
Summarizing dbt Project Metadata From YAML in One Report
Read the dbt manifest built from your properties YAML and report documentation coverage, untested models, owners, tags and source freshness in one script.
Everything you need to level up your coding skills.

Read the dbt manifest built from your properties YAML and report documentation coverage, untested models, owners, tags and source freshness in one script.

The Excel formulas data people use every week: lookups, conditional sums, text and date cleanup, arrays, errors and LET, with their SQL equivalents.

Turn XML sensor readings into a pandas time series, resample to hourly means, find a 50 minute gap and a silent switch from Celsius to Fahrenheit.

Convert CSV to JSON with the csv module, then decide on types: zip stays text, money stays exact. pandas gave 2134.0 for 02134; converters took 0.4 to 36 s.

How Google Sheets and Excel formulas differ: array handling, lookup and text functions, dates, locale, errors and what breaks when a file moves between them.

A working guide to JSON Schema: write a schema, run it in Python and Node, handle formats, refs and versions, and check JSON stored in a database.

Convert one awkward CSV to JSON, JSON Lines, XML, YAML, Excel, Parquet, Markdown and SQL, read each back and see the cost on 193,708 rows.

Count 400,000 orders by status in a 132 MB XML file with grep in 0.4 s, lxml iterparse in 2.0 s or xmlstarlet in 5.1 s, and know when each can be trusted.

What Sheets IMPORTDATA can and cannot do as a live feed from a CSV URL: format, refresh, auth, size, parsing quirks and a way to measure it for your data.

A cron export that cannot publish a half-written file: lock, temporary name, row-count check, atomic rename. Real cron failed first, on the environment.

Flatten Kubernetes Deployments into one row per container and audit limits, probes, latest tags and privileged mode with SQL, then rank workloads by findings.

Read JSON Lines into a pandas DataFrame with read_json(lines=True): dtypes, chunking, nested fields, big integers, bad lines and the pyarrow engine.
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