article-downloader | Uses publisher APIs to programmatically retrieve | Predictive Analytics library

 by   olivettigroup Python Version: 3.0 License: MIT

kandi X-RAY | article-downloader Summary

kandi X-RAY | article-downloader Summary

article-downloader is a Python library typically used in Analytics, Predictive Analytics applications. article-downloader has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However article-downloader has 56 bugs. You can install using 'pip install article-downloader' or download it from GitHub, PyPI.

Uses publisher-approved APIs to programmatically retrieve large amounts of scientific journal articles for text mining. Exposes a top-level ArticleDownloader class which provides methods for retrieving lists of DOIs (== unique article IDs) from text search queries, downloading HTML and PDF articles given DOIs, and programmatically sweeping through search parameters for large scale downloading. Important Note: This package is only intended to be used for publisher-approved text-mining activities! The code in this repository only provides an interface to existing publisher APIs and web routes; you need your own set of API keys / permissions to download articles from any source that isn’t open-access.
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            kandi-support Support

              article-downloader has a low active ecosystem.
              It has 62 star(s) with 24 fork(s). There are 17 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 1 open issues and 6 have been closed. On average issues are closed in 78 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of article-downloader is 3.0

            kandi-Quality Quality

              article-downloader has 56 bugs (0 blocker, 0 critical, 32 major, 24 minor) and 71 code smells.

            kandi-Security Security

              article-downloader has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              article-downloader code analysis shows 0 unresolved vulnerabilities.
              There are 23 security hotspots that need review.

            kandi-License License

              article-downloader is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              article-downloader releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              article-downloader saves you 2136 person hours of effort in developing the same functionality from scratch.
              It has 4682 lines of code, 18 functions and 43 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed article-downloader and discovered the below as its top functions. This is intended to give you an instant insight into article-downloader implemented functionality, and help decide if they suit your requirements.
            • Parse a start tag .
            Get all kandi verified functions for this library.

            article-downloader Key Features

            No Key Features are available at this moment for article-downloader.

            article-downloader Examples and Code Snippets

            Examples,Getting metadata
            Pythondot img1Lines of Code : 11dot img1License : Permissive (MIT)
            copy iconCopy
            from articledownloader.articledownloader import ArticleDownloader
            downloader = ArticleDownloader(els_api_key='your_elsevier_API_key')
            
            #Get 500 DOIs from articles published after the year 2000 from a single journal
            downloader.get_dois_from_journal_is  
            Examples,Downloading a single PDF article
            Pythondot img2Lines of Code : 5dot img2License : Permissive (MIT)
            copy iconCopy
            from articledownloader.articledownloader import ArticleDownloader
            downloader = ArticleDownloader(els_api_key='your_elsevier_API_key')
            my_file = open('my_path/something.pdf', 'w')  # Need to use 'wb' on Windows
            
            downloader.get_pdf_from_doi('my_doi', m  
            Examples,Downloading a single HTML article
            Pythondot img3Lines of Code : 5dot img3License : Permissive (MIT)
            copy iconCopy
            from articledownloader.articledownloader import ArticleDownloader
            downloader = ArticleDownloader(els_api_key='your_elsevier_API_key')
            my_file = open('my_path/something.html', 'w')
            
            downloader.get_html_from_doi('my_doi', my_file, 'elsevier')  

            Community Discussions

            QUESTION

            will TensorFlow utilize GPU for predictive Analysis?
            Asked 2020-Nov-21 at 21:35

            GPU is good for parallel computing but the problem is some machine learning libraries don't utilize the GPU, unless that machine learning based on image processing or some sort of graphics processing, what if I am using machine learning for predictive Analytics? do libraries like TensorFlow utilize the GPU? or they use only CPU? or can I choose which processing unit to use? whats the deal here?

            note: predictive Analysis requires no graphics processing.

            ...

            ANSWER

            Answered 2020-Nov-21 at 21:35
            The short answer: yes, it will! The slightly longer answer:

            The computation that happens in the GPU in any of the machine learning frameworks that support GPUs is not limited to graphical processing. For instance, if your model is a simple logistic regression, a framework such as TensorFlow will run it on the GPU if properly configured.

            The advantage of GPUs for machine learning is that training big neural networks benefits greatly from the high level of parallelism that the GPUs offer.

            If you want to know more about this, I'd recommend you start here or here.

            some things to consider:
            • how much a model will benefit from running in the GPU will depend on how much it will benefit from parallel computation in general.
            • Deep Learning models can be applied to predictive analytics, as well as more classical machine learning models. Bear in mind that neural nets are possibly the category of models that will benefit inherently from the GPU (see links above).
            • Even though running models using GPUs (or even more specialised hardware) can bring benefits, I would suggest that you don't choose a framework and, especially, don't choose an algorithm based solely on the fact that it will benefit from parallelism, but rather look at how appropriate a given algorithm is for the data you have.

            Source https://stackoverflow.com/questions/64948197

            QUESTION

            Restructuring Pandas Dataframe for large number of columns
            Asked 2020-Nov-01 at 19:39

            I have a pandas dataframe which is a large number of answers given by users in response to a survey and I need to re-structure it. There are up to 105 questions asked each year, but I only need maybe 20 of them.

            The current structure is as below.

            What I want to do is re-structure it so that the row values become column names and the answer given by the user is then the value in that column. In a picture (from Excel), what I want is the below (I know I'll need to re-name my columns, but that's fine once I can create the structure in the first place):

            Is it possible to re-structure my dataframe this way? The outcome of this is to use some predictive analytics to predict a target variable, so I need to re-strcture before I can use Random Forest, kNN, and so on.

            ...

            ANSWER

            Answered 2020-Nov-01 at 19:39

            You might want try pivoting your table:

            Source https://stackoverflow.com/questions/64630691

            QUESTION

            Display data from two json files in react native
            Asked 2020-May-17 at 23:55

            I have js files Dashboard and Adverts. I managed to get Dashboard to list the information in one json file (advertisers), but when clicking on an advertiser I want it to navigate to a separate page that will display some data (Say title and text) from the second json file (productadverts). I can't get it to work. Below is the code for the Dashboard and next for Adverts. Then the json files

            ...

            ANSWER

            Answered 2020-May-17 at 23:55

            The new object to get params in React Navigation 5 is:

            Source https://stackoverflow.com/questions/61859411

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install article-downloader

            Use pip install articledownloader. If you don’t have pip installed, you could also download the ZIP containing all the files in this repo and manually import the ArticleDownloader class into your own Python code.

            Support

            You can read the documentation for this repository [here](https://article-downloader.readthedocs.io/en/latest/articledownloader.articledownloader/).
            Find more information at:

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