Girl Scout cookie-buying serial killer.
In some cases, fictional neighborhoods can be confining to the
point that the scriptwriters clearly decide to scrap them for
more liberating venues. Murder She Wrote's Jessica Fletcher
clearly needed to move out of Cabot Cove for the more sophisticated
and grittier locations of New York, Los Angeles and London, not
just because Maine was sleepy. It was also because at the rate
the show was going, it was fairly clear that half of her neighbors
were homicidal lunatics and the other half were their victims.
This is not to say that fictional neighborhoods cannot reflect
truth. Certainly Agatha Christie made a great point of showing
us that her sleuth Miss Jane Marple detected crime using the
small neighborhood of "St. Mary Mead" as a lens through
which to view the larger world. Everyone in her tiny village
had an analog somewhere in the world; it was simply a matter
of finding the similarity.
Of course, Nazis Among Us quickly became (literally) Aliens Among
Us in the 1950s once Kenneth Arnold spotted those flying saucers,
although we were never quite certain whether those aliens were
Communists or extra-terrestrials. While My Favorite Martian,
3d Rock from the Sun, and Alf played the idea of
neighbors next door as real aliens for laughs, some Americans
truly believe that aliens do dwell among us. The movies that
depicted popularity of fifties movies such as I Married a
Monster from Outer Space (1958) and Invasion of the Body
Snatchers (1956) translated fairly easily into I Married
a Monster (1998) and Invasion of the Body Snatchers
(1978) and Body Snatchers (1993), films which represented
Communism for some people and real alien invasion for others.
Indeed, the invasion narrative is now such a part of our culture
that both Hollywood and independent filmmakers now parody it
easily: Evolution (2001), Galaxy Quest (1999),
and the much underrated Top of the Food Chain a/k/a Invasion
(1999). Is it safe to go out at night? Many of us believe the
law no longer protects us adequately. It's better to stay home
with our security systems and our pay-per-view. For myself, after
assessing the risk, I think I'll still go out at night, to plays
and to concerts and to movies, I'll still talk to my neighbors,
even if they think I'm a little bit of a nut. I want to rely
on them, and I want them to rely on me, even if I don't keep
watching the skies.
Posted May 19, 2004
|


Module simplify
Simplify or linearize a path.
Each of the simplify functions is based on a different
algorithm and produces different, simplified results in (very) different
run times for the same path of LatLon
points.
Function simplify1 eliminates points based on edge lengths
shorter than a given tolerance.
The functions simplifyRDP and simplifyRDPm use the original, respectively modified
Ramer-Douglas-Peucker (RDP) algorithm, iteratively finding the
point farthest from each path edge. The difference is that function simplifyRDP exhaustively searches the most distant point
in each iteration, while modified simplifyRDPm stops at the first point exceeding the
distance tolerance.
Function simplifyRW use the Reumann-Witkam method, sliding
a "pipe" over each path edge, removing all subsequent points
within, closer than the pipe radius up to the first point outside the
pipe.
Functions simplifyVW and simplifyVWm are based on the original, respectively
modified Visvalingam-Whyatt (VW) method using the area of the
triangle formed by three neigboring points. Function simplifyVW removes only a single point per iteration,
while modified simplifyVWm eliminates in each iteration all points with
a triangular area not exceeding the tolerance.
Functions simplifyRDP, simplifyRDPm and simplifyRW provide keyword argument shortest to
specify of the distance between a point and a path edge. If
True
, use the shortest distance to the path edge or
edge points, otherwise use the perpendicular distance to the
extended line through both path edge points.
Keyword argument radius
of all fuctions is set to
the mean earth radius in meter
. Other units can be used,
provided that the radius and tolerance are always specified in the same
units.
Use keyword argument indices=True
in any function
to return a list of simplified point indices instead of the
simplified points. The first and last index are always the first and last
original index.
Finally, any additional keyword arguments options
to all functions are passed thru to function pygeodesy.equirectangular_ to specify the distance
approximation.
To process NumPy
arrays containing rows of lat-,
longitude and possibly other values, use class Numpy2LatLon to wrap the NumPy
array into
on-the-fly-LatLon points. Pass the Numpy2LatLon instance to any simplify function
and the returned result will be a NumPy
array containing the
simplified subset, a partial copy of the original NumPy
array. Use keyword argument indices=True
to return a
list of array row indices inlieu of the simplified array subset.

Eliminates any points closer together than the given distance
tolerance.
- Arguments:
points - Path points (LatLon []).
distance - Tolerance (meter , same units as
radius ).
radius - Mean earth radius (meter ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
|
simplifyRDP (points,
distance=0.001,
radius=6371008.771415,
shortest=False,
indices=False,
**options)
|
|
Ramer-Douglas-Peucker (RDP) simplification of a path of
LatLon points.
Eliminates any points too close together or closer to an edge than the
given distance tolerance.
This RDP method exhaustively searches for the point with
the largest distance, resulting in worst-case complexity O(n**2) where n is the number of
points.
- Arguments:
points - Path points (LatLon []).
distance - Tolerance (meter , same units as
radius ).
radius - Mean earth radius (meter ).
shortest - If True use the shortest otherwise the
perpendicular distance (bool ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
|
simplifyRDPm (points,
distance=0.001,
radius=6371008.771415,
shortest=False,
indices=False,
**options)
|
|
Modified Ramer-Douglas-Peucker (RDPm) simplification of a path
of LatLon points.
Eliminates any points too close together or closer to an edge than the
given distance tolerance.
This RDPm method stops at the first point farther than
the given distance tolerance, significantly reducing the run time (but
producing results different from the original RDP
method).
- Arguments:
points - Path points (LatLon []).
distance - Tolerance (meter , same units as
radius ).
radius - Mean earth radius (meter ).
shortest - If True use the shortest otherwise the
perpendicular distance (bool ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
|
simplifyRW (points,
pipe=0.001,
radius=6371008.771415,
shortest=False,
indices=False,
**options)
|
|
Reumann-Witkam (RW) simplification of a path of
LatLon points.
Eliminates any points too close together or within the given
pipe tolerance along an edge.
- Arguments:
points - Path points (LatLon []).
pipe - Pipe radius, half-width (meter , same units as
radius ).
radius - Mean earth radius (meter ).
shortest - If True use the shortest otherwise the
perpendicular distance (bool ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
|
simplifyVW (points,
area=0.001,
radius=6371008.771415,
attr=None,
indices=False,
**options)
|
|
Visvalingam-Whyatt (VW) simplification of a path of
LatLon points.
Eliminates any points too close together or with a triangular area not
exceeding the given area tolerance squared.
This VW method exhaustively searches for the single point
with the smallest triangular area, resulting in worst-case complexity O(n**2) where n is the number of
points.
- Arguments:
points - Path points (LatLon []).
area - Tolerance (meter , same units as
radius ).
radius - Mean earth radius (meter ).
attr - Optional, points attribute to save the area value
(str ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
AttributeError - If an attr is specified for Numpy2
points .
LimitError - Lat- and/or longitudinal delta exceeds the
limit , see function pygeodesy.equirectangular_.
ValueError - Tolerance area or radius
too small.
|
simplifyVWm (points,
area=0.001,
radius=6371008.771415,
attr=None,
indices=False,
**options)
|
|
Modified Visvalingam-Whyatt (VWm) simplification of a path of
LatLon points.
Eliminates any points too close together or with a triangular area not
exceeding the given area tolerance squared.
This VWm method removes all points with a triangular area
below the tolerance in each iteration, significantly reducing the run
time (but producing results different from the original VW
method).
- Arguments:
points - Path points (LatLon []).
area - Tolerance (meter , same units as
radius ).
radius - Mean earth radius (meter ).
attr - Optional, points attribute to save the area value
(str ).
indices - If True return the simplified point indices instead
of the simplified points (bool ).
options - Optional keyword arguments passed thru to function pygeodesy.equirectangular_.
- Returns:
- Simplified points (
LatLon []).
- Raises:
AttributeError - If an attr is specified for Numpy2
points .
LimitError - Lat- and/or longitudinal delta exceeds the
limit , see function pygeodesy.equirectangular_.
ValueError - Tolerance area or radius
too small.
|


| MautiCon |
The Ideal Community Model: Lessons Learned |
17-11-2020
|
San Francisco, United States |
| Open
Core Summit |
Design from the Realm of Open Source |
19-11-2020
|
San Francisco, United States |
| All Day DevOps |
Securing Serverless Applications using Azure |
12-11-2020
|
McLean, Virginia |
| FrontEnd Connect |
Progressive Imaging & Handling: React + WebPack |
08-12-2020
|
Warszawa, Polska |
| Frontend Love Conference |
Design from the dimension of Open Source |
01-02-2021
|
Amsterdam, Noord-Holland |
| Codemotion Amsterdam 2 |
Getting up to Speed With Deno |
Spring 2021
|
Amsterdam, The Netherlands |


{% extends 'base.html' %} {% block content %}
Name: {{hood.name}}
Location:{{hood.location}}
Occupants: {{hood.occupants_count}}
Description: {{hood.description}}
Emergency Contact: {{hood.emergency_contact}}


What is it all about?
Imagine sitting at your computer and controlling a video game
character through a mall or market. isn't it fun? Imagine How AI &
IOT will transform industries. What is your contribution to make
life easier, faster and smarter without giving up values of
sustainability, eco-friendliness and culture? Amrita is providing an
opportunity to Young and Talented minds to showcase their young
talents, ideas and creativity.
Information
How to participate?
Registration Mandatory
There Shall be teacher from your school as contact point for a team
Two categories:
High School Students (class 5 to 8)
Higher Secondary School Students (class 9 to 12)
Team Size (+1 Mentor for Team)
Minimum no of Student Participants: 2
Maximum no of Student Participants: 5
Important Dates
Abstract Submission
First round -Last Date August 15
Second Round Submission- last date September 15
Announcement of Winning Teams on Sept 20
Event Dates: October 25 to 28
Accommodation & Travel
Travel Reimbursement for both Mentors & Students (Up to sleeper Class(train))
Accommodation and reimbursement of travel expenses will be provided only for students and Mentors, persons
accompanying will be provided accommodation on payment basis.


Parliament Impact at Opendata.ch Research Hackdays
June 6 2015
Measuring the impact of political action by comparing the occurrences of keywords contained in the Swiss Parliament documents (motions, postulates, interpellations, questions, etc.) and the occurrences of the same keywords in a national newspaper.
Data visualizations
- interactive bubble chart, with time slider
- many static visualizations (histograms, etc.)
- experimental network visualization (see it online here)
- party-patterns
Data
Team
Tools
- Crawling tool: Quantinum
- Visualization: Gephi, D3.JS, Inkscape, Illustrator
Continue reading...
Links
Prototype
Github


PeopleFinder Offline for Palm OS v3.1 |
HP has a totally awesome employee register called People Finder which is accessible on the intranet or in an offline form built for Pocket PC devices. Unfortunately, a Palm OS counterpart is missing.
PeopleFinder Offline for Palm OS tries to fill that gap.
On this website I have a couple of documents describing how to install and use PeopleFinder Offline for Palm OS. These are listed below in the order you should read them:
If you have any comments, requests for enhancements or just want to drop me a note, well, then you can find me using PFO - just search for:
schau brian
I look forward to receive your comments, criticism and good ideas!
2006-04-06 3.1 * Changed some minor graphical errors and text. 2006-03-07 3.0 * Rewrote most of PFOC so it looks more like a wizard. * Changed the GUI in PFO. * Support for 5-way navigation in PFO. * Fixed some memory leaks. * Phone numbers can now be searched. * The details screen in PFO is now a bit more smoother - no blinks :-) 2006-01-19 2.2 * Fixed a bug where PFOC would crash if it encountered an empty line in the database file. * Dialing now works on the Treo 650. 2005-10-27 2.1 * Support for BtToggle. Bluetooth can now (reliably) be turned on. This requires either BtToggle Classic or BtToggle Pro from: http://www.whizoo.com/apps/bttoggle.php * Removed the "double-draw" glitch on the main screen. 2005-08-17 2.0 * Managers can now be tracked (again) from the Details view. * When the Mobile and Primary phone numbers are equal, only show one of them in the dialing list. * You can now enter any number in the dialing list. * "Missing persons" can now be found :-) * PFO can now on some Palms optionally turn on Bluetooth before dialing a number. 2005-08-15 1.1 * You can now dial a person from within the details view. * The delay encountered when searching on card has been minimized considerably. * Small help function implemented. * The search term is now remembered between searches. * Changed version numbering - v1.1 _is_ newer than v1r1. 2005-08-09 1.0 * Initial release


[CHAPTER 435C]
HAWAII MEDICAL MALPRACTICE UNDERWRITING PLAN
Section
435C-1 Purpose
435C-2 Definitions
435C-3 Joint underwriting plan, establishment
435C-4 Procedures
435C-5 Participation
435C-6 Directors
435C-7 Appeals and judicial review
435C-8 Privileged communications
435C-9 Annual statements
435C-10 Examinations
435C-11 Initiation of plan


Note that write() does NOT add a new line after each statement:
Note that writeln() add a new line after each statement: