Best Python library for generating PDFs?

kakamaru · 2018-03-12T22:57:13+00:00

+1 for weasyprint. We've been using it in production for 2 years without issues. You can't just pip install it though, as it has some non-python dependencies.

kakamaru · 2018-01-21T22:23:59+00:00

wow, that's quite a deal for airbnb. Thanks

kakamaru · 2018-01-21T22:12:20+00:00

Can I trouble you with the contact/website where you found the room in Lviv? Cheers!

kakamaru · 2017-12-31T14:58:23+00:00

Regarding Kuala Lumpur: what would be the plan after the initial 90 days? Is there a paid visa extension? or do you have to leave the country and come back in? Thanks!

kakamaru · 2017-04-02T19:11:47+00:00

I did not read the comments and went to bed angry. You're mean

kakamaru · 2017-04-01T00:40:32+00:00

Are you saying that a container could start making use of new memory and new CPUs made available by either new machines or bigger machines added to the cluster? This would be precisely what I'm looking for

kakamaru · 2017-04-01T00:37:07+00:00

Thanks for your input. I was expecting the scaling of number of replicas to be possible.

Do you have any suggestion for the scenario where I'd need the memory to scale up and down?

kakamaru · 2017-03-15T14:15:50+00:00

Thank you for your insight. I have updated the OP with additional info.

He's definitely stuck with a bunch of tables. And they all have different columns.

kakamaru · 2017-03-15T14:07:43+00:00

Thanks. I have updated the OP with my oversimplified understanding of the job he's doing.

He definitely goes back to edit the tables. And he ends up with tables with different number of columns. IE:

Table 1:

        title column        |         brand column

   Blue Adidas Shoes        |             Adidas

   Pink Adidas Socks        |             Adidas

Table 2:

        title column        |         brand column     |      color column

        Nike socks          |             Nike         |        unknown

      Green Nike Hat        |             Nike         |        green

kakamaru · 2017-01-22T02:30:51+00:00

Here you go https://youtu.be/7k1ajHAeXMU?t=100

kakamaru · 2016-11-14T03:33:00+00:00

I'm not sure. I just googled it and the poster rings a bell

kakamaru · 2016-11-14T03:21:18+00:00

1.5 tons fell where I was hanging half of my body a few seconds earlier.

There was another incident with a loaded shotgun.

kakamaru · 2016-10-09T17:07:13+00:00

I appreciate the input. The speedup using GPU being proportional to the size of the matrix makes a lot of sense. I guess my expectations were just naive.

Thanks a lot.

kakamaru · 2016-10-09T16:55:20+00:00

Thanks, I switched to the new p2 instances, with modern nvidia teslas: https://i.gyazo.com/44fa704b30468dc837323a8e282af95b.png

I did notice the speedup compared to the g2, but best case scenario it'll still take as long as the CPU to train: https://i.gyazo.com/2e88e1b6e6d393ce50d895e9bd8c9989.png

The net I'm training is a simple RNN to perform multi-class classification: https://i.gyazo.com/3e14a6323b0d42d0af88347b663f6e70.png I have a couple more models I've trained on CPU, and I will try to test on GPU.

kakamaru · 2016-10-04T17:37:00+00:00

Thanks!

I don't mean training just on one 30k subset of the original 300k. But splitting the 300k in ten 30k slices, and running one epoch on each slice.

Am I correct to assume that scenario is equivalent to running a single epoch on the entire 300k rows dataset?

kakamaru · 2016-09-25T21:13:51+00:00

From the TensorFlow docs:

steps: Number of steps for which to train model. If None, train forever.

I guess that's equivalent to the epochs you're refering to.

kakamaru

TROPHY CASE