jira | Development | Command Line Interface library
kandi X-RAY | jira Summary
kandi X-RAY | jira Summary
Python Jira library. Development chat available on https://matrix.to/#/#pycontribs:matrix.org
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Top functions reviewed by kandi - BETA
- Update the JIRA
- Creates a new user
- Convert a dict to a ResourceHolder
- Parse Jira error message
- Raise a JIRAError
- Load a resource from the API
- Extracts the error list from the response
- Safely parse response
- Parse raw data into resource
- Return the Resource class for a resource
- Get configuration options
- Process config file
- Process command line arguments
- Get Jira instance
- Get file content
- Add user to JIRA
- Perform OAuth request
- Handle basic authentication
jira Key Features
jira Examples and Code Snippets
Lines of Code : 10License : Strong Copyleft (GPL-3.0)
CopyCREATE DATABASE jira_source
WITH
engine='Jira',
parameters={
"jira_url": "https://jira.linuxfoundation.org",
"user_id": "balaceg",
"api_key": "4Rhq&Ehd#KV4an!",
"jira_query": "project = RELENG and status != Done"
};
SELECT * FROM COMMAND THAT YOU RAN TO CREATE DATABASE.
COMMAND THAT YOU RAN TO CREATE PREDICTOR.
COMMAND THAT YOU RAN TO DO A SELECT FROM.
private JiraRestClient getJiraRestClient() {
return new AsynchronousJiraRestClientFactory()
.createWithBasicHttpAuthentication(getJiraUri(), this.username, this.password);
} private URI getJiraUri() {
return URI.create(this.jiraUrl);
} import json
def dict_to_json_file(some_dict, file_name):
fp = open(file_name, 'w+)
fp.write(json.dumps(some_dict))
fp.close()
def json_file_to_dict(file_name):
fp = open(file_name, 'r+)
some_dict = json.loads(fp.read(jira_token = os.environ.get()
jira_server = {"server": "https://issues.mycompany.com/"}
auth_jira = JIRA(options = jira_server, token_auth = jira_token)
$(document).ready(function() {
$.fn.dataTable.moment( 'HH:mm MMM D, YY' );
...
JavaScript: 3
C#: 9
Visual studio: 2
Docker: 4
Azure: 4
AngularJs: 2
Java: 3
Visual Studio: 5
tech_count = {'JavaScript': 3, 'Visual studio': 2, 'Visual Studio': 5, 'Javascript': 5}
consolidated = d>>> pd.json_normalize(d['histories'], 'items', 'created')
field fieldtype from fromString to toString created
0 Link jira NaN None This issue child-of 2Community Discussions
Trending Discussions on jira
QUESTION
I am trying to validate a string the way it is done in Jira in Javascript. I'm trying to replicate how it is validated in Jira. I am guessing I could do this with Regex but I am not sure how.
A user can type a string in the format of "1d 6h 30m" which would mean 1 day, 6 hours, 30 minutes. I do not need the weeks for my use case. I want to show an error if the user uses an invalid character (anything except 'd','h','m', or ' '). Also the string must separate the time durations by spaces and ideally I would like to force the user to enter the time durations in descending order meaning '6h 1d' would be invalid because the days should come first. Also the user does not have to enter all information so '30m' would be valid.
This is my code for getting the days, hours and minutes which seems to work. I just need help with the validation part.
...ANSWER
Answered 2022-Apr-14 at 16:30Based on your comment, I have added a validation regex to be run first before running the match regex.
For validation, you want
QUESTION
I need to create a new branch, from the existing branch using the git checkout and option start-point but I am not sure how I can determine it properly.
from git log I need to find a commit which has specific transaction number in the message.
E.g. from git log
ANSWER
Answered 2022-Mar-21 at 18:02To find a revision that has a certain message you do:
QUESTION
Update: the root issue was a bug which was fixed in Spark 3.2.0.
Input df structures are identic in both runs, but outputs are different. Only the second run returns desired result (df6). I know I can use aliases for dataframes which would return desired result.
The question. What is the underlying Spark mechanics in creating df3? Spark reads df1.c1 == df2.c2 in the join's on clause, but it's evident that it does not pay attention to the dfs provided. What's under the hood there? How to anticipate such behaviour?
First run (incorrect df3 result):
ANSWER
Answered 2021-Sep-24 at 16:19Spark for some reason doesn't distinguish your c1 and c2 columns correctly. This is the fix for df3 to have your expected result:
QUESTION
Mongo appears to be returning duplicate documents for the same query, i.e. it returns more documents than there are unique _ids in the returned documents:
ANSWER
Answered 2022-Feb-09 at 13:59Try checking if you store indexes for a_boolean_key field.
When performing a
count, MongoDB can return the count using only the index
So, maybe you don't have indexes for all documents, so count method result is not equal to your manual count.
QUESTION
I am trying to bring in JIRA data into Foundry using an external API. When it comes in via Magritte, the data gets stored in AVRO and there is a column called response. The response column has data that looks like this...
...ANSWER
Answered 2021-Aug-31 at 13:08Parsing Json in a string column to a struct column (and then into separate columns) can be easily done using the F.from_json function.
In your case, you need to do:
QUESTION
I am using Husky to set my git hooks, and am trying to change to default format of the header expected by Commitlint:
...ANSWER
Answered 2022-Jan-10 at 07:48This should work for :gitmoji:? [scope] subject
QUESTION
Using Python on an Azure HDInsight cluster, we are saving Spark dataframes as Parquet files to an Azure Data Lake Storage Gen2, using the following code:
...ANSWER
Answered 2021-Dec-17 at 16:58ABFS is a "real" file system, so the S3A zero rename committers are not needed. Indeed, they won't work. And the client is entirely open source - look into the hadoop-azure module.
the ADLS gen2 store does have scale problems, but unless you are trying to commit 10,000 files, or clean up massively deep directory trees -you won't hit these. If you do get error messages about Elliott to rename individual files and you are doing Jobs of that scale (a) talk to Microsoft about increasing your allocated capacity and (b) pick this up https://github.com/apache/hadoop/pull/2971
This isn't it. I would guess that actually you have multiple jobs writing to the same output path, and one is cleaning up while the other is setting up. In particular -they both seem to have a job ID of "0". Because of the same job ID is being used, what only as task set up and task cleanup getting mixed up, it is possible that when an job one commits it includes the output from job 2 from all task attempts which have successfully been committed.
I believe that this has been a known problem with spark standalone deployments, though I can't find a relevant JIRA. SPARK-24552 is close, but should have been fixed in your version. SPARK-33402 Jobs launched in same second have duplicate MapReduce JobIDs. That is about job IDs just coming from the system current time, not 0. But: you can try upgrading your spark version to see if it goes away.
My suggestions
- make sure your jobs are not writing to the same table simultaneously. Things will get in a mess.
- grab the most recent version spark you are happy with
QUESTION
I am using the following code and I am trying to print the following code into HTML:
...ANSWER
Answered 2021-Dec-14 at 18:31You can use regular expression with two capturing groups. The first one will match the color and the second one will get the message. Then you can replace whole matched text with
... .
So after def body = comment.body use this code:
QUESTION
Using mysql(v8.0.21) image with mac docker-desktop (v4.2.0, Docker-Engine v20.10.10)
As soon service up:
- entrypoints ready
- innoDB initialization done
- ready for connection
But as soon try to run the direct script(query) it crashes, refused to connect (also from phpmyadmin) and restarted again.
In the logs we are able to see an Error:
[ERROR] [MY-011947] [InnoDB] Cannot open '/var/lib/mysql/ib_buffer_pool' for reading: No such file or directory
The error we are able to see into log is not an issue, as it is fixed and updated by InnoDB already, here is the reference below:
Note: docker-compose file we are pretty much sure that, there is no error as same is working fine for windows as well ubuntu, but the issue is only for macOS.
...ANSWER
Answered 2021-Dec-14 at 08:17Thanks @NicoHaase and @Patrick for going through the question and suggestions.
Found the reason for connection refused and crashing, posting answer so that it maybe helpful for others.
It was actually due to docker-desktop macOS client there was by default 2GB Memory was allocated as Resource, and for our scenario it was required more than that.
We just allocate more memory according to our requirement and it was just started working perfectly fine.
For resource allocation:
QUESTION
I'm trying to specify a set of tests by fully qualified package name, using Maven 3.6.3 with maven-surefire-plugin 3.0.0-M5 on OpenJDK 11. The documentation states...
As of Surefire Plugin 2.19.1, the syntax with fully qualified class names or packages can be used
...and goes on to give an example:
...ANSWER
Answered 2021-Oct-20 at 09:10To be honest, this looks like a bug in maven-surefire-plugin, or at best some behavior change that isn't documented properly.
I took the sample you posted to GitHub, downgraded it to maven-surefire-plugin 2.19.1, and it works just fine.
You may want to report this bug Apache's Jira.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install jira
You can use jira like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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