Learnt something new today. If we are to perform an inline commenting within a Jinja2 HTMl template...
The following will be rendered as a comment - via the {# and #} tags.
{# {{ Hello World }} #}
The following however may cause problem - because Jinja2 will try to parse the Python variable Hello and World, which may not exist.
| import os | |
| from PIL import Image | |
| ''' | |
| I searched high and low for solutions to the "extract animated GIF frames in Python" | |
| problem, and after much trial and error came up with the following solution based | |
| on several partial examples around the web (mostly Stack Overflow). | |
| There are two pitfalls that aren't often mentioned when dealing with animated GIFs - |
| from PyPDF2 import PdfFileWriter, PdfFileReader | |
| # https://stackoverflow.com/questions/490195/split-a-multi-page-pdf-file-into-multiple-pdf-files-with-python#490203 | |
| def pdf_split(fname, start, end=None): | |
| print('pdf_split', fname, start, end) | |
| # pdf_split ~/Downloads/4-27-files/Invoice Email-0.pdf 1 4 | |
| #inputpdf = PdfFileReader(open("document.pdf", "rb")) | |
| inputpdf = PdfFileReader(open(fname, "rb")) |
| # -*- coding: utf-8 -*- | |
| # | |
| # Used like this: | |
| # | |
| # from repermute import ipermute | |
| # | |
| # for s in ipermute('[A-Z]\d'): | |
| # print s | |
| # | |
| # Almost all regular expression constructs are supported except for '*' |
| %%%%%%%%%%%%%%%%% | |
| % This is an example CV created using altacv.cls (v1.1.3, 30 April 2017) written by | |
| % LianTze Lim ([email protected]), based on the | |
| % Cv created by BusinessInsider at http://www.businessinsider.my/a-sample-resume-for-marissa-mayer-2016-7/?r=US&IR=T | |
| % | |
| %% It may be distributed and/or modified under the | |
| %% conditions of the LaTeX Project Public License, either version 1.3 | |
| %% of this license or (at your option) any later version. | |
| %% The latest version of this license is in | |
| %% http://www.latex-project.org/lppl.txt |
One can use MD5 or plain text diff to see differences in PDF files. If that's not enough, here's how to use diff-pdf which knows how to diff based on appearance or words:
brew install diff-pdf~/.gitconfig to add this:[difftool "diffpdf"]
cmd = diff-pdf --view \"$LOCAL\" \"$REMOTE\"
| def ClassicalDifferential(x): | |
| return differentialfx(x) | |
| def NumericalDifferential(x): | |
| return differentiate(f,x,h=1e-6) | |
| def TorchDifferential(x): | |
| x = torch.autograd.Variable(torch.Tensor([0.5]),requires_grad=True) | |
| y = fnew(x) | |
| y.backward() |
| Keras==2.4.3 # keras tools | |
| tensorflow==2.3.0 # tensorflow 2.x and extensions | |
| textblob==0.15.3 # get TextBlob and dependencies | |
| streamlit==0.71.0 # fetch Streamlit for Web Application | |
| numpy==1.19.4 # numerical computations | |
| pandas==1.1.4 # data manipulations |