<commit_before># TabulaRazr
Web App to extract and browse through tabular data from text and pdf files. Contains experimental calculation of the [internal rate of return](http://www.investopedia.com/terms/i/irr.asp) for Municpal Bonds.
Issues, forks and heavy usage welcome. Distributed under APGL v3.

# Setup and run

    pip install -r requirements.txt
    python server.py

Navigate to `http://localhost:7081` and upload an example document (see below).
You may set your PORT variable to other ports than 7081.

# Folder structure
- /templates ... Jinja2 template
- /static ... all stylesheets and media goes there
- /static/ug/<project_name> ... user uploaded data and analysis files (graphs, json)

# Example documents on temporary running instance
- deep learning paper: http://tabularazr.eastus.cloudapp.azure.com:7081/show/_other/sentence_entailment_attention_LSTM.pdf.txt
- Municipal Bond from Flint: http://tabularazr.eastus.cloudapp.azure.com:7081/show/muni_bonds/ER544111-ER421289-ER823264.pdf.txt#2813
- Annual Report Bosch 2014: http://tabularazr.eastus.cloudapp.azure.com:7081/show/business_reports/Bosch_Annual_Report_2014_Financial_Report.pdf.txt#2238
- Annual Report Oakland: http://tabularazr.eastus.cloudapp.azure.com:7081/show/business_reports/OAK056920.pdf.txt#8920

# Other documents 
Choose any financial document, research paper or annual report to upload yourself. Or browse these sources.

### Example pdfs from public data (municipal bonds, audit reports, finanical reviews)

- http://emma.msrb.org/EP753324-ER508056-ER910760.pdf
- http://emma.msrb.org/EP407966-EP321048-EP717328.pdf
- http://emma.msrb.org/ER544111-ER421289-ER823264.pdf (very high cost of issuance)<commit_msg>provided context of DeveloperWeek 2016<commit_after># TabulaRazr
Web App to extract and browse through tabular data from text and pdf files. Contains experimental calculation of the [internal rate of return](http://www.investopedia.com/terms/i/irr.asp) for Municpal Bonds.
This is a partly release from prior work and the submission to DeveloperWeek 2016 that also builds semantic links across tables to quickly compare deals and research across a large corpora of financial documents.

Presentation at [DeveloperWeek2016](https://www.youtube.com/watch?v=Snqul2fJT5c).

Original [project page](http://accelerate.im/projects/362). 


Issues, forks and heavy usage welcome. Distributed under APGL v3.

# Setup and run

    pip install -r requirements.txt
    python server.py

Navigate to `http://localhost:7081` and upload an example document (see below).
You may set your PORT variable to other ports than 7081.

# Folder structure
- /templates ... Jinja2 template
- /static ... all stylesheets and media goes there
- /static/ug/<project_name> ... user uploaded data and analysis files (graphs, json)

# Example documents on temporary running instance
- deep learning paper: http://tabularazr.eastus.cloudapp.azure.com:7081/show/_other/sentence_entailment_attention_LSTM.pdf.txt
- Municipal Bond from Flint: http://tabularazr.eastus.cloudapp.azure.com:7081/show/muni_bonds/ER544111-ER421289-ER823264.pdf.txt#2813
- Annual Report Bosch 2014 - sales figures: http://tabularazr.eastus.cloudapp.azure.com:7081/show/business_reports/Bosch_Annual_Report_2014_Financial_Report.pdf.txt#2238
- Annual Report Oakland: http://tabularazr.eastus.cloudapp.azure.com:7081/show/business_reports/OAK056920.pdf.txt#8920

# Other documents 
Choose any financial document, research paper or annual report to upload yourself. Or browse these sources.

### Example pdfs from public data (municipal bonds, audit reports, finanical reviews)

- http://emma.msrb.org/EP753324-ER508056-ER910760.pdf
- http://emma.msrb.org/EP407966-EP321048-EP717328.pdf
- http://emma.msrb.org/ER544111-ER421289-ER823264.pdf (very high cost of issuance)
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