Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 4 years ago.
Improve this question
One of the most popular tools to generate static sites is Sphinx which is largely used in the Python community to document code. It converts .rst files into other formats like HTML, PDF and others. But how is it possible that a static documentation with plain HTML files is searchable without losing performance?
I guess, it's done by creating an index (like a JSON file for example) that will be loaded via AJAX and is interpreted by something like lunr.js. Since many major projects in the world of Python have a huge documentation (like the Python docs itself). Therefore, how is it possible, to create such a good search without creating a gigantic index file that needs to be loaded?
You can use Google Search Engine to use Google´s power on your site. It is difficult to customize yet powerful. Other reference in this question
Related
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 8 months ago.
Improve this question
First time poster here. I'm trying to convert one or multiple .docx files to PDF but I can't figure out how to do it without importing any libraries/modules aside from what is available in python 3.3.
I've read through the packages documentation but nothing stuck out as a solution. I also don't know what I am looking for as I am pretty new to python. I found plenty of articles and resources that mention how to do it with an imported library, but not without.
Is it possible to accomplish this without importing a library?
Any advice/resources are welcome.
Code it from scratch. If you're not going to use an external library, that is by definition pretty much your only option.
You'll want to become an expert in the formal specifications for both PDF
and MS Word. Given the complexity and history of each of those, I expect a senior developer will want 6-12 months of experience with each to obtain the necessary understanding.
You should also have 6-12 months' experience with Python, since you'll likely need to be familiar with the language in order to define and use all the functions you'll need. But in just a few years of dedication, you should be able to write the necessary code.
MORE REALISTICALLY, import Python libraries for managing PDFs and MS Word. That should only take a week or two.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 1 year ago.
Improve this question
I'm trying to find a library (any language, but preferably C# or Python) which will let me open an XLSX file, iterate through the chart objects, and find data about the chart - ideally including the data backing the chart.
The Pandas Python package, or ExcelDataReader NuGet package have useful functionality for opening the file and reading a grid of numbers, as well as ways to add charts, but I don't find any way to read the charts.
Curious to hear from anyone who has ideas/solutions.
Hey I have a good solution for C#. In C# you can use OLEDB, this allows you to connect a C# code to a excel or access database (so long the database is in the C# code files). You don't need to get any addons for this is you have C# on Visual Studio.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 5 years ago.
Improve this question
I have a working R script. Can this be wrapped in a Python code so it can be deployed as an API ?
As mentioned in an earlier post, things that are not easy in R can be relatively simple in other languages. Another example would be connecting to Amazon Web Services. In relation to s3, although there are a number of existing packages, many of them seem to be deprecated, premature or platform-dependent. (I consider the cloudyr project looks promising though.)
If there isn’t a comprehensive R-way of doing something yet, it may be necessary to create it from scratch. Actually there are some options to do so by using AWS Command Line Interface, AWS REST API or wrapping functionality of another language.
http://jaehyeon-kim.github.io/2015/11/Quick-Test-to-Wrap-Python-in-R.html
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 6 years ago.
Improve this question
I just started learing python for my new job, so everything is quite difficult to me, even if the task sounds pretty straight forward.
I would like to extract several nodes from multiple xml-files, at best putting the information into an excel file in the end. Every row should contain the information from one xml-file, the columns should represent the specific nodes I am looking for, like "Zip-code" "town". Not all xml-files contain all nodes, so it would be perfect, if node "Zip-code" doesnt exist it just leaves the cell blank.
Could someone please point out a few hints how to start with this or, this is also possible, a special programm, which is easy to learn and use? My company and me only need to do it once for about 2000 files.
Thank you very much =)
For opening the files and getting their contents, you can use the Python functions: Documentation.
For XML parsing, I always use Beautiful Soup. It's a HTML/XML parser with good documentation that mostly "just works".
For creating the Excel file, you can use Xlsxwriter.
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 7 years ago.
Improve this question
Sorry if the title is confusing.
What I am trying to say is this:
I have worked with Python before, but I'm by no means an expert. So far everything I have done has just been 'somefile.py' with lots of methods and code in it, but it doesn't really have any organizational structure. In Java (which I am more familiar with than Python), there are usually different classes that each have methods and are called from each other. How do you make a file full of code organized and structured when working on a large project? Break them up into files by class?
Hopefully this is clearer. Let me know if this needs clarification.
In Python, the file unit is called module. Modules are organized in packages.
You usually put your classes each in a module and also use modules to group related code that doesn't belong to any class. Related modules are grouped in packages (physically represented by directories) which effectively create namespaces.
Then you use the import command to import the desired pieces of the code into other modules.
You can read about modules, packages and import in the Python documentation here.
Logically, it isn't much different than Java or other languages.