atlantis | Terraform Pull Request Automation | Continous Integration library
kandi X-RAY | atlantis Summary
kandi X-RAY | atlantis Summary
A self-hosted golang application that listens for Terraform pull request events via webhooks.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of atlantis
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Trending Discussions on atlantis
QUESTION
I currently have a dictionary where the values are:
...ANSWER
Answered 2022-Apr-07 at 17:45You're not that far off. In your for-loop you iterate over values of the dict, but you want to iterate over the titles. Also the string slicing syntax is [id1:id2]. So this would probably do what you are looking for:
QUESTION
I'm trying to set Lighthouse CI
Authentication using Terraform
K8s
Deployment(https://github.com/GoogleChrome/lighthouse-ci/blob/main/docs/server.md#basic-authentication) but I keep getting a 403
Error. I have tried below steps but I get the same message.
FYI, the password
is set from kubectl_manifest
resourece
- Using Terraform Set
ENV
fromkubernetes_deployment
resource
ANSWER
Answered 2022-Mar-23 at 19:47This may be specific to my case but I went with the first approach and changed the http_get
path for readiness_probe
from /
to /healthz
. The issue got fixed.
e.g.
QUESTION
https://www.canparkavm.com.tr/tr/markalar
As i said at title, how can i access/convert JavaScript variable as JSON value on Python using the BeautifulSoup
and requests
libraries?
I tried this topic for solve my problem but did not worked actually: Extract JSON from HTML Script tag with BeautifulSoup in Python
...ANSWER
Answered 2022-Mar-22 at 03:16You need to find a suitable regex pattern to grab that content. One such is as follows:
QUESTION
print(df.sample(50)):
match_datetime country league home_team away_team home_odds draw_odds away_odds run_time home_score away_score
72170 2021-10-17 12:30:00 Ukraine Persha Liga Alliance Uzhhorod 1.22 5.62 9.71 2021-10-17 09:22:20.212731 NaN NaN
100398 2021-11-02 14:35:00 Saudi Arabia Division 1 Al Qadisiya Bisha 1.61 3.61 4.94 2021-11-02 09:13:18.768604 2.0 1.0
33929 2021-09-11 23:00:00 Panama LPF Veraguas Plaza Amador 2.75 2.75 2.71 2021-09-10 23:47:54.682982 1.0 1.0
12328 2021-08-15 15:30:00 Poland Ekstraklasa Slask Wroclaw Leczna 1.74 3.74 4.59 2021-08-14 22:44:26.136608 0.0 0.0
81500 2021-10-24 13:00:00 Italy Serie D - Group A Caronnese Saluzzo 1.69 3.60 4.28 2021-10-23 13:37:16.920175 2.0 2.0
143370 2021-12-05 14:00:00 Poland Division 1 Chrobry Glogow Widzew Lodz 3.36 3.17 2.15 2021-11-30 17:40:24.833519 0.0 0.0
175061 2022-01-08 18:00:00 Spain Primera RFEF - Group 1 R. Union Extremadura UD 1.26 4.40 18.00 2022-01-08 17:00:46.662761 0.0 1.0
21293 2021-08-29 16:00:00 Italy Serie B Cittadella Crotone 2.32 3.11 3.31 2021-08-26 18:04:46.221393 4.0 2.0
97427 2021-11-01 17:00:00 Israel Leumit League M. Nazareth Beitar Tel Aviv 1.92 3.26 3.75 2021-10-30 09:40:08.966330 4.0 2.0
177665 2022-01-13 12:30:00 Egypt Division 2 - Group C Said El Mahalla Al Magd 4.12 3.08 1.94 2022-01-12 17:53:33.570126 0.0 0.0
69451 2021-10-17 05:00:00 South Korea K League 1 Gangwon Gwangju FC 2.06 3.38 3.65 2021-10-15 09:55:54.578112 NaN NaN
4742 2021-08-10 20:30:00 Peru Liga 2 Deportivo Coopsol Grau 3.14 3.49 2.06 2021-08-10 18:14:01.996860 0.0 2.0
22266 2021-08-29 13:00:00 France Ligue 1 Angers Rennes 2.93 3.27 2.56 2021-08-27 12:26:34.904374 2.0 0.0
46412 2021-09-26 04:00:00 Japan J2 League Okayama Blaublitz 2.24 2.90 3.63 2021-09-23 09:08:26.979783 1.0 1.0
133207 2021-11-27 21:15:00 Bolivia Division Profesional Palmaflor Blooming 1.51 4.05 5.10 2021-11-25 18:22:28.275844 3.0 0.0
140825 2021-11-28 11:00:00 Spain Tercera RFEF - Group 6 Valencia B Torrellano 1.58 3.56 5.26 2021-11-28 19:54:40.066637 2.0 0.0
226985 2022-03-04 00:30:00 Argentina Copa de la Liga Profesional Central Cordoba Rosario Central 2.36 3.26 2.86 2022-03-02 17:23:10.014424 0.0 1.0
137226 2021-11-28 12:45:00 Greece Super League 2 Apollon Pontou PAOK B 3.37 3.25 2.01 2021-11-27 15:13:05.937815 0.0 3.0
182756 2022-01-22 10:30:00 Turkey 1. Lig Umraniyespor Menemenspor 1.40 4.39 7.07 2022-01-19 17:25:27.128331 2.0 1.0
89895 2021-10-28 16:45:00 Netherlands KNVB Beker Ajax Cambuur 9.10 5.55 1.26 2021-10-27 07:46:56.253996 0.0 5.0
227595 2022-03-06 17:00:00 Israel Ligat ha'Al Ashdod Maccabi Petah Tikva 2.30 3.21 3.05 2022-03-02 17:23:10.014424 NaN NaN
57568 2021-10-02 13:00:00 Estonia Meistriliiga Kalju Legion 1.58 4.10 4.84 2021-10-02 10:55:35.287359 2.0 2.0
227035 2022-03-04 19:00:00 Denmark Superliga FC Copenhagen Randers FC 1.70 3.84 5.06 2022-03-02 17:23:10.014424 NaN NaN
108668 2021-11-07 13:30:00 Germany Oberliga Mittelrhein Duren Freialdenhoven 1.35 5.20 6.35 2021-11-06 17:37:37.629603 2.0 0.0
86270 2021-10-25 18:00:00 Belgium Pro League U21 Lommel SK U21 Lierse K. U21 3.23 3.84 1.92 2021-10-26 01:22:31.111441 0.0 0.0
89437 2021-11-01 02:10:00 Colombia Primera A America De Cali Petrolera 1.86 2.92 4.60 2021-10-27 07:41:24.427246 NaN NaN
13986 2021-08-21 13:00:00 France Ligue 2 Dijon Toulouse 3.92 3.51 1.94 2021-08-16 13:22:02.749887 2.0 4.0
105179 2021-11-06 15:00:00 England NPL Premier Division Atherton South Shields 3.90 3.42 1.82 2021-11-05 10:01:28.567328 1.0 1.0
142821 2021-12-01 12:30:00 Bulgaria Vtora liga Marek Septemvri Simitli 1.79 3.38 4.35 2021-11-30 17:40:24.833519 2.0 2.0
45866 2021-09-24 00:30:00 Venezuela Primera Division Dep. Tachira Portuguesa 1.96 3.60 3.22 2021-09-23 09:08:26.979783 4.0 1.0
76100 2021-10-22 16:30:00 Denmark 1st Division Hvidovre IF Koge 1.91 3.56 3.81 2021-10-21 08:43:12.445245 NaN NaN
115896 2021-11-14 16:00:00 Spain Tercera RFEF - Group 6 Olimpic Xativa Torrellano 2.78 2.89 2.39 2021-11-13 12:21:45.955738 1.0 0.0
156159 2021-12-12 16:00:00 Spain Segunda RFEF - Group 1 Marino de Luanco Coruxo FC 2.19 3.27 3.07 2021-12-10 09:26:45.001977 0.0 0.0
18240 2021-08-21 12:00:00 Germany Regionalliga West Rodinghausen Fortuna Koln 3.25 3.60 2.00 2021-08-21 03:30:43.193978 NaN NaN
184913 2022-01-22 10:00:00 World Club Friendly Zilina B Trinec 3.56 4.14 1.78 2022-01-22 16:44:32.650325 0.0 3.0
16782 2021-08-22 23:05:00 Colombia Primera A Petrolera Dep. Cali 3.01 3.00 2.44 2021-08-19 18:24:24.966505 2.0 3.0
63847 2021-10-10 09:30:00 Spain Tercera RFEF - Group 7 Carabanchel RSD Alcala 4.39 3.42 1.75 2021-10-09 12:03:50.720013 NaN NaN
7254 2021-08-12 16:45:00 Europe Europa Conference League Hammarby Cukaricki 1.72 3.87 4.13 2021-08-11 23:48:31.958394 NaN NaN
82727 2021-10-24 14:00:00 Lithuania I Lyga Zalgiris 2 Neptunas 1.76 3.78 3.35 2021-10-24 12:02:06.306279 1.0 3.0
43074 2021-09-22 18:00:00 Ukraine Super Cup Shakhtar Donetsk Dyn. Kyiv 2.57 3.49 2.59 2021-09-19 09:39:56.624504 NaN NaN
65187 2021-10-11 18:45:00 World World Cup Norway Montenegro 1.56 4.17 6.28 2021-10-11 10:56:09.973470 NaN NaN
120993 2021-11-18 00:00:00 USA NISA Maryland Bobcats California Utd. 2.76 3.23 2.39 2021-11-17 20:36:26.562731 1.0 1.0
201469 2022-02-12 15:00:00 England League One AFC Wimbledon Sunderland 3.30 3.48 2.17 2022-02-10 17:47:36.501159 1.0 1.0
142180 2021-12-01 19:45:00 Scotland Premiership St. Mirren Ross County 2.06 3.25 3.85 2021-11-29 18:28:22.249662 0.0 0.0
4681 2021-08-10 18:30:00 Europe Champions League Young Boys CFR Cluj 1.48 4.29 6.92 2021-08-10 18:14:01.996860 3.0 1.0
67321 2021-10-17 13:00:00 Spain LaLiga Rayo Vallecano Elche 1.78 3.64 4.99 2021-10-13 11:22:34.979378 NaN NaN
27499 2021-09-04 14:00:00 Iceland Inkasso-deildin Kordrengir Fjolnir 2.18 3.66 2.82 2021-09-02 23:28:49.414126 1.0 4.0
48962 2021-09-25 21:00:00 Mexico Liga Premier Serie B Uruapan Lobos Huerta 1.83 3.69 3.70 2021-09-25 13:02:58.238466 NaN NaN
65636 2021-10-16 17:00:00 Switzerland Super League Young Boys Luzern 1.26 6.04 9.43 2021-10-11 10:56:09.973470 NaN NaN
17333 2021-08-21 14:00:00 Finland Kakkonen Group A Atlantis Kiffen 1.57 4.29 4.42 2021-08-20 12:41:03.159846 1.0 1.0
...ANSWER
Answered 2022-Mar-05 at 01:38If I understand correctly, you would like to filter the dataframe to retain, for each run_time
, the last two rows (or up to two rows) by match_datetime
.
Simplified answer
This can be done relatively easily without any join, using GroupBy.tail()
. (Note, my original answer was using GroupBy.rank()
, but this is simpler, although slower):
QUESTION
I have this dataframe of 11527 rows in csv format constitued of a list of marks and models of boats
...ANSWER
Answered 2022-Mar-02 at 19:53Having the following DataFrame
QUESTION
I'm trying to enable basic auth for atlantis
I have followed the official docs here however it seems the below settings are not honored by atlantis
ANSWER
Answered 2022-Feb-09 at 16:37According to https://github.com/runatlantis/atlantis/releases/tag/v0.18.2 version v0.18.2
has fixed issue with basic auth
fix: add back basic auth support by @Aayyush in #2008
QUESTION
Suppose the following piece of code:
...ANSWER
Answered 2021-Oct-19 at 15:17Global variables can be a little bit wonky in intelephense, an issue already exists to improve the support. In this specific case, the type that is inferred is determined by the first assignment. Since that is the explode statement, it'll assume $dest
is an array of strings.
There are a couple of solutions to this:
Make sure to intelephense what the type of
$dest
is with comments.
QUESTION
I'm trying to run schtasks with exec() but always get an access denied error as response.
On my local win10 machine it works seamlessly but on windows server 2019 the scrip exits with the error. I found serveral similar questions but wether they had no answeer or the given answer didn't work for my specific problem. Unfortunately the error doesn't specify WHO is missing permition to WHAT. So i tryed giving the IUSR and the IIS_USERS access to the cmd.exe, the schtasks.exe and the taks folder (C:\Windows\System32\Tasks) according to some other answers.
My code example:
...ANSWER
Answered 2021-Nov-26 at 07:33Eventually i could find the missing permission with some help. The IUSR was missing access to the C:\Windows\ SysWOW64 \schtasks.exe but i tried giving it access to the C:\Windows\ System32 \schtasks.exe before. So after giving the IUSR read and execute privileges for the C:\Windows\ SysWOW64 \schtasks.exe everything works as expected.
QUESTION
The job given to me was to edit the query, but I could not do the operation I wanted. First of all, the query output I want to explain is as follows:
...ANSWER
Answered 2021-Nov-22 at 09:34I think you should delete from your query:
- Distinct - there is no point in having "group by" and "distinct".
- g.BrutPrice and g.NetPrice from the group by. If you have them in group by there is no point to use aggregation function such as "sum" on them.
so:
QUESTION
So, I have a pandas data frame where one column contains the description of the nationality of a user and I want to replace this whole description with the country he's from.
My inputs are the df and the list of countries:
Description ID I am from Atlantis 1 My family comes from Narnia 2 ...ANSWER
Answered 2021-Aug-28 at 09:04You can use pd.Series.str.extract
:
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