rosa | project contains the rosa command line tool | Cloud library
kandi X-RAY | rosa Summary
kandi X-RAY | rosa Summary
This project contains the rosa command line tool that simplifies the use of Red Hat OpenShift Service on AWS, also known as ROSA.
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Top functions reviewed by kandi - BETA
- buildGithubIdp builds an IdentityProviderBuilder
- buildLdapIdp builds the identity provider
- buildOpenidIdp builds OpenID provider
- Run the CLI command
- buildGitlabIdp builds an identity provider
- buildCommand builds an ocm command
- getReplicas gets the desired replicas of the machine pool
- buildGoogleIdp is responsible for creating an identity provider
- createRoles creates roles
- ParseUnknownFlags parses command - line flags .
rosa Key Features
rosa Examples and Code Snippets
go get -u github.com/openshift/rosa
cd $GOPATH/src/github.com/openshift/rosa
make install
sudo mv $GOPATH/bin/rosa /usr/local/bin
Community Discussions
Trending Discussions on rosa
QUESTION
I have two large-ish data frames I am trying to append...
In df1, I have state codes, county codes, state names (Alabama, Alaska, etc.), county names, and years from 2010:2020.
In df2, I have county names, state abbreviations (AL, AK), and data for the year 2010 (which I am trying to merge into df1. The issue lies in that without specifying the state name and simply merging df1 and df2, some of the data which I am trying to get into df1 is duplicated due to there being some counties with the same name...hence, I am trying to also join by state to prevent this, but I have state abbreviations, and state names.
Is there any way in which I can make either the state names in df1 abbreviations, or the state names in df2 full names? Please let me know! Thank you for the help.
Edit: dput(df2)
...ANSWER
Answered 2022-Apr-18 at 03:52Here's one way you could turn state abbreviations into state names using R's built in state vectors:
QUESTION
I have a data frame which looks like:
...ANSWER
Answered 2022-Apr-17 at 15:11Not the most elegant solution but this will work.
Basically we use the grouped data to add a row number then ungroup and filter out any row numbers that equal 1
QUESTION
So here is my code.
...ANSWER
Answered 2022-Apr-16 at 02:48import pandas as pd
data = pd.read_csv('cast.csv')
data_2 = data[data['type'] == 'actor']
output = data_2[data['name'].str.startswith('Aaron')]
print(output)
QUESTION
{
"query": {
"project": "all",
"images": [
"dc5f659df9a4bcf90fc109830564d821"
],
"organs": [
"leaf"
],
"includeRelatedImages": true
},
"language": "en",
"preferedReferential": "the-plant-list",
"bestMatch": "Hibiscus rosa-sinensis L.",
"results": [
{
"score": 0.92912,
"species": {
"scientificNameWithoutAuthor": "Hibiscus rosa-sinensis",
"scientificNameAuthorship": "L.",
"genus": {
"scientificNameWithoutAuthor": "Hibiscus",
"scientificNameAuthorship": "",
"scientificName": "Hibiscus"
},
"family": {
"scientificNameWithoutAuthor": "Malvaceae",
"scientificNameAuthorship": "",
"scientificName": "Malvaceae"
},
"commonNames": [
"Hawaiian hibiscus",
"Hibiscus",
"Chinese hibiscus"
],
"scientificName": "Hibiscus rosa-sinensis L."
},
"images": [
{
"organ": "leaf",
"author": "Tela Botanica − Antoine AFFOUARD",
"license": "cc-by-sa",
"date": {
"timestamp": 1413870558000,
"string": "October 21, 2014"
},
"url": {
"o": "https://bs.plantnet.org/image/o/1d562e3be39e3297e6bdcff60d5f7d3fabe04eef",
"m": "https://bs.plantnet.org/image/m/1d562e3be39e3297e6bdcff60d5f7d3fabe04eef",
"s": "https://bs.plantnet.org/image/s/1d562e3be39e3297e6bdcff60d5f7d3fabe04eef"
},
"citation": "Tela Botanica − Antoine AFFOUARD / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Antonio Sánchez Morales",
"license": "cc-by-sa",
"date": {
"timestamp": 1548682043000,
"string": "January 28, 2019"
},
"url": {
"o": "https://bs.plantnet.org/image/o/3abd84f086c90ed70306d950532f4e165f681bfe",
"m": "https://bs.plantnet.org/image/m/3abd84f086c90ed70306d950532f4e165f681bfe",
"s": "https://bs.plantnet.org/image/s/3abd84f086c90ed70306d950532f4e165f681bfe"
},
"citation": "Antonio Sánchez Morales / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "femenia mayra",
"license": "cc-by-sa",
"date": {
"timestamp": 1601041463219,
"string": "September 25, 2020"
},
"url": {
"o": "https://bs.plantnet.org/image/o/caa5ddc33d4b0b482b8c9f8ff8e0ba850d9af07f",
"m": "https://bs.plantnet.org/image/m/caa5ddc33d4b0b482b8c9f8ff8e0ba850d9af07f",
"s": "https://bs.plantnet.org/image/s/caa5ddc33d4b0b482b8c9f8ff8e0ba850d9af07f"
},
"citation": "femenia mayra / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Antonio Sánchez Morales",
"license": "cc-by-sa",
"date": {
"timestamp": 1544800115000,
"string": "December 14, 2018"
},
"url": {
"o": "https://bs.plantnet.org/image/o/8e2c190839ebbb1bb6ab7dd26cc413bb001080f4",
"m": "https://bs.plantnet.org/image/m/8e2c190839ebbb1bb6ab7dd26cc413bb001080f4",
"s": "https://bs.plantnet.org/image/s/8e2c190839ebbb1bb6ab7dd26cc413bb001080f4"
},
"citation": "Antonio Sánchez Morales / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "ire110",
"license": "cc-by-sa",
"date": {
"timestamp": 1599948160933,
"string": "September 12, 2020"
},
"url": {
"o": "https://bs.plantnet.org/image/o/394caf62b3ce20c47f005d425488806f138a8493",
"m": "https://bs.plantnet.org/image/m/394caf62b3ce20c47f005d425488806f138a8493",
"s": "https://bs.plantnet.org/image/s/394caf62b3ce20c47f005d425488806f138a8493"
},
"citation": "ire110 / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Andreas Vogelsinger",
"license": "cc-by-sa",
"date": {
"timestamp": 1579618800636,
"string": "January 21, 2020"
},
"url": {
"o": "https://bs.plantnet.org/image/o/cc9f39d17007bb5fd36b890cf0043a0a683352be",
"m": "https://bs.plantnet.org/image/m/cc9f39d17007bb5fd36b890cf0043a0a683352be",
"s": "https://bs.plantnet.org/image/s/cc9f39d17007bb5fd36b890cf0043a0a683352be"
},
"citation": "Andreas Vogelsinger / Pl@ntNet, cc-by-sa"
}
],
"gbif": {
"id": "3152559"
}
},
{
"score": 0.03652,
"species": {
"scientificNameWithoutAuthor": "Hibiscus schizopetalus",
"scientificNameAuthorship": "(Dyer) Hook.f.",
"genus": {
"scientificNameWithoutAuthor": "Hibiscus",
"scientificNameAuthorship": "",
"scientificName": "Hibiscus"
},
"family": {
"scientificNameWithoutAuthor": "Malvaceae",
"scientificNameAuthorship": "",
"scientificName": "Malvaceae"
},
"commonNames": [
"Campanilla",
"Chinese lantern",
"Japanese hibiscus"
],
"scientificName": "Hibiscus schizopetalus (Dyer) Hook.f."
},
"images": [
{
"organ": "leaf",
"author": "nanni pri",
"license": "cc-by-sa",
"date": {
"timestamp": 1619808048797,
"string": "April 30, 2021"
},
"url": {
"o": "https://bs.plantnet.org/image/o/4ca16c7045b6b2e56cbbc0f4afed08ddc3f556f7",
"m": "https://bs.plantnet.org/image/m/4ca16c7045b6b2e56cbbc0f4afed08ddc3f556f7",
"s": "https://bs.plantnet.org/image/s/4ca16c7045b6b2e56cbbc0f4afed08ddc3f556f7"
},
"citation": "nanni pri / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "sharlaine bustamants",
"license": "cc-by-sa",
"date": {
"timestamp": 1591247217009,
"string": "June 4, 2020"
},
"url": {
"o": "https://bs.plantnet.org/image/o/c4722a732fef3bfd1eab6d6d80b500bb036e5215",
"m": "https://bs.plantnet.org/image/m/c4722a732fef3bfd1eab6d6d80b500bb036e5215",
"s": "https://bs.plantnet.org/image/s/c4722a732fef3bfd1eab6d6d80b500bb036e5215"
},
"citation": "sharlaine bustamants / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Hugo SANTACREU",
"license": "cc-by-sa",
"date": {
"timestamp": 1531233524000,
"string": "July 10, 2018"
},
"url": {
"o": "https://bs.plantnet.org/image/o/3ddba92c55e30e0cb70b10feb1cd021190dfec76",
"m": "https://bs.plantnet.org/image/m/3ddba92c55e30e0cb70b10feb1cd021190dfec76",
"s": "https://bs.plantnet.org/image/s/3ddba92c55e30e0cb70b10feb1cd021190dfec76"
},
"citation": "Hugo SANTACREU / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Pierre Bonnet",
"license": "cc-by-sa",
"date": {
"timestamp": 1534366939000,
"string": "August 15, 2018"
},
"url": {
"o": "https://bs.plantnet.org/image/o/f68ad5f10d76837924537d560cbb62b6cb4003c5",
"m": "https://bs.plantnet.org/image/m/f68ad5f10d76837924537d560cbb62b6cb4003c5",
"s": "https://bs.plantnet.org/image/s/f68ad5f10d76837924537d560cbb62b6cb4003c5"
},
"citation": "Pierre Bonnet / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "Tobias Jacobsen",
"license": "cc-by-sa",
"date": {
"timestamp": 1571130043838,
"string": "October 15, 2019"
},
"url": {
"o": "https://bs.plantnet.org/image/o/44da8a021cfe8dcc1004a2998ff13982cce545f3",
"m": "https://bs.plantnet.org/image/m/44da8a021cfe8dcc1004a2998ff13982cce545f3",
"s": "https://bs.plantnet.org/image/s/44da8a021cfe8dcc1004a2998ff13982cce545f3"
},
"citation": "Tobias Jacobsen / Pl@ntNet, cc-by-sa"
},
{
"organ": "leaf",
"author": "abderrahim Lamari",
"license": "cc-by-sa",
"date": {
"timestamp": 1619785453625,
"string": "April 30, 2021"
},
"url": {
"o": "https://bs.plantnet.org/image/o/e669d09a54681d3d56fabfb588d3ecb50b523490",
"m": "https://bs.plantnet.org/image/m/e669d09a54681d3d56fabfb588d3ecb50b523490",
"s": "https://bs.plantnet.org/image/s/e669d09a54681d3d56fabfb588d3ecb50b523490"
},
"citation": "abderrahim Lamari / Pl@ntNet, cc-by-sa"
}
],
"gbif": {
"id": "9064581"
}
}
],
"version": "2022-02-14 (5.0)",
"remainingIdentificationRequests": 491
}
...ANSWER
Answered 2022-Mar-31 at 08:46Here I am sharing "Deserialize your JSON string into Java objects in four different ways". There are a lot of other java JSON libraries.
1. Using Moshi
2. Using Jackson
3. Using Gson
4. Using Genson
"Remember - The POJOs in java are useful in defining objects to increase their readability and reusability."
We'll use the following Root class with multiple fields as the object to deserialize throughout.
Root.javaQUESTION
I have this JSON response that I get by using GuzzleHttp, this is my controller
...ANSWER
Answered 2022-Mar-19 at 04:12you have returned $news;
before returning view.Also you are accessing object but returned array.Here is the complete code
QUESTION
I'm trying to retrieve wikipedia pages' characters count, for articles in different languages. I'm using a dictionary with as key the name of the page and as value a dictionary with the language as key and the count as value.
The code is:
...ANSWER
Answered 2022-Mar-15 at 14:14Please try this code. I didn't run it because I don't have the wikipedia module.
Notes:
- Since your expected result is
dict[page,dict[lan,cnt]]
, I think first iterate pages is more natural, then iterate languages. Maybe for performance reason you want first iterate languages, please comment. - Characters count of
text
can simply belen(text)
, why iterate and sum again? - Variable names. You will soon be lost in
x
y
like variables.
QUESTION
I want to get a count of how many times each Player's name appears in my data frame ph1
. My code is showing how many times each name is in the dataset, but I cannot group it by n
so I can see how many times each Player's name is in the dataset.
I would prefer a dplyr solution but am open to others.
For example:
...ANSWER
Answered 2022-Feb-13 at 17:12ph %>%
filter(!is.na(Player)) %>%
group_by(Player) %>% count() %>%
group_by(n) %>%
count(name="Number_Players")
# A tibble: 2 x 2
# Groups: n [2]
n Number_Players
1 1 21
2 2 2
QUESTION
I'm trying to avoid duplicates and not be allowed to add empty items. If I send the same titolo (example, Harry Potter) again, I don't want it to be added to the $scope.libri for the second time. How can I check it before adding? This is my code now:
angular .module('myApp', []) .controller('myCtr', function ($scope){
...ANSWER
Answered 2021-Nov-29 at 15:15Just use $scope.libri.find(x => x.titolo === $scope.titolo)
in your add function before pushing to the array.
QUESTION
If the table have only two columns with employee name and their supervisor column and if it doesn't have any other numeric or number column with employee_number or employee_id, then how the results can be produced. I'm not getting logic to show the results.
Code for creating table in Mysql:
...ANSWER
Answered 2021-Nov-19 at 02:23For this particular set of data, it can LEFT JOIN
the table itself to get the expected results
QUESTION
I'm tying a LAG function to retrieve the last non null value from the table to replace the null values in a row. The code I'm using:
...ANSWER
Answered 2021-Oct-27 at 10:28I don't see any test data to play with, so here is an simple example
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install rosa
Follow the AWS Command Line Interface documentation to install and configure the AWS CLI for your operating system.
Download the latest release of rosa and add it to your path.
Initialize your AWS account by running rosa init and following the instructions.
Create your first ROSA cluster by running rosa create cluster --interactive
If you'd like to build this project from source use the following steps:.
Checkout the repostiory into your $GOPATH
cd to the checkout out source directory
Install the binary (This will install to $GOPATH/bin)
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