Boost Your Python Productivity: 5 Essential PyCharm Hacks

Learn five practical PyCharm techniques—including auto‑PEP8 formatting, recovering deleted files via Local History, integrating Vim with ideaVim, leveraging code templates, and using bookmarks—to dramatically improve Python development efficiency on macOS and Windows.

Python Crawling & Data Mining
Python Crawling & Data Mining
Python Crawling & Data Mining
Boost Your Python Productivity: 5 Essential PyCharm Hacks

1. Code formatting, autoPEP8

pep8

is the Python style guide. For quick compliance, install autopep8 globally: sudo pip install autopep8 Then add it as an External Tool in PyCharm:

Name: AutoPep8
Description: autopep8 your code
Program: autopep8
Arguments: --in-place --aggressive --aggressive $FilePath$
Working directory: $ProjectFileDir$
Output filters: $FILE_PATH$:$LINE$:$COLUMN$:.*

After writing non‑PEP8 code, right‑click External Tools → AutoPep8 to reformat, or use the shortcut Command+Option+L for one‑click formatting.

2. Recover deleted files instantly

If a file is deleted without backup, PyCharm’s Local History can restore it. Right‑click the project folder, choose Local History → Show History, locate the delete entry, right‑click and select Revert.

3. Embrace Vim, ditch the mouse

Install the ideaVim plugin in PyCharm to edit code with Vim keybindings, offering faster, keyboard‑centric navigation.

4. Code templates for rapid coding

Define file templates in PyCharm to auto‑populate new files with boilerplate (interpreter path, encoding, author info, etc.). Use the template panel (triggered by Command+J) to insert common snippets such as main functions or for loops.

5. Use bookmarks for quick navigation

Press Command+F11 to set a numbered bookmark at any location, then jump back with Control+1 (or the assigned number). View all bookmarks with Shift+F11 and delete with F11 (Windows only).

Command + F11    Set bookmark
Shift + F11      Show all bookmarks
F11              Delete bookmark (Windows)
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Vimcode templatesbookmarksautopep8
Python Crawling & Data Mining
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