The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Geospatial-data-lake Alternatives
Similar projects and alternatives to geospatial-data-lake
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
Installation
The premier source of truth powering network automation. Open source under Apache 2. Public demo: https://demo.netbox.dev
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
conda
A system-level, binary package and environment manager running on all major operating systems and platforms.
-
template-python-hello-world
:triangular_ruler: Python Hello World | Minimal template for Python development
-
pydantic-factories
Discontinued Simple and powerful mock data generation using pydantic or dataclasses
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
geospatial-data-lake reviews and mentions
-
A curated list of questionable installation instructions
One option is to trust on first use, checksum the installation script and at least casually verify the diff each time the checksum changes[1].
Pros:
- Protects against simple hijacking.
- Reproducible as long as the installer doesn't also call out to a moving target, such as example.com/releases/latest.
Cons:
- Build breaks as soon as the installer is bumped. If it's bumped often (or just before an important release) this can cause pain.
- TOFU may not be acceptable, but of course you could review the code thoroughly before even the first use.
[1] https://github.com/linz/geostore/blob/b3cd162605109da8a3a688...
-
Ask HN: Good Python projects to read for modern Python?
I'd recommend a project from work, Geostore[1]. Highlights:
- 100% test coverage (with some typical exceptions like `if __name__ == "__main__":` blocks)
- Randomises test sequence and inputs reproducibly
- Passes Pylint with max McCabe complexity of 6
- Passes `mypy --strict`
- Formatted using Black and isort
[1] https://github.com/linz/geostore
-
Python Best Practices for a New Project in 2021
The current work project[1] has all of these: Pyenv, Poetry, Pytest, pytest-cov with 100% branch coverage, pre-commit, Pylint rather than Flake8, Black, mypy (with a stricter configuration than recommended here), and finally isort. These are all super helpful.
There's also a simpler template repo[2] with almost all of these.
[1] https://github.com/linz/geostore/
[2] https://github.com/linz/template-python-hello-world
- Codecov bash uploader was compromised
-
AWS CloudFormation Best Practices
As someone who's used CDK for a few months and never handcoded CF, that sounds completely correct. If you're comfortable with Python, here's a simple but non-trivial architecture you can check out: https://github.com/linz/geospatial-data-lake/blob/master/app....
-
A note from our sponsor - WorkOS
workos.com | 23 Apr 2024
Stats
linz/geospatial-data-lake is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of geospatial-data-lake is Python.
Popular Comparisons
- geospatial-data-lake VS pydantic-factories
- geospatial-data-lake VS template-python-hello-world
- geospatial-data-lake VS asgi-correlation-id
- geospatial-data-lake VS aws-cdk
- geospatial-data-lake VS pip
- geospatial-data-lake VS devpi
- geospatial-data-lake VS dev-tasks
- geospatial-data-lake VS global_tectonics
- geospatial-data-lake VS pypiserver
- geospatial-data-lake VS flake8-alphabetize
Sponsored