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curl -o /dev/null -s -w 'Total: %{time_total}s\n' https://example.com/

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SELECT 
   table_name, 
   column_name, 
   data_type 
FROM 
   information_schema.columns
WHERE 
   table_name = '<table name>';

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openssl rsa -in privkey.pem -out privkey.key

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export GOOS=linux
export GOARCH=arm64

go build -o bin/main cmd/main.go
go tool dist list
go tool dist list | grep linux

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tcpdump port 3001 -v -nn

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kill -9 $(ps aux | grep 'fast' | awk '{print $2}')

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SELECT * FROM pg_stat_activity;

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#  Recursive search
find . -type f -name '*.log' -printf x | wc -c

# Non-recursive search
find . -maxdepth 1 -type f -name '*.log' -printf x | wc -c

# Delete by .ext
find /path/ -maxdepth 3 -type f -name "*.xlsx" -delete

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#!/bin/bash
# https://stackoverflow.com/questions/19653245/use-ignore-table-with-mysql-while-execute-sql-file
sed '/INSERT INTO `big_log`/ d' ${1} > dumpLog

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Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.