orjsonl VS gcp-log

Compare orjsonl vs gcp-log and see what are their differences.

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orjsonl gcp-log
1 1
14 2
- -
6.6 5.3
6 months ago 9 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

orjsonl

Posts with mentions or reviews of orjsonl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-09.

gcp-log

Posts with mentions or reviews of gcp-log. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing orjsonl and gcp-log you can also consider the following projects:

dataconf - Simple dataclasses configuration management for Python with hocon/json/yaml/properties/env-vars/dict/cli support.

python-logfmter - Using the stdlib logging module and without changing a single logging call, logfmter supports global (first and third party) logfmt structured logging.

mashumaro - Fast and well tested serialization library

structlog - Simple, powerful, and fast logging for Python.

orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy

pygogo - A Python logging library with superpowers

json-lines - Read JSON lines (jl) files, including gzipped and broken

structlog-gcp - Google Cloud Logging formatter for structlog

ratarmount - Access large archives as a filesystem efficiently, e.g., TAR, RAR, ZIP, GZ, BZ2, XZ, ZSTD archives

jsonpickle - Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.