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ThumbmarkJS: A free, open source device fingerprinting JavaScript library for the web

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I needed a decent JavaScript fingerprinting library. I wanted something that was 'good enough': not crappy, but didn't need to be perfect. I noticed the great FingerprintJS , but sadly, they changed their license to a paid one. Boo! What is a good alternative to FingerprintJS? There are alternatives out there too, but to be honest, they all have faults. FingerprintJS is great, but they're monetizing their product in a way that I don't like. I might need hundreds of thousands of requests per month, but I can't pay thousands of dollars. It doesn't need to be perfect either, so I don't want to pay such a high premium. ImprintJS used to be a thing, but it's now archived for a few years already. ClientJS hasn't been updated for a few years either. It is promising, but I find it a little too complicated to extend and I see nowhere any statistics on how good is it. BroprintJS is the new kid on the block and hats off for trying, but it's very lim
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How to access AWS S3 with pyspark locally using AWS profiles tutorial

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At Zervant , we currently use databricks for our ETL processes, and it's quite great. However, there's been some difficulty in setting up scripts that work both locally and on the databricks cloud. Specifically, databricks uses their own prorpietary libraries to connect to AWS S3 based on AWS hadoop 2.7. That version does not support accessing using AWS profiles. Internally, we use SSO to create temporary credentials for an AWS profile that then assumes a role. Therefore, reading the ACCESS_ID and ACCESS_SECRET from the .credentials file is something we don't want to do. In order to accomplish this, we need to set two hadoop configurations to the Spark Context fs.s3a.aws.credentials.provider com.amazonaws.auth.profile.ProfileCredentialsProvider This is done by running this line of code: sc._jsc.hadoopConfiguration().set("fs.s3a.aws.credentials.provider", "com.amazonaws.auth.profile.ProfileCredentialsProvider") Note! You need to set your environment var
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Snowflake UPSERT operation (aka MERGE)

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You want to insert data to a table, but if a corresponding row already exists (by some rule, e.g. unique key) you want to update that instead of adding a new row, keeping the dataset's unique requirements intact. That's an "UPDATE AND INSERT" operation, or UPSERT. Some SQL languages have native support for it.  PostgreSQL has UPSERT as native. Also MySQL supports the operation with INSERT and ON DUPLICATE KEY UPDATE. How do you do UPSERT on Snowflake? Here's how: Snowflake UPSERT i.e. MERGE operation Snowflake's UPSERT is called MERGE and it works just as conveniently. It just has a different name. Here's the simple usage: MERGE INTO workspace.destination_table d USING workspace.source_table s ON d.id = s.id AND d.val1 = s.val1 WHEN MATCHED THEN update SET d.val2 = s.val2, d.val3 = s.val3 WHEN NOT MATCHED THEN INSERT (id, val1, val2, val3) VALUES (s.id, s.val1, s.val2, s.val3); Here the destination_table and source_table are of similar form,
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