Display, filter and search log messages in your terminal

Overview

Textualog

Display, filter and search logging messages in the terminal.

screenshot

This project is powered by rich and textual.

Some of the ideas and code in this project are based on:

Installation

The easiest way to install the package is by running the pip command in the Python virtual environment of your project:

$ python -m pip install [--upgrade] textualog

Usage

The textualog app should have been installed in your environment, then run the following command:

$ textualog --log <path to the log file>

In the examples directory of this project, you can find an example log file to inspect and play with.

The main view is divided in three panels, (1) a Records panel that displays all the logging records in a colored view, (2) a Record Info panel that displays more details about the selected logging message (a message can be selected by a mouse click), and (3) a Levels panel that displays the standard logging levels. Logging levels can be switched on or off with a key press, d=debug, i=info, w=warning, e=error, c=critical. When you click inside the Record Info panel, the main view will change in a Record Details view that displays all information associated with the selected logging message. This view is mainly used when the logging message has extra multi-line information attached, and depending on the amount of information, this view is scrollable. When the selected logging message contains extra information, the Record Info panel will have an asterisk in the title. Use the Escape key to return to the main view.

The app can be terminated with the 'q' key or by pressing CTRL-C. If you need a little help on the keyboard shortcuts, press the '?' key to present the Info Help panel on the right side of the terminal. Also here use the Escape key to hide the help panel again.

Pressing the 'n' key will slide in a Namespaces panel on the left side of the Terminal. This panel is currently not functional. The idea is to allow the user to filter the logging messages by selecting one or more namespaces.

Log file formats

The current support is for a key-value type of log file. The log line shall have a fixed format, which is what I currently use in my main other projects. The following key=value pairs shall be there in the given order:

  • level=<logging level>
  • ts=<'%Y-%m-%dT%H:%M:%S,%f'>
  • process=<process name>
  • process_id=<PID>
  • caller=<calling function:lineno>
  • msg=<logging message>

In the future other formats can be supported by implementing a plugin class. Planned formats are the JSON format, ...

Roadmap

  • Display message details including extra lines that contain further information like e.g. traceback info.
  • Implement search functionality to search for strings or regular expressions and position the screen at the first match
  • Start work on filtering log messages based on their namespace
Owner
Rik Huygen
Self-educated Pythonista. Seriously trying to write clean and Pythonic code.
Rik Huygen
Code release for paper: The Boombox: Visual Reconstruction from Acoustic Vibrations

The Boombox: Visual Reconstruction from Acoustic Vibrations Boyuan Chen, Mia Chiquier, Hod Lipson, Carl Vondrick Columbia University Project Website |

Boyuan Chen 12 Nov 30, 2022
the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]

BGNet This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet] Environment Python 3.6.* C

3DCV developer 87 Nov 29, 2022
BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training

BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training By Likun Cai, Zhi Zhang, Yi Zhu, Li Zhang, Mu Li, Xiangyang Xue. This

290 Dec 29, 2022
Large-scale open domain KNOwledge grounded conVERsation system based on PaddlePaddle

Knover Knover is a toolkit for knowledge grounded dialogue generation based on PaddlePaddle. Knover allows researchers and developers to carry out eff

607 Dec 31, 2022
AI Summer's complete catalog of articles

Learn Deep Learning with AI Summer A collection of all articles (almost 100) written for the AI Summer blog organized by topic. Deep Learning Theory M

AI Summer 95 Dec 29, 2022
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene

Jiaxuan 568 Dec 29, 2022
A visualisation tool for Deep Reinforcement Learning

DRLVIS - Visualising Deep Reinforcement Learning Created by Marios Sirtmatsis with the support of Alex Bäuerle. DRLVis is an application used for visu

Marios Sirtmatsis 1 Nov 04, 2021
TLXZoo - Pre-trained models based on TensorLayerX

Pre-trained models based on TensorLayerX. TensorLayerX is a multi-backend AI fra

TensorLayer Community 13 Dec 07, 2022
Talk covering the features of skorch

Skorch Talk Skorch - A Union of Scikit-learn and PyTorch Presentation The slides can be downloaded at: download link. Google Colab Part One - MNIST Pa

Thomas J. Fan 3 Oct 20, 2020
PyTorch-lightning implementation of the ESFW module proposed in our paper Edge-Selective Feature Weaving for Point Cloud Matching

Edge-Selective Feature Weaving for Point Cloud Matching This repository contains a PyTorch-lightning implementation of the ESFW module proposed in our

5 Feb 14, 2022
Generative Query Network (GQN) in PyTorch as described in "Neural Scene Representation and Rendering"

Update 2019/06/24: A model trained on 10% of the Shepard-Metzler dataset has been added, the following notebook explains the main features of this mod

Jesper Wohlert 313 Dec 27, 2022
An end-to-end implementation of intent prediction with Metaflow and other cool tools

You Don't Need a Bigger Boat An end-to-end (Metaflow-based) implementation of an intent prediction flow for kids who can't MLOps good and wanna learn

Jacopo Tagliabue 614 Dec 31, 2022
ICCV2021 - Mining Contextual Information Beyond Image for Semantic Segmentation

Introduction The official repository for "Mining Contextual Information Beyond Image for Semantic Segmentation". Our full code has been merged into ss

55 Nov 09, 2022
PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

FullSubNet This Git repository for the official PyTorch implementation of "A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech E

郝翔 357 Jan 04, 2023
MediaPipe is a an open-source framework from Google for building multimodal

MediaPipe is a an open-source framework from Google for building multimodal (eg. video, audio, any time series data), cross platform (i.e Android, iOS, web, edge devices) applied ML pipelines. It is

Bhavishya Pandit 3 Sep 30, 2022
A Fast Monotone Rotating Shallow Water model

pyRSW A Fast Monotone Rotating Shallow Water model How fast? As fast as a sustained 2 Gflop/s per core on a 2.5 GHz cpu (or 2048 Gflop/s with 1024 cor

Guillaume Roullet 13 Sep 28, 2022
Python and C++ implementation of "MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation". Accepted at LXCV @ CVPR 2021.

MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation This is a PyTorch and LibTorch implementation of MarkerPose: a

Jhacson Meza 47 Nov 18, 2022
5 Jan 05, 2023
ELSED: Enhanced Line SEgment Drawing

ELSED: Enhanced Line SEgment Drawing This repository contains the source code of ELSED: Enhanced Line SEgment Drawing the fastest line segment detecto

Iago Suárez 125 Dec 31, 2022
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic

Hila Chefer 489 Jan 07, 2023