I haven’t written anything here for almost a year. I needed to break the silence. So, here we go with a not-so-useful post showing how frequently I have been posting to this blog, to get a sense of how long this break has been in comparison to other silences in the past.

Neither the code below, nor the plots are very insightful. But, I just hope this will get me started on the path to blogging more regularly. See you around!

Parsed post content

I wrote some code to parse the content of the blog, and each post object looks something like this:

{'date': datetime.datetime(2010, 3, 17, 18, 30, tzinfo=<UTC>),
 'draft': False,
 'tags': ['blab', 'life', 'poem'],
 'title': 'Just another bunch'}
Post count: 190

Post frequency by year

import pandas
posts = pandas.DataFrame(posts)
counts = posts['date'].groupby(posts['date'].dt.year).count()
plot = counts.plot(kind='bar', figsize=(8, 6))
plot.set_xlabel('Years')
plot.set_ylabel('# of posts')

<matplotlib.text.Text at 0x7f7d99ee20f0>

<matplotlib.figure.Figure at 0x7f7d99ea7390>

Post frequency by month

# Add a DatetimeIndex to the Dataframe
posts.index = pandas.DatetimeIndex(posts['date'].values)
counts = posts['date'].groupby(pandas.TimeGrouper('M')).count()
ax = counts.plot(kind='bar', figsize=(12, 8))

n = 5
ticks = ax.xaxis.get_ticklocs()
labels = counts.index.strftime('%Y-%m')
labels = ax.xaxis.set_ticklabels(labels[::n])
ticks = ax.xaxis.set_ticks(ticks[::n])

ax.set_xlabel('year-month')
ax.set_ylabel('# of posts')

<matplotlib.text.Text at 0x7f7d99e2f240>

<matplotlib.figure.Figure at 0x7f7d99e2cf98>

Work-flow

I jumped onto the hugo bandwagon too.

I was totally impressed by how fast it is, and have been meaning to try it out for a while, but wasn’t impressed with the built-in org-mode support it came with. This changed when I finally came across the ox-hugo package that does a wonderful job of exporting blog posts from an org file to hugo’s markdown format. I have contributed a couple of patches to it, to make it work better for myself and hopefully for others too.

Also, for this post, I used ob-ipython with the enhancements from scimax and it has really made the whole experience quite enjoyable.

Among other things, I think one of the reasons for those peaks in the second half of 2010, was having a smooth work-flow. My current work-flow feels pretty nice too, and I hope it’ll reduce some of the friction in writing more posts.

Onwards!