renovate | Universal dependency update tool that fits into your workflows | DevOps library

You should add "automergeType": "branch". Ref: https://docs.renovatebot.com/noise-reduction/#branch-automerging

Solution was actually quite trivial.

Simply take your SearchClient and index the documents with a batch created from your List of objects. See below:

Assuming your field that you want to facet on is createdDate and is of type Edm.DateTimeOffset. For your requirement, I think there will be some calculations that you'd have to do after you get the facet data back.

These are the dates you are interested in

(today) - 2021-08-12T00:00:00Z

yesterday - (today - 1 day) 2021-08-11T00:00:00Z

last week - (yesterday - 1 week) 2021-08-04T00:00:00Z

last month - (4 weeks back to 1 weeks back) 2021-07-12T00:00:00Z

last year - (1 year ago to last month) 2020-08-12T00:00:00Z

so you will specify 4 values in your facet - yesterday, last week, last month, last year. I will first use these names in the actual query to make it more readable. The second is the actual query you will make

1. human readable query - facet=createdDate,values:last year | last month | last week | yesterday
2. actual search query - facet=createdDate,values:2020-08-12T00:00:00Z| 2021-07-12T00:00:00Z | 2021-08-04T00:00:00Z | 2021-08-11T00:00:00Z

This will result in 5 buckets of data as follows.

a - everything older than last year (you don't need this, you can throw it away)

b - everything from last year to last month

c - everything from last month to last week

d - everythng from last week to yesterday

e - everything from yesterday to today

Now the following will be the calculations in order to get the ranges you need.

• Created Today (123) - e

• Created in the last week (3,455) - d + e

• Created in the last month (12,234) - c + d + e

• Created in the last year (112,234) - b + c + d + e

• Created prior to last year (547,838) - a

Ok. Here is the solution: Actually my approach was correct. And the preset was retrieved and applied. I just made a mistake in formulating the rules:

This works:

Apparently it was a bug

https://github.com/renovatebot/renovate/pull/9949

In the version 25.18.5 should be fixed

It is pretty easy to work with quanteda and topicmodels. The former is for data management and quantitative analysis of textual data, the latter is for topic modeling inference.

Here I take your comment object and transform it to a corpus and then to a dfm. I then convert it to be understandable by topicmodels.

The function LDA() gives you all you need to easily extract information. IN particular, with get_topics() you get the most probable topic for each document. If you instead want to see the document-topic-weights you can do so with ldamodel@gamma. You will see that get_topics() does exactly what you asked.

Please, see if this works for you.

I downgraded the sqlite3 package to v5.0.0 and it rebuilt correctly. Hope this helps anyone else with the same issue.

Source: nodejs electronjs sqlite3 - use of undeclared identifier 'napi_is_detached_arraybuffer'

The log already leads to a good resource: https://www.pulumi.com/docs/troubleshooting/#conflict It's actually a feature of the Pulumi state management provided by app.pulumi.com:

One of the services that pulumi.com provides is concurrency control. The service will allow at most one user to update a particular stack at a time.

So using only one Stack like the default dev at app.pulumi.com it looks like this:

Using GitHub Actions or other CI/CD platforms, this becomes an obstacle. I see 2 options here: We could either switch to another Pulumi state management backend (like the Local Filesystem Backend, which would not create a stack on app.pulumi.com but rather CI locally). Or we could create a GitHub Action job specific stack on app.pulumi.com, where the stack is named after the specific job id or something.

As I don't mind to use app.pulumi.com here - and also use the additional log, if something did go wrong - I wanted to have a solution for the second option. The GitHub Action workflow file design could be described with the following steps:

1. Standard Pulumi GitHub Action pipeline: Defining needed variables, checking out the repo, setting up the nodejs environment incl. installing the npm dependencies - and finally configuring the Pulumi CLI using the action-install-pulumi-cli Action.
2. Creating a Pulumi stack on app.pulumi.com using pulumi stack init github-${{ github.run_id }}, which resembles the github.run_id GitHub Action default context variable. This variables represents "a unique number for each run within a repository."
3. Leveraging the (or multiple) pulumi/actions@v2 Action in version v2 (since only from v2 we have the stack-name configuration option) and configuring the Pulumi app.pulumi.com stack name with stack-name: github-${{ github.run_id }}
4. Removing the Pulumi app.pulumi.com stack using a final pulumi stack rm github-${{ github.run_id }} -y

The full GitHub Action workflow looks like this:

If you look into the document of JWT object, it doesn't has a "decode" function, so you cannot stub it.

https://github.com/panva/jose/blob/master/docs/README.md#jwt-json-web-token