Import sam_buff_t class and VCF functions from ad2vcf
Add BED and GFF support
Isolate headers under include/biolibc
Numerous small enhancements and fixes
Upstream change log: https://github.com/auerlab/biolibc/releases
v1.6.4
* Add testing config for Python 3.10 (Tox and CI)
* Fix internal _PurePath class with Python 3.10
* Remove redundant xmlns="" declaration when encoding with lxml
v1.6.3
* Refactor normalize_url() using pathlib.PurePath
* Support UNC paths
* Fix API docs
0.10.1
Bugs fixed
Fix blocking of pty_read when there isn't pty data ready to read
Contributors to this release
0.10.0
Enhancements made
Support creating terminal given name in kwargs.
Bugs fixed
avoid persistent handle on IOLoop instance
Maintenance and upkeep improvements
async/await syntax
PR: Pin pywinpty version to 1.1.0
0.9.5
Pin pywinpty version
0.9.4
Allow non-strict decode for process output
Switch to GitHub Actions
Add generated changelog
0.9.3
Make sure SIGPIPE has default handler set
0.9.2
Add js files in package manifest
Add support to ppc64le
Fix config files for publication
0.9.1
v0.9.1
0.9.0
Drop python 2 and 3.4 and 3.5 support
Make sure that all process output makes it to the terminal
Libxtend is a library of miscellaneous functions, the likes of
which might be found in libc or libm. It provides some convenient
functionality lacking in standard library functions as well some
more esoteric features.
The easysw.com domain now redirects to hotels-of-london.com, and the
archived files don't seem to be accessible anymore, despite some
continued relationship between the two entities.
Centralize some basics so ispell-en_GB doesn't need to be manually
adjusted every time ispell gets an update. Addresses a lingering issue
from PR pkg/55972 noted by Greg A. Woods.
7.6
---
To see the full list of pull requests and issues, see the [7.6.0 milestone](https://github.com/jupyter-widgets/ipywidgets/milestone/31?closed=1) on GitHub.
The main change in this release is that installing `ipywidgets` 7.6.0 will now automatically enable ipywidgets support in JupyterLab 3.0—a user has no extra JupyterLab installation step and no rebuild of JupyterLab, nor do they need Node.js installed. Simply install the python ipywidgets package with pip (`pip install ipywidgets==7.6.0`) or conda/mamba (`conda install -c conda-forge ipywidgets=7.6.0`) and ipywidgets will automatically work in classic Jupyter Notebook and in JupyterLab 3.0.
This is accomplished with the new python package `jupyterlab_widgets` version 1.0, on which `ipywidgets` 7.6.0 now depends (similar to how `ipywidgets` already depends on the `widgetsnbextension` package to configure ipywidgets for the classic Jupyter Notebook). The `jupyterlab_widgets` Python package is a JupyterLab 3.0 prebuilt extension, meaning that it can be installed into JupyterLab 3.0 without rebuilding JupyterLab and without needing Node.js installed.
Updates for Widget Maintainers
Custom widget maintainers will need to make two changes to update for JupyterLab 3:
1. Update the `@jupyter-widgets/base` dependency version to include `^4` to work in JupyterLab 3.0. For example, if you had a dependency on `@jupyter-widgets/base` version `^2 || ^3`, update to `^2 || ^3 || ^4` for your widget to work in classic Jupyter Notebook, JupyterLab 1, JupyterLab 2, and JupyterLab 3.
2. In the `package.json`, add the following `sharedPackages` configuration inside the `jupyterlab` key. See the [JupyterLab extension documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html#requiring-a-service) for more information.
```json
"jupyterlab": {
"sharedPackages": {
"@jupyter-widgets/base": {
"bundled": false,
"singleton": true
}
}
}
```
Separate from these two steps to update for JupyterLab 3, we also recommend that you make your widget's JupyterLab extension a prebuilt extension for JupyterLab 3.0. Users will be able to install your JupyterLab 3.0 prebuilt extension without rebuilding JupyterLab or needing Node.js. See the [JupyterLab 3 extension developer documentation](https://jupyterlab.readthedocs.io/en/stable/extension/extension_dev.html) or the new [widget extension cookiecutter](https://github.com/jupyter-widgets/widget-ts-cookiecutter/tree/jlab3) for more details.
5.1.3
=====
- Change id generation to be hash based to avoid problematic word combinations
- Added tests for python 3.9
- Fixed setup.py build operations to include package data
5.1.2
=====
- Fixed missing file in manifest
5.1.1
=====
- Changes convert.upgrade to upgrade minor 4.x versions to 4.5
5.1.0
=====
- Implemented CellIds from JEP-62
- Fixed a regression introduced when using fastjsonschema,
which does not directly support to validate a "reference"/"subschema"
- Removed unreachable/unneeded code
- Added CI workflow for package release on tag push
5.5.5
-----
- Keep preferring SelectorEventLoop on Windows. (:ghpull:`669`)
5.5.4
-----
- Import ``configure_inline_support`` from ``matplotlib_inline`` if available (:ghpull:`654`)
5.5.3
-----
- Revert Backport of 605: Fix Handling of ``shell.should_run_async`` (:ghpull:`622`)
5.5.2
-----
**Note:** This release was deleted from PyPI since it had breaking changes.
- Changed default timeout to 0.0 seconds for stop_on_error_timeout. (:ghpull:`618`)
5.5.1
-----
**Note:** This release was deleted from PyPI since it had breaking changes.
- Fix Handling of ``shell.should_run_async``. (:ghpull:`605`)
5.5.0
-----
- Kernelspec: ensure path is writable before writing ``kernel.json``. (:ghpull:`593`)
- Add ``configure_inline_support`` and call it in the shell. (:ghpull:`590`)
6.1.11
======
- Move jedi pinning to test requirements (:ghpull:`599`)
6.1.10
======
- Add change parameter needed for observer method of kernel_spec_manager trait (:ghpull:`598`)
6.1.9
=====
- Pin jedi<=0.17.2 (:ghpull:`596`)
6.1.8
=====
- Doc updates (:ghpull:`563`, :ghpull:`564`, :ghpull:`587`)
- Fix path to the connection file (:ghpull:`568`)
- Code cleanup (:ghpull:`574`, :ghpull:`579`)
- Silence kill_kernel when no process is present (:ghpull:`576`)
- Remove extra_env and corresponding test (:ghpull:`581`)
- Add documentation dependencies to setup.py (:ghpull:`582`)
- Fix for Windows localhost IP addresses (:ghpull:`584`)
- Drop Travis CI, add GitHub Actions (:ghpull:`586`)
- Adapt KernelManager._kernel_spec_manager_changed to observe (:ghpull:`588`)
- Allow use ~/ in the kernel's command or its arguments (:ghpull:`589`)
- Change wait_for_ready logic (:ghpull:`592`)
- Fix test_session with msgpack v1 (:ghpull:`594`)
4.7.1
- Allow creating user to delete secure file (:ghpull:`213`)
4.7.0
- Add a new ``JUPYTER_PREFER_ENV_PATH`` variable, which can be set to switch the order of the environment-level path and the user-level path in the Jupyter path hierarchy (e.g., ``jupyter --paths``). It is considered set if it is a value that is not one of 'no', 'n', 'off', 'false', '0', or '0.0' (case insensitive). If you are running Jupyter in multiple virtual environments as the same user, you will likely want to set this environment variable.
- Drop Python 2.x and 3.5 support, as they have reached end of life.
- Add Python 3.9 builds to testing, and expand testing to cover Windows, macOS, and Linux platforms.
- ``jupyter --paths --debug`` now explains the environment variables that affect the current path list.
- Update the file hidden check on Windows to use new Python features rather than ctypes directly.
- Add conda environment information in ``jupyter troubleshoot``.
- Update ``_version.version_info`` and ``_version.__version__`` to follow Python conventions.
sed 's/\(.*MINIUPNPC_API_VERSION\s\+\)[0-9]\+/\117/' < miniupnpc.h.bak > miniupnpc.h
sed: 1: "s/\(.*MINIUPNPC_API_VER ...": RE error: trailing backslash (\)
I held back on updating this package because of exactly this error...
pkgsrc change: update HOMEPAGE.
3.3.8 (2021-06-09)
Improvements
* msginit: Added support for generating plural forms with Unicode's CLDR
plural rules data. [GitHub#85][Suggested by Michaël Hoste]
* rxgettext ui: Added support for GtkBuilder UI definitions format with
.glade extension. [GitHub#74][Reported by dorle-o]
Fixes
* rxgettext ruby: Fixed a bug that Nn_ isn't extracted. [GitHub#86][Reported
by Kai Ramuenke]
Thanks
* Kai Ramuenke
* Michaël Hoste
* dorle-o
Red Datasets
Red Datasets provides classes that provide common datasets such as iris
dataset.
You can use datasets easily because you can access each dataset with
multiple ways such as #each and Apache Arrow Record Batch.
