guides

Twelve guides. Seven are how-to pages, one for a SQLite database, one for an Excel workbook, one for a Parquet dataset, one for a JSONL or NDJSON file, one for a log file, one for a JVM heap dump, and one for the outputs of a Jupyter notebook. Each says which product opens the file, where to install that product from, and what the paid tier adds.

• open a .db or .sqlite file in a JetBrains IDE

  SQLite Lens: install, open, and read the schema tree and the paged grid, on a database some running app still owns

• open an Excel workbook in the IDE, without Excel

  XLSX Lens: an .xlsx or .xlsm streamed into an editor tab, every sheet, merged cells and number formats, one cell at a time in the inspector

• open a parquet file in the IDE

  Parquet Lens: the footer read first, the schema before any row decodes, and the avro, TFRecord, arrow and feather files that open the same way

• read a JSONL or NDJSON file in the editor

  JSONL Lens: the same file in a JetBrains IDE and in VS Code, what each one indexes, and how the two paid tiers differ

• open a large log file in the editor

  Log Lens: a .log, .log.gz or rotated .log.N set in a JetBrains IDE and in VS Code, the level chips and Find in file, and what the plugin has that the extension does not

• open a .hprof heap dump in a JetBrains IDE

  Heap Dump Lens: the class histogram of a multi-gigabyte dump on a laptop, the thread dump and the GC log of the same incident, and the retained sizes Pro adds

• see Jupyter notebook outputs in PyCharm Community Edition

  Notebook Lens: the read-only preview, the free PyCharm since 2025.3, JupyterLab and VS Code, and the saved outputs rendered with no kernel

• opening a large file without loading it whole

  how paging works in each product, what the status line says, and what happens with compressed files and databases

• reading a multi-gigabyte log in place

  the line index and the level chips in the IDE and on a Jira issue, what is free and what Pro adds, and what a compressed or rotated log does

• opening a parquet, avro or arrow file without a notebook

  the three places these files open as a table, what is free and what Pro adds, and what the schema tab says before a row is read

• the exports

  CSV, JSONL and Parquet from each product, the column profile report, and the rules every export follows

• reading data attachments in confluence and jira

  what Data Lens does with permissions and data, and how the macro and the panel are used