pyreportjasper 1.0.2

This package aims to be a solution to compile and process JasperReports (.jrxml & .jasper files).

Is using Linux servers?

Do not forget to grant permission 777 for the directory where is the package.

Introduction

This package aims to be a solution to compile and process JasperReports (.jrxml & .jasper files).

Why?

Did you ever had to create a good looking Invoice with a lot of fields for your great web app or desktop?

I had to, and the solutions out there were not perfect. Generating HTML + CSS to make a PDF? WTF? That doesn’t make any sense! :)

Then I found JasperReports the best open source solution for reporting.

What can I do with this?

Well, everything. JasperReports is a powerful tool for reporting and BI.

From their website:

The JasperReports Library is the world’s most popular open source reporting engine. It is entirely written in Java and it is able to use data coming from any kind of data source and produce pixel-perfect documents that can be viewed, printed or exported in a variety of document formats including HTML, PDF, Excel, OpenOffice and Word.

It is recommended using Jaspersoft Studio to build your reports, connect it to your datasource (ex:JSON, XML, MySQL, POSTGRES, SQL Server), loop thru the results and output it to PDF, XLS, DOC, RTF, ODF, etc.

Some examples of what you can do:

• Invoices

• Reports

• Listings

Package to generate reports with JasperReports library through JasperStarter command-line tool.

Requirements

• Java JDK 1.8

• Python subprocess.run() function

Optional

• Mysql JDBC (if you want to use database)

• PostgreSQL JDBC (if you want to use database)

• SQL Server JDBC (if you want to use database)

• Oracle JDBC (if you want to use database)

• MongoDB JDBC (if you want to use database)

• Jaspersoft Studio (to draw and compile your reports)

Note

• The JDBC driver of your database should be place in the pyreportjasper/jasperstarter/jdbc/ directory.

• Using pyreportjasper, you can also access different types of data sources, including CSV, JDBC, JSON, NoSQL, XML, or your own custom data source.

Java (JDK and JRE)

Check if you already have Java installed:

$ javac -version
javac version 1.8.0_101

If you get:

command not found: javac

Then install it with: (Ubuntu/Debian)

$ sudo apt-get install default-jdk

To install on: (centOS/Fedora)

# yum install java-1.8.0-openjdk.x86_64

To install on windows visit the link-> JDK and look for the most appropriate version for your system.

Now run the javac -version again and check if the output is ok.

Installation

Install PyPI if you don’t have it.

pip install pyreportjasper

Using the code

Pyreport is actively developed in GitHub, where code is always available.

You can clone the public repository:

git clone git://github.com/jadsonbr/pyreportjasper.git

Download tar file:

curl -OL https://github.com/jadsonbr/pyreportjasper/tarball/master

Or, Download the zip file:

curl -OL https://github.com/jadsonbr/pyreportjasper/zipball/master

Unzip the downloaded file

Navigate to the unzipped folder

Once you have a copy of the code, you can easily include it in your Pytohn package, or install it in your site-packages directory:

$ python setup.py install

Examples

The Hello World example.

Go to the examples directory in the root of the package Open the test/examples/hello_world.jrxml file with Jaspersoft Studio or with your favorite text editor and take a look at the source code.

Compiling

First we need to compile our JRXML file into a JASPER binary file. We just have to do this one time.

Note 1: You don’t need to do this step if you are using Jaspersoft Studio. You can compile directly within the program.

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def compiling():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world.jrxml'
    jasper = JasperPy()
    jasper.compile(input_file)

This commando will compile the hello_world.jrxml source file to a hello_world.jasper file.

Processing

Now lets process the report that we compile before:

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def processing():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world.jrxml'
    output = os.path.dirname(os.path.abspath(__file__)) + '/output/examples'
    jasper = JasperPy()
    jasper.process(
        input_file, output_file=output, format_list=["pdf", "rtf"])

Now check the examples folder! :) Great right? You now have 2 files, hello_world.pdf and hello_world.rtf.

Check the API of the compile and process functions in the file pyreportjasper/jasperpy.py file.

Listing Parameters

Querying the jasper file to examine parameters available in the given jasper report file:

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def listing_parameters():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world_params.jrxml'
    jasper = JasperPy()
    output = jasper.list_parameters(input_file)
    print(output)

Advanced example - using a database

We can also specify parameters for connecting to database:

# -*- coding: utf-8 -*-
import os
from platform import python_version
from pyreportjasper import JasperPy

def advanced_example_using_database():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world.jrxml'
    output = os.path.dirname(os.path.abspath(__file__)) + '/output/examples'
    con = {
        'driver': 'postgres',
        'username': 'DB_USERNAME',
        'password': 'DB_PASSWORD',
        'host': 'DB_HOST',
        'database': 'DB_DATABASE',
        'schema': 'DB_SCHEMA',
        'port': '5432'
    }
    jasper = JasperPy()
    jasper.process(
        input_file,
        output_file=output,
        format_list=["pdf", "rtf", "xml"],
        parameters={'python_version': python_version()},
        db_connection=con,
        locale='pt_BR'  # LOCALE Ex.:(en_US, de_GE)
    )

Note 2:

For a complete list of locales see Supported Locales

Reports from a XML

See how easy it is to generate a report with a source an XML file:

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def xml_to_pdf():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/CancelAck.jrxml'

    output = os.path.dirname(os.path.abspath(__file__)) + '/output/_CancelAck'

    data_file = os.path.dirname(os.path.abspath(__file__)) + \
        '/examples/CancelAck.xml'

    jasper = JasperPy()

    jasper.process(
        input_file,
        output_file=output,
        format_list=["pdf"],
        parameters={},
        db_connection={
            'data_file': data_file,
            'driver': 'xml',
            'xml_xpath': '/CancelResponse/CancelResult/ID',
        },
        locale='pt_BR'  # LOCALE Ex.:(en_US, de_GE)
    )

    print('Result is the file below.')
    print(output + '.pdf')

Reports from a JSON File

See how easy it is to generate a report with a source an JSON file:

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def json_to_pdf():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/json.jrxml'

    output = os.path.dirname(os.path.abspath(__file__)) + '/output/_Contacts'
    json_query = 'contacts.person'

    data_file = os.path.dirname(os.path.abspath(__file__)) + \
        '/examples/contacts.json'

    jasper = JasperPy()
    jasper.process(
        input_file,
        output_file=output,
        format_list=["pdf"],
        parameters={},
        db_connection={
            'data_file': data_file,
            'driver': 'json',
            'json_query': json_query,
        },
        locale='pt_BR'  # LOCALE Ex.:(en_US, de_GE)
    )

    print('Result is the file below.')
    print(output + '.pdf')

Note 3:

JasperReports can process JSON files using either the original JSON DataSource or the newer JSONQL Data Source. Refer to the JSONQL DataSource documentation for the differences. The example above uses the JSON DataSource. To use the enhanced capabilities of the JSONQL DataSource instead use:

• the jsonql.jrxml input file

• the jsonql driver setting

• the jsonql_query query setting

by changing these three parts of the example:

...
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/jsonql.jrxml'
...
        db_connection={
...
            'driver': 'jsonql',
            'jsonql_query': json_query,
        },

Subreport Example

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy

def subreport_example():

    input_file_header = os.path.dirname(os.path.abspath(__file__)) + \
                        '/examples/subreports/header.jrxml'

    input_file_details = os.path.dirname(os.path.abspath(__file__)) + \
                         '/examples/subreports/details.jrxml'

    input_file_main = os.path.dirname(os.path.abspath(__file__)) + \
                      '/examples/subreports/main.jrxml'

    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/subreports/main.jasper'

    data_file = os.path.dirname(os.path.abspath(__file__)) + \
                '/examples/subreports/contacts.xml'

    output = os.path.dirname(os.path.abspath(__file__)) + '/output/examples/subreports/'

    jasper = JasperPy()

    jasper.compile(input_file_header)
    jasper.compile(input_file_details)
    jasper.compile(input_file_main)

    jasper.process(
                input_file,
                output_file=output,
                format_list=["pdf"],
                parameters={},
                db_connection={
                    'data_file': data_file,
                    'driver': 'xml',
                    'xml_xpath': '"/"',
                },
                locale='pt_BR',  # LOCALE Ex.:(en_US, de_GE)
                resource='examples/subreports/'
            )

Flask Example

Get parameters via URL and filter them if they are valid parameters for the jrxml file:

After runnig you could visit http://localhost:5000/?myString=My%20Beautiful%20String&myInt=1&myDate=2017-01-01&this_parameter=ignored

# -*- coding: utf-8 -*-
import os
from pyreportjasper import JasperPy
from flask import Flask, request, make_response


app = Flask(__name__)
input_file =  os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world_params.jrxml'
jasper = JasperPy()


def compiling():
    jasper.compile(input_file)

def processing(parameters):
    output_file = os.path.dirname(os.path.abspath(__file__)) + '/output/examples'
    jasper.process(
        input_file, output_file, parameters=parameters, format_list=["pdf"])

def filter_parameters(request_args):
    list_parameters = jasper.list_parameters(input_file)
    parameters = {}
    for key in list_parameters:
      if key in request_args:
        parameters[key] = request_args[key]
    return parameters

@app.route('/')
def my_route():
  request_args = request.args.to_dict()
  parameters = filter_parameters(request_args)

  processing(parameters)

  try:
      with app.open_resource(os.path.dirname(os.path.abspath(__file__)) + '/output/examples/hello_world_params.pdf') as f:
          content = f.read()
      resposta = make_response(content)
      resposta.headers['Content-Type'] = 'application/pdf; charset=utf-8'
      resposta.headers['Content-Disposition'] = 'inline; filename=hello_world_params.pdf'
      return resposta
  except IOError:
      return make_response("<h1>403 Forbidden</h1>", 403)

if __name__ == '__main__':
    compiling()
    app.run(host='0.0.0.0')

Working with resources (i18n resource bundles, icons or images)

If you need provide resource to report, you can do that by set parameter resource in method jasper.process. More details jasper starter manual page.

# -*- coding: utf-8 -*-
import os
from platform import python_version
from pyreportjasper import JasperPy

def advanced_example_using_database():
    input_file = os.path.dirname(os.path.abspath(__file__)) + \
                 '/examples/hello_world.jrxml'
    output = os.path.dirname(os.path.abspath(__file__)) + '/output/examples'
    con = {
        'driver': 'postgres',
        'username': 'DB_USERNAME',
        'password': 'DB_PASSWORD',
        'host': 'DB_HOST',
        'database': 'DB_DATABASE',
        'schema': 'DB_SCHEMA',
        'port': '5432'
    }
    jasper = JasperPy()
    jasper.process(
        input_file,
        output_file=output,
        format_list=["pdf", "rtf", "xml"],
        parameters={'python_version': python_version()},
        db_connection=con,
        locale='pt_BR',  # LOCALE Ex.:(en_US, de_GE)
        resource='path/to/my/resource/myresource.jar'
    )

Tests

All tests are in in the test directory. To run them

python setup.py test

Performance

Depends on the complexity, amount of data and the resources of your machine (let me know your use case).

I have a report that generates a Invoice with a DB connection, images and multiple pages and it takes about 3/4 seconds to process. I suggest that you use a worker to generate the reports in the background.

Questions?

Open a Issue

Contribute

Contribute to the community Python, feel free to contribute, make a fork!!

Contributors

• List of contributors

Thanks

Thanks to Cenote GmbH for the JasperStarter tool.