scancode-toolkit
nbdev
scancode-toolkit | nbdev | |
---|---|---|
4 | 45 | |
1,973 | 4,744 | |
1.3% | 0.6% | |
9.6 | 6.5 | |
6 days ago | 7 days ago | |
Python | Jupyter Notebook | |
- | Apache License 2.0 |
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.
scancode-toolkit
- ScanCode: Scan license and packages, dependencies and origin information
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User beware: Modified AGPLv3 removes freedoms, adds legal headaches
Hey, pabs3! Actually this is not using a rolling checksum for detection but rather a combo of language model, checksums, automatons, bitvectors, inverted indexes and multiple sequences alignment (e.g. a specialized diff). I put some docs there to explain the approach at ahttps://github.com/nexB/scancode-toolkit/blob/develop/src/li...
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I've just started using python at work, is there anything I need to be careful about?
If you're concerned about licensing in your dependencies, use a license scanner like scancode toolkit. Similar scanners are available in products like JFrog Artifactory or GitLab (paid versions)
nbdev
- The Jupyter+Git problem is now solved
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What is literate programming used for?
One example I've seen is ML/DL folks using jupyter notebooks to develop DL libraries in jupyter notebooks, see https://github.com/fastai/nbdev
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GitHub Accelerator: our first cohort and what's next
- https://github.com/fastai/nbdev: Increase developer productivity by 10x with a new exploratory programming workflow.
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Startups are in first batch of GitHub OS Accelerator
9. Nbdev: Boost developer productivity with an exploratory programming workflow - https://nbdev.fast.ai/
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Start learning python for a Statistician with SAS experience and little R experience
See if you like nbdev way of working with data through python and jupyter. nbdev is an optional part that will create python packages from jupyter notebooks. Also even the simple tutorials are opinionated and will guide you to unit test your code and write CICD pipelines.
- FastKafka - free open source python lib for building Kafka-based services
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isn't this just too much for a take home assignment?
You probably don’t have time for this for the purposes of your task, but I will also throw in the recommendation of nbdev especially if you’re a Python person. I haven’t had a project to use it on yet, but I’ve gone through the docs and the walkthrough and it seems like a great framework for starting potential projects with all the infrastructure needed for if/when they eventually get big and need all the packaging and stuff
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Any experience dealing with a non-technical manager?
nbdev: jupyter notebooks -> python package
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Resources to bridge the gap between jupyter notebooks and regular python development
Take a look at https://github.com/fastai/nbdev - haven't used it but supposedly the whole if fast.ai library was written that way. It sounds like a natural direction in your scenario - allowing your to keep working in a familiar environment and still producing production ready code (will, at least in paper 😅)
- Rant: Jupyter notebooks are trash.
What are some alternatives?
dependency-track - Dependency-Track is an intelligent Component Analysis platform that allows organizations to identify and reduce risk in the software supply chain.
papermill - 📚 Parameterize, execute, and analyze notebooks
ort - A suite of tools to automate software compliance checks.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
cyclonedx-gradle-plugin - Creates CycloneDX Software Bill of Materials (SBOM) from Gradle projects
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
fossology - FOSSology is an open source license compliance software system and toolkit. As a toolkit you can run license, copyright and export control scans from the command line. As a system, a database and web ui are provided to give you a compliance workflow. License, copyright and export scanners are tools used in the workflow.
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Neo4j - Graphs for Everyone
rr - Record and Replay Framework
spdx-license-matcher - A tool to match license text with SPDX license list using a an algorithm with finds close matches. It follows SPDX Matching guidelines to keep the substantial text as well as ignore the replaceable text for matching purposes.
Jupyter-PowerShell - Jupyter Kernel for PowerShell