I have my resume online in an html page (www.mysite.com/resume.html). Every time I need a PDF version of it, I use Google Chrome's print dialog to save it as a PDF, which uses my print CSS stylesheet.
I want to be able to navigate to www.mysite.com/resume.pdf to always have an up to date PDF version without having to go through Google Chrome manually. Is there a way to programmatically and automatically create a resume.pdf from resume html? If I can write a script that runs once every 24 hours or something like that, that would be good.
PhantomJS is perfect for this. It invokes an instance of WebKit from the command line which can then be used to output to file such as PDF.
PhantomJS:
http://phantomjs.org/
Specific instructions for exporting screen output to a file:
http://phantomjs.org/screen-capture.html
e.g.:
phantomjs rasterize.js 'http://www.example.com/resume.html' resume.pdf
Chrome has started headless program.
With that, we can create a pdf. e.g. for windows navigate your commandline to
C:\Users\{{your_username}}\AppData\Local\Google\Chrome SxS\Application>
Then hit the command:
chrome --headless --print-to-pdf="d:\\{{path and file name}}.pdf" https://google.com
If you are looking to do this server-side via PHP might I recommend the Browsershot library which leverages the Puppeteer (NodeJS package) and Chrome / Chromium headless browser?
It works really well. Way easier to install and get going than wkhtmltopdf (which is another option that doesn't rely on a NodeJS package nor the Chrome/Chromium headless browser. Personally, I recommend Browsershot solution since wkhtmltopdf has some issues depending on the type of server (Linux distro and version) you're running. That is, the only reliable way to install wkhtmltopdf that I've found is to download and compile from source on the server that you're running and not through a package manager).
Also, if you happen to be needing a solution specifically while working on a Laravel project then there's a wrapper library for Browsershot available.
Check out this tutorial to get started.
Related
Using atom-editor 1.13 with the love-ide package installed to run LOVE2d 10.2 games (windows 7)
Apparently if you create a conf.lua file in the same folder as your main.lua file you can add some configuations to main.lua. So, I've got these lines of code in my conf.lua to show console.
function love.conf(t)
t.console = true
end
But when I go back to my main.lua and type print("ballz"), all I see is a blank LOVE2d game screen with no extra console window. Not really sure if this is because I'm using atom editor or not. Everything seems to be PATH'ed correctly.
On a side note, whenever I run atom using the love-ide package it always tries to install some "dependecy files" like the hyperclick-love package, and the auto-complete-love package. These fail to install because I don't have git installed.. honestly I really don't know what git is, but neither it, hyperclick, or auto-complete seemed like requirements to run my game, so in the spirit of not installing unnecessary things onto my computer I never installed these things... annoying as it is to see this notification always pop up when I start atom. Anyone know if this is contributing to the issue, or know a way to remove these notifications or auto-download-attempts? My LOVE2d code still seems to run without these packages.
Have you set up the terminal emulator in your configuration?
(Windows only) Try using the lovec.exe executable instead of the normal love.exe. The first one attaches to the console that executed the game, the second one ignores it.
Lua has a buffered output, try adding io.stdout:setvbuf('no') to the top of main.lua
I have a Jupyter Notebook that plots some data and lets the user interact with it via a slider.
What would be the easiest way to make a web app with a similar functionality? (reusing as much of the code...)
I believe the easiest way is to use voilà.
After installing you just have to run:
voila <path-to-notebook> <options>
And you will have a server running your notebook as a web app, with all the input code omitted.
AppMode is "A Jupyter extension that turns notebooks into web applications".
From the README:
Appmode consist of a server-side and a notebook extension for Jupyter.
Together these two extensions provide the following features:
One can view any notebook in appmode by clicking on the Appmode button in the toolbar. Alternatively one can change the url from
baseurl/notebooks/foo.ipynb to baseurl/apps/foo.ipynb. This also
allows for direct links into appmode.
When a notebook is opened in appmode, all code cells are automatically executed. In order to present a clean UI, all code cells
are hidden and the markdown cells are read-only.
A notebook can be opened multiple times in appmode without interference. This is achieved by creating temporary copies of the
notebook for each active appmode view. Each appmode view has its
dedicated ipython kernel. When an appmode page is closed the kernel is
shutdown and the temporary copy gets removed.
To allow for passing information between notebooks via url parameters, the current url is injected into the variable
jupyter_notebook_url.
To be complete - there exists also https://www.streamlit.io/ .
I still dont understand the exact difference between voila and streamlit.
At the moment I just struggle with the possibility to re-run everything with new parameters... I have bad luck with voila still.
Edit: I see that streamlit requires a raw python, not .ipynb, this fact would mean that this answer is completely wrong, I will search a bit more on streamlit before further action/comment.
Edit2: Voila looks great. However, I found few things that uncover the underlying complexity and thus a troubles that may arise.
callbacks. Widgets work great in jupyter, but since it is not possible to re-run one cell, sometimes the logic must be modified to work in Voila.
interactive java objects need a special treatment, e.g. matplotlib has a cheap solution, but there was nothing for e.g. jsroot
links. It is easy to create (a file and) a download link in jupyter, Voila can also serve a file, but it needs another extra treatment.
After all, I pose myself a question - is it better to learn many tricks and modifications to jupyter or to use some other system? I am going to see if streamlit can give em some answer.
The Jupyter Dashboards Bundlers extension from the Jupyter Incubator is one way to do it while retaining interactivity.
EDIT: While pip installing this package will also install the cms package dependency, like dashboard_bundlers, cms needs to be explicitly enabled/quick-setup as a notebook extension for the dashboard tools to work.
#raphaelts has the right idea and should be the accepted answer. As of Dec 2019, Voila is the most appropriate method to deploy Jupyter notebooks to production as a stand alone webapp. Think internal datascience teams sharing their analytics workload with internal C-Suite teams using SPA stlye Notebooks with all the code hidden and custom GUI/interactions thrown in. Recently discussed on HN
https://news.ycombinator.com/item?id=20160634 and the official announcement from the Jupyter maintainer https://blog.jupyter.org/and-voil%C3%A0-f6a2c08a4a93enter link description here
As mentioned above, voilà is a very powerful tool which hides the input cells from your notebooks and therefore provides a clean interface. In order to deploy your notebook with voilà you need to follow the specific steps of your organization. But if you want to quickly run it on your machine, simply install it with pip install voila. Then you can enter start from the command-line: voila my_notebook.ipynb or use the "Voila" button which should have appeared in your Jupyter notebook.
Note, however, that using voilà is only one part of the story. You also need to build the required interactivity, ie. to set up how to respond to input changes. There are quite a few frameworks for this.
The simplest one is to use the interact function or the observe method from the Ipywidgets library. This is very direct, but things can easily get out of control as you start having more and more widgets and complexity.
There are complete frameworks, some of them mentioned above. E.g. streamlit, dash and holoviz. These are very powerful and suited for larger projects.
But if you want to keep it simple, I also recommend to check out autocalc. It is a very easy-to-use library, which lets you define the dependencies between your widgets/variables and let all the recalculation be triggered automatically. A tutorial can be found here.
Disclaimer: I am the author of the autocalc package.
The easiest way is to use the Mercury framework. You can reuse all your code. To convert the notebook to web app you will need to add the YAML header in the first cell of the notebook (very similar to R Markdown). The widgets are generated based on YAML. The end-user can tweak widgets values and click the Run button to execute the notebook from the top to the bottom. You can easily hide the notebook's code (if you want) by setting the show-code: False in the YAML. The example notebook and corresponding web app are below.
Example of the notebook with YAML header
Example web app generated from notebook with Mercury
I load extensions to IPython notebook (powered by Jupyter) with the following command in ~\.ipython\profile_default\static\custom\custom.js.
IPython.load_extensions("calico-spell-check", "calico-document-tools");
The extensions are correctly loaded in the first notebook I open. But they are typically disabled in the following notebooks I open. Then when I close, reopen, etc. the notebooks they are loaded (seldom) or not (often) without any specific message in the console.
Is it a problem of compatibility with Jupyter or rather a bad configuration of mine?
You are hitting a race condition. Most of the instruction on how to activate extension in custom.js are wrong/too old when they tell you to directly copy past code in custom.js. Please follow official docs, use requirejs, and register the extension following the information in official docs.
I'm trying to use the latest Google NaCl SDK. Following the instructions at https://developers.google.com/native-client/pepper18/devguide/tutorial
I downloaded the naclsdk tool from their site, ran update, and got a pepper_18 folder.
I set NACL_SDK_ROOT to the pepper_18 folder, went in to 'examples' and ran make. Everything seemed to compile just fine.
I started Chrome, looked in about: flags and about: plugins, and verified that NaCl is enabled. I installed the SDK Examples app (from: https://developers.google.com/native-client/pepper18/sdk/examples) and that works just fine.
Then I tried to run my locally built and hosted examples, going to http://localhost: 5301. The HTML loads fine but the NaCl content does not load. In the hello world examples, it says "Status: LOADING..." forever.
I double checked the HTTP server logs and I don't see any errors there. Is there another place I should be looking for logged errors?
Check for version mismatch
In Chrome navigate to about:version and check that the major version of Chrome is at least that of the Pepper version you used to build your examples.
Check the JavaScript console in Chrome for any errors
You can find it by clicking the wrench icon in the upper right-hand corner in Chrome and selecting Tools -> JavaScript Console.
Inspect the NaCl module for further information
In the JavaScript console, you can also inspect the embed element of the NaCl module. E.g., if the embed tag has id="nacl_module" you can inspect it by typing
theModule = document.getElementById('nacl_module');
theModule.lastError;
Check Chrome's output to stdout/stderr
On Mac or Linux start Chrome from the terminal and look at the output on the console. E.g., on the Mac, you'd typically go
/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome --enable-nacl
On Windows, Chrome does not write to the terminal if started from a command prompt. For this reason you need to redirect stdout/stderr from Chrome by setting the environment variables NACLLOG, NACL_EXE_STDOUT, and NACL_EXE_STDERR. Point them to different files, e.g.,
NACLLOG = c:\my_project\nacl.log
NACL_EXE_STDOUT = c:\my_project\nacl_stdout.log
NACL_EXE_STDERR = c:\my_project\nacl_stderr.log
Then (re-)start Chrome (making sure these environment variables are in effect).
Connect a debugger
Instructions on using the debugging support (currently only 64-bit Windows and 64-bit Linux) are available at https://developers.google.com/native-client/pepper18/beta-docs/debugging.
Restarting Chrome means closing all windows
When developing for Native Client one often restarts Chrome. It is important to close all Chrome windows; otherwise it hasn't actually restarted.
I muddled through a few issues which I will document in case they help others:
Neglected to 'make' the examples (got a clue to make them from the asker's description).
Chrome would not let me run non-store chrome apps. Went to chrome://flags and enabled Native Client and Native Client GDB-based debugging.
The JavaScript console said the demo's nmf file under .../debug/ was missing. I changed the make config to build Debug instead of Release based on this.
Chrome console complained NativeClient: NaCl module load failed: ServiceRuntime: failed to start; NaCl's GDB debug stub requires --no-sandbox flag on Windows. See crbug…. Tried running Chrome from cmd with --no-sandbox. This results in an alert You are using an unsupported command-line flag: --nosandbox. Stability and security will suffer. The aforementioned error went away, but the examples still would not run - no UI.
Went back to chrome://flags and disabled Native Client GDB-based debugging.
Then most of the examples worked. The Google Drive demo complains Error: must be run as a packged app.
have you confirmed that you've run httpd.py from the examples folder? This script creates the localhost:5103 server that the apps can be ran from.
Also, what OS are you using?
~Main
I tried using freopen() to redirect the "cout" function to the console, but it doesn't produce the desired effect. Instead of just double clicking on the executable and having the console show it's message, I need to use a command prompt or a batch file, and that's a problem, because I want the user to be able to close the console after the message has been displayed without closing the SDL window. This is supposed to be a console application. I apologize if I am not clear enough.
If using freopen() doesn't work the SDL Console FAQ gives a tutorial on recompiling the SDLmain library that is relatively easy to understand, especially if you already have MSYS and MinGW installed. You can use the resulting SDLmain library instead of your current one and it should work (It did for my project).