---
layout: null
section-type: projects
title: Projects
---
Projects
---
Current
BITCOIN LIBRARY
Building a [Bitcoin library](https://github.com/karask/python-bitcoin-utils){:target="_blank"} that provides tools/utilities to interact with the Bitcoin network. One of the primary goals of the library is to explain the low-level details of Bitcoin. The code is easy to read and properly documented explaining in detail all the thorny aspects of the implementation. It is a low-level library which assumes some high-level understanding of how Bitcoin works. In the future this might change.
This is an early version of the library (v0.5.9) and currently, it supports private/public keys, all type of addresses (incl.segwit) and creation of P2PKH, P2SH and segwit transactions (with all SIGHASH types). All script op codes are included. Timelock and non-standanrd transactions are supported. Currently, a simple node proxy exists to enable easy calls to a Bitcoin core node. Additional functionality will be added continuously and the documentation will be improved as the work progresses. I use this library in the courses that I teach (University of Nicosia, Aristotle University of Thessaloniki and in seminars).
BITCOIN PROGRAMMING TEXTBOOK
Writing a [Bitcoin programming book](/assets/bitcoin-textbook.pdf). It is open source under the CC-SA license and available in its [repository](https://github.com/karask/bitcoin-textbook){:target="_blank"}. The first chapters attempt to summarize what you need to know to progress with the rest of the material but it is not intended for complete beginners. It aims to be a practical guide and thus is full of examples either in the command-line or using Python programs. It is based in the open source Bitcoin library, python-bitcoin-utils (see above) that I have also created for educational purposes.
BLOCKCHAIN CERTIFICATES
Has architected and implemented the University of Nicosia's blockchain certificate platform which enables easy, fast and independent publishing verification of certificates/diplomas/etc. More details on the [website](https://verifiable-pdfs.org/){:target="_blank"} and on [github](https://github.com/verifiable-pdfs){:target="_blank"}. A certificate [validator](http://verify.unic.ac.cy/verify){:target="_blank"} (using the open source code) was set up for the University of Nicosia. Currently, only Bitcoin is supported but the infrastructure exists for other platforms. Also created a library ([Blockchain-Proofs](https://github.com/karask/blockchain-proofs){:target="_blank"}) to allow blockchain certificates validation which currently supports [Chainpoint v2](http://www.chainpoint.org/){:target="_blank"} but might incorporate/wrap others in the future (e.g. [OpenTimestamps](https://github.com/opentimestamps){:target="_blank"}).
Has also contributed on MIT's Media Lab/Learning Machine blockchain certificates project, blockcerts.
RAISING BLOCKCHAIN TECHNOLOGY AWARENESS
Currently organizing and speaking in local meetups and events throughout Greece, e.g. [Thessaloniki's](https://www.meetup.com/BlockchainGreece-1/){:target="_blank"} and [Athen's](https://www.meetup.com/BlockchainGreece-0/){:target="_blank"} meetups, and guest lecturing in academic institutions, doing both introductory and more advanced technical talks.
Also teaching Bitcoin and Ethereum programming in Master courses of University of Nicosia and Aristrotle University of Thessaloniki.
Past
#### BITCOIN INTRODUCTION
Has written an "_Introduction to Bitcoin for new users_" available in [pdf](/assets/introductionToBitcoin.pdf), [epub](/assets/introductionToBitcoin.epub), and [mobi](/assets/introductionToBitcoin.mobi) (outdated, written in 2016).
#### BITCOIN ANDROID APPLICATIONS
Developed a Point of Sale application for merchants that wish to accept Bitcoins. The need arose in the meetups when some users asked for more features than other solutions. You can find it in play store [here](https://play.google.com/store/apps/details?id=gr.cryptocurrencies.bitcoinpos&hl=en){:target="_blank"} (outdated).
Developed a simple quiz application to test your Bitcoin knowledge at different levels. There are around 150 questions right now but more are added occasionally. You can find it in play store [here](https://play.google.com/store/apps/details?id=gr.cryptocurrencies.bitcoinchallenge&hl=en){:target="_blank"} (outdated).
WORKFLOW TECHNOLOGY
Worked with [workflows](https://en.wikipedia.org/wiki/Workflow){:target="_blank"} for several years both in academia and in the bioinformatics industry. The output of that work was several open source contributions, like [OGSA-DAI](http://www.ogsadai.org.uk){:target="_blank"} that included a workflow engine to capture federation rules, [Taverna Workflows to Web application](https://rubygems.org/gems/t2-web){:target="_blank"}, [Workflows to Galaxy](https://rubygems.org/gems/workflow-to-galaxy){:target="_blank"} and the [MyExperiment REST API library](https://rubygems.org/gems/myexperiment-rest){:target="_blank"}.
#### DISTRIBUTED DATA ACCESS AND MANAGEMENT
Member of the [OGSA-DAI project](http://www.ogsadai.org.uk/){:target="_blank"} for 4.5 years years working on data federation and access via web services, grids, or clouds. Conducted research on improving the architecture of OGSA-DAI and demonstrated new ideas with prototypes as well as acted as a bridge between the academic research and the development team.
#### EVEN OLDER PROJECTS
Very early projects involved both low- and high-level technical expertise. Some examples of low-level projects were: a Linux bootstrap sequence, a simple floppy device driver and porting C/C++ projects to Windows, e.g. the [OGSA-DQP](http://ieeexplore.ieee.org/document/5070877/){:target="_blank"} software.
Higher-level projects included an editor, libraries to create text menus (back in the day) and some networking applications like a chat server/client and a MUD.
---


An enthusiastic and reliable IT support engineer, with extensive practical experience on hardware and software, operating systems and basic computer programming. With a proven ability to administer and control the operation, configuration and maintenance of computer based information systems. Familiar with electronic equipment, Internet applications and network support, eager to develop new skills from a challenging position in the field of technical support and network engineering. Possessing an excellent team spirit, deadline orientated, now looking for a suitable position at a dynamic company that offers room for further progress.
Education
Licenses & certifications
Certification
Time
Cisco certified Network Assosiate (CCNA)
2006
Mikrotik Certified Network Assosiate (MTCNA)
2012
Work Experince
Position
Company
Place
Time Period
Internship at the department of Telecommunication Metric Network (ΤMN)
Hellenic Telecomunication Organization S.A
GR-Thessaloniki
Marc 2005 - Aug 2005
Network Technician
Pan Dacom Networking AG
GR-Thessaloniki
Jul 2006 -Nov 2006
Production and audiovisual support
Remembering the Past-Building the Future festival funded by the European program Europe for Citizens


Transmission coefficient:
Reflexion coefficient:
Information:
n=
n'=
Transmission factor:
Reflexion factor:


PHPStan analysis result
2021-01-17 19:38:02
0 error found
This file was made thanks to
PHPStan
and was outputted by
PHPStan FileOutput


Updates
v0.4.1
- Fixing broken re-search after an initial search of library
v0.4.0
- Added Updates Page
- GitHub CI/CD Builds
- New Gaps Logo
- New Gaps Icon
- New Icons
- Updated Navbar
- Updated End to End Testing
- Springboot 2.3.0
- Cypress 4.7.0
v0.3.1
- Fixed titles showing the wrong language
- Added collection information to the cards in recommended
v0.3.0
- Added option to delete all files and reset Gaps. It is available in the configuration tab.
v0.2.2
- Bootstrap integration
- UI Improvements everywhere
- Cards for owned and recommended movies
- Broken up Plex search from Gaps search
- Multi library search
- Caching system for movies for faster searching
- Springboot version update 2.2.5
- Cypress testing integration
- Server side rendering
- Removed cookies
- Performance improvements with caching and server side rendering
v0.2.0
- Showing owned movies now
- Supporting movies in languages other than English/US during searching
v0.1.6
v0.1.5
v0.1.4
- Fixing bugs with many Plex libraries
- Updating dependency versions
- Fixing movie title's in different languages bug
v0.1.2
- Windows Support
- Bug Fixes
v0.1.0
- Updated to Spring Boot 2.2.2-RELEASE
- Switched to Jackson instead of JSON Org for faster XML/JSON Parsing
- Refined movie cache to reduce lookups to TMDB for faster search
- Removed MaterializeCSS and replaced with Bootstrap
- Added error handling
- Created dual builds
- SSL docker pull housewrecker/gaps:latest
- No SSL docker pull housewrecker/gaps:latest-no-ssl
- Coded clean up
- Added Thymeleaf for server side rendered to speed up web pages
- Added DataTables.js to render movies
- Added TMDB links to results
- Added persistent 'recommended' page and tab to show results in DataTables from the last
search
- Added persistent 'rss' page and tab to link to results in Radarr
- Removed cookies and replaced with server side storage of configuration to persist across
multiple browsers, quicker rendering, and safer configuration


World Learning is proud to host the 2016 International Women of Courage as part of an exchange program sponsored by the U.S. Department of State.
The International Women of Courage Award annually recognizes women around the globe who have demonstrated exceptional courage and leadership in advocating for peace, justice, human rights, gender equality and women’s empowerment, often at great personal risk. The group of 14 extraordinary women received their awards from Secretary of State John Kerry in a ceremony at the State Department on March 29.
“This year we recognize a group of women who are demonstrating courage in three pivotal areas, Secretary Kerry said of the honorees. “They are exposing and opposing gender-based violence, they are combating corruption and strengthening rule of law and they are promoting justice and human rights for all.”
Since the inception of this award in 2007, the Department of State has honored nearly 100 women from 60 different countries. To mark the tenth anniversary of the award the State Department hosted a forum after the ceremony.
The 2016 awardees are:
- Sara Hossain, Barrister, Supreme Court, Bangladesh
- Debra Baptist-Estrada, Port Commander, Belize Immigration and Nationality, Belize
- Ni Yulan, Human Rights Activist, China
- Latifa Ibn Ziaten, Interfaith Activist, France
- Thelma Aldana, Attorney General, Guatemala
- Nagham Nawzat, Yezidi Activist and Gynecologist, Iraq
- Nisha Ayub, Transgender Rights Advocate, Malaysia
- Fatimata M’baye, Co-founder and President of the Mauritanian Association for Human Rights, Mauritania
- Zhanna Nemtsova, Journalist and Activist, Russia
- Zuzana Števulová, Director of the Human Rights League, Slovakia
- Awadeya Mahmoud, Founder and Chair of the Women’s Food and Tea Sellers’ Cooperative and the Women’s Multi-Purpose Cooperative for Khartoum State, Sudan
- Vicky Ntetema, Executive Director of Under the Same Sun, Tanzania
- Rodjaraeg Wattanapanit, Bookstore Owner and Co-founder of Creating Awareness for Enhanced Democracy, Thailand
- Nihal Naj Ali Al-Awlaqi, Minister of Legal Affairs, Yemen
On April 1 the honorees will travel to seven U.S. states including Alabama, California, Kentucky, Michigan, Minnesota, North Carolina and Pennsylvania on individual programs through an International Visitor Leadership Program, which World Learning is organizing. They will reconvene in Los Angeles at the end of the program to discuss their time in the United States and how to collaborate to improve life for women and girls worldwide.
Video was produced by the U.S. Department of State's Bureau of International Information Programs.


NumModelMarbre
class NumModelMarbre extends NumModel (View source)
NumModelMarbre class
Class to manage module numbering rules Marbre
Properties
| $error | from NumModel | ||
| $version | |||
| $nom | |||
| protected | $const_name | ||
| protected | $table_name | ||
| protected | $field_name | ||
| protected | $prefix |
Methods
string
info()
Return description of numbering model
string
getExample()
Return an example of numbering
boolean
canBeActivated()
Check if the numbers already existing in the database doesn't have conflicts with this numbering model
string
getNextValue(Societe $objsoc = null)
Return next free value
__construct($const_name_prefix, $model_name = '')
Constructor
Details
at line 68
string
info()
Return description of numbering model
at line 80
string
getExample()
Return an example of numbering
at line 90
boolean
canBeActivated()
Check if the numbers already existing in the database doesn't have conflicts with this numbering model
at line 128
string
getNextValue(Societe $objsoc = null)
Return next free value
at line 41
__construct($const_name_prefix, $model_name = '')
Constructor


| ^a${value} Second(s) Recharge | 25
|
| ${value} Energy Cost | 50 54 59 63 68 72 77 81 86 90 95 99 104 108
|
| ${value} Second Duration | 4
|
| ${value}% Chance to Avoid Projectiles | 300
|
| ${value}% Chance to Dodge Attacks | 300
|
| ${value}% Damage Absorption | 100
|
| ${value}% Damage Reflected | -300
|
| ${value}RetaliationDurationManaLeachModifier | -300
|
| ${value}RetaliationStunModifier | -300
|
| +${value} Health Regeneration per second | 15 29.5 43.25 57 70.75 84.5 97 112 124.5 137 149.5 164.5 178.25 192
|
| +${value}% Bleeding Damage Retaliation | -300
|
| +${value}% Burn Retaliation | -300
|
| +${value}% Cold Damage Retaliation | -300
|
| +${value}% Electrical Burn Retaliation | -300
|
| +${value}% Fire Damage Retaliation | -300
|
| +${value}% Frostburn Retaliation | -300
|
| +${value}% Instant Poison Retaliation | -300
|
| +${value}% Life Leech Retaliation | -300
|
| +${value}% Lightning Damage Retaliation | -300
|
| +${value}% Physical Retaliation | -300
|
| +${value}% Pierce Damage Retaliation | -300
|
| +${value}% Poison Retaliation | -300
|
| +${value}% Total Damage | -300
|
| +${value}% Vitality Damage Retaliation | -300
|
| +${value}% Vitality Decay Retaliation | -300
|
| MaxLevel | 10
|
| UltimateLevel | 14
|


Welcome To Fultala
There are many variations of passages of Lorem Ipsum available, buthe majority have suffered alteration in some form, by injeed randomised words which don't look even sliglieable.All the Lorem Ipsum generators on the Internet tend to repe defined chunks as necessary, making this the first true generator on the Internet. It uses


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Day 2: Lines
Day 1: Points


|
2NVIDIA Research |
Designing machine learning architectures for processing neural networks in their raw weight matrix form is a newly introduced research direction. Unfortunately, the unique symmetry structure of deep weight spaces makes this design very challenging. If successful, such architectures would be capable of performing a wide range of intriguing tasks, from adapting a pre-trained network to a new domain to editing objects represented as functions (INRs or NeRFs). As a first step towards this goal, we present here a novel network architecture for learning in deep weight spaces. It takes as input a concatenation of weights and biases of a pre-trained MLP and processes it using a composition of layers that are equivariant to the natural permutation symmetry of the MLP’s weights: Changing the order of neurons in intermediate layers of the MLP does not affect the function it represents. We provide a full characterization of all affine equivariant and invariant layers for these symmetries and show how these layers can be implemented using three basic operations: pooling, broadcasting, and fully connected layers applied to the input in an appropriate manner. We demonstrate the effectiveness of our architecture and its advantages over natural baselines in a variety of learning tasks
We address learning in spaces that represent a concatenation of weight (and bias) matrices of Multilayer Perceptrons (MLPs). We analyze the symmetry structure of neural weight spaces. Then we design architectures that are equivariant to the natural symmetries of the data. Specifically, we focus on the main type of symmetry found in the weights of MLPs: for any two consecutive internal layers of an MLP, simultaneously permuting the rows of the first layer and the columns of the second layer generates a new sequence of weight matrices that represent exactly the same underlying function. We provide a full characterization of all affine equivariant and invariant layers for these symmetries and show how these layers can be implemented using three basic operations: pooling, broadcasting, and fully connected layers applied to the input in an appropriate manner.
We term our linear equivariant layers, DWS-layers, and the architectures that use them (interleaved with pointwise nonlinearities) DWSNets (for Deep Weight-Space Networks).
To first illustrate the operation of DWSNets, we look into a regression problem. We train INRs to fit sine waves on $[-\pi, \pi]$, with different frequencies sampled from $U(0.5, 10)$. Each sine wave is represented as an MLP trained as an INR network, and the task is to have the DWSNet predict the frequency of a given test INR network. To illustrate the generalization capabilities of the architectures, we repeat the experiment by training the DWSNet with a varying number of training examples (INRs). DWSNets performs significantly better than baseline methods even with a small number of training examples.
Here, INRs were trained to represent images from MNIST and Fashion-MNIST. The task is to have the DWSNet recognize the image content, like the digit in MNIST, by using the weights of these INRs as input. Table 1 shows that DWSNets outperforms all baseline methods by a large margin.
Here we wish to embed neural networks into a semantic coherent low dimensional space. To that end, we fit INRs on sine waves of the form a $\sin(bx)$ on $[−\pi, \pi]$. Here $a, b \sim U(0, 10)$. We use a SimCLR-like training procedure and objective, by generating random views from each INR by adding Gaussian noise and random masking. We qualitatively observe a 2D TSNE of the resulting space.


Lorem Ipsum is simply dummy of the printing.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make atype specimen book. It has survived not only five centuries.
© Solução de Filipe Gaspar


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Register New Candidate
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Use the below form to register a new candidate contesting in elections
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--- layout: post title: Bayes's theorem tagline: " in examples" permalink: /bayes/overview.html categories: [math] tags: [Bayes, theorem] ---
Bayes' theorem is a formula that describes how to update the probabilities of hypotheses when given evidence. It follows simply from the axioms of conditional probability, but can be used to powerfully reason about a wide range of problems involving belief updates.
Given a hypothesis H and evidence E, Bayes' theorem states that the relationship between the probability of the hypothesis P(H) before getting the evidence and the probability P(H|E) of the hypothesis after getting the evidence is:
\(P(H|E) = \frac{P(E|H)}{P(E)}P(H)\)
1% of women at age forty who participate in routine screening have breast cancer. 80% of women with breast cancer will get positive mammographies. 9.6% of women without breast cancer will also get positive mammographies. A woman in this age group had a positive mammography in a routine screening. What is the probability that she actually has breast cancer?
The correct answer is 7.8%, obtained as follows: Out of 10,000 women, 100 have breast cancer; 80 of those 100 have positive mammographies. From the same 10,000 women, 9,900 will not have breast cancer and of those 9,900 women, 950 will also get positive mammographies. This makes the total number of women with positive mammographies 950+80 or 1,030. Of those 1,030 women with positive mammographies, 80 will have cancer. Expressed as a proportion, this is 80/1,030 or 0.07767 or 7.8%.
To put it another way, before the mammography screening, the 10,000 women can be divided into two groups:
Summing these two groups gives a total of 10,000 patients, confirming that none have been lost in the math. After the mammography, the women can be divided into four groups:


Hello, world! My name is Gipsi. I live in Sussex. The sea-side is awesome.
One of my hobbies is gardening. I rebalance by feeling grounded with the natural world when I lose myself and get involved with the activities of plants and trees and the creatures that live amongst them. The changing weather and light and shade, sunshine and rain, their effects on the rocks and stones and soil.
Here is a picture of a kitten because my page is boring without a photo.
My favourite website is Google.


Om is a Technical Enthusiast. He is mainly known for his contributions as an open-source contributor and blogging. He has taken many sessions as part of NGOs and technical sessions in Data Science. He is a speaker at Toastmasters and has given 30+ speeches. He is a Scout by Nature and Developer by Passion. He is an Avid Reader and Reseacher.
Apart from working, Om loves to dance and draw comics. He loves to play football and chess. He is a friendly guy and would love to help. Feel free to reach out to him on any social platform. If you are not in need of help, just drop a "Hi", he shall love to connect with you! He is very active on social media!
Effective Use of Stack Overflow for better search and problem solving approach!
View BlogThis article is part of my "Tech Hack" Series! I hope this helps you!
View BlogView More Technical Blogs
Understanding the proper colaboration of head, heart and head for better results!
View BlogTalent is not a unbeaten thing! How hard work gets over, makes all the difference!
View BlogActions are at times not able to see a growth! Is your initiative under trouble? Do have a look!
View BlogView More Life Blogs
A Java Developer working with Access Secure Team in the domain of Cyber Security. Known for the developement mainly in Kotlin, Angular and Security Tools.
Deep Learning Model developer. Worked in Keras, Tensorflow and AWS for building various projects. Sales Prediction Modeling for better sales approach. Working on BERT Algorithm to optimize the HR chatbot search. Using OpenCV and NLP for extraction of details and data wrangling. Understanding employee retention data and making pipelines to analysis them.
Working on Medical Dataset and making a Portal for handling the medicine related issues. Making a Demo of meet handler similar to Google Meetups. Using Web Crawler to extract data using python.
See More in Om's LinkedIn Profile
An effective way to understand the way in which the cars are been parked and handled. The iterative methods of storing the cars in queues and allocating them according to the parking space. Designed to understand the growth of parking problems and graphics for visualization!
View ProjectMask Detection using MT-CNN classification and with time and location capturing for better data extraction. This has been done for various location and timing analysis and works great with all cases.
View ProjectA Kaggle Challenge project to predict the delay of flights and the data visualization. This project was selected as one of the winning projects and this added a great value for the prediction of the competition.
View ProjectSee More in Om's Github Profile


Id: 391
Name: Uncle Steve
Status: Dead
Species: Alien
Type: Parasite
Gender: Male
OriginName: unknown
OriginUrl:
LocationName: Earth (Replacement Dimension)
LocationUrl: https://rickandmortyapi.com/api/location/20
Image: https://rickandmortyapi.com/api/character/avatar/391.jpeg
Episode: ['https://rickandmortyapi.com/api/episode/15']
Url: https://rickandmortyapi.com/api/character/391
Created: 2018-01-14T13:34:50.096Z


In this example, we are going to study a variety of tomatoes (Ida Gold) grown outdoors in plots located on the INRA BFP site.
First, we will describe the entire experimental design using the MIAPPE forms available to you. In a second step, we will describe the metadata associated with the experience and the entry of this metadata. The culture will take place from March 15 to August 15, 2021. In total, 5 observation points will be established, one per month (April 15, May 15, June 15, July 15 and August 15). At this observation point, we will take 5 leaf samples which will be measured. Several experimental factors will be taken into account, the soil moisture rate, the nitrogen rate in the growing medium, the sunshine on the plot (lit / in the shade).
A total of 72 plants will be cultivated, 9 per condition (plot). the size of the land is 10 m by 5 m. Each plot measures 1.80 m by 1.80 m.
The plants are treated with different rates of nitrogen. a low rate (2%) and a high rate (10%)
The plants are grown under different conditions and treatment. These experimental factors will be described using the corresponding form.
First of all, you need to create an investigation, just click on the associated and a menu will appear from which you can choose between three proposals
Three choices are available to the user
The MIAPPE model form for an investigation. The description of the fields for each structure of the MIAPPE model can be found here
The user can save a pre-filled template by checking the save template option when validating the form. These pre-filled templates can then be reused as many times as needed. However, it is rare to create the same investigation twice but it can be useful to replay type / model studies in other investigations
The user can save the whole of an investigation with all the elements composing it as a compressed folder in .zip format. Therefore, the user can also upload an entire investigation as .zip files.
At this point, we choose to start from the empty template because we haven't saved any templates. there are 8 fields to fill in to describe your investigation. The first two are mandatory and must be unique.
Once the form is completed, you can choose to save it as a template, in order to be able to reuse it later as a template in other projects, by activating the option save as template at the top right. Then, click on the Submit button to add your investigation to the investigation tree.
The investigation is the highest level of the MIAPPE hierarchy and may contain different studies within it. In our case, we are going to create a single study that we will name "tomato1_study1". The form for describing a study contains 20 fields to fill in Study . Some fields are mandatory, such as the study identifier, which must be unique.
To describe a biological material, the MiAPPE standard requires to describe at least the studied organism, the genus, the species and the name of the sub-taxa if they exist.
The original source of that material (e.g., the seeds or the original plant cloned) is called the material source, which, when held by a material repository, should have its stock identified The material source must be identified with a unique identifier. Other information is used to describe various characteristics of the material.


Lets play Sweet n Salty
Select your start point and end point
Start Number
End Number
Per Line Number


Quickstart¶
This page gives a good introduction in how to get started with fnapy.
Before starting, make sure you have your credentials to connect to the FNAC API.
Create a connection to the FNAC Marketplace API with your credentials:
>>> from fnapy.fnapy_manager import FnapyManager >>> connection = FnapyConnection(credentials)
Create the manager:
>>> from fnapy.connection import FnapyConnection >>> manager = FnapyManager(connection)
Now you should be able to access the different web services.
Update your offers¶
Let’s create some offers in our catalog:
offer_data1 = {'product_reference':'0711719247159',
'offer_reference':'B76A-CD5-153',
'price':15, 'product_state':11, 'quantity':10,
'description': 'New product - 2-3 days shipping, from France'}
offer_data2 = {'product_reference':'5030917077418',
'offer_reference':'B067-F0D-75E',
'price':20, 'product_state':11, 'quantity':16,
'description': 'New product - 2-3 days shipping, from France'}
response = manager.update_offers([offers_data1, offer_data2])
Behind the scene, the manager sent an XML request to the offers_update service. We can have a look at this request with the attribute offers_update_request:
>>> request = manager.offers_update_request
>>> print request.xml
<?xml version='1.0' encoding='utf-8'?>
<offers_update xmlns="http://www.fnac.com/schemas/mp-dialog.xsd" partner_id="XXX" shop_id="XXX" token="XXX">
<offer>
<product_reference type="Ean">0711719247159</product_reference>
<offer_reference type="SellerSku"><![CDATA[B76A-CD5-153]]></offer_reference>
<price>15</price>
<product_state>11</product_state>
<quantity>10</quantity>
<description><![CDATA[New product - 2-3 days shipping, from France]]></description>
</offer>
<offer>
<product_reference type="Ean">5030917077418</product_reference>
<offer_reference type="SellerSku"><![CDATA[B067-F0D-75E]]></offer_reference>
<price>20</price>
<product_state>11</product_state>
<quantity>16</quantity>
<description><![CDATA[New product - 2-3 days shipping, from France]]></description>
</offer>
</offers_update>
Actually this request is an instance of the Request
class.
We’ll talk about it later. For now, let’s see what we’ve got in our response:
>>> print response.xml
<?xml version="1.0" encoding="utf-8"?>
<offers_update_response status="OK" xmlns="http://www.fnac.com/schemas/mp-dialog.xsd">
<batch_id>88BD9517-A73C-78E0-04DB-AC5ADE1D63F6</batch_id>
</offers_update_response>
The response sent by the server is just an instance of the Response
class. We can see that the status of the response is OK and the
batch_id is 88BD9517-A73C-78E0-04DB-AC5ADE1D63F6. This is basically the id
you’ll have to use to get information about the status of your offers.
Get the batch status¶
batch_id = response.dict['offers_update_response']['batch_id']
response = manager.get_batch_status(batch_id)
Note that FnapyManager
stores the last batch_id so if
you want the latest batch_status you can do:
response = manager.get_batch_status()
Query the offers¶
When you’re satisfised with your offers you may want to know if they were actually created and retrieve information about them.
Let’s say you want to know the offers created between 2016-08-25 and 2016-08-31:
from fnapy.utils import Query
dmin = datetime(2016, 8, 25, 0, 0, 0).replace(tzinfo=pytz.utc).isoformat()
dmax = datetime(2016, 8, 31, 0, 0, 0).replace(tzinfo=pytz.utc).isoformat()
date Query('date', type='Created').between(min=dmin, max=dmax)
response = manager.query_offers(date=date)
Query the pricing¶
In order to stay competitive, you have to know the offers created by the other sellers for a list of codes or at least the current best offer these products. You can get these information with query_pricing:
response = manager.query_pricing(codes)
where codes can be:
A list of EANs.
Example:
codes = ["7321900286480", "9780262510875", "5060314991222"]
A list of any code type.
Example:
codes = [ {"value":<PHONE_NUMBER>875, "type": "Ean"}, {"value":<PHONE_NUMBER>, "type": "Isbn"}, {"value": 8172119, "type": "FnacId"}, ]
The available code types are:
FnacId: The code given is the Fnac product identifier
- PartnerId: The code given is the id from a partner, if this
value is set, a partner id will be mandatory
Ean: The code given is the global Ean of this product
Isbn: The code given is the global Isbn of this product
PartNumber: The code given is the global partNumber of this product
CnetId: The code given is the global Cnet reference of this product
Delete offers¶
You can delete the offers you created with delete_offers:
response = manager.delete_offers(offer_references)
where offer_references is a list of SKUs.
Query the orders¶
Once customers placed an order on your items in your catalog, you can query these orders.
If you want to retrieve the first 10 created orders, you’ll have to sent this request with:
response = manager.query_orders(results_count=10, paging=1)
Update the orders¶
Orders statuses are following this workflow:
Created > Accepted > ToShip > Shipped > Received
The seller acts only at acceptation and shipping steps.
This is the how we accept the first and refuse the second order for the order_id 003ECCA1YVFBW:
action1 = {"order_detail_id": 1, "action": "Accepted"}
action2 = {"order_detail_id": 2, "action": "Refused"}
actions = [action1, action2]
response = manager.update_orders('003ECCA1YVFBW', "accept_order", actions)
Tracking information¶
It is also possible to include the tracking information in the order (tracking_number and tracking_company):
action = {"order_detail_id": 1, "action": "Shipped",
"tracking_number": "1234", "tracking_company": "Track Inc."}
response = manager.update_orders('003ECCA1YVFBW', "update", [action])
Request and Response¶
Both Request
and Response
share the same
interface.


A simple POS System
Jeffrey POS has two running instances. One for public use and one for private use. Select an option below


My Web Design Portfolio
Here are some examples of my work. I hope you enjoy them, and don't
hesitate to contact me if you like what you see. Even if it's just to say,
"Hey! Cool sites!"
David's Cat Companion Page
This is one of the first sites I built back in 2011 for a school project.I recently updated the look and re-uploaded it.
My Indie Rock Page
Another oldie but goodie that's been given a facelift.
Saguaro Vinyl
Website for a fictional record store I created for a former employer.
Dave's Page
A goofy page with a subliminal tribute to blues legend John Lee Hooker.
Basic PHP Form
Another PHP page, this one is an example of a basic form.
Rock and Roll Page
Another fun page dedicated to rock music, one of my many passions.
Want to get in touch?
Click Here
Copyright 2011-2021 David Hunsdon


{{ `` | safeHTML }} {{ `` | safeHTML }} {{ `` | safeHTML }}
{{- partial "cdts/head.html" . -}} {{- partial "cdts/deftop.html" . -}}
{{ block "main" . }} {{ end }} {{- partial "cdts/defprefooter.html" . -}}
{{- partial "cdts/deffooter.html" . -}} {{- partial "cdts/reffooter.html" . -}}


Cheesecake Order Form
Quantity Topping
1
2
3
4
5
Plain
Cherry
Chocolate
Notes:
Orders for
Jan
Jan
Feb
Apr
Mar
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
11 cherry
17 chocolate
31 plain


Home
Guns
Gameplay
MODERN WARFARE
#END
SARS
A collection of top Guns used in Call of Duty - Modern Warfare


Express is a minimal, open source and flexible Node.js web app framework designed to make developing websites, web apps and APIs much easier.
npm install express
npm install jade
npm install -g express-generator
app.get('/index', function (req, res) {});
var express = require('express');
var app = express();
app.get('/', function (req, res) {
res.json({message:'hooray! welcome to our api!'});
});
app.listen(process.env.PORT || 8080);
© 2016-2017 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.


@* Copyright 2012 Igor Laborie 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. *@ @(message: String) @bootstrap(message, true) { @intro() @x01.NewGame() @* Game *@
@* History *@ @ScriptGame() }


Created By Ajay Ramachandran
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This module provides regular expression matching operations similar to those found in Perl. Both patterns and strings to be searched can be Unicode strings as well as 8-bit strings.
Regular expressions use the backslash character ('\') to indicate special forms or to allow special characters to be used without invoking their special meaning. This collides with Python’s usage of the same character for the same purpose in string literals; for example, to match a literal backslash, one might have to write '\\\\' as the pattern string, because the regular expression must be \\, and each backslash must be expressed as \\ inside a regular Python string literal.
The solution is to use Python’s raw string notation for regular expression patterns; backslashes are not handled in any special way in a string literal prefixed with 'r'. So r"\n" is a two-character string containing '\' and 'n', while "\n" is a one-character string containing a newline. Usually patterns will be expressed in Python code using this raw string notation.
It is important to note that most regular expression operations are available as module-level functions and RegexObject methods. The functions are shortcuts that don’t require you to compile a regex object first, but miss some fine-tuning parameters.
See also
A regular expression (or RE) specifies a set of strings that matches it; the functions in this module let you check if a particular string matches a given regular expression (or if a given regular expression matches a particular string, which comes down to the same thing).
Regular expressions can be concatenated to form new regular expressions; if A and B are both regular expressions, then AB is also a regular expression. In general, if a string p matches A and another string q matches B, the string pq will match AB. This holds unless A or B contain low precedence operations; boundary conditions between A and B; or have numbered group references. Thus, complex expressions can easily be constructed from simpler primitive expressions like the ones described here. For details of the theory and implementation of regular expressions, consult the Friedl book referenced above, or almost any textbook about compiler construction.
A brief explanation of the format of regular expressions follows. For further information and a gentler presentation, consult the Regular Expression HOWTO.
Regular expressions can contain both special and ordinary characters. Most ordinary characters, like 'A', 'a', or '0', are the simplest regular expressions; they simply match themselves. You can concatenate ordinary characters, so last matches the string 'last'. (In the rest of this section, we’ll write RE’s in this special style, usually without quotes, and strings to be matched 'in single quotes'.)
Some characters, like '|' or '(', are special. Special characters either stand for classes of ordinary characters, or affect how the regular expressions around them are interpreted. Regular expression pattern strings may not contain null bytes, but can specify the null byte using the \number notation, e.g., '\x00'.
The special characters are:
Either escapes special characters (permitting you to match characters like '*', '?', and so forth), or signals a special sequence; special sequences are discussed below.
If you’re not using a raw string to express the pattern, remember that Python also uses the backslash as an escape sequence in string literals; if the escape sequence isn’t recognized by Python’s parser, the backslash and subsequent character are included in the resulting string. However, if Python would recognize the resulting sequence, the backslash should be repeated twice. This is complicated and hard to understand, so it’s highly recommended that you use raw strings for all but the simplest expressions.
Used to indicate a set of characters. Characters can be listed individually, or a range of characters can be indicated by giving two characters and separating them by a '-'. Special characters are not active inside sets. For example, [akm$] will match any of the characters 'a', 'k', 'm', or '$'; [a-z] will match any lowercase letter, and [a-zA-Z0-9] matches any letter or digit. Character classes such as \w or \S (defined below) are also acceptable inside a range, although the characters they match depends on whether LOCALE or UNICODE mode is in force. If you want to include a ']' or a '-' inside a set, precede it with a backslash, or place it as the first character. The pattern []] will match ']', for example.
You can match the characters not within a range by complementing the set. This is indicated by including a '^' as the first character of the set; '^' elsewhere will simply match the '^' character. For example, [^5] will match any character except '5', and [^^] will match any character except '^'.
Note that inside [] the special forms and special characters lose their meanings and only the syntaxes described here are valid. For example, +, *, (, ), and so on are treated as literals inside [], and backreferences cannot be used inside [].
(One or more letters from the set 'i', 'L', 'm', 's', 'u', 'x'.) The group matches the empty string; the letters set the corresponding flags: re.I (ignore case), re.L (locale dependent), re.M (multi-line), re.S (dot matches all), re.U (Unicode dependent), and re.X (verbose), for the entire regular expression. (The flags are described in Module Contents.) This is useful if you wish to include the flags as part of the regular expression, instead of passing a flag argument to the re.compile() function.
Note that the (?x) flag changes how the expression is parsed. It should be used first in the expression string, or after one or more whitespace characters. If there are non-whitespace characters before the flag, the results are undefined.
Similar to regular parentheses, but the substring matched by the group is accessible within the rest of the regular expression via the symbolic group name name. Group names must be valid Python identifiers, and each group name must be defined only once within a regular expression. A symbolic group is also a numbered group, just as if the group were not named. So the group named id in the example below can also be referenced as the numbered group 1.
For example, if the pattern is (?P<id>[a-zA-Z_]\w*), the group can be referenced by its name in arguments to methods of match objects, such as m.group('id') or m.end('id'), and also by name in the regular expression itself (using (?P=id)) and replacement text given to .sub() (using \g<id>).
Matches if the current position in the string is preceded by a match for ... that ends at the current position. This is called a positive lookbehind assertion. (?<=abc)def will find a match in abcdef, since the lookbehind will back up 3 characters and check if the contained pattern matches. The contained pattern must only match strings of some fixed length, meaning that abc or a|b are allowed, but a* and a{3,4} are not. Note that patterns which start with positive lookbehind assertions will never match at the beginning of the string being searched; you will most likely want to use the search() function rather than the match() function:
>>> import re
>>> m = re.search('(?<=abc)def', 'abcdef')
>>> m.group(0)
'def'
This example looks for a word following a hyphen:
>>> m = re.search('(?<=-)\w+', 'spam-egg')
>>> m.group(0)
'egg'
Will try to match with yes-pattern if the group with given id or name exists, and with no-pattern if it doesn’t. no-pattern is optional and can be omitted. For example, (<)?(\w+@\w+(?:\.\w+)+)(?(1)>) is a poor email matching pattern, which will match with<EMAIL_ADDRESS>as well as<EMAIL_ADDRESS>but not with<EMAIL_ADDRESS>New in version 2.4.
The special sequences consist of '\' and a character from the list below. If the ordinary character is not on the list, then the resulting RE will match the second character. For example, \$ matches the character '$'.
Most of the standard escapes supported by Python string literals are also accepted by the regular expression parser:
\a \b \f \n
\r \t \v \x
\\
Octal escapes are included in a limited form: If the first digit is a 0, or if there are three octal digits, it is considered an octal escape. Otherwise, it is a group reference. As for string literals, octal escapes are always at most three digits in length.
Python offers two different primitive operations based on regular expressions: match checks for a match only at the beginning of the string, while search checks for a match anywhere in the string (this is what Perl does by default).
Note that match may differ from search even when using a regular expression beginning with '^': '^' matches only at the start of the string, or in MULTILINE mode also immediately following a newline. The “match” operation succeeds only if the pattern matches at the start of the string regardless of mode, or at the starting position given by the optional pos argument regardless of whether a newline precedes it.
>>> re.match("c", "abcdef") # No match
>>> re.search("c", "abcdef") # Match
<_sre.SRE_Match object at ...>
The module defines several functions, constants, and an exception. Some of the functions are simplified versions of the full featured methods for compiled regular expressions. Most non-trivial applications always use the compiled form.
Compile a regular expression pattern into a regular expression object, which can be used for matching using its match() and search() methods, described below.
The expression’s behaviour can be modified by specifying a flags value. Values can be any of the following variables, combined using bitwise OR (the | operator).
The sequence
prog = re.compile(pattern)
result = prog.match(string)
is equivalent to
result = re.match(pattern, string)
but using re.compile() and saving the resulting regular expression object for reuse is more efficient when the expression will be used several times in a single program.
Note
The compiled versions of the most recent patterns passed to re.match(), re.search() or re.compile() are cached, so programs that use only a few regular expressions at a time needn’t worry about compiling regular expressions.
Make \w, \W, \b, \B, \d, \D, \s and \S dependent on the Unicode character properties database.
New in version 2.0.
This flag allows you to write regular expressions that look nicer. Whitespace within the pattern is ignored, except when in a character class or preceded by an unescaped backslash, and, when a line contains a '#' neither in a character class or preceded by an unescaped backslash, all characters from the leftmost such '#' through the end of the line are ignored.
That means that the two following regular expression objects that match a decimal number are functionally equal:
a = re.compile(r"""\d + # the integral part
\. # the decimal point
\d * # some fractional digits""", re.X)
b = re.compile(r"\d+\.\d*")
If zero or more characters at the beginning of string match the regular expression pattern, return a corresponding MatchObject instance. Return None if the string does not match the pattern; note that this is different from a zero-length match.
Note
If you want to locate a match anywhere in string, use search() instead.
Split string by the occurrences of pattern. If capturing parentheses are used in pattern, then the text of all groups in the pattern are also returned as part of the resulting list. If maxsplit is nonzero, at most maxsplit splits occur, and the remainder of the string is returned as the final element of the list. (Incompatibility note: in the original Python 1.5 release, maxsplit was ignored. This has been fixed in later releases.)
>>> re.split('\W+', 'Words, words, words.')
['Words', 'words', 'words', '']
>>> re.split('(\W+)', 'Words, words, words.')
['Words', ', ', 'words', ', ', 'words', '.', '']
>>> re.split('\W+', 'Words, words, words.', 1)
['Words', 'words, words.']
>>> re.split('[a-f]+', '0a3B9', flags=re.IGNORECASE)
['0', '3', '9']
If there are capturing groups in the separator and it matches at the start of the string, the result will start with an empty string. The same holds for the end of the string:
>>> re.split('(\W+)', '...words, words...')
['', '...', 'words', ', ', 'words', '...', '']
That way, separator components are always found at the same relative indices within the result list (e.g., if there’s one capturing group in the separator, the 0th, the 2nd and so forth).
Note that split will never split a string on an empty pattern match. For example:
>>> re.split('x*', 'foo')
['foo']
>>> re.split("(?m)^$", "foo\n\nbar\n")
['foo\n\nbar\n']
Changed in version 2.7: Added the optional flags argument.
Return all non-overlapping matches of pattern in string, as a list of strings. The string is scanned left-to-right, and matches are returned in the order found. If one or more groups are present in the pattern, return a list of groups; this will be a list of tuples if the pattern has more than one group. Empty matches are included in the result unless they touch the beginning of another match.
New in version 1.5.2.
Changed in version 2.4: Added the optional flags argument.
Return an iterator yielding MatchObject instances over all non-overlapping matches for the RE pattern in string. The string is scanned left-to-right, and matches are returned in the order found. Empty matches are included in the result unless they touch the beginning of another match.
New in version 2.2.
Changed in version 2.4: Added the optional flags argument.
Return the string obtained by replacing the leftmost non-overlapping occurrences of pattern in string by the replacement repl. If the pattern isn’t found, string is returned unchanged. repl can be a string or a function; if it is a string, any backslash escapes in it are processed. That is, \n is converted to a single newline character, \r is converted to a linefeed, and so forth. Unknown escapes such as \j are left alone. Backreferences, such as \6, are replaced with the substring matched by group 6 in the pattern. For example:
>>> re.sub(r'def\s+([a-zA-Z_][a-zA-Z_0-9]*)\s*\(\s*\):',
... r'static PyObject*\npy_\1(void)\n{',
... 'def myfunc():')
'static PyObject*\npy_myfunc(void)\n{'
If repl is a function, it is called for every non-overlapping occurrence of pattern. The function takes a single match object argument, and returns the replacement string. For example:
>>> def dashrepl(matchobj):
... if matchobj.group(0) == '-': return ' '
... else: return '-'
>>> re.sub('-{1,2}', dashrepl, 'pro----gram-files')
'pro--gram files'
>>> re.sub(r'\sAND\s', ' & ', 'Baked Beans And Spam', flags=re.IGNORECASE)
'Baked Beans & Spam'
The pattern may be a string or an RE object.
The optional argument count is the maximum number of pattern occurrences to be replaced; count must be a non-negative integer. If omitted or zero, all occurrences will be replaced. Empty matches for the pattern are replaced only when not adjacent to a previous match, so sub('x*', '-', 'abc') returns '-a-b-c-'.
In addition to character escapes and backreferences as described above, \g<name> will use the substring matched by the group named name, as defined by the (?P<name>...) syntax. \g<number> uses the corresponding group number; \g<2> is therefore equivalent to \2, but isn’t ambiguous in a replacement such as \g<2>0. \20 would be interpreted as a reference to group 20, not a reference to group 2 followed by the literal character '0'. The backreference \g<0> substitutes in the entire substring matched by the RE.
Changed in version 2.7: Added the optional flags argument.
Perform the same operation as sub(), but return a tuple (new_string, number_of_subs_made).
Changed in version 2.7: Added the optional flags argument.
The RegexObject class supports the following methods and attributes:
Scan through string looking for a location where this regular expression produces a match, and return a corresponding MatchObject instance. Return None if no position in the string matches the pattern; note that this is different from finding a zero-length match at some point in the string.
The optional second parameter pos gives an index in the string where the search is to start; it defaults to 0. This is not completely equivalent to slicing the string; the '^' pattern character matches at the real beginning of the string and at positions just after a newline, but not necessarily at the index where the search is to start.
The optional parameter endpos limits how far the string will be searched; it will be as if the string is endpos characters long, so only the characters from pos to endpos - 1 will be searched for a match. If endpos is less than pos, no match will be found, otherwise, if rx is a compiled regular expression object, rx.search(string, 0, 50) is equivalent to rx.search(string[:50], 0).
>>> pattern = re.compile("d")
>>> pattern.search("dog") # Match at index 0
<_sre.SRE_Match object at ...>
>>> pattern.search("dog", 1) # No match; search doesn't include the "d"
If zero or more characters at the beginning of string match this regular expression, return a corresponding MatchObject instance. Return None if the string does not match the pattern; note that this is different from a zero-length match.
The optional pos and endpos parameters have the same meaning as for the search() method.
Note
If you want to locate a match anywhere in string, use search() instead.
>>> pattern = re.compile("o")
>>> pattern.match("dog") # No match as "o" is not at the start of "dog".
>>> pattern.match("dog", 1) # Match as "o" is the 2nd character of "dog".
<_sre.SRE_Match object at ...>
Match Objects always have a boolean value of True, so that you can test whether e.g. match() resulted in a match with a simple if statement. They support the following methods and attributes:
Returns one or more subgroups of the match. If there is a single argument, the result is a single string; if there are multiple arguments, the result is a tuple with one item per argument. Without arguments, group1 defaults to zero (the whole match is returned). If a groupN argument is zero, the corresponding return value is the entire matching string; if it is in the inclusive range [1..99], it is the string matching the corresponding parenthesized group. If a group number is negative or larger than the number of groups defined in the pattern, an IndexError exception is raised. If a group is contained in a part of the pattern that did not match, the corresponding result is None. If a group is contained in a part of the pattern that matched multiple times, the last match is returned.
>>> m = re.match(r"(\w+) (\w+)", "Isaac Newton, physicist")
>>> m.group(0) # The entire match
'Isaac Newton'
>>> m.group(1) # The first parenthesized subgroup.
'Isaac'
>>> m.group(2) # The second parenthesized subgroup.
'Newton'
>>> m.group(1, 2) # Multiple arguments give us a tuple.
('Isaac', 'Newton')
If the regular expression uses the (?P<name>...) syntax, the groupN arguments may also be strings identifying groups by their group name. If a string argument is not used as a group name in the pattern, an IndexError exception is raised.
A moderately complicated example:
>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.group('first_name')
'Malcolm'
>>> m.group('last_name')
'Reynolds'
Named groups can also be referred to by their index:
>>> m.group(1)
'Malcolm'
>>> m.group(2)
'Reynolds'
If a group matches multiple times, only the last match is accessible:
>>> m = re.match(r"(..)+", "a1b2c3") # Matches 3 times.
>>> m.group(1) # Returns only the last match.
'c3'
Return a tuple containing all the subgroups of the match, from 1 up to however many groups are in the pattern. The default argument is used for groups that did not participate in the match; it defaults to None. (Incompatibility note: in the original Python 1.5 release, if the tuple was one element long, a string would be returned instead. In later versions (from 1.5.1 on), a singleton tuple is returned in such cases.)
For example:
>>> m = re.match(r"(\d+)\.(\d+)", "24.1632")
>>> m.groups()
('24', '1632')
If we make the decimal place and everything after it optional, not all groups might participate in the match. These groups will default to None unless the default argument is given:
>>> m = re.match(r"(\d+)\.?(\d+)?", "24")
>>> m.groups() # Second group defaults to None.
('24', None)
>>> m.groups('0') # Now, the second group defaults to '0'.
('24', '0')
Return a dictionary containing all the named subgroups of the match, keyed by the subgroup name. The default argument is used for groups that did not participate in the match; it defaults to None. For example:
>>> m = re.match(r"(?P<first_name>\w+) (?P<last_name>\w+)", "Malcolm Reynolds")
>>> m.groupdict()
{'first_name': 'Malcolm', 'last_name': 'Reynolds'}
Return the indices of the start and end of the substring matched by group; group defaults to zero (meaning the whole matched substring). Return -1 if group exists but did not contribute to the match. For a match object m, and a group g that did contribute to the match, the substring matched by group g (equivalent to m.group(g)) is
m.string[m.start(g):m.end(g)]
Note that m.start(group) will equal m.end(group) if group matched a null string. For example, after m = re.search('b(c?)', 'cba'), m.start(0) is 1, m.end(0) is 2, m.start(1) and m.end(1) are both 2, and m.start(2) raises an IndexError exception.
An example that will remove remove_this from email addresses:
>>> email =<EMAIL_ADDRESS>>>> m = re.search("remove_this", email)
>>> email[:m.start()] + email[m.end():]
<EMAIL_ADDRESS>In this example, we’ll use the following helper function to display match objects a little more gracefully:
def displaymatch(match):
if match is None:
return None
return '<Match: %r, groups=%r>' % (match.group(), match.groups())
Suppose you are writing a poker program where a player’s hand is represented as a 5-character string with each character representing a card, “a” for ace, “k” for king, “q” for queen, j for jack, “0” for 10, and “1” through “9” representing the card with that value.
To see if a given string is a valid hand, one could do the following:
>>> valid = re.compile(r"[0-9akqj]{5}$")
>>> displaymatch(valid.match("ak05q")) # Valid.
"<Match: 'ak05q', groups=()>"
>>> displaymatch(valid.match("ak05e")) # Invalid.
>>> displaymatch(valid.match("ak0")) # Invalid.
>>> displaymatch(valid.match("727ak")) # Valid.
"<Match: '727ak', groups=()>"
That last hand, "727ak", contained a pair, or two of the same valued cards. To match this with a regular expression, one could use backreferences as such:
>>> pair = re.compile(r".*(.).*\1")
>>> displaymatch(pair.match("717ak")) # Pair of 7s.
"<Match: '717', groups=('7',)>"
>>> displaymatch(pair.match("718ak")) # No pairs.
>>> displaymatch(pair.match("354aa")) # Pair of aces.
"<Match: '354aa', groups=('a',)>"
To find out what card the pair consists of, one could use the group() method of MatchObject in the following manner:
>>> pair.match("717ak").group(1)
'7'
# Error because re.match() returns None, which doesn't have a group() method:
>>> pair.match("718ak").group(1)
Traceback (most recent call last):
File "<pyshell#23>", line 1, in <module>
re.match(r".*(.).*\1", "718ak").group(1)
AttributeError: 'NoneType' object has no attribute 'group'
>>> pair.match("354aa").group(1)
'a'
Python does not currently have an equivalent to scanf(). Regular expressions are generally more powerful, though also more verbose, than scanf() format strings. The table below offers some more-or-less equivalent mappings between scanf() format tokens and regular expressions.
| scanf() Token | Regular Expression |
|---|---|
| %c | . |
| %5c | .{5} |
| %d | [-+]?\d+ |
| %e, %E, %f, %g | [-+]?(\d+(\.\d*)?|\.\d+)([eE][-+]?\d+)? |
| %i | [-+]?(0[xX][\dA-Fa-f]+|0[0-7]*|\d+) |
| %o | 0[0-7]* |
| %s | \S+ |
| %u | \d+ |
| %x, %X | 0[xX][\dA-Fa-f]+ |
To extract the filename and numbers from a string like
/usr/sbin/sendmail - 0 errors, 4 warnings
you would use a scanf() format like
%s - %d errors, %d warnings
The equivalent regular expression would be
(\S+) - (\d+) errors, (\d+) warnings
If you create regular expressions that require the engine to perform a lot of recursion, you may encounter a RuntimeError exception with the message maximum recursion limit exceeded. For example,
>>> s = 'Begin ' + 1000*'a very long string ' + 'end'
>>> re.match('Begin (\w| )*? end', s).end()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
File "/usr/local/lib/python2.5/re.py", line 132, in match
return _compile(pattern, flags).match(string)
RuntimeError: maximum recursion limit exceeded
You can often restructure your regular expression to avoid recursion.
Starting with Python 2.3, simple uses of the *? pattern are special-cased to avoid recursion. Thus, the above regular expression can avoid recursion by being recast as Begin [a-zA-Z0-9_ ]*?end. As a further benefit, such regular expressions will run faster than their recursive equivalents.
In a nutshell, match() only attempts to match a pattern at the beginning of a string where search() will match a pattern anywhere in a string. For example:
>>> re.match("o", "dog") # No match as "o" is not the first letter of "dog".
>>> re.search("o", "dog") # Match as search() looks everywhere in the string.
<_sre.SRE_Match object at ...>
Note
The following applies only to regular expression objects like those created with re.compile("pattern"), not the primitives re.match(pattern, string) or re.search(pattern, string).
match() has an optional second parameter that gives an index in the string where the search is to start:
>>> pattern = re.compile("o")
>>> pattern.match("dog") # No match as "o" is not at the start of "dog."
# Equivalent to the above expression as 0 is the default starting index:
>>> pattern.match("dog", 0)
# Match as "o" is the 2nd character of "dog" (index 0 is the first):
>>> pattern.match("dog", 1)
<_sre.SRE_Match object at ...>
>>> pattern.match("dog", 2) # No match as "o" is not the 3rd character of "dog."
split() splits a string into a list delimited by the passed pattern. The method is invaluable for converting textual data into data structures that can be easily read and modified by Python as demonstrated in the following example that creates a phonebook.
First, here is the input. Normally it may come from a file, here we are using triple-quoted string syntax:
>>> input = """Ross McFluff:<PHONE_NUMBER> 155 Elm Street
...
... Ronald Heathmore:<PHONE_NUMBER> 436 Finley Avenue
... Frank Burger:<PHONE_NUMBER> 662 South Dogwood Way
...
...
... Heather Albrecht:<PHONE_NUMBER> 919 Park Place"""
The entries are separated by one or more newlines. Now we convert the string into a list with each nonempty line having its own entry:
>>> entries = re.split("\n+", input)
>>> entries
['Ross McFluff:<PHONE_NUMBER> 155 Elm Street',
'Ronald Heathmore:<PHONE_NUMBER> 436 Finley Avenue',
'Frank Burger:<PHONE_NUMBER> 662 South Dogwood Way',
'Heather Albrecht:<PHONE_NUMBER> 919 Park Place']
Finally, split each entry into a list with first name, last name, telephone number, and address. We use the maxsplit parameter of split() because the address has spaces, our splitting pattern, in it:
>>> [re.split(":? ", entry, 3) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155 Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436 Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662 South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919 Park Place']]
The :? pattern matches the colon after the last name, so that it does not occur in the result list. With a maxsplit of 4, we could separate the house number from the street name:
>>> [re.split(":? ", entry, 4) for entry in entries]
[['Ross', 'McFluff', '834.345.1254', '155', 'Elm Street'],
['Ronald', 'Heathmore', '892.345.3428', '436', 'Finley Avenue'],
['Frank', 'Burger', '925.541.7625', '662', 'South Dogwood Way'],
['Heather', 'Albrecht', '548.326.4584', '919', 'Park Place']]
sub() replaces every occurrence of a pattern with a string or the result of a function. This example demonstrates using sub() with a function to “munge” text, or randomize the order of all the characters in each word of a sentence except for the first and last characters:
>>> def repl(m):
... inner_word = list(m.group(2))
... random.shuffle(inner_word)
... return m.group(1) + "".join(inner_word) + m.group(3)
>>> text = "Professor Abdolmalek, please report your absences promptly."
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Poefsrosr Aealmlobdk, pslaee reorpt your abnseces plmrptoy.'
>>> re.sub(r"(\w)(\w+)(\w)", repl, text)
'Pofsroser Aodlambelk, plasee reoprt yuor asnebces potlmrpy.'
findall() matches all occurrences of a pattern, not just the first one as search() does. For example, if one was a writer and wanted to find all of the adverbs in some text, he or she might use findall() in the following manner:
>>> text = "He was carefully disguised but captured quickly by police."
>>> re.findall(r"\w+ly", text)
['carefully', 'quickly']
If one wants more information about all matches of a pattern than the matched text, finditer() is useful as it provides instances of MatchObject instead of strings. Continuing with the previous example, if one was a writer who wanted to find all of the adverbs and their positions in some text, he or she would use finditer() in the following manner:
>>> text = "He was carefully disguised but captured quickly by police."
>>> for m in re.finditer(r"\w+ly", text):
... print '%02d-%02d: %s' % (m.start(), m.end(), m.group(0))
07-16: carefully
40-47: quickly
Raw string notation (r"text") keeps regular expressions sane. Without it, every backslash ('\') in a regular expression would have to be prefixed with another one to escape it. For example, the two following lines of code are functionally identical:
>>> re.match(r"\W(.)\1\W", " ff ")
<_sre.SRE_Match object at ...>
>>> re.match("\\W(.)\\1\\W", " ff ")
<_sre.SRE_Match object at ...>
When one wants to match a literal backslash, it must be escaped in the regular expression. With raw string notation, this means r"\\". Without raw string notation, one must use "\\\\", making the following lines of code functionally identical:
>>> re.match(r"\\", r"\\")
<_sre.SRE_Match object at ...>
>>> re.match("\\\\", r"\\")
<_sre.SRE_Match object at ...>


Academics
I am a student in the Department of Physics, IIT Bombay pursuing a B.Tech in Engineering Physics. I have completed three semesters of my B.Tech and have a cumulative performance index of 9.58 out of 10 so far with a semester performance index of 9.76 out of 10 in my third semester. I have been a teaching assistant for the course PH 107 (Quantum physics and application) where I conducted weekly tutorial sessions for a class of 40 first year students and correct course quizzes and exams.
List of courses I have taken or am taking
Department of Physics, IIT Bombay
- PH 544 - General Theory of Relativity
- PH 233 - Electronics Lab II (Op amp circuits)
- PH 231 - Electronics Lab I (Basic circuits)
- PH 232 - Physics Laboratory I (General Physics Lab)
- PH 204 - Quantum Mechanics I
- PH 202 - Waves & Oscillations & Optics
- PH 567 - Non linear Dynamics
- PH 219 - Data Analysis and Interpretation
- PH 217 - Classical Mechanics
- PH 215 - Thermal Physics
- PH 207 - Introduction to Special Relativity
- PH 108 - Basics of Electricity & Magnetism
- PH 117 - Physics Lab
- PH 107 - Quantum Physics and Application
Department of Computer Science and Engineering, IIT Bombay
- CS 213 - Data Structures and Algorithms
- CS 228 - Logic in CS
- CS 101 - Computer Programming and Utilization
Department of Mathematics, IIT Bombay
- MA 214 - Introduction to Numerical Analysis
- MA 207 - Differential Equations 2
- MA 205 - Complex Analysis
- MA 106 - Linear Algebra
- MA 105 - Calculus
Department of Electrical Engineering, IIT Bombay
Department of Chemistry, IIT Bombay
Department of Mechanical Engineering, IIT Bombay
Department of Biosciences and Bioengineering, IIT Bombay
MOOCs
- Deeplearning Specialization of deeplearning.ai (Coursera)


Working and directing some of Australia’s leading salons.
With over 13 years of experience, she is widely known for her love of texture and versatility in styling. Her positive, easy to work with demeanour and hard work ethic has allowed her to become a highly sought after stylist in the Australian industry. Jemma has showcased her work locally and internationally, most notably with her affiliation with haircare brand, Oribe.
This style works best on hair that's shoulder length and longer, and works particularly well with hair that has a natural wave, however it's not essential.Make sure you tag us on Instagram if you give this style a go; we'd love to see your creations! Good luck!
read moreHi there! Welcome to our very first step-by-step styling tutorial. I hope I can help to inspire you to try out some different styles and ways to wear your hair.
There's really not that much to it, once
you see it broken down into steps! The textured bun is a great option for ‘special event’ hair when you want an up-style that doesn't look or feel too stiff or structured.
The casual texture balances out the prettiness of the style, making it look effortless and chic.
read moreSince being introduced to the brand in 2015, Lauren has worked on numerous fashion shows in 2015-16, was selected as member of the exclusive Chanel show team in 2016, has assisted international stylists such as Joey George and Kien Hoang and has trained with the International Oribe team.
Lauren has literally brought my hair back from the dead. I had no idea how bad the condition my hair truly was until Lauren saved it and brought it back to life. Now my hair is the longest and healthiest it's ever been.
Lauren is simply the best of the best.  They do not come any better than this.
As part of her love of sharing knowledge with others in the industry,
Lauren offers one-on-one styling training for hairstylists and make up artists
looking to expand their hairstyling skills.
Each styling day can be adapted to the stylists preference and level of ability,
and takes place at Edwards & Co in Melbourne (models provided).
Sample text. Lorem ipsum dolor sit amet, consectetur adipiscing elit nullam nunc justo sagittis suscipit ultrices.
Read Morecreated with
Website Builder Software .


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Add
Text data
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Business logic


Setting custom parameters
for your nesC/TinyOS build environment. If you are doing the tutorial with
a group of people, you probably want to use the DEFAULT_LOCAL_GROUP setting.
Lesson 1 introduces the major concepts required to program TinyOS applications.
These include a description of components, interfaces, commands, and events.
The TinyOS programming model is explained. The role of each of the different
file types is detailed.
The TinyOS platform provides primitives to obtain sensing data from tiny
networked devices. This lesson details how to build a simple sensing application
that records the light exposure on a photo diode.
The roles of both tasks and events are described. This lesson illustrates
the use of tasks to process data from the sense application in lesson 2
and events to receive the sensor data and pass it on to the background
running task.
Lesson 4 introduces basic abstraction to send integers via the RFM radio
stack. A counter application is built that sends the current value of the
counter over the RF radio.
In order to utilize the data from the tiny networked sensors, we must be
able to analyze it on the host computer. This lesson provides an example
application that graphs the light readings from the sensors over time.
It shows how to inject packets from a host environment.
This is used to drive a simple message-based command interpreter. A general
abstraction is used for sending arbitrary packets over the RFM radio stack.
A multihop broadcast application is built that floods the network with
a task to be performed.
The final lesson provides a fairly complete application for remote data
logging and collection. It also illustrates a simple multihop data propogation
method that allows data to be collected by a central location.
Several other tutorials are available for important subsystems:


Virtual Node Edit
Back
Delete
Fields marked with * are mandatory
Error detail here
Virtual Node Information
Node *
Management IPAddress
Specify an address that can be accessed by SNMP / TELNET / SSH etc.
Vendor Name
Node Type
Specify the Vendor Name. ex) VMWare
Specify the Node Type. ex) VMWare VM
OS Type
OS Version
SNMP Mode
SNMP v1
SNMP Community (RO)
Console Account
Console Password
Enter the account name for telnet / ssh login.
Enter the account password for telnet / ssh login.
Console Administrator Account
Console Administrator Password
Enter the account name for privileged mode transition.
enter the account password for privileged mode transition.
Console Type
TELNET
SSH
Purpose
Note
OK


Sign Up
Empowering low income earners through financial inclusion
Quick Credit is an online lending platform that provides short term loans to individuals
Get Loan


--- layout: slides title: 'Bringing XMPP to the browser' description: 'Bringing XMPP to the browser' theme: moon ---
XMPP is amazing federated, realtime, messaging system
Its mature, stable, and secure
XMPP uses XML so it can be extensible
Developers want to build realtime apps quickly & easily
Browsers are all about native JSON
Web developers have an aversion to XML
...its non-trivial to translate without losing extensibility
<message<EMAIL_ADDRESS>id="1"
<EMAIL_ADDRESS>type="chat">
<body>My kingdom for a JSON-based interface!</body>
</message>
{
to<EMAIL_ADDRESS>message: 'O, XML, XML! whereart art thou XML?'
}
<iq type="set" to="pubsub.example.com" id="1">
<pubsub xmlns="http://jabber.org/protocol/pubsub">
<publish node="blog">
<item>
<entry xmlns="http://www.w3.org/2005/Atom">
<content>I got tired typing this!</content>
<entry>
</item>
</publish>
</pubsub>
</iq>
{
to: 'pubsub.example.com',
node: 'blog',
content: {
atom: {
content: 'So much quicker and easier!'
}
}
}


| Class | Description |
|---|---|
| Benchmark |
Runs 10 iterations of 10-fold crossvalidation on the supplied arff file(s)
using weka.classifiers.trees.RandomForest, and FastRandomForest, and prints
accuracy, AUC (averaged over all classes) and computation time to stdout.
|
| DataCache |
Stores a dataset that in FastRandomTrees use for training.
|
| FastRandomForest |
Based on the "weka.classifiers.trees.RandomForest" class, revision 1.12,
by Richard Kirkby, with minor modifications:
- uses FastRfBagger with FastRandomTree, instead of Bagger with RandomTree. |
| FastRfUtils |
Utility functions for sorting float (single-precision) arrays, and for
normalizing double arrays.
|
| FRFAttributeEval |
Evaluate the merit of each attribute using a random forest.
|
| SplitCriteria |
Functions used for finding best splits in FastRfTree.
|
| VotesCollector |
Used to retrieve the out-of-bag vote of an ensemble classifier for a single
instance.
|
| VotesCollectorDataCache |
Used to retrieve the out-of-bag vote of an FastRandomForest classifier for a
single instance from a DataCache the forest was trained on.
|


ReadEZ 5.0 is a software application used to help the user read more efficiently. ReadEZ allows the user to copy in as much text as they want and listen to that text in different reading speeds and accents. ReadEZ also allows the user to click on any word to find the definition on dictionary.com.


@* * Copyright 2023 HM Revenue & Customs * * 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. *@ @this( govukWarningText: GovukWarningText ) @()(implicit messages: Messages)


|
|
|
|
|
DOCKET NUMBER |
PLAINTIFF TRIBE |
PAGE NUMBER |
|
304
|
The Ottawa Tribe and Guy Jennison, Bronson Edward and Gene Jennison, as representatives of the Ottawa Tribe
Opinion of the Commission
Findings of Fact
Interlocutory Order
|
1
10
20
|
|
236-H
|
Gila Riva Pima-Maricopa Indian Community, etc.
Order Dismissing Petition
|
21
|
|
316-A
|
The Kickapoo Tribe of Kansas, the Kickapoo Tribe of Oklahoma, et al.
Order Allowing Attorneys' Fee
|
22
|
|
73-A
|
The Seminole Indians of the State of Florida
Opinion of the Commission
Findings of Fact
Order
|
25
39
53
|
|
18-U
|
The Minnesota Chippewa Tribe, et al., on behalf of the Chippewas of Lake Superior
Opinion of the Commission
Additional Findings of Fact
Interlocutory Order
|
55
62
82
|
|
263
|
The Kikiallus Tribe
Opinion of the Commission
Findings of Fact
Interlocutory Order
|
83
88
98
|
|
186
|
The Confederated Tribes of the Colville Reservation as the representative of the Joseph Band of the Nez Perce Tribe • Charles E. Williams, Joseph Redthunder and Harry Owhi, as the representatives of the Joseph Band of the Nez Perce Tribe • The Confederated Tribes of the Colville Reservation, as successor to the claims of the Joseph Band of the Nez Perce Tribe
Opinion of the Commission
Findings of Fact
Interlocutory Order
|
99
128
144
|
|
18-T
|
Minnesota Chippewa Tribe, et al., on behalf of the Chippewa Indians of the Mississippi and Lake Superior
Opinion of the Commission
Additional Findings of Fact
Interlocutory Order
|
146
157
177
|
|
350-B, 350-C • 113 • 246 • (Cont'd) 350-B, 350-C, 113, 246 • 191 • 221 • 74 • 221-A
|
The Three Affiliated Tribes of the Fort Berthold Reservation • Turtle Mountain Band of Chippewa Indians • Red Lake Band and Peter Graves, et al., ex. rel. Red Lake Band, Pembina Band and Katherine Carl Barrett, et al., ex rel., Pembina Band, John B. Azure, et al., ex rel., Chief Little Shell's Band of Pembina Chippewa Indians • The Little Shell Band of Chippewa Indians, and Joseph H. Dussome, et al., ex. rel., said band • Chippewa Cree Tribe of the Rocky Boy's Reservation, Montana, and Joe Corcoran, ex. rel., Chippewa Cree Tribe of the Rocky Boy's Reservation, Blanche Patenaude, et al., ex. rel., Little Shell Band of Indians and the Chippewa Cree Tribe • The Sioux Nation, et al. • The Chippewa Cree Tribe of Rocky Boy's Reservation
Opinion of the Commission
Findings of Fact
Final Order Dismissing the Claim in Docket No. 350-B and Interlocutory Order in Docket No. 350-C
|
179
190
212
|
|
138
|
The Iowa Tribe of the Iowa Reservation in Kansas and Nebraska, the Iowa Tribe of the Iowa Reservation in Oklahoma, et al., Omaha Tribe of Nebraska, et al., the Sac and Fox Tribe of Indians of Oklahoma, the Sac and Fox Tribe of Missouri, the Sac and Fox Tribe of the Mississippi in Iowa, et al.
Order Allowing Reimbursement of Expenses of the Attorneys for the Sac and Fox Tribe of Indians of Oklahoma
|
215
|
|
143
|
The Sac and Fox Tribe of Indians of Oklahoma, the Sac and Fox Tribe of Missouri, Sac and Fox Tribe of the Mississippi in Iowa, et al.
Order Allowing Reimbursement of Expenses of the Attorneys for the Sac and Fox Tribe of Indians of Oklahoma
|
218
|
|
220
|
The Jicarilla Apache Tribe of the Jicarilla Apache Reservation, New Mexico
Order Allowing Reimbursement of Attorneys' Expenses
|
223
|
|
22-A
|
The Jicarilla Apache Tribe of the Jicarilla Apache Reservation, New Mexico
Additional Findings of Fact
Final Award
|
227
248
|
|
236-A, 236-B
|
Gila River Indian Community
Opinion of the Commission
Findings of Fact
|
250
260
|
|
236-A
|
Gila River Indian Community
First Interlocutory Order
|
278
|
|
236-B
|
Gila River Indian Community
First Interlocutory Order
|
279
|
|
300-A
|
The Stockbridge Munsee Community, the Stockbridge Tribe of Indians and the Munsee Tribe of Indians and the Munsee Tribe of Indians by Arvid E. Miller and Fred L. Robinson
Opinion of the Commission
Findings of Fact
Interlocutory Order
|
281
293
302
|
|
279-A
|
The Assiniboine Tribes of Indians
Order Allowing Reimbursement of Attorney's Expenses
|
303
|
|
236-I
|
Gila River Pima-Maricopa Indian Community, et al.
Opinion on Defendant's Motion for Preliminary Adjudication
Order Denying Motion for a Preliminary Adjudication
|
305
310
|
|
334-B
|
The Absentee Shawnee Tribe of Oklahoma (on behalf of the Shawnee Nation)
Opinion of the Commission
Findings of Fact on Compromise Settlement
Final Award
|
311
314
324
|
|
105, 106, 107, 108
|
The Osage Nation
Findings of Fact on Award of Attorneys' Fee
Order Allowing Attorneys' Fees
|
325
338
|
|
167
|
The Creek Nation
Additional Findings of Fact
Final Award
|
340
351
|
|
30-A, 48-A
|
The Fort Sill Apache Tribe of the State of Oklahoma, • The Chiricahua Apache Tribe, ex rel. Sam Haozous, Benedict Johze, James Kaywaykla, Robert Gooday, David Chinney, • The Warm Springs Apache Band, ex rel. Sam Haozous, Benedict Johze, Raymond John Loco • The Chiricahua Apache Band, ex rel. Robert Gooday, David Chinney, Casper Calio
Opinion of the Commission
Additional Findings of Fact
Interlocutory Order
|
352
364
380
|
|
30-A, 48-A, 30, 48, 182
|
The Fort Sill Apache Tribe of the State of Oklahoma • The Chiricahua Apache Tribe, ex rel. Sam Haozous, Benedict Johze, James Kaywaykla, Robert Gooday, David Chinney • The Warm Springs Apache Band, ex rel. Sam Haozous, Benedict Johze, Raymond John Loco • The Chiricahua Apache Band, ex rel. Robert Gooday, David Chinney, Casper Calio
Order Denying "Defendant's Motion to Consolidate the Cases Styled Fort Sill Apache, et al. v. United States, Docket Nos. 30-A, 48-A, 30, 48 and 182"
|
382
|
|
30, 48
|
The Fort Sill Apache Tribe of the State of Oklahoma • The Chiricahua Apache Tribe, ex rel. Sam Haozous, Benedict Johze, James Kaywaykla, Robert Gooday, David Chinney • The Warm Springs Apache Band, ex rel. Sam Haozous, Benedict Johze, Raymond John Loco • The Chiricahua Apache Band, ex rel. Robert Gooday, David Chinney, Casper Calio
Interlocutory Order
|
384
|
|
138
|
The Iowa Tribe of the Iowa Reservation in Kansas and Nebraska, the Iowa Tribe of the Iowa Reservation in Oklahoma, et al., Omaha Tribe of Nebraska, et al., the Sac and Fox Tribe of Indians of Oklahoma, the Sac and Fox Tribe of Missouri, the Sac and Fox Tribe of the Mississippi in Iowa, et al.
Order Allowing Reimbursement of Expenses of the Attorneys for the Sac and Fox Tribe of Missouri
|
386
|
|
143
|
The Sac and Fox Tribe of Indians of Oklahoma, the Sac and Fox Tribe of Missouri, Sac and Fox Tribe of the Mississippi in Iowa, et al.
Order Allowing Reimbursement of Expenses of the Attorneys for the Sac and Fox Tribe of Missouri
|
389
|
|
148
|
Cabazon Band of Mission Indians of California
Findings of Fact on Compromise Settlement
Final Award
|
392
405
|
|
195
|
The Sac and Fox Tribe of Missouri
Order Allowing Reimbursement of Attorneys' Expenses
|
406
|
|
295-A
|
The Mohave Tribe of Indians of Arizona, California, and Nevada
Opinion of the Commission
Order Denying Defendant's Motion for Rehearing
|
409
413
|
|
83
|
The Sac and Fox Tribe of Indians of Oklahoma, et al.
Opinion of the Commission
Additional Findings of Fact
Interlocutory Order
|
414
423
429
|
|
243, 244, 245
|
The Winnebago Tribe and Nation of Indians, the Winnebago Tribe of Nebraska and Frank Beaver, Moses Whitebear, John Little Wolf, James Smoke, and Joshua Sanford, ex rel. Winnebago Tribe and Nation and the Winnebago Indians of Wisconsin, Minnesota, Nebraska and the Winnebago Tribe of Nebraska
Findings of Fact on Award of Attorneys' Fees
Order Allowing Attorneys' Fees
|
431
440
|
|
218
|
Simon Plamondon, on relation of the Cowlitz Tribe of Indians
Opinion on Rehearing
Amendments to and Additional Findings of Fact
Order Amending Findings and Interlocutory Order
Order Admitting Exhibit
|
442
453
462
464
|
|
293
|
Swinomish Tribal Community
Opinion of the Commission
Findings of Fact
Order of Dismissal
|
465
468
474
|
|


Started my education at Orange Coast College where I took course work in Photography, some Fashion Design, and even Sailing before getting stuck in the work grind.
Ten years of experience working as a Handy Woman in commercial/ residential repairs, remodels, and installations.
Almost a year of experience as a Cable Technician with Spectrum(formally Time Warner Cable) climbing Telephone Poles for residential internet and cable installations.
Decided to make a career change and finished my Associates in Arts for transfer in Southern California.
Moved to the Bay Area to Continue my education at Cal State University East Bay.

- AA in Art History Santa Ana College
- BFA in Interactive Game Design CSUEB 2019


Massive.js is a data mapper for Node.js that goes all in on PostgreSQL and fully embraces the power and flexibility of the SQL language and relational metaphors. Providing minimal abstractions for the interfaces and tools you already use, its goal is to do just enough to make working with your data as easy and intuitive as possible, then get out of your way.
This project is maintained by dmfay
Hosted on GitHub Pages — Theme by orderedlist
npm install massive --save
Starting with version 3, Massive uses Promises exclusively. If you need a callback-based API, download version 2.x from the Releases page.
Examples are presented using the standard then()
construction for compatibility, but use of ES2017 async
and await
or a flow control library such as co to manage promises is highly recommended.
const express = require('express');
const http = require('http');
const massive = require('massive');
const app = express();
massive({
host: '<IP_ADDRESS>',
port: 5432,
database: 'appdb',
user: 'appuser',
password: 'apppwd'
}).then(instance => {
app.set('db', instance);
app.get('/', (req, res) => {
req.app.get('db').feed_items.find({
'rating >': 0
}, {
order: 'created_at desc'
}).then(items => {
res.json(items);
});
});
http.createServer(app).listen(3000);
});


#include <tracking_bound.h>
Public Member Functions | |
| virtual void | FromRos (const SR &res)=0 |
| virtual SR | ToRos () const =0 |
| virtual void | Visualize (const ros::Publisher &pub, const std::string &frame) const =0 |
| virtual | ~TrackingBound () |
Protected Member Functions | |
| TrackingBound () | |
Definition at line 56 of file tracking_bound.h.
|
inlinevirtual |
Definition at line 57 of file tracking_bound.h.
|
inlineexplicitprotected |
Definition at line 70 of file tracking_bound.h.
|
pure virtual |
Implemented in fastrack::bound::Box.
|
pure virtual |
Implemented in fastrack::bound::Box.
|
pure virtual |
Implemented in fastrack::bound::Box.


# Yhvr
Hi, I'm Yhvr. I've made some games, and other stuff.
The stuff more worth checking out is up top, while everything is on the bottom.
## Cool Stuff
Tree Game
undo2
## Other Stuff
undo
Mathcord (broken(?))
Cloaker (really old) (security vulnerability(?)
simpleformat.js (typo in title) (archived)
typewriter (RIP)
YouNicks (just repl) (bitburner clone)
Survival (yeah, that sucked)
homepage (old) (desktop only)
XMP (AD ripoff) (why?)
incremental (broken)


| JP GDP - Quarter on Quarter * | Actuals | ||||
| Release Date | For period | Expected | Previous | Released | Revision |
| 8-Sep-17 | Q1 17 2nd Pre | 0.7% | 1.0% | 0.6% | - |
| 15-Nov-17 | Q2 17 1st Pre | 0.4% | 0.6% | 0.3% | - |
| 8-Dec-17 | Q2 17 2nd Pre | 0.4% | 0.3% | 0.6% | - |
| 14-Feb-18 | Q3 17 1st Pre | - | 0.6% | - | - |
| * % change in GDP over previous quarter (not annualised) | |||||
| Copyright: Kshitij Consultancy Services |