class: center, middle, inverse, title-slide # Presenting monstR: ## Why R was vital to our response to COVID-19 ### Emma Vestesson
@gummifot
### 2020-08-25 --- ## About me Senior data analyst at the Health Foundation Part-time PhD student at UCL Great Ormond Street Institute of Child Health Organiser of R-ladies London `#rdogladies`  --- class: middle .pull-left[ ![](https://www.health.org.uk/themes/custom/health_foundation/assets/images/logo--default.png) ] .pull-right[ The Health Foundation is an independent charity committed to bringing about better health and health care for people in the UK. We connect what works on the ground with effective policymaking and vice versa. ] --- class: inverse, middle, center # Ensuring everyone’s health and care benefits from analytics and data-driven technology --- # .pull-left[  ] .pull-right[  ] --- ## Open analytics at the Health Foundation .pull-left[ ### Sharing our code  ] .pull-right[ ### Sharing our learning  ] --- ## How did COVID-19 change our ways of working? - Working remotely -- - Workload increased -- - Work became more reactive - often responding to data releases the same day -- - Outputs updated when new data became available -- - Aiming to inform policy - vital to be transparent -- Even more committed to being open but we need an open data pipeline to enable us to analyse data more quickly in a transparent and reproducible way. --- # Open data pipeline 1. download publicly available data 1. clean the data 1. create charts and tables
 --
 .pull-left[  ] .pull-right[  ] --- # Getting your hands on the data --
from Imgflip Meme Generator
 --- # Letting R do all the work You can download the data directly from the internet without leaving RStudio. `download.file()` from base R `curl_download()` from the `curl` package -- .pull-left[  ] .pull-right[ The link changes every time the data is updated ] --- # Scrape the link ```r link <- 'https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales' bow(link) page <- read_html(link) links <- page %>% html_nodes(css=".btn--thick") %>% html_attr('href') file_names <- fs::path_file(links) link_2020 <- links[stringr::str_detect(links, '2020.')] name_2020 <- links[stringr::str_detect(file_names, '2020.')] destfile_ONS <- here::here('data', 'original data', name_2020) curl_download(paste0('https://www.ons.gov.uk/', link_2020), destfile = destfile_ONS) ``` -- Depends on structure of website so requires time setting up ---  -- - `clean_names()` and `remove_empty()` functions from the `janitor` package -- - skiping rows when reading in data and dropping certain rows `filter(row_number()<14, row_number()>=3) ` (risky, what if data changes next week) -- - wrote unit tests using `testthat` package to warn us if data changes --- # Clean up our pipeline Working with Neale Swinnerton from [MastodonC](https://www.mastodonc.com/)  --- class: # The birth of monstR  --- # What is an API? **My pre-monstR understanding** : I have no idea but if there is one then I should use it. -- **Wikipedia definition** : An application programming interface (API) is a computing interface which defines interactions between multiple software intermediaries. -- **My definition** : A bunch of json files that will eventually give me a link. Let's have a look! https://api.beta.ons.gov.uk/v1/datasets --- class: inverse, middle #`monstR` makes navigating those files easier! --- # Main functions Only really 3 functions you need to worry about - `available_datasets()` - `available_editions()` - `available_versions()` --- ### Available data sets ```r datasets <- ons_available_datasets() ```

  id 	  title 	  description 	  unit_of_measure 	  next_release

  cpih01 	  Consumer Prices Index including owner occupiers' housing costs (CPIH) 	  CPIH is the most comprehensive measure of inflation. It extends CPI to include a measure of the costs associated with owning, maintaining and living in one's own home, known as owner occupiers' housing costs (OOH), along with council tax. This dataset provides CPIH time series (2005 to latest published month), allowing users to customise their own selection, view or download. 	  Index: 2015=100 	  16 September 2020

  mid-year-pop-est 	  Population Estimates for UK, England and Wales, Scotland and Northern Ireland 	  Estimates of the usual resident population for the UK as at 30 June of the reference year. Provided by administrative area, single year of age and sex. 	  Number of people 	  June 2021

  ashe-table-7-hours 	  Annual summary of hours worked, place of work by Local Authority 	  Estimates of paid hours worked for UK employees by gender and full/part-time working by work based Region to Local Authority level. 	  Hours per week 	  To be announced

  ashe-table-7-earnings 	  Annual summary of earnings, place of work by Local Authority 	  Estimates of weekly, hourly and annual earnings for UK employees by gender and full/part-time working by work based Region to Local Authority level. 	  £ 	  To be announced

  ashe-table-8-hours 	  Annual summary of hours worked, place of residence by Local Authority 	  Estimates of paid hours worked for UK employees by gender and full/part-time working by home based Region to Local Authority level. 	  Hours per week 	  To be announced

  ashe-table-8-earnings 	  Annual summary of earnings, place of residence by Local Authority 	  Estimates of weekly, hourly and annual earnings for UK employees by gender and full/part-time working by home based Region to Local Authority level. 	  £ 	  To be announced

  opss-rates 	  Occupational Pension Schemes Survey, Rates 	  The nature of occupational pension provision in the UK providing summary data on the rates of contributions paid 	  Millions of people 	  September 2019 (provisional)

  opss-membership 	  Occupational Pension Schemes Survey, Membership 	  The nature of occupational pension provision in the UK providing summary data on the membership of schemes 	  Millions of people 	  September 2019 (provisional)

  wellbeing-year-ending 	  Personal well-being estimates 	  Estimates of life satisfaction, worthwhile, happiness and anxiety in the UK for the years ending March 2012 to September 2018. 	  Estimates displayed are the percentage value with the exception of 'Average (mean)' where this is the average score out of 10. 	  To be announced

  wellbeing-local-authority 	  Personal well-being estimates by local authority 	  Estimates of life satisfaction, worthwhile, happiness and anxiety at the UK, country and local authority level. 	  NA 	  TBC

  trade 	  UK trade: country by commodity 	  Country by commodity data on the UK's trade in goods, including trade by all countries and selected commodities, exports and imports, non seasonally adjusted. 	  £ 	  11 September 2020

  life-expectancy-local-authority 	  Health state life expectancy at birth and at age 65 by local areas, UK 	  Life expectancy, healthy life expectancy and disability-free life expectancy – at birth and age 65 by sex for local areas in the UK, from 2013-2015 to 2015-2017. 	  NA 	  December 2019

  suicides-in-the-uk 	  Suicide registrations in England and Wales by local authority 	  Number of suicides by local authority in England and Wales, registered from 2002. 	  NA 	  To be announced

  ashe-tables-7-and-8 	  Earnings and hours worked, place of work and residence by local authority: ASHE Tables 7 and 8 	  Allows you to produce customisable time series of XLS and CSV tables for key variables and measures from Annual Survey of Hours and Earnings (ASHE) Tables 7 & 8 down to local authority level. 	  NA 	  To be announced

  index-private-housing-rental-prices 	  Index of Private Housing Rental Prices 	  An experimental price index tracking the prices paid for renting property from private landlords in the United Kingdom 	  NA 	  16 September 2020

  ashe-tables-9-and-10 	  Earnings and hours worked, place of work and place of residence by Parliamentary constituency: ASHE Tables 9 and 10 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by home and work-based Parliamentary constituency 	  NA 	  To be announced

  ashe-tables-11-and-12 	  Earnings and Hours Worked, Work and Residence-Based Travel to Work Area: ASHE Tables 11 and 12 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by home-based and work-based travel to work area. 	  NA 	  To be announced

  ashe-table-5 	  Earnings and Hours Worked, UK Region by Industry by Two-Digit SIC: ASHE Table 5 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by region, and public and private sector, and non-profit bodies and mutual associations 	  NA 	  To be announced

  labour-market 	  UK labour market 	  The LFS is a data source compiled from a survey of the UK population. It uses internationally recognised definitions of employment, unemployment and economic activity. It also captures other personal characteristics of household members over the age of 16 such as occupation, education and training. The LFS reflects only a sample of the total population. All cases are therefore weighted on the basis of sub-national population totals by age and sex to give estimates for the entire UK household population. 	  NA 	  15 September 2020

  regional-gdp-by-quarter 	  Quarterly GDP for England, Wales and the English regions 	  Quarterly economic activity within England, Wales and the nine English regions (North East, North West, Yorkshire and The Humber, East Midlands, West Midlands, East of England, London, South East, South West). 	  NA 	  October 2020

  regional-gdp-by-year 	  Annual GDP for England, Wales and the English regions 	  Annual economic activity within England, Wales and the nine English regions (North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East of England, Greater London, South East, South West). 	  NA 	  To be announced

  childrens-wellbeing 	  Children's Well-being Measures 	  How children aged 0 to 15 years in the UK are coping in a range of areas that matter to their quality of life, reflecting the circumstances of their lives and their own perspectives. This is a subset of the children's well-being indicators. For the full dataset, please see 'Children's well-being and social relationships, UK: 2018' in the 'Related datasets' section. 	  NA 	  To be announced

  generational-income 	  Generational income: The effects of taxes and benefits 	  The effects of direct and indirect taxation and benefits received in cash or kind on household income, across the generations and by age. This data is estimated by combining multiple years of the Living Costs and Food Survey, from 1978 to financial year ending March 2019, with the exception of 1979, 1981 and 1984. All financial amounts are adjusted for inflation using the Consumer Prices Index including owner occupiers’ housing costs (CPIH) excluding Council Tax, to their financial year ending March 2018. For example, the mean disposable income for those aged 35 and born in the 1970’s (£34,930) is estimated by taking the average (in real terms) of the household disposable income for these people across the combined dataset. 	  £ (Mean average amount) 	  To be announced

  ashe-tables-26 	  Earnings and hours worked, care workers: ASHE Table 26 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, for care workers, home carers and senior care workers as defined in the Standard Occupational Classification. 	  NA 	  To be announced

  ashe-tables-25 	  Earnings and hours worked, UK region by public and private sector: ASHE Table 25 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by region, and public and private sector, and non-profit bodies and mutual associations. 	  NA 	  To be announced

  ashe-tables-3 	  Earnings and hours worked, region by occupation by two-digit SOC: ASHE Table 3 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by region and two-digit Standard Occupational Classification 2010. 	  NA 	  To be announced

  ashe-tables-20 	  Earnings and hours worked, age group by occupation by two-digit SOC: ASHE Table 20 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by age group and two-digit Standard Occupational Classification 2010. 	  NA 	  To be announced

  ashe-tables-27-and-28 	  Earnings and hours worked, place of work and place of residence by local enterprise partnerships: ASHE Tables 27 and 28 	  Annual estimates of paid hours worked and earnings for UK employees by sex, and full-time and part-time, by work-based and home-based local enterprise partnerships. 	  NA 	  To be announced

  wellbeing-quarterly 	  Quarterly personal well-being estimates 	  Seasonally adjusted quarterly estimates of life satisfaction, worthwhile, happiness and anxiety in the UK. 	  NA 	  TBD

  ageing-population-estimates 	  Local authority ageing statistics, based on annual mid-year population estimates 	  Indicators included have been derived from the published 2019 mid-year population estimates for the UK, England, Wales, Scotland and Northern Ireland. These are the number of persons and percentage of the population aged 65 years and over, 85 years and over, 0 to 15 years, 16 to 64 years, 16 years to State Pension age, State Pension age and over, median age and the Old Age Dependency Ratio (the number of people of State Pension age per 1000 of those aged 16 years to below State Pension age). This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which will be published in July 2020. The tool will enable users to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. 	  NA 	  June 2021

  older-people-sex-ratios 	  Local authority ageing statistics, sex ratios for people aged 65 and over and 85 and over 	  Both indicators included have been derived from the published 2019 mid-year population estimates for the UK, England, Wales, Scotland and Northern Ireland.  A sex ratio shows the number of males in the population for every 100 females. This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which will be published in July 2020. The tool will enable users to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. 	  NA 	  June 2021

  older-people-net-internal-migration 	  Local authority ageing statistics, net internal migration people aged 65 and over and 85 and over 	  Figures presented show the movement of older people between local authorities and regions. Both indicators included in this dataset have been derived from the published 2019 internal migration dataset for England and Wales. The numbers presented are the net number of people aged 65 years and over and 85 years and over entering/ leaving the local authority or region in the 12-month period stated. This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which will be published in July 2020. The tool will be interactive, and users will be able to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. 	  NA 	  June 2021

  older-people-economic-activity 	  Local authority ageing statistics, older people economic activity 	  Indicators included are economic activity and employment rates for those aged 50-64 years, by country, region and local authority. Both economic activity and employment rates are displayed as percentages. These have been calculated from the ONS Annual Population Survey and have been extracted from NOMIS. https://www.nomisweb.co.uk/ This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which will be published in July 2020. The tool will be interactive, and users will be able to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. Note on update frequency: NOMIS provide quarterly updates on both indicators. For consistency with other indicators presented in the subnational ageing tool, these will be updated on an annual basis. 	  NA 	  June 2021

  health-accounts 	  Expenditure on healthcare: UK Health Accounts 	  Healthcare expenditure statistics, produced to the international definitions of the System of Health Accounts 2011. Subcategories may not sum to aggregates due to rounding. 	  NA 	  To be announced

  weekly-deaths-age-sex 	  Deaths registered weekly in England and Wales by age and sex 	  Provisional counts of the number of deaths registered in England and Wales, by age and sex, in the latest weeks for which data are available. 	  NA 	  2 September 2020

  weekly-deaths-region 	  Deaths registered weekly in England and Wales by region 	  Provisional counts of the number of deaths registered in England and Wales, by region, in the latest weeks for which data are available. 	  NA 	  2 September 2020

  weekly-deaths-health-board 	  Death registrations and occurrences by health board and place of death 	  Provisional counts of the number of deaths registered in Wales, by health board and place of death, in the latest weeks for which data are available. 	  NA 	  1 September 2020

  weekly-deaths-local-authority 	  Death registrations and occurrences by local authority and place of death 	  Provisional counts of the number of deaths registered in England and Wales, including deaths involving the coronavirus (COVID-19), by local authority, health board and place of death in the latest weeks for which data are available. 	  NA 	  1 September 2020

  house-prices-local-authority 	  House price statistics for small areas in England and Wales 	  Summary statistics for housing transactions by local authority in England and Wales, on an annual basis, updated quarterly using HM Land Registry Price Paid Data. Select values from the Year and Month dimensions for data for a 12-month period ending that month and year (e.g. selecting June and 2018 will return the twelve months to June 2018). 	  NA 	  TBA

  ageing-population-projections 	  Local authority ageing statistics, population projections for older people 	  Projected indicators included are derived from the published 2018-based subnational population projections for England, Wales, Scotland and Northern Ireland up to the year 2043. The indicators are the projected percentage of the population aged 65 years and over, 85 years and over, 0 to 15 years, 16 to 64 years, 16 years to State Pension age, State Pension age and over, median age and the Old Age Dependency Ratio (the number of people of State Pension age per 1000 of those aged 16 years to below State Pension age). This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. Note on data sources: England, Wales, Scotland and Northern Ireland independently publish subnational population projections and the data available here are a compilation of these datasets. The ONS publish national level data for the UK, England, Wales and England & Wales, which has been included. National level data for Scotland and Northern Ireland have been taken from their subnational population projections datasets. 	  NA 	  To be announced

  projections-older-people-sex-ratios 	  Local authority ageing statistics, projected sex ratios for older people 	  Projected indicators included are derived from the published 2018-based subnational population projections for England, Wales, Scotland and Northern Ireland up to the year 2043.  A sex ratio shows the number of males in the population for every 100 females. This dataset has been produced by the Ageing Analysis Team for inclusion in the subnational ageing tool, which was published on July 20, 2020 (see link in Related datasets). The tool is interactive, and users can compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. Note on data sources: England, Wales, Scotland and Northern Ireland independently publish subnational population projections and the data available here are a compilation of these datasets. The ONS publish national level data for the UK, England, Wales and England & Wales, which has been included. National level data for Scotland and Northern Ireland have been taken from their subnational population projections datasets. 	  NA 	  To be announced

  faster-indicators-shipping-data 	  Coronavirus and the latest indicators for the UK economy and society: Shipping indicators 	  These shipping indicators are based on counts of all vessels, and cargo and tanker vessels. As discussed in Faster indicators of UK economic activity: shipping (please see the related links), we expect the shipping indicators to be related to the import and export of goods. 	  NA 	  27 August 2020

  projections-older-people-in-single-households 	  Local authority ageing statistics, household projections for older people 	  Projected indicators included are derived from the published 2018-based household projections for England for the years 2018 up to 2043. The indicators are the percentage of one-person households, in which the householder is aged 65 years and over and the percentage of one-person households, in which the householder is aged 85 years and over. This dataset has been produced by the Ageing Analysis Team for inclusion in a subnational ageing tool, which will be published in July 2020. The tool will be interactive, and users will be able to compare latest and projected measures of ageing for up to four different areas through selection on a map or from a drop-down menu. Note on data availability: England, Wales, Scotland and Northern Ireland independently publish subnational household projections. Each country publishes a different set of age breakdowns and only England provide the breakdowns required to calculate the indicators included above. 	  NA 	  To be announced

  tax-benefits-statistics 	  Effects of Taxes and Benefits on Household Income 	  Estimates of mean and median annual incomes in the UK, by quintile groups. The redistribution effects on individuals of direct and indirect taxation and benefits received in cash or kind. 	  NA 	  TBA

  online-job-advert-estimates 	  Faster Indicators - Online Job Advert Estimates 	  Experimental job advert indices covering the UK job market. 	  NA 	  27 August 2020

  gdp-4-dp 	  GDP monthly estimate (incoporating the Index of Services and Index of Production) 	  Gross domestic product (GDP) measures the value of goods and services produced in the UK. It estimates the size of and growth in the economy. This dataset also contains the Index of Services (monthly movements in output for the services industries) and the Index of Production (movements in the volume of production for the UK production industries: manufacturing, mining and quarrying, energy supply, and water and waste management). Figures are seasonally adjusted. 	  Index. Seasonally adjusted 2016=100 	  11 September 2020

 --- ### Available editions ```r ons_available_editions(id="weekly-deaths-region") ``` ``` ## edition ## 1 2010-19 ## 2 covid-19 ``` --- ### Available versions ```r ons_available_versions(id="weekly-deaths-region", edition='covid-19') ``` ``` ## version ## 1 1 ## 2 2 ## 3 3 ## 4 4 ## 5 5 ## 6 6 ## 7 7 ## 8 8 ## 9 9 ## 10 10 ## 11 11 ## 12 12 ## 13 13 ## 14 14 ## 15 15 ## 16 16 ## 17 17 ## 18 18 ``` --- # Full pipeline - set-up ```r *monstr_pipeline_defaults() %>% * ons_datasets_setup() %>% *ons_dataset_by_id("weekly-deaths-region") %>% ons_download(format="csv") %>% monstr_read_file() %>% monstr_clean() %>% monstr_write_clean(format="all") ``` --- # Full pipeline - download ```r monstr_pipeline_defaults() %>% ons_datasets_setup() %>% ons_dataset_by_id("weekly-deaths-region") %>% *ons_download(format="csv") %>% monstr_read_file() %>% monstr_clean() %>% monstr_write_clean(format="all") ``` --- # Full pipeline - cleaning ```r monstr_pipeline_defaults() %>% ons_datasets_setup() %>% ons_dataset_by_id("weekly-deaths-region") %>% ons_download(format="csv") %>% *monstr_read_file() %>% *monstr_clean() %>% *monstr_write_clean(format="all") ``` --- # What did we learn building our first package? - `usethis` package makes package building easy - `packagedown`package makes it incredibly easy to set up a website! - github actions let's you automate the boring bits (and you get badges for your readme!) --- # What's next - improve documentation -- - add units tests -- - work with the ONS team -- - build into our data pipeline --- ## Please try monstR - download the package - let's us know what works and what doesn't - suggest new features https://github.com/HFAnalyticsLab/monstR  --- class: middle # Thanks! All of contributors can be found on our github page - Neale Swinnerton - wrote most of the code - Fiona Grimm - designed the logo - Richard Brine - came up with the name


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The latest summary can always be found at
data.openaddresses.io.
A plain text version of data on this page can be found at
state.txt.
| Name | Type | Cached? | Processed? | Problems | |
|---|---|---|---|---|---|
| {{ state.shortname }} | {{ state.type }} |
{% if state.cache %}
{{ state.cache_date }}
{% elif state.cache_date %}
|
{% if state.processed %} csv {% else %} – {% endif %} | {% set suggest_conform = False %} {% if not state.processed %} {% if state.skip %} source says to skip {% elif not state.cache %} cache failed ( log ) {% elif not state.conform %} source is missing conform {% set suggest_conform = True %} {% else %} unknown ( log ) {% endif %} {% elif not state['coverage complete'] %} source has incomplete coverage {% endif %} | {% if state.sample and state.sample_data %} {% else %} No sample data ( log ) {% endif %} |


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I have been attending a lot of meetups. I don't find enough time to make a simple note on the experience, so as to come back and pick those information later. Here is an attempt to do the same. The meetup was conducted by CentOS India Meetup.com group.
The meetup was organized at Kerala Startup Mission, Kinfa, Near Medical College, HMT, Kalamassery. It was consisting of two workshops related to OpenShift and Ansible. The experience of the Meetup was awesome. I really enjoyed most out of it.
Pre-requisites installation
I downloaded centos minimal iso from here https://www.centos.org/download/.
# Downloaded latest minimal iso from centos website (From Debian 9 Host)
sudo apt install aria2
aria2c -x2 http://centos.mirror.snu.edu.in/centos/7.5.1804/isos/x86_64/CentOS-7-x86_64-Minimal-1804.iso http://centos.mirror.snu.edu.in/centos/
7.5.1804/isos/x86_64/CentOS-7-x86_64-Minimal-1804.iso
Later I installed it in VirtualBox.
First issue I faced was something related to internet. By default, CentOS Guest was not connecting to internet.
# this command was ended in error
# sudo yum update
# So I had to do this after every boot of the Guest VM
sudo dhclient
# re run previous failed command
sudo yum update
Following command was really useful.
yum search podman
Then I had to add epel repository (Now, I'm not sure, it's needed or not :-p )
sudo yum --enablerepo=extras install epel-release
Installing packages
sudo yum install ansible podman buildah skopeo
Here is a really useful link I found https://www.server-world.info/en/note?os=CentOS_7&p=podman&f=1.
As you have noticed, I have skipped installing docker in the GuestVM. Instead, I installed docker in my Debian 9 Host. Here is a short description of the same.
sudo apt-get update
sudo apt-get install -y apt-transport-https ca-certificates wget software-properties-common
wget https://download.docker.com/linux/debian/gpg
sudo apt-key add gpg
echo "deb [arch=amd64] https://download.docker.com/linux/debian $(lsb_release -cs) stable" | sudo tee -a /etc/apt/sources.list.d/docker.list
sudo apt-get update
sudo apt-get -y install docker-ce
sudo systemctl start docker
Here is the link I followed, https://www.itzgeek.com/how-tos/linux/debian/how-to-install-docker-on-debian-9.html [Note:- It's always better to read about commands your running before copy-paste].
Later I learned that, I didn't wanted to install both docker and podman together.
Meetup Resources
https://learn.openshift.com/playgrounds/openshift39/
https://learn.openshift.com/subsystems/container-internals-lab-1/
https://docs.google.com/document/d/1FeQ55sVEhechOqwIHPyivsOUyajtYR8ECMT-qh7b-90/edit
https://docs.google.com/document/d/1x06QEfe1b9SRofRr1cVNg7MDtffBuhTx2WXmxO5FLzk/edit?usp=sharing


{{ nodeParams | json }}
LuigiClient hasBack/GoBack:
Modify goBackContext value, that you receive then via LuigiClient.addContextUpdateListener():
Click here to go back to your preserved view.


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TuteOne Plus Two Mathematics
Decide which system you use Android/ Windows
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Relations and Functions
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERInverse Trigonometric Functions
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERMatrices
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERDeterminants
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERContinuity and Differentiability
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERApplications of Derivatives
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERIntegrals
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERApplications of the Integrals
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERDifferential Equations
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERVectors
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERThree-dimensional Geometry
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERLinear Programming
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERProbability
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERRelations and Functions
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERInverse Trigonometric Functions
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERMatrices
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERDeterminants
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERContinuity and Differentiability
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERApplications of Derivatives
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERIntegrals
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERApplications of the Integrals
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERDifferential Equations
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERVectors
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERThree-dimensional Geometry
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERLinear Programming
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERProbability
REGULAR CLASS NOTES REVISION CLASS I WANT THIS CHAPTERTuteone Learning Management System (LMS) is virtual campus where you get access your assignments, exams, clarify your doubt, track your progress etc.
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Subject GCC 10.1.0 kernel issue
From Dylan Araps<EMAIL_ADDRESS>Date Wed, 9 May 2020 01:05:09 +0100
The kernel compiled with GCC 10.1.0 may crash on boot. This doesn't
seem to affect every system. I have thus far received a single report
by an affected user.
Attached below is a patch which has been reported to fix the issue.
This fix has not yet made it into a kernel release (let alone Linus'
tree).
I recommend applying the patch if compiling a kernel with GCC 10.1.0.
An additional note will be added to the installation guide for the
benefit of new users.
Patch: f670269a42bfdd2c83a1118cc3d1b475547eac22
Commit: git.kernel.org
UPDATE (May 19 2020):
Kernel versions 5.6.14 (latest stable) and 5.4.42 (latest LTS)
contain fixes for GCC 10 and no patch is needed.
UPDATE:
Another alternative is to simply disable the stack protector in your
kernel configuration. This will also fix the kernel crashing during
the boot up process.
CONFIG_STACKPROTECTOR=n
CONFIG_STACKPROTECTOR_STRONG=n
Dylan
---
Notes:
- Reported to apply cleanly to kernel version 5.6.11.
- Hop on IRC, Reddit or send me an email<EMAIL_ADDRESS>if you
require any assistance. I'm here to help.
________________________________________________________________________________
Dylan Araps (C) 2019-2020
kiss-community (C) 2020-2021
Dilyn Corner (C) 2021
Linux(R) is the registered trademark of Linus Torvalds in the U.S. and
other countries.


Unai Emery opens up Arsenal board's attitude towards him after Southampton draw
Alexandre Lacazette scored a last-gasp leveller to rescue a share of the spoils but Arsrenal's winless run extended to five games to turn up the heat on Unai Emery
by Mark Mann-BryansArsenal head coach Unai Emery admits it is up to him to get more out of his players after a stoppage-time Alexandre Lacazette goal salvaged a draw at home to struggling Southampton .
The Gunners looked on course for a damaging defeat when James Ward-Prowse finished from close range after seeing his penalty saved by Bernd Leno - only for Lacazette to stab home deep into added time to secure a 2-2 draw.
Southampton had already held the lead through Danny Ings before Lacazette levelled in the first half, the Frenchman's double his first goals for the club since September 1.
Although they battled back to earn a share of the spoils, it did little to appease the supporters who have now seen their side win just two of their last 11 Premier League games.
Saints should have been out of sight after creating more chances as Arsenal went in search of their late equaliser, substitute Moussa Djenepo seeing a shot cleared off the line before missing another fine opportunity.
Emery was publicly backed by the Arsenal hierarchy at the start of the international break but the pressure will continue to grow following another frustrating 90 minutes, after which he conceded the challenge to improve lies with him.
"The club are supporting me every day and also I have a responsibility," he said.
"I know I can do better, I can take more performances with the players and I'm going to try to do that. Now my job is to analyse, to try to move on with confidence with the players.
"It's difficult but we need to move on in the next days. After analysing that match we are going to play at home again on Thursday, prepare as well as possible.
"We know, and I know, that we need to connect with our supporters."
Lacazette hardly celebrated a late goal which would usually be greeted with jubilation by a team rescuing a result at the death.
But Emery said the subdued reaction only proves that the players knew that a share of the spoils was still not good enough.
"That's an example of how they felt," he added. "They felt the point was not enough. Our performance, individually and collectively, was about achieving the victory.
"
We are frustrated and we understand the supporters as well. We lost an opportunity to connect with our supporters because they helped us.
"We drew at the last moment but it's not enough. Really, we can be disappointed and the fans also, and me, with the result."
While Emery professed his disappointment at taking a point, Southampton boss Ralph Hasenhuttl felt the visitors did enough to leave with all three.
Saints remain without a Premier League win since September 14 after conceding so late, but Hasenhuttl was pleased with the display.
"You are thinking we can win this game with three, four or five goals but we didn't," he said.
"After the 70th minute only we played. We tried to score, we tried to create chances. It was a fantastic performance.
"They didn't have so many chances in the last 20 minutes. We had much more. In that moment you must win the game."


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Orange is a powerful antioxidant due to the large amount of Vitamin C, which is why it favors healing and strengthens the body's immune system. It also contains calcium, magnesium, beta carotene, folic acid, phosphorus, potassium, copper, zinc, malic, oxalic, tartaric, and citric acids.
Variety:
The frequently consume of this fruit helps to reduce high blood pressure. It is rich in vitamins A, B1, B2, B3 C and K and minerals, which has numerous health benefits.
Variety:
The Lemon is a real nutritional treasure and greatly beneficial for our health. It is a curative fruit par excellence because it provides vitamins, eliminates toxins and is a powerful bactericide.
Variety:
The variety that occupies the most surface in Chile is Hass. Addition it is the only variety that is exported. This variety has proven to be a good producer and has high internal quality fruit, it is not as old as other varieties
Availability tableThe range of the size fruit is between 70 and 120 gr. It has an orange color and thin and semi-smooth skin, so it is easy to peel and separate the slices.
Availability tableKiwis is known because of its high concentration of vitamin C. In addition of being a powerful antioxidant, mineral and low in calories.
Variety:
It is considered a diuretic fruit bacause of its high concentration of potasium. Also helps to controlling blood pressure and may reduce the risk of a heart attack.
Variety:
Are very appreciated for its nutritional properties. Because its high % of water, they are very digestive. Also recommended in low caloric diet and rich in vitamins B1,B2 and Niacin or B3 are included as well as vitamins A and C which are rich in minerals such as calcium and potassium, among others.
Variety:
Cherries have excellent antioxidant properties with a great nutritional contribution, since are rich in vitamin A, C and E and potassium, magnesium making. This fruit a highly attractive product for the consumer.
Variety:
Blueberries are extremely popular all around the Word, because for their organoleptic properties as well as for their high nutritional value and health properties. One main is the high content of antioxidant, vitamin C and low in calories. The Chilean blueberry is characterized by its firmness, size, and extraordinary flavor.
Variety:


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Welcome to Mountlake Terrace High School’s TSA! Here, we strive for student success and full financial coverage for our committed TSA members. We meet every Thursday for up to two hours, where students work together to finish TSA projects and events. We are a young chapter that specializes in engineering and writing events. What makes our TSA stand out from others? At the MTHS TSA, we believe that leadership and fundraising are of utmost importance: Students are given a multitude of opportunities to participate in STEM outreach events, as well as TSA fundraisers for our school. Students work to design, produce, and sell various items, where all of the proceeds go towards TSA students who are in need of financial aid. Here, we believe that students should never have to pay a dime to compete!


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Gain |
|
Frequency |
|
Q (bandwidth) |
Input -> EQ parameters
Output -> EQ parameters
Latent space
Select a point
Each point decodes to EQ config
The encoder becomes probabilistic and generates μ and σ
centers latent codes around origin
similar samples placed together
dense population of latent space
The beta term weighs the KL loss against the reconstruction loss
Larger beta means greater disentanglement
VAE architecture
Fast inference time for seamless real-time use
Straightforward matrix operations in MATLAB code
Low data dimensionality doesn't require large network
Twelve different models with different latent sizes and values of β
We use Keras and save the model weights for each model as HDF5
Adam optimizer with learning rate of 0.001
Each model is trained for 200 epochs
Entire training process takes about 2 hours on CPU
| Model | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Latent | 1D | 1D | 1D | 1D | 2D | 2D | 2D | 2D | 3D | 3D | 3D | 3D |
| β | 0.000 | 0.001 | 0.01 | 0.02 | 0.000 | 0.001 | 0.01 | 0.02 | 0.000 | 0.001 | 0.01 | 0.02 |
β = 0.000
β = 0.001
β = 0.010
β = 0.020
Features an extremely simple interface


Mathematicians invented several kinds of formal logic, which are used in various domains of computer science.
Classical logic describes statements that can be either true or false. Operations of classical logic are "not", "and", "or", "implies". Statements are derived from axioms or from previously derived statements ("theorems").
Intuitionistic logic logic describes statements that can be true, false, or undecided (not yet proved). Operations of intuitionistic logic are the same as in classical logic - "not", "and", "or", "implies". However, while proving theorems one cannot assume that every statement is necessarily either true or false. So proofs by contradiction are not admissible; all proofs must be "constructive".
As an example, suppose we wanted to prove that if n2 is odd then n is also odd, for any integer n. A proof in classical logic is simple: if n were not odd then n2 would have been even, which contradicts the given condition that n2 is odd. However, this proof is not admissible in intuitionistic logic. Instead, we have to prove this statement "constructively" by taking the given odd number n2, obtaining the corresponding n by actually computing the square root of n2, and then proving that the resulting value of n is odd.
The simplest version of modal logic adds to classical logic the operators "possibly true" and "necessarily true". More generally, modal logic introduces the idea that a statement can be true "under certain circumstances" and false otherwise. The notion of "circumstances" is made formal by introducing labels. Something is "necessarily true" if it is true under "all possible circumstances".
Temporal logic is a particular case of modal logic where the "different circumstances" are just different moments of time. Time is discrete, and all available moments of time are numbered 0, 1, 2, ... A given statement can be true at one moment and false at another moment.


NotaryInfo |
Stores information about notaries available in the network. interface NotaryInfo |
UniqueIdentifier |
This class provides a truly unique identifier of a trade, state, or other business object, bound to any existing external ID. Equality and comparison are based on the unique ID only; if two states somehow have the same UUID but different external IDs, it would indicate a problem with handling of IDs. data class UniqueIdentifier : Comparable<UniqueIdentifier> |
net.corda.v5.application.node.MemberInfo |
|
net.corda.v5.application.node.NetworkParameters |
NOTARIES_KEY |
const val NOTARIES_KEY: String |
NOTARY_SERVICE_PARTY |
const val NOTARY_SERVICE_PARTY: String |


MVP Studio is all about connecting people with tech ideas with people who can help make those ideas a reality. Teamwork is where all the action is, so we desire to be a means of connections and provisions. As a sponsor, you are an integral part of bringing interns, developers, and clients together. We are not–for–profit, so your support is very appreciative.


Jim Weirich throws down the gauntlet with Ten Things a Java Programmer Should Know About Ruby: "Fixes what's wrong with Python".
OK, I actually don't care about that dig, I'm in a friendly mood these days. But it's interesting how many of the points are just as true for Python as Ruby; to me this merely confirms that they are extremely similar (and maybe that this post inspired some of the points). Quoting from the list (which no longer numbers ten) here's the few that aren't the same for Ruby and Python (ignoring trivial or syntactic differences). My comments are italic:
Well, for the most part the list is notable in how few differences there are. If you look at this comparison and ignore the points that are out of date, you'll notice that there's a difference in heritage and perspective (Ruby coming from a Smalltalk-OO background), but very little (any?) functional difference besides closures and blocks. And a whole bunch of syntactic differences, but that's neither here nor there.
I read "An instance of a class can be extended to be subtly different, without needing to subclass" to mean simply
o = Foo() o.nonstandardattribute = bar
# Jonathan Ellis
Yes, I think that's mostly what he means. Also, you can add and override methods in the same way. You can change the class directly -- monkey patching -- or you can create an instance and assign a function to an instance variable to override the method that the class contains. Other uses of first-class functions can accomplish all sorts of things; though honestly how they do that in Ruby (generally) I'm not sure, since it doesn't have "functions" per se, just methods. I get the impression there's some confusion there, with a couple techniques available.
they just write:
def an_instance.amethod(args) ... endIt is a nice way to write stuff since it also allows for clear specification of class/module methods:
class Foo # we are in Foo's scope, "self" is Foo def foo() puts "I'm an instance method" end def self.foo() puts "I'm a singleton method of a Class instance" end def self.bar() puts "In java parlance, I'm a static method of class Foo" end end(Formatting fixed; I'm not actually the author of this comment)
# Ian Bicking
There's also this:
module Mod def hello "Hello from Mod.\n" end end class Klass def hello "Hello from Klass.\n" end end k = Klass.new k.hello -> "Hello from Klass.\n" k.extend(Mod) -> #<Klass:0x4018d554> k.hello -> "Hello from Mod.\n"
"o = Foo(); o.nonstandardattribute = bar"
this can't be done.
attributes in ruby are set via setter methods
class Foo def std_attr= v @std_attr = v end endalthough the simpler way to do it is
class Foo attr_writer :std_attr endwhat "An instance of a class can be extended to be subtly different, without needing to subclass" actually means is
s = 'a string' class << s def consonants gsub /[aeiou]/i, '' end ends.consonants will give you " strng", but on any other string, it'll raise an undefined method error.
I like both Python and Ruby. I agree with your summation that there isn't much to choose between them; except for blocks/closures, but for me that is all the reason I need to choose Ruby.
Until you have experience of them you probably won't get how powerful blocks/closures are. I'm generalising from me, because I didn't get it for a long time, to you. Probably unfairly.
- [1] I know, I know, superlative overload .. but in this case, I think, well deserved.
# Rob Lally
Ack! Ian, sorry about the gauntlet. I didn't actually throw it, more like I accidently bdropped it on the floor.
Last week I asked for suggestions for a "Ten Things Java Programmers Should Know About Ruby" list. The Ta-Da list you linked to is a (temporary) compilation of all the suggestions coming in, without any editting on my part. (Obviously, for the list is a "bit" longer than my targetted goal of ten items). It is there so that people can review all the current suggestions before making new ones. I'm putting together a small presentation for a group of Java programmers and was just soliciting feedback.
Unfortunately, there is no easy place in a Ta-Da list to capture the above meta-information. The list is short-lived anyways, it will probably go away when I've compiled my final version.
For the record, "Fixes what's wrong with Python" does even come close to making the top ten things a _Java_ programmer would need to know. (For that matter, I wouldn't even put it in a list of things a Python programmer would need to know). Ruby and Python are much more similar than different (as you point out), especially compared to what makes it as mainstream languages these days. Your comments on the differences are pretty much right on too.
Although a Java developer wouldn't care, one Ruby feature I'm waiting for in Python is continuations (callcc in Ruby, also available in Stackless Python).
I agree that Python's default string interpolation sucks, but it's simple enough to fix. Just import the sys and Itpl [1] libraries and write sys.stdout=Itpl.filter() to get real string interpolation. Definitely not as clean as native string interpolation, but if that's a deal-breaker for anybody, it's easy enough to fix.
String interpolation by default is a _bad_ thing. It introduces unexpected behavior which are frequently security holes. Explicit interpolate(string, map) of some sort is better.# Oliver X
How about writing a "Why Python is better than Ruby" point by point and let Ruby guys respond?# James
I guess I'd be afraid of lots of "Ruby has that too!" responses, but I suppose if prefaced properly maybe that would be okay. Or it could just go on the Python Wiki, and let collective editing clear out the issues and debate. The Pattern Repository has a page: http://c2.com/cgi/wiki?PythonVsRuby -- but it's not that up-to-date and there's no clear distinction between exposition and discussion.
To me, most of it comes down to some vague design principles: Python emphasizes uniformity, and in this way it's much more like Smalltalk. It also has some different perspectives on how to address the same issues, e.g. loops and first class functions instead of blocks. There's also some things that I have intuitions about, but haven't tried enough in Ruby to confirm. E.g., a traditional procedural perspective makes libraries easier to wrap, and encourages two-level wrapping -- a very thin wrapper that interfaces with C, and another wrapper that provides "Pythonic" abstractions over that library. This is a design technique that I really like; I'm sure people do it in Ruby as well, but I suspect it's not as easy to do the trully thin wrapper in a strict OO world.
There's some other important design issues that I have with Ruby. One in particular is the ways you can globally effect the system, and effect the basic types in the system. Being able to implement (globally and transparently) case-insensitive comparisons of strings is an anti-feature to me. This is an aspect of Smalltalk I dislike.
But the big one for me is the libraries and infrastructure. Python has gained a considerable degree of acceptance, has become part of the standard installation of most Unixy OSes (including Mac OS X), is a first-tier target for open source libraries (there's a lot of C libraries that have Python bindings from day one), and there's a large community of people who have learned how to do interesting and novel things in Python without requiring changes (or even good support!) from the language. Twisted, for example, would have been a lot easier in Ruby, and yet they seem to be doing pretty well despite that. All the really exciting stuff in Python these days isn't in the core language, and yet there's a lot of exciting things happening.
What really discourages me from the comparison and debate is that I don't think there's much to be gained from it. For Python and Ruby to try to take users from each other is a losing game -- we're both small players, and there's much better and bigger pools of developers we should be trying to attract. There's also so much more we can say about why you should use either language instead of Java or C# or what-have-you, compared to why you should use Python instead of Ruby or vice versa.
I looked at Ruby over two years ago. The ugly Perl-like syntax is a definite turn-off, but the deal-breaker for me was multithreading, or the lack thereof. If you think Python global interpreter lock is bad, Ruby's cooperative multithreading is far worse. This may have been fixed in the last 2 years, however.
Surprises me is no ones mentioned unicode, as in Python "does" while Ruby "doesn't" (yet). Kind of a crucial fact that I imagine Java programmers would definately want to know about.
An excellent point -- it's far more valuable to introduce people to the benefits of dynamic languages than to argue so much about which language to use. And I also suspect that Ruby may have been (and continue to be) a stimulation for Python improvements, as C# has definitely been for Java. Until Ruby, there hasn't been much competition for Python IMO, and now there is.# Bruce Eckel
Definitely - competition for Python is a good thing. I'm sure everyone's tired of hearing about it, but Rails is of course a recent (loud) example. And it's already sprung up a challenger in Python (Subway). I think it clearly raised the bar in terms of overall "polish", and while often reaching hyperbole, shows the buzz you can get by extensive promotion and attention to detail (docs don't hurt!).
A difference I've noted though as a "consumer" of web frameworks (I'm no genius) is that Rails was very actively promoted - I've not seen any python web framework promoted anywhere near as much (and I don't mean claims of "10x faster"). Zope and Plone are quite well known, but holy learning curve. They almost make J2EE look simple. And Rails was very much designed - after being mostly built on the fly assembling Basecamp - to be packaged and presented as something you should use , whereas most python projects strike me as this works well for us, try it, if you like it great. if not, 'roll your own, it's easy.  Of course I'm broadly generalizing, but I think the broad point is valid...  And that attitude is rarely explicit - it's more often evident in responses to newbies and lack of docs and so on.
I hope this is taken as constructive criticism, 'cause that's how it's meant. I fear sometimes all you guys who write the guts of python and the serious libs are sometimes not aware of the view from the cheap seats (newcomers).
# Todd G
>. Zope and Plone are quite well known, but holy learning curve.
I know this is off topic but one thing I don't get is why people always say the Zope has a huge learning curve. I have never seen a framework that didn't have a learning curve, but comparing zope to J2EE (oh an whatever App server you also need to run your J2EE solution) is being way to unfair on zope. (Have you ever had to set up a tomcat/apache/J2EE/oracle environment, just so you can do some basic persistent web app ;-)
With zope you can be very productive very quickly. The more you use it the more you learn and the greater the sophistication of what you can then do. But you don't have to get into the bowels from day one.
# TIm
Maybe it's the lack of docs. Last time I looked at least. And the near-requirement to setup Squid for any reasonable speed. The big long paper the Quixote guys at MEMS wrote (about why they developed Quixote rather than using Zope) addresses it far better than I ever could.
And getting a java servlet container up and running these days isn't so bad at all. Dropping jar's in is nice too.
"An instance of a class can be extended to be subtly different, without needing to subclass" to mean using something like Delegator or SimpleDelegate. I wouldn't be suprised if python could do something similar, or had a similar mechanism for the pattern.
They also could mean doing something like:
str = "" puts "Not Moo" unless str.respond_to? "moo" class String def moo " I AM A SPECIAL STRING I CAN MOO" end end puts "Is moo! " if str.respond_to? "moo"Extending the availible methods of the class String at runtime, for all Strings
# Ian Bicking
Python has singletons. They are called "modules".


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Synergy Advance Public Preview Release 0.1.1
-
Greg Hurrell
A new public preview release is out, and boasts a long list of new features and bug fixes:
https://wincent.com/a/products/synergy-advance/history/
The first public preview release was quite successful. Thanks to everybody who submitted bug reports; they really help improve the quality of the software.
I wanted to do this 0.1.1 release quickly to fix a couple of little things. The next public preview release 0.2 will be a bigger update, hopefully fixing all reported issues as well as adding a couple of new modules. The 0.2 release will come out before the end of this month.
Download:
https://wincent.com/download.php?item=SynergyAdvance.dmg
Website:
Road map:
https://wincent.com/a/products/synergy-advance/road-map/
Known issues:
https://wincent.com/a/products/synergy-advance/known-issues/
Bug reports (please):
Bug reporting tips:
https://wincent.com/a/knowledge-base/archives/2004/11/how_to_file_a_g.php
Instructions for beta testers:
https://wincent.com/a/knowledge-base/archives/2005/04/information_for.php
Activation information:
https://wincent.com/a/support/activation/
Purchase:
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WITNESS LIST
Business & Commerce
March 24, 2015 8:00 AM
FOR:
Bueche, Jay (Self; Texas Federation of Drug Stores), New Braunfels, TX
Rodriguez, Miguel (Texas Pharmacy Business Council), Austin, TX
AGAINST:
Horne, Allen VP Government Affairs, CVS Health (CVS Health), Austin, TX
Registering, but not testifying:
FOR:
Fain, J.D. Pharmacist (Self; Texas independant pharmacies association), Giddings, TX
Galligher, Duane (Texas Independent Pharmacies Association), Austin, TX
Heal, John Director, Governmental Affairs (Self; Texas TrueCare Pharmacies), Austin, TX
Reagan, Karen (Walgreen Company), Austin, TX
Rodriguez, Micah General Counsel (HEB), Austin, TX
Wilkes, Morris (United Supermarkets), Lubbock, TX
Wright, Michael Texas pharmacy business council (Texas pharmacy business council),
Austin, TX
AGAINST:
Wilson, Wendy (Prime Therapeutics), Austin, TX
Wilson, Wendy (Prime Therapeuticss), Austin, TX
ON:
Bolduc, David (Texas Department of Insurance), Austin, TX
Bolduc, David (Texas Department of Insurance), Austin, TX
Diaz-Lara, Debra (Texas Department of Insurance), Austin, TX
Nicolas, Sandra (Texas Department of Insurance), Austin, TX
FOR:
Bueche, Jay (Self; Texas Federation of Drug Stores), New Braunfels, TX
Rodriguez, Miguel (Texas Pharmacy Business Council), Austin, TX
Wright, Michael Texas pharmacy business council (Texas pharmacy business council),
Austin, TX
Registering, but not testifying:
FOR:
Fain, J.D. Pharmacist (Self; Texas independant pharmacies association), Giddings, TX
Galligher, Duane (Texas Independent Pharmacies Association), Austin, TX
Heal, John Director, Governmental Affairs (Self; Texas TrueCare Pharmacies), Austin, TX
Horne, Allen VP Government Affairs, CVS Health (CVS Health), Austin, TX
Hudman, Justin Senior Director Public Affairs (Texas Pharmacy Association), Austin, TX
McGarry, Mignon (Express Scripts), Austin, TX
Wilkes, Morris (United Supermarkets), Lubbock, TX
Wilson, Wendy (Prime Therpeutics), Austin, TX
Wilson, Wendy (Prime Therapeutics), Austin, TX
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Business & Commerce
March 24, 2015 8:00 AM
ON:
Danzeiser, Doug (Texas Department of Insurance), Austin, TX
FOR:
Dudensing, Jamie CEO (Texas Association of Health Plans), Austin, TX
AGAINST:
Mahon, Kirk Changes to SB 425 (Self; SAFER-Tx), Dallas, TX
McGee, John COO (Self; ER Centers of America Inc), Plano, TX
Rankins, Robert MD (E-care emergency centers), Mckinney, TX
Sandel, Rhonda Immediate padt president (Self; TAFEC Texas Association of
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Sarabia, Michael MD, FACEP (Self; PhysiciansER), Houston, TX
Woody, Jay (Self), Frisco, TX
ON:
Bailey, Charles General Counsel (Texas Hospital Association), Austin, TX
Feanny, Mark (Self), Pearland, TX
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Berndt, Trey Associate State Director Ste. 750 (AARP), Austin, TX
Brooks, Jeffrey (Texas conservative coalition), Austin, TX
Cawley, Jennifer Executive Director, TALHI (Texas Association of Life and Health
Insurers), Austin, TX
Devine, Teresa Sr Health Policy Analyst (Blue Cross Blue Shield of Texas), Austin, TX
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Sanaie, Kandice (UnitedHealthcare), Austin, TX
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Strama, Keith Attorney (Self; First choice emergency rooms), Austin texas, TX
ON:
Danzeiser, Doug (Texas Department of Insurance), Austin, TX
FOR:
Dudensing, Jamie CEO (Texas Association of Health Plans), Austin, TX
Fryar, Michael (Self), Grapevine, TX
Hammond, Bill CEO (Texas association of business), Austin, TX
Hawkins, Don (Self), Austin, TX
Hopper, Jennifer (also providing written testimony) (Self), Austin, TX
Hutson, Blake (also providing written testimony) (Self; Consumers union), Austin, TX
Pogue, Stacey Senior Policy Analyst (also providing written testimony) (Center for Public
Policy Priorities), Austin, TX
WITNESS LIST
Business & Commerce
March 24, 2015 8:00 AM
ON:
Buckingham, Dawn (also providing written testimony) (Texas Medical Association),
Austin, TX
Zaafran, Sherif Dr. (Texas Society of Anesthesiologists), Austin, TX
Registering, but not testifying:
FOR:
Berndt, Trey Associate State Director Ste. 750 (AARP), Austin, TX
Brooks, Jeffrey (Texas conservative coalition), Austin, TX
Manross, Lee (Self; Texas association of health underwriters), Austin, TX
Nichols-Segers, Simone (National MS Society), Austin, TX
AGAINST:
Aldred, Brian MD (Five Star ER), Round rock, TX
McGee, John COO (Self; ER Centers of America Inc), Plano, TX
Sandel, Rhonda Immediate padt president (Self; TAFEC Texas Association of
Freestanding Emergency Centers), Cypress, TX
ON:
Danzeiser, Doug (Texas Department of Insurance), Austin, TX
Registering, but not testifying:
ON:
Harrison, Amy Director of Licensing (TABC), Austin, TX
Registering, but not testifying:
ON:
Ivie, Julie Assistant Director (Legislative Budget Board), Austin, TX
Kimbriel, Todd Director egovernment (Dept of information resources), Austin, TX
McKay, Kyle Analyst (Lbb), Austin, TX
Pigott, Ron Commissioner for procurement and contracting (HHSC), Austin, TX
Saldivar, Cesar Audit Manager (State Auditor's Office), Austin, TX
Spock, Karl Senior manager (Sunset commission), Austin, TX
Young, John Audit Manager (State Auditor's Office), Austin, TX
FOR:
Redman, Margaret Reinsurance Counsel (also providing written testimony) (First
American), Santa Ana, CA
ON:
Baker, Marianne Program specialist for personal and commercial lin (Texas Department of
Insurance), Austin, TX
Baker, Marianne (Texas Department of Insurance), Austin, TX
Brady, Kevin (Texas Department of Insurance), Austin, TX
Brady, Kevin Deputy Chief of Staff (Texas Department of Insurance), Austin, TX
WITNESS LIST
Business & Commerce
March 24, 2015 8:00 AM
Registering, but not testifying:
FOR:
Cain, Randy Attorney (Wind Coalition), Austin, TX
Junge, Heidi Texas Underwriting Counsel (Stewart Title Guaranty Company and Texas
Land Title Association), San Antonio, TX
Lee, Randy Senior Vice President (Stewart Title Guaranty Company), Austin, TX
Place, Allen Attorney (Texas Land Title Association), Austin, TX
Registering, but not testifying:
ON:
Willis, Cathy Section supervisor (Comptroller), Austin, TX
Registering, but not testifying:
FOR:
Heasley, John (Texas Bankers Association), Austin, TX
ON:
Bacon, Robert Deputy Commissioner (Texas Dept of Banking), Austin, TX
Cooper, Charles Commissioner (Texas Dept Of Banking), Austin, TX
Jobe, Everette Attorney (Tx dept of banking), Austin, TX
FOR:
Frazier, Kyle (Texas wine and grape growers association), Austin, TX
Yates, Ron (Self; Texas Wine and Grape Growers), Austin, TX
ON:
York, Mary Administrator, Texas Department of Agriculture (Texas Department of
Agriculture), Austin, TX
Registering, but not testifying:
ON:
Carlton, Neal (Texas Department of Agriculture), Austin, TX
Registering, but not testifying:
ON:
Cooper, Charles Commissioner (Texas Dept Of Banking), Austin, TX
Newberg, Stephanie (Texas Department of Banking), Austin, TX
Registering, but not testifying:
FOR:
Cawley, Jennifer Executive Director, TALHI (Texas Association of Life and Health
Insurers), Austin, TX
Hadley, Elizabeth (Aflac), Austin, TX
ON:
Danzeiser, Doug Director for Regulatory Matters and Policy Initiat (Texas Department of
Insurance), Austin, TX
WITNESS LIST
Business & Commerce
March 24, 2015 8:00 AM
FOR:
Neeley, Karen (Business law foundation), Austin, TX
FOR:
Fain, J.D. Pharmacist (Self; Texas independant pharmacies association), Giddings, TX
Galligher, Duane (Texas Independent Pharmacies Association), Austin, TX
ON:
Dudensing, Jamie CEO (Texas Association of Health Plans), Austin, TX
Registering, but not testifying:
FOR:
Heal, John Director, Governmental Affairs (Self; Texas TrueCare Pharmacies), Austin, TX
Hudman, Justin Senior Director Public Affairs (Texas Pharmacy Association), Austin, TX
Shields, Bradford (Texas Federation of Drug Stores), Austin, TX
Wright, Michael Texas pharmacy business council (Texas pharmacy business council),
Austin, TX
ON:
Diaz Lara, Debra Director for Managed Care Quality Assurance Office (Texas Department
of Insurance), Austin, TX
Harrigan, Chris Attorney of Office of Financial Counsel (Texas Department of Insurance),
Austin, TX
Vasquez, Andy Deputy director of vendor drug program (HHSc), Austin, TX
FOR:
Pendleton, DJ Executive Director (Texas Manufactured Housing Association), Austin, TX
Registering, but not testifying:
FOR:
Mintz, David VP, Government Affairs (Texas Apartment Association), Austin, TX
ON:
Ferrie, George Director of Compliance (Texas Department of Licensing and Regulation),
Austin, TX


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Welcome to Background Hum, the official newsletter of EE-IITB
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--- short: t-singlegraphunion type: transformer color: indigo title: Union description: Represents a union of RDF data. Useful to make nicer pipelines. ---
Transformer, represents a union of RDF data. Useful to make nicer pipelines where multiple edges would have to be duplicated otherwise.
The {{page.title}} component merges the input RDF data and passes it on. Useful when outputs of multiple components should again be used by multiple components, where instead of m*n edges we get m+n edges.


⚠ This library is a work in progress and is not ready for use!
All types and the core test suite have been implemented.
This module has not been packaged for or tested in any real-world environments.
The API has been changed where necessary to accommodate differences between Python and JavaScript language features.
Examples
Generated using TypeDoc


| I l@ve RuBoard |
In this section, we introduce a few module-related ideas that seem important enough to stand on their own (or obscure enough to defy our organizational skills).
As currently implemented, the Python system is often called an interpreter, but it's really somewhere between a classic interpreter and compiler. As in Java, Python programs are compiled to an intermediate form called bytecode, which is then executed on something called a virtual machine. Since the Python virtual machine interprets the bytecode form, we can get away with saying that Python is interpreted, but it still goes through a compile phase first.
Luckily, the compile step is completely automated and hidden in Python. Python programmers simply import modules and use the names they define; Python takes care to automatically compile modules to bytecode when they are first imported. Moreover, Python tries to save a module's bytecode in a file, so it can avoid recompiling in the future if the source code hasn't been changed. In effect, Python comes with an automatic make system to manage recompiles.[5]
[5] For readers who have never used C or C++, a make system is a way to automate compiling and linking programs. make systems typically use file modification dates to know when a file must be recompiled (just like Python).
Here's how this works. You may have noticed .pyc files in your module directories after running programs; these are the files Python generates to save a module's bytecode (provided you have write access to source directories). When a module M is imported, Python loads a M.pyc bytecode file instead of the corresponding M.py source file, as long as the M.py file hasn't been changed since the M.pyc bytecode was saved. If you change the source code file (or delete the .pyc), Python is smart enough to recompile the module when imported; if not, the saved bytecode files make your program start quicker by avoiding recompiles at runtime.
As we've seen, Python modules export all names assigned at the top level of their file. There is no notion of declaring which names should and shouldn't be visible outside the module. In fact, there's no way to prevent a client from changing names inside a module if they want to.
In Python, data hiding in modules is a convention, not a syntactical constraint. If you want to break a module by trashing its names, you can (though we have yet to meet a programmer who would want to). Some purists object to this liberal attitude towards data hiding and claim that it means Python can't implement encapsulation. We disagree (and doubt we could convince purists of anything in any event). Encapsulation in Python is more about packaging, than restricting.[6]
[6] Purists would probably also be horrified by the rogue C++ programmer who types #define private public to break C++'s hiding mechanism in a single blow. But then those are rogue programmers for you.
As a special case, prefixing names with an underscore (e.g., _X) prevents them from being copied out when a client imports with a from* statement. This really is intended only to minimize namespace pollution;since from* copies out all names, you may get more than you bargained for (including names which overwrite names in the importer). But underscores aren't "private" declarations: you can still see and change such names with other import forms.
Here's a special module-related trick that lets you both import a module from clients and run it as a standalone program. Each module has a built-in attribute called __name__, which Python sets as follows:
If the file is being run as a program, __ name _ _ is set to the string __ main __ when it starts
If the file is being imported, __name__ is set to the module's name as known by its clients
The upshot is that a module can test its own _ _name__ to determine whether it's being run or imported. For example, suppose we create the module file below, to export a single function called tester:
def tester(): print "It's Christmas in Heaven..." if __name__ == '__main__': # only when run tester() # not when imported
This module defines a function for clients to import and use as usual:
% python >>> import runme >>> runme.tester() It's Christmas in Heaven...
But the module also includes code at the bottom that is set up to call the function when this file is run as a program:
% python runme.py It's Christmas in Heaven...
Perhaps the most common place you'll see the _ _main__ test applied is for self-test code: you can package code that tests a module's exports in the module itself by wrapping it in a __ main __ test at the bottom. This way, you can use the file in clients and test its logic by running it from the system shell.
We've mentioned that the module search path is a list of directories in environment variable PYTHONPATH. What we haven't told you is that a Python program can actually change the search path, by assigning to a built-in list called sys.path (the path attribute in the built-in sys module). sys.path is initialized from PYTHONPATH (plus compiled-in defaults) on startup, but thereafter, you can delete, append, and reset its components however you like:
>>> import sys >>> sys.path ['.', 'c:\\python\\lib', 'c:\\python\\lib\\tkinter'] >>> sys.path = ['.'] # change module search path >>> sys.path.append('c:\\book\\examples') # escape backlashes as "\\" >>> sys.path ['.', 'c:\\book\\examples'] >>> import string Traceback (innermost last): File "<stdin>", line 1, in ? ImportError: No module named string
You can use this to dynamically configure a search path inside a Python program. Be careful, though; if you delete a critical directory from the path, you may lose access to critical utilities. In the last command above, for example, we no longer have access to the string module, since we deleted the Python source library's directory from the path.
Packages are an advanced tool, and we debated whether to cover them in this book. But since you may run across them in other people's code, here's a quick overview of their machinery.
In short, Python packages allow you to import modules using directory paths; qualified names in import statements reflect the directory structure on your machine. For instance, if some module C lives in a directory B, which is in turn a subdirectory of directory A, you can say import A.B.C to load the module. Only directory A needs to be found in a directory listed in the PYTHONPATH variable, since the path from A to C is given by qualification.
Packages come in handy when integrating systems written by independent developers; by storing each system's set of modules in its own subdirectory, we can reduce the risk of name clashes. For instance, if each developer writes a module called spam.py, there's no telling which will be found on PYTHONPATH first if package qualifier paths aren't used. If another subsystem's directory appears on PYTHONPATH first, a subsystem may see the wrong one.
Again, if you're new to Python, make sure that you've mastered simple modules before stepping up to packages. Packages are more complex than we've described here; for instance, each directory used as a package must include a __ init __.py module to identify itself as such. See Python's reference manuals for the whole story.
Why You Will Care: Module PackagesNow that packages are a standard part of Python, you're likely to start seeing third-party extensions shipped as a set of package directories, rather than a flat list of modules. The PythonWin port of Python for MS-Windows was one of the first to jump on the package bandwagon. Many of its utility modules reside in packages, which you import with qualification paths; for instance, to load client-side COM tools, we say: from win32com.client import constants, Dispatch which fetches names from the client module of the PythonWin win32com package (an install directory). We'll see more about COM in Chapter 10. |
Like functions, modules present design tradeoffs: deciding which functions go in which module, module communication mechanisms, and so on. Here too, it's a bigger topic than this book allows, so we'll just touch on a few general ideas that will become clearer when you start writing bigger Python systems:
There's no way to write code that doesn't live in some module. In fact, code typed at the interactive prompt really goes in a built-in module called __main __.
Like functions, modules work best if they're written to be closed boxes. As a rule of thumb, they should be as independent of global names in other modules as possible.
You can minimize a module's couplings by maximizing its cohesion; if all the components of a module share its general purpose, you're less likely to depend on external names.
It's perfectly okay to use globals defined in another module (that's how clients import services, after all), but changing globals in another module is usually a symptom of a design problem. There are exceptions of course, but you should try to communicate results through devices such as function return values, not cross-module changes.
Finally, because modules expose most of their interesting properties as built-in attributes, it's easy to write programs that manage other programs. We usually call such manager programs metaprograms , because they work on top of other systems. This is also referred to as introspection, because programs can see and process object internals.
For instance, to get to an attribute called name in a module called M, we can either use qualification, or index the module's attribute dictionary exposed in the built-in _ _dict__ attribute. Further, Python also exports the list of all loaded modules as the sys.modules dictionary (that is, the modules attribute of the sys module), and provides a built-in called getattr that lets us fetch attributes from their string names. Because of that, all the following expressions reach the same attribute and object:
M.name # qualify object M.__dict__['name'] # index namespace dictionary manually sys.modules['M'].name # index loaded-modules table manually getattr(M, 'name') # call built-in fetch function
By exposing module internals like this, Python helps you build programs about programs.[7] For example, here is a module that puts these ideas to work, to implement a customized version of the built-in dir function. It defines and exports a function called listing, which takes a module object as an argument and prints a formatted listing of the module's namespace:
[7] Notice that because a function can access its enclosing module by going through the sys.modules table like this, it's possible to emulate the effect of the global statement we met in Chapter 4. For instance, the effect of global X; X=0 can be simulated by saying, inside a function: import sys; glob=sys.modules[_ _name__ ]; glob.X=0 (albeit with much more typing). Remember, each module gets a __ name__ attribute for free; it's visible as a global name inside functions within a module. This trick provides a way to change both local and global variables of the same name, inside a function.
# a module that lists the namespaces of other modules verbose = 1 def listing(module): if verbose: print "-"*30 print "name:", module.__ _name__, "file:", module.__file__ print "-"*30 count = 0 for attr in module.__dict__.keys(): # scan namespace print "%02d) %s" % (count, attr), if attr[0:2] == "__": print "<built-in name>" # skip __file__, etc. else: print getattr(module, attr) # same as .__dict__[attr] count = count+1 if verbose: print "-"*30 print module.__name__, "has %d names" % count print "-"*30 if __name__ == "__main__": import mydir listing(mydir) # self-test code: list myself
We've also provided self-test logic at the bottom of this module, which narcissistically imports and lists itself. Here's the sort of output produced:
C:\python> python mydir.py ------------------------------ name: mydir file: mydir.py ------------------------------ 00) __file__ <built-in name> 01) __name__ <built-in name> 02) listing <function listing at 885450> 03) __doc__ <built-in name> 04) __builtins__ <built-in name> 05) verbose 1 ------------------------------ mydir has 6 names ------------------------------
We'll meet getattr and its relatives again. The point to notice here is that mydir is a program that lets you browse other programs. Because Python exposes its internals, you can process objects generically.[8]
[8] By the way, tools such as mydir.listing can be preloaded into the interactive namespace, by importing them in the file referenced by the PYTHONSTARTUP environment variable. Since code in the startup file runs in the interactive namespace (module _ _main__), imports of common tools in the startup file can save you some typing. See Chapter 1 for more details.
| I l@ve RuBoard |


Hi, I’m an Independent Web and Software Developer based in Los Angeles, California.
I work primarily with Java and Front-End Web Technologies.
Looking for a Web Developer? I would be a great contribution to your team. Take a look at my resume and reach out!
GitHub
LinkedIn
Resume


There will be other monthly or annually expenses for the house, such as Taxes, Home Insurance, and sometimes HOA fees. Please check with your agent.


Secure Storage
Storing
Retrieving
Caching
Set Item
Get Item
Remove Item
Clear Cache
Working Offline
Storing a Request
Flushing Requests
Notifications
Examples shown below are using angularJS and ionic, which come included with the appworksJS starter template.
Full example
Retrieving all notifications
Recieiving new notifications
Clearing notifications


use arrow keys for movement.
Up: Jump
Right: Move Forward
Left: Move Backward
P: Pause the Game or use the Button
R: Resume the Game or use the Button
F: Flip the polarity of Your Magnet
**Collect Keys to score high.
**Cacti are Obstacles. The Game will be Over if you touch them.
**Foreign Magnets: If you collide with the magnets having the polarity opposite to your magnet, you loose the game, else it will be repelled.


G_gamma
Heterotrimeric GTP-binding protein subunits that tightly associate with GTP-BINDING PROTEIN BETA SUBUNITS. A dimer of beta and gamma subunits is formed when the GTP-BINDING PROTEIN ALPHA SUBUNIT dissociates from the GTP-binding protein heterotrimeric complex. The beta-gamma dimer can play an important role in signal transduction by interacting with a variety of second messengers.
(mesh:D044388)
Cross-references
Synonyms
| Synonym |
Reference |
Specificity |
| G protein gamma |
|
Exact
|
| G protein gamma subunit |
|
Exact
|
| G protein γ subunit |
|
Exact
|
| G protein γ |
|
Exact
|
Incoming Relations
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David A. Krane
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Golang Warsaw #19
Let's go!
Let's go!
- slack: #poland na gophers.slack.com
- slack: #golang na devspl.slack.com
- Facebook: Golang poland
Selecting talks
- Sharing experience from everyday work
- Best practises: DDD, TDD, ...
- New tech
Always in English.
Proposed format
- 2x 10 minutes
- 2x 20 minutes or 1x 40 minutes
News
- go1.11 (see details)
- package manager saga...
- new lib for...
Agenda
- Jakub Daliga - Abusing Idiomatic Go - 25 min
- Slices strike back - Tomek Janiszewski - 10 min
- Go-critic - Oleg Kovalov - 10 min


At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi sint occaecati cupiditate non provident.
But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system, and expound the actual teachings of the great explorer of the truth, the master-builder of human happiness.Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam.
On the other hand, we denounce with righteous indignation and dislike men who are so beguiled and demoralized by the charms of pleasure of the moment, so blinded by desire, that they cannot foresee the pain and trouble that are bound to ensue; and equal blame belongs to those who fail in their duty through weakness of will, which is the same as saying through shrinking from toil and pain. These cases are perfectly simple and easy to distinguish.
At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum deleniti atque corrupti quos dolores et quas molestias excepturi sint occaecati cupiditate non provident.


What a responsive site is, and why responsiveness is important.
A responsive site is a webpage that responds to the size of your device,
adjusting its layout to the size of the device. For example a desktop would show
a title possibly a drop down nav bar some contents and lots of blogs all in a
row whereas a mobile would show the title an easy nav bar and singular blogs
all in line vertically. I feel it is important because its hard trying to push
little desktop button on a small cellphone screen.
What mobile first design is, and why it's important?
Mobile internet usage grows and grows everyday. Making mobile design the
number one priority all you need to do is focus on creating a great user
experience without all the fancy desktop stuff, because you have a much smaller
screen to work with. Making an easy use and clear mobile webpage or app makes
everything much easier.
What frameworks are, and their pros and cons?
A framework provides functionalities/solution to the particular problem area.
Definition from wiki: "A software framework, in computer programming, is an abstraction
in which common code providing generic functionality can be selectively overridden or
specialized by user code providing specific functionality." Some of the pros and cons
are you can visually design what you want and then learn exactlly which codes you need to achieve that goal.
What a wireframe is and why we use it?
These are my wireframes. Hover your mouse over the image to know which wireframe is which. We use them to
The aspects of your wireframes you found difficult to implement, and why?
Well for my 'Desktop Index Page' wireframe I couldn't make my top nav bar fixed
to the top in a full-length black bar, I ended up changing the layout of the blogs
because what I had in mind didn't quite work out either so I pretty much tweak it all
and changed it up. For my 'Desktop Blog Page' I changed everything about it to make
it clearer to read, the only thing that annoys me about the layout is that my nav
bar isn't fixed to the top also I've been trying to add my wireframe pictures all
in a row (side by side) on this blog. Havent quite figured out how to implement the
mobile wireframes either.
Meditation Process
How did the 'process over product' concept affect the way you tackled
the site redesign and rebuild?
Reading this article
Process Over Product
gave me a better understanding of what it actually is. It affect me quite good,
I really loved all the processes I had to go through to redesign my website I got
quite caught up in how my webpage was looking and so I spent waaaay longer than
I should have tweaking things on my webpage but I definately enjoyed the process
of it all.
What did you think about meditation before reading chapter 2?
My thoughts on meditation were that you just sit on the ground and relax
take deep breaths and focus on that moment only, I never really thought too
much about it, just a relaxing strategy.
What new things have you learnt about meditation?
Now that I have read Mindfulness (Chapter 2)
of Search Inside Yourself I have learnt that you need to create an intention
for meditating, secondly 'follow your breath' by focusing on it, thirdly gather
your attention and see how long you can hold it before distractions take over,
and when they do just regain your attention once again.
The meditation techniques that stood out to me was the “grandmother mind”:
adopting the mind of a loving grandmother”.


During wednesday we've gone to Prague. The ride there was a bit longer due to a traffic jam but we've made it in one piece. We have visited Petřín Lookout Tower, St. Vitus Cathedral, Prague Castle and Golden Lane. When we were in Prague we have also visited shopping center PALLADIUM Prague. After coming back from the trip we've had another workshop from the polish group.


Shawarma Palace.
70W 39th Street, New York, NY
New York City, NY 12345
<EMAIL_ADDRESS>Item
Quantity
Price
Total:


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Exporting data¶
Note
This tutorial assumes you have installed QIIME 2 using one of the procedures in the install documents.
In order to use QIIME 2, your input data must be stored in QIIME 2 artifacts (i.e. .qza
files). This is what enables distributed and automatic provenance tracking, as well as semantic type validation and transformations between data formats (see the core concepts page for more details about QIIME 2 artifacts).
Sometimes you’ll want to export data from a QIIME 2 artifact, for example to analyze data with a different microbiome analysis program, or to do statistical analysis in R. This can be achieved used the qiime tools export
command, which takes a QIIME 2 artifact (.qza
) file and an output directory as input. The data in the artifact will exported to one or more files depending on the specific artifact.
Warning
When exporting data from a QIIME 2 artifact, there will no longer be provenance associated with the data. If you subsequently re-import the exported data, the provenance associated with the new artifact will begin with the import step and all existing provenance will be lost. It’s therefore best to only export data from artifacts when you are done with all processing steps that can be achieved with QIIME 2 to maximize the value of each artifact’s provenance.
The following sections provide examples of exporting data from QIIME 2 artifacts. It is possible to export data from any QIIME 2 artifact or visualization; the process is the same as what is described below.
Exporting a feature table¶
A FeatureTable[Frequency]
artifact will be exported as a BIOM v2.1.0 formatted file.
Download URL: https://data.qiime2.org/2017.4/tutorials/exporting/feature-table.qza
Save as: feature-table.qza
wget -O "feature-table.qza" "https://data.qiime2.org/2017.4/tutorials/exporting/feature-table.qza"
curl -sL "https://data.qiime2.org/2017.4/tutorials/exporting/feature-table.qza" > "feature-table.qza"
qiime tools export \
feature-table.qza \
--output-dir exported-feature-table
Exporting a phylogenetic tree¶
A Phylogeny[Unrooted]
artifact will be exported as a newick formatted file.
Download URL: https://data.qiime2.org/2017.4/tutorials/exporting/unrooted-tree.qza
Save as: unrooted-tree.qza
wget -O "unrooted-tree.qza" "https://data.qiime2.org/2017.4/tutorials/exporting/unrooted-tree.qza"
curl -sL "https://data.qiime2.org/2017.4/tutorials/exporting/unrooted-tree.qza" > "unrooted-tree.qza"
qiime tools export \
unrooted-tree.qza \
--output-dir exported-tree
Exporting versus extracting¶
QIIME 2 artifacts can be extracted using qiime tools extract
. Extracting an artifact differs from exporting an artifact. When exporting an artifact, only the data files will be placed in the output directory. Extracting will additionally provide QIIME 2’s metadata about an artifact, including for example the artifact’s provenance, in the output directory in plain-text formats. An artifact can be extracted as follows. The directory that you’re extracting to must already exist.
mkdir extracted-feature-table
qiime tools extract \
feature-table.qza \
--output-dir extracted-feature-table
The output directory will contain a new directory whose name is the artifact’s UUID. All artifact data and metadata will be stored in that directory.
Note
While it is possible to view an artifact’s provenance from its extracted metadata text files, the graphical provenance viewer at https://view.qiime2.org is the recommended way to view an artifact’s provenance.