serhii.net

Difference between %time and %%time in Jupyter Notebook - Stack Overflow

• when measuring execution time, %time refers to the line after it, %%time refers to the entire cell
• As we remember¹:
  • real/wall the ‘consensus reality’ time
  • user: the process CPU time
    • time it did stuff
  • sys: the operating system CPU time due to system calls from the process
    • interactions with CPU system r/w etc.

Format

• GBIF Infrastructure: Data processing has a detailed description of the flow
  • occurrences.txt is an improved/cleaned/formalized verbatim.txt
  • metadata
    • meta.xml has list of all colum data types etc.
      • for all files in the zip!
      • columns links lead to DCMI: DCMI Metadata Terms
    • metadata.xml is things like download doi, license, number of rows, etc.
• .zips are in Darwin format: FAQ
  • Because there are cases when both single and double quotes etc., and neither '/" as quotechar work.

  df = vx.read_csv(DS_LOCATION,convert="verbatim.hdf5",progress=True, sep="\t",quotechar=None,quoting=3,chunk_size=500_000)
  

Tools

• GBIF .zip parser lib:
  • BelgianBiodiversityPlatform/python-dwca-reader: 🐍 A Python package to read Darwin Core Archive (DwC-A) files.
  • Tried it, took a long time both for the zip and directory, so I gave up
• gbif/pygbif: GBIF Python client
  • API client, can also do graphs etc., neat!

Analysis

Things to try:

• limit number of columns through pd.read_csv.usecols()¹ to the ‘interesting’ ones
  • optionally take a smaller subset of the dataset and drop all NaNs
  • take column indexes from meta.xml
  • See if someone already did this:BelgianBiodiversityPlatform/python-dwca-reader: 🐍 A Python package to read Darwin Core Archive (DwC-A) files.

Use Virtual Environments Inside Jupyter Notebooks & Jupter Lab [Best Practices]

Create and activate it as usual, then:

python -m ipykernel install --user --name=myenv

It all started with the menu bar disappearing on qutebrowser but not firefox:

Broke everything when trying to fix it, leading to not working vim bindings in lab. Now I have vim bindings back and can live without the menu I guess.

It took 4h of very frustrating trial and error that I don’t want to document anymore, but - the solution to get vim bindings inside jupyterlab was to use the steps for installing through jupyter of the extension for notebooks, not the recommended lab one.
Installation · lambdalisue/jupyter-vim-binding Wiki:

mkdir -p $(jupyter --data-dir)/nbextensions/vim_binding
jupyter nbextension install https://raw.githubusercontent.com/lambdalisue/jupyter-vim-binding/master/vim_binding.js --nbextensions=$(jupyter --data-dir)/nbextensions/vim_binding
jupyter nbextension enable vim_binding/vim_binding

I GUESS the issue was that previously I didn’t use --data-dir, and tried to install as-is, which led to permission hell. Me downgrading -lab at some point also helped maybe.

The recommended jupyterlab-vim package installed (through pip), was enabled, but didn’t do anything: jwkvam/jupyterlab-vim: Vim notebook cell bindings for JupyterLab.

Also, trying to install it in a clean virtualenv and then doing the same with pyenv was not part of the solution and made everything worse.

Useful bits

Getting paths for both -lab and classic:

> jupyter-lab paths
Application directory:   /home/sh/.local/share/jupyter/lab
User Settings directory: /home/sh/.jupyter/lab/user-settings
Workspaces directory: /home/sh/.jupyter/lab/workspaces

> jupyter --paths
config:
    /home/sh/.jupyter
    /home/sh/.local/etc/jupyter
    /usr/etc/jupyter
    /usr/local/etc/jupyter
    /etc/jupyter
data:
    /home/sh/.local/share/jupyter
    /usr/local/share/jupyter
    /usr/share/jupyter
runtime:
    /home/sh/.local/share/jupyter/runtime

Removing ALL packages I had locally:

pip uninstall --yes jupyter-black jupyter-client jupyter-console jupyter-core jupyter-events jupyter-lsp jupyter-server jupyter-server-terminals jupyterlab-pygments jupyterlab-server jupyterlab-vim jupyterlab-widgets
pip uninstall --yes jupyterlab nbconvert nbextension ipywidgets ipykernel nbclient nbclassic ipympl notebook 

To delete all extensions: jupyter lab clean --all

Related: 230606-1428 pip force reinstall package

Versions of everything

> pip freeze | ag "(jup|nb|ipy)"
ipykernel==6.23.1
ipython==8.12.2
ipython-genutils==0.2.0
jupyter-client==8.2.0
jupyter-contrib-core==0.4.2
jupyter-contrib-nbextensions==0.7.0
jupyter-core==5.3.0
jupyter-events==0.6.3
jupyter-highlight-selected-word==0.2.0
jupyter-nbextensions-configurator==0.6.3
jupyter-server==2.6.0
jupyter-server-fileid==0.9.0
jupyter-server-terminals==0.4.4
jupyter-server-ydoc==0.8.0
jupyter-ydoc==0.2.4
jupyterlab==3.6.4
jupyterlab-pygments==0.2.2
jupyterlab-server==2.22.1
jupyterlab-vim==0.16.0
nbclassic==1.0.0
nbclient==0.8.0
nbconvert==7.4.0
nbformat==5.9.0
scipy==1.9.3
widgetsnbextension==4.0.7

Bad vibes screenshot of a tiny part ofhistory | grep jup

“One of the 2.5 hours I’ll never get back”, Serhii H. (2023). Oil on canvas
Kitty terminal, scrot screenshotting tool, bash.

Docker image runs a Python script that uses print() a lot, but docker logs is silent because python print() uses buffered output, and it takes minutes to show.

Solution¹: tell python not to do that through an environment variable.

docker run --name=myapp -e PYTHONUNBUFFERED=1 -d myappimage

TIL about pip install packagename --force-reinstall¹

• Since then, we have witnessed an increased research interest into
• Technical developments have gradually found their way into
• comprehensive but not exhaustive review

…

(On a third thought, I realized how good ChatGPT is at suggesting this stuff, making this list basically useless. Good news though.)

I love Dia, and today I discovered that:

• It can do layers! That work as well as expected in this context
• To save an antialiased PNG, you have to explicitly pick “png (antialiased)” when exporting, it’s in the middle of the list and far away from all the other flavours of .png extensions

Before and after:

The Radar chart and its caveats: “radar or spider or web chart” (c)

… are best done in plotly:

• Radar charts in Python
• Polar charts in Python

For a log axis:

fig.update_layout(
    template=None,
    polar = dict(
        radialaxis = dict(type="log"),
    )

EDIT: for removing excessive margins, use

fig.update_layout( margin=dict(l=20, r=20, t=20, b=20), )

Trivial option: Label data points with Seaborn & Matplotlib | EasyTweaks.com

TL;DR

for i, label in enumerate (data_labels):
    ax.annotate(label, (x_position, y_position))

BUT! Overlapping texts are sad:

SO sent me to the library Home · Phlya/adjustText Wiki and it’s awesome

fig, ax = plt.subplots()
plt.plot(x, y, 'bo')
texts = [plt.text(x[i], y[i], 'Text%s' %i, ha='center', va='center') for i in range(len(x))]
# adjust_text(texts)
adjust_text(texts, arrowprops=dict(arrowstyle='->', color='red'))

Not perfect but MUCH cleaner:

More advanced tutorial: adjustText/Examples.ipynb at master · Phlya/adjustText · GitHub

Pypy doesn’t have the latest version, which has:

• min_arrow_len
• some other bits like expand
• more: adjustText/init.py at master · Phlya/adjustText · GitHub