How do I type hint a method with the type of the enclosing class?
TL;DR: As of today (2019), in Python 3.7+ you can turn this feature on using a "future" statement, from __future__ import annotations. (The behaviour enabled by from __future__ import annotations is scheduled to become the default in Python 3.14 as 'Deferred Evaluation Of Annotations'. It was going to be made the default in Python 3.10 as 'Postponed Evaluation of Annotations'. However, the change
Rails server doesn't see code changes and reload files
I noticed that my rails server doesn't reload controllers, models and probably any other files after I change them. I use Vagrant and Rails API, and I found that some people fix this problem by adding below line to the Vagrantfile. config.vm.provider "virtualbox" do |vb| vb.customize [ "guestproperty", "set", :id, "/VirtualBox/GuestAdd/VBoxService/--timesync-set-threshold", 5000 ] end It doesn't f
How to SSH to docker container in kubernetes cluster?
I am fairly new to the Google Cloud platform and Docker and set-up a cluster of nodes, made a Dockerfile that copies a repo and runs a Clojure REPL on a public port. I can connect to it from my IDE and play around with my code, awesome! That REPL should however probably be tunneled through SSH, but here is where my problem starts. I can't find a suitable place to SSH into making changes to the rep
Run node.js database migrations on Google Cloud SQL during Google Cloud Build
In the case with Cloud SQL and Node.js it would look something like this: steps: # Install Node.js dependencies - id: yarn-install name: node:18 entrypoint: yarn args: ["install", "--frozen-lockfile"] waitFor: ["-"] # Install Cloud SQL proxy - id: proxy-install name: node:18 entrypoint: sh args: - "-c" - "wget https://storage.googleapis.com/cloud-sql-connectors/cloud-sql-proxy/v2.4.0/cloud-sql-pro
SQL-like window functions in PANDAS: Row Numbering in Python Pandas Dataframe
I come from a sql background and I use the following data processing step frequently: Partition the table of data by one or more fields For each partition, add a rownumber to each of its rows that ranks the row by one or more other fields, where the analyst specifies ascending or descending EX: df = pd.DataFrame({'key1' : ['a','a','a','b','a'], 'data1' : [1,2,2,3,3], 'data2' : [1,10,2,3,30]}) df d
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