actuary | business professional | Continuous Deployment library

by diogomonica Go Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | actuary Summary

actuary is a Go library typically used in Devops, Continuous Deployment, Docker applications. actuary has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

An actuary is a professional who analyzes the financial consequences of risk. Docker's Actuary is an application that checks for dozens of common best-practices around deploying Docker containers in production. Actuary takes in a checklist of items to check, and automates the running, inspecting and aggregation of the results. Actuary is an evolution of DockerBench, with a focus on the creation, sharing and reuse of different security profiles by the Docker security community. Go to dockerbench.com, if you wish to view, share or create your own profiles.

Support

Quality

Security

License

Reuse

Support

actuary has a low active ecosystem.

It has 65 star(s) with 11 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 13 have been closed. On average issues are closed in 32 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of actuary is current.

Quality

actuary has no bugs reported.

Security

actuary has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

actuary does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

actuary releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed actuary and discovered the below as its top functions. This is intended to give you an instant insight into actuary implemented functionality, and help decide if they suit your requirements.

CheckRegistryCertPerms verifies registry certificate files
CheckRegistryCertOwner verifies that the registry certificate file is valid
CheckImageSprawl returns true if there are any images in the target container .
CheckTrustedUsers returns a list of trusted users
CheckSSHRunning checks if the passed target is running
basicAuth returns a string containing the HTTP Basic Auth header .
CheckSensitiveDirs verifies that the target directory contains sensitive directories .
CheckContainerUser checks the user to see if the containers are running
CheckContainerSprawl returns true if there are any running containers running .
Check Separate partition

Get all kandi verified functions for this library.

actuary Key Features

No Key Features are available at this moment for actuary.

actuary Examples and Code Snippets

No Code Snippets are available at this moment for actuary.

Community Discussions

Trending Discussions on actuary

Count distinct of a column based on 2 variables of another column in SQL

Flutter - TextField auto complete suggestions from SQLite

Python: IF statement consisting of data frame and list

awk: print range of fields if other field matches value

Python 3.7: Error while sending a file through python socket

How to find duplicate values in a column and copy paste the rows found duplicated [VBA]

Displaying JSON in table with JQuery

AWS Glue fail to write parquet, out of memory

Why does $post not work but $ajax works on the asp.net web api controller?

Nested array response in JSON returning only last row from Mysql table

QUESTION

Count distinct of a column based on 2 variables of another column in SQL

Asked 2021-May-19 at 21:29

How to get Count distinct of a column based on 2 variables of another column in SQL?

EX:

...

ANSWER

Answered 2021-May-19 at 21:08

here is one way :

Source https://stackoverflow.com/questions/67610627

QUESTION

Flutter - TextField auto complete suggestions from SQLite

Asked 2020-Dec-14 at 14:11

I am trying to create an autocomplete TextField. This one is working when I used the below hardcoded List.

...

ANSWER

Answered 2020-Dec-13 at 14:47

Assuming that this code is within your DBManager class:

Source https://stackoverflow.com/questions/65267434

QUESTION

Python: IF statement consisting of data frame and list

Asked 2020-Apr-13 at 15:40

I am very new to python and require help. I have a list of keywords which was obtained from a data frame as follows: key_a_list = df_key_words['words'].tolist()

I have a second data frame which consists of statements: df_response['statement'] I have already corrected spelling errors, tokenised and stemmed the text in the df_response['statement'] column. I need to check if there are any words in the key_a_list that match words in the df_response['statement']; then I must set a counter to count the number of times a word from the key_a_list is present in the df_response['statement'].

Thank you for your time and help, it is greatly appreciated :)

This is the current code that I have but it gives me an error: ValueError: Lengths must match to compare

...

ANSWER

Answered 2020-Apr-13 at 15:01

I think you want to change the key_a_list in your if statement to "x" as x holds each word in key_a_list that the loop is iterating through. Next, you can use the keyword "in" to check if x is in df_response["statement"] and count up if it is.

Also, you can define count_a inside the function so it's not a global variable to avoid reset it each time you run the function count(x) instead of adding to the existing counter.

I think it should work this way, please more experienced members correct me if I'm wrong:

Source https://stackoverflow.com/questions/61190532

QUESTION

awk: print range of fields if other field matches value

Asked 2019-Nov-04 at 19:46

I have a file with a very old format. Here's a couple of lines of examples:

...

ANSWER

Answered 2019-Nov-04 at 12:59

Could you please try following.

Source https://stackoverflow.com/questions/58693215

QUESTION

Python 3.7: Error while sending a file through python socket

Asked 2019-Jul-09 at 20:46

Using Python, I want to publish data to socket.
I written a client/server program in Python 3.7 to send a large csv file over the network. The client and server codes are given below.

Sample file:

...

ANSWER

Answered 2019-Jul-09 at 20:46

l is a bytes object. From the documentation:

While bytes literals and representations are based on ASCII text, bytes objects actually behave like immutable sequences of integer

So when you write for line in l:, each value of line is a integer containing a single byte from the file. The argumentg to s.send() has to be bytes, not an integer. So you could use:

Source https://stackoverflow.com/questions/56960081

QUESTION

How to find duplicate values in a column and copy paste the rows found duplicated [VBA]

Asked 2019-Jun-07 at 07:13

The problem is that there are duplicated values in the first column (ISIN numbers of financial products), but different characteristics in the other columns (i.e. different product name, different modified duration etc.) where should be the same characteristics.

I wanted to find ISIN numbers that already exist in my first column (at least two times), then take specific elements from the other columns (of the same row that was found the duplicated value) such as issuer name, modified duration etc. and paste them to the other's ISIN elements in order to report the same elements (data in other columns) in case where ISIN numbers are the same. I also wanted to compare the modified duration of these duplicated products and take the bigger one (for conservative reasons, because these data are used in further calculations).

...

ANSWER

Answered 2019-Jun-06 at 12:53

Without changing anything you've done (as after all you say it works), you could try disabling some of the automatic features of Excel before you call your sub:

Source https://stackoverflow.com/questions/56477684

QUESTION

Displaying JSON in table with JQuery

Asked 2019-Apr-24 at 09:16

Before, a button was clicked retrieving a template and context data from a Django view and rendering it like this:

...

ANSWER

Answered 2019-Apr-24 at 07:09

See below the implementation. It works.

Source https://stackoverflow.com/questions/55824067

QUESTION

AWS Glue fail to write parquet, out of memory

Asked 2019-Jan-29 at 17:56

I think AWS Glue is running out of memory after failing to write parquet output ...

An error occurred while calling o126.parquet. Job aborted due to stage failure: Task 82 in stage 9.0 failed 4 times, most recent failure: Lost task 82.3 in stage 9.0 (TID 17400, ip-172-31-8-70.ap-southeast-1.compute.internal, executor 1): ExecutorLostFailure (executor 1 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 5.5 GB of 5.5 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead.

More complete log below

Traceback (most recent call last): File "script_2019-01-29-06-53-53.py", line 71, in .parquet("s3://.../flights2") File "/mnt/yarn/usercache/root/appcache/application_1548744646207_0001/container_1548744646207_0001_01_000001/pyspark.zip/pyspark/sql/readwriter.py", line 691, in parquet File "/mnt/yarn/usercache/root/appcache/application_1548744646207_0001/container_1548744646207_0001_01_000001/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in call File "/mnt/yarn/usercache/root/appcache/application_1548744646207_0001/container_1548744646207_0001_01_000001/pyspark.zip/pyspark/sql/utils.py", line 63, in deco File "/mnt/yarn/usercache/root/appcache/application_1548744646207_0001/container_1548744646207_0001_01_000001/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o126.parquet. : org.apache.spark.SparkException: Job aborted. at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply$mcV$sp(FileFormatWriter.scala:213) at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:166) at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:166) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:166) at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:145) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56) at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117) at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92) at org.apache.spark.sql.execution.datasources.DataSource.writeInFileFormat(DataSource.scala:435) at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:471) at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:50) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56) at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:117) at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:138) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:135) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:116) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:92) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:92) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:609) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:233) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:217) at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:508) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:280) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:214) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 82 in stage 9.0 failed 4 times, most recent failure: Lost task 82.3 in stage 9.0 (TID 17400, ip-172-31-8-70.ap-southeast-1.compute.internal, executor 1): ExecutorLostFailure (executor 1 exited caused by one of the running tasks) Reason: Container killed by YARN for exceeding memory limits. 5.5 GB of 5.5 GB physical memory used. Consider boosting spark.yarn.executor.memoryOverhead. Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029) at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply$mcV$sp(FileFormatWriter.scala:186)

It appears the failing line is:

...

ANSWER

Answered 2019-Jan-29 at 17:56

If ur LEFT JOIN has 1:N mapping it will result into exponentially large rows in DF which may cause OOM. In glue, there is no provision to setup your own infra configuration e.g. 64GB memory per vCPU. If that is case, first try using spark.yarn.executor.memoryOverhead option or/and increasing DPUs. Otherwise, you have to bucket data using pushdown predicate and then run in for loop over all data

Source https://stackoverflow.com/questions/54416848

QUESTION

Why does $post not work but $ajax works on the asp.net web api controller?

Asked 2018-Oct-22 at 11:14

I interested in knowing why does the $.ajax() request work but the $.post() returns just an empty array on the controller.

controller

...

ANSWER

Answered 2018-Oct-22 at 10:02

$.post() use the default contentType: 'application/x-www-form-urlencoded; charset=UTF-8' but you are using contentType: 'application/json; charset=utf-8', with stringified data in your $.ajax() method.

If you were to use $.post() you would need to generate the data with collection indexers to match your List parameter, for example

Source https://stackoverflow.com/questions/52926629

QUESTION

Nested array response in JSON returning only last row from Mysql table

Asked 2017-Oct-05 at 12:18

My database have three tables(category,catgory_details,questions), Now one category have many questions. I want to have a JSON response like this:

...

ANSWER

Answered 2017-Oct-05 at 12:08

Try to change :
'questions' => [$question_fetch['question'][1],$question_fetch['question'][2]],
to :
'questions' => $question_fetch['question'],

So you will have the full array of questions included in the response.

Source https://stackoverflow.com/questions/46585095

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install actuary

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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