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ps-mem

A utility to report core memory usage per program

ps-mem v3.14 1.3M downloads/30d#4,030 on PyPI1,636
Copyleft license LGPLv2 Abandoned released

What it is and what it does

ps_mem is a command-line utility that measures and displays the actual memory footprint of running processes on Linux. Unlike tools that report virtual memory, it calculates core memory by accounting for both private memory (unique to each process) and shared memory (libraries and resources used by multiple processes), then attributes a fair share of shared memory to each program. The tool runs as a standalone script with no Python runtime dependencies, making it lightweight and easy to deploy.

You invoke it from the shell to see a summary table of all processes ranked by memory usage, or filter results by PID, user, or other criteria. It supports options to split arguments, show totals, and report swap usage. The output format clearly separates private and shared components so you can understand whether a process is genuinely memory-hungry or just sharing a lot of system libraries.

Use it for:

  • Identify which processes are consuming the most actual RAM on a Linux system for capacity planning.
  • Diagnose memory bloat in a running application by comparing its private vs. shared memory footprint.
  • Generate per-user memory usage summaries for multi-user systems or shared hosting environments.
  • Monitor a specific process or set of processes (by PID) to track memory growth over time.
  • Understand the true cost of running multiple instances of the same program (e.g., browser tabs, containers).

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

ps_mem reports the actual core memory usage (private plus shared) for each running program on Linux, breaking down RAM consumption by process.

Yes, if you need accurate per-process memory reporting on Linux and are comfortable with an unmaintained tool. The package is stable, has no dependencies, and works well for its narrow purpose. However, the project has not been updated since 2022, so it may not work correctly on very recent Linux kernels or distributions, and no fixes will be forthcoming. Suitable for systems where the tool's behavior is already proven to work.

Install

ps-mem on PyPI

pip

pip install ps-mem

uv

uv add ps-mem

poetry

poetry add ps-mem

Installing ps-mem

Before you install

Installation is straightforward with no runtime dependencies. The project is marked abandoned with the last commit in 2022, so expect no active maintenance or bug fixes going forward.

License in practice

Licensed under LGPLv2 (copyleft), which requires that any modifications you distribute must also be released under LGPLv2 or a compatible license. Using the package as-is carries no obligation.

Quickstart

pip install ps_mem
ps_mem
# or filter by PID:
ps_mem -p $(pgrep -d, -u $USER)

Requires Linux; the tool reads from /proc filesystem which is Linux-specific.

Verify before relying

  • Whether the tool works correctly on modern Linux kernels and distributions post-2022.
  • Compatibility with Python versions beyond what the fact sheet specifies (python_support is unspecified).

Package facts

License LGPLv2 (copyleft)
Python support not specified
Install friction low — pure-Python wheel
Runtime dependencies none
Maintenance abandoned — 1,539 days since the last release
Last repo commit
First released
Downloads 1,340,778/month — #4,030 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: ps_mem-3.14-py2.py3-none-any.whl

Keywords: memory, RAM, profile, program, linux

Development Status :: 5 - Production/StableLicense :: OSI Approved :: GNU Lesser General Public License v2 (LGPLv2)Programming Language :: PythonTopic :: System :: Systems AdministrationTopic :: Utilities

Tags

memory usage per processRAM profiling by programlinux process memory reportingcore memory analysis toolshared vs private memorysystem memory breakdown
linux-sysadminmemory-profiling

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