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Government Publications Portal
The New York City Municipal Library provides information about City government to the public This includes hard-copy materials dating to the 19th Century and up-to-the minute reports that are available on our website.
We have revamped the government publications portal to provide easy access to reports issued by City agencies and we have increased the number of reports available online. This new portal includes reports from most City offices and agencies. You will not find documents from the following entities on this portal: The Equal Employment Practices Commission and the Center for Economic Opportunity. We will be adding additional types of information to the portal in the upcoming months and we will continue to solicit past reports and additional government participants.
This application was built under the direction of Joel Castillo by three talented interns from the NYU Polytechnic School of Engineering, Alan Chen, Alvi Kabir, and Panagis (Peter) Alisandratos using Python and the Django framework.
We currently use the following packages in our application:
- Django 1.6.6
- django-endless-pagination 2.0
- ecdsa 0.11
- elasticsearch 1.2.0
- MySQL-python 1.2.5
- paramiko 1.15.1
- pycrypto 2.6.1
- requests 2.3.0
- urllib3 1.9
We are also making use of MySQL Community Edition (v 5.1) to house our database and Elasticsearch (v1.4) to provide the backend search functionality.
- Basic Search – The default search will comb through the database searching document titles, descriptions, agencies, types, and categories to give you the best possible results.
- Advanced Search – You can filter your results By Agency, Category, and Type to make the search even faster and targeted.
- Sorting – All searches can be sorted by Agency, Category, Type, and Relevance.
- Dynamic Pagination – Allows users to view 10, 20, 50, or 100 results per page.
- Embedded PDFs – To make it easier to view the documents, the files are embedded in the results page, allowing the user to view their document without manually saving to their computer.
- Full Text Search – Full text search will be available for all documents in the near future, making it even easier to find the right document.
- Relevancy Scores – A percentage based score of how relevant a result is to your original search query.
- CSV Export – Users will be able to export their search results to a CSV file for manipulation in a program such as Microsoft Excel.
- API – Allows other applications to take advantage of our database of documents and display them in unique ways to users.
We are launching this product as a beta so that we can get your input. Please use our feedback form or Github Issues to submit new requests and bug reports. We would also encourage you to send any improvements on our code. Clone our repository and show us what you can do with our codebase to make it even better.
Additionally, BetaNYC has created an open discussion group to talk about future improvements.
Special thanks to our four talented interns: Alan Chen, Alvi Kabir, Brandon Tang, and Panagis Alisandratos; to Jeff Merritt from the Mayor’s Office and to Steve Bezman, Prince Gupta, and Anand Krishnan at DOITT.