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A command-line tool (and Python library) to extract data from CommCareHQ into a SQL database or Excel workbook

Project description

CommCare Export

`|Build Status| <>`_ `|Test
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A command-line tool (and Python library) to generate customized exports
from the CommCareHQ REST API.

Installation & Quick Start

0a. Install Python and ``pip``. This tool is `tested with Python 2.6,
2.7, and 3.3 <>`_.

0b. Sign up for CommCareHQ at
if you have not already.

1. Install CommCare Export via ``pip``


$ pip install commcare-export

2. Visit the CommCareHQ Exchange and add the `Simple CommCare
Demo/Tutorial" <>`_
app to a new project space.

3. Visit the Release Manager, make a build, click the star to release

4. Visit CloudCare and fill out a bunch of forms.

5. Try out the example queries in the ``examples/`` directory, providing
your project name on the command line:


$ commcare-export \
--query examples/demo-registration.xlsx \
--project YOUR_PROJECT \
--output-format markdown

$ commcare-export \
--query examples/demo-registration.json \
--project YOUR_PROJECT \
--output-format markdown

$ commcare-export \
--query examples/demo-deliveries.xlsx \
--project YOUR_PROJECT \
--output-format markdown

$ commcare-export \
--query examples/demo-deliveries.json \
--project YOUR_PROJECT \
--output-format markdown

You'll see the tables printed out. Change to
``--output-format sql --output URL_TO_YOUR_DB --since DATE`` to sync all
forms submitted since that date.

All examples are present in Excel and also equivalent JSON.

Command-line Usage

The basic usage of the command-line tool is with a saved Excel or JSON
query (see how to write these, below)


$ commcare-export --commcare-hq <URL or alias like "local" or "prod"> \
--username <username> \
--project <project> \
--version <api version, defaults to latest known> \
--query <excel file, json file, or raw json> \
--output-format <csv, xls, xlsx, json, markdown, sql> \
--output <file name or SQL database URL>

See ``commcare-export --help`` for the full list of options.

There are example query files for the CommCare Demo App (available on
the CommCareHq Exchange) in the ``examples/`` directory.

Excel Queries

An excel query is any ``.xlsx`` workbook. Each sheet in the workbook
represents one table you wish to create. There are two grouping of
columns to configure the table:

- **Data Source**: Set this to ``form`` to export form data, or
``case`` for case data.
- **Filter Name** / *Filter Value*: These columns are paired up to
filter the input cases or forms.
- **Field**: The destination in your SQL database for the value.
- **Source Field**: The particular field from the form you wish to
extract. This can be any JSON path.

JSON Queries

JSON queries are a described in the table below. You build a JSON object
that represents the query you have in mind. A good way to get started is
to work from the examples, or you could make an excel query and run the
tool with ``--dump-query`` to see the resulting JSON query.

Python Library Usage

As a library, the various ``commcare_export`` modules make it easy to

- Interact with the CommCareHQ REST API
- Execute "Minilinq" queries against the API (a very simple query
language, described below)
- Load and save JSON representations of Minilinq queries
- Compile Excel configurations to Minilinq queries

To directly access the CommCareHq REST API:


>>> import getpass
>>> from commcare_export.commcare_hq_client import CommCareHqClient
>>> api_client = CommCareHqClient('', project='your_project').authenticated('your_username', getpass.getpass())
>>> forms = api_client.iterate('form', {'app_id': "whatever"})
>>> [ (form['received_on'], form['form.gender']) for form in forms ]

To issue a ``minilinq`` query against it, and then print out that query
in a JSON serialization:


>>> import getpass
>>> import json
>>> from commcare_export.minilinq import *
>>> from commcare_export.commcare_hq_client import CommCareHqClient
>>> from commcare_export.commcare_minilinq import CommCareHqEnv
>>> from commcare_export.env import BuiltInEnv
>>> api_client = CommCareHqClient('', project='your_project').authenticated('your_username', getpass.getpass())
>>> saved_query = Map(source=Apply(Reference("api_data"), Literal("form"), Literal({"filter": {"term": {"app_id": "whatever"}}})),
body=List([Reference("received_on"), Reference("form.gender")]))

>>> forms = saved_query.eval(BuiltInEnv() | CommCareHqEnv(api_client) | JsonPathEnv())
>>> print json.dumps(saved_query.to_jvalue(), indent=2)

Which will output JSON equivalent to this:


"Map": {
"source": {
"Apply": {
"fn": {"Ref": "api_data"},
"args": [
{"Lit": "form"},
{"Lit": {"filter": {"term": {"app_id": "something"}}}}
"body": {
"List": [
{"Ref": "received_on"},
{"Ref": "form.gender"}

MiniLinq Reference

The abstract syntax can be directly inspected in the
``commcare_export.minilinq`` module. Note that the choice between
functions and primitives is deliberately chosen to expose the structure
of the MiniLinq for possible optimization, and to restrict the overall

Here is a description of the astract syntax and semantics

\| Python \| JSON \| Which is evaluates to \|
\| ``Literal(v)`` \| ``{"Lit": v}`` \| Just ``v`` \| \| ``Reference(x)``
\| ``{"Ref": x}`` \| Whatever ``x`` resolves to in the environment \| \|
``List([a, b, c, ...])`` \| ``{"List": [a, b, c, ...}`` \| The list of
what ``a``, ``b``, ``c`` evaluate to \| \| ``Map(source, name, body)``
\| ``{"Map": {"source": ..., "name": ..., "body": ...}`` \| Evals
``body`` for each elem in ``source``. If ``name`` is provided, the elem
will be bound to it, otherwise it will replace the whole env. \| \|
``FlatMap(source, name, body)`` \| ``{"FlatMap": {"source" ... etc}}``
\| Flattens after mapping, like nested list comprehensions \| \|
``Filter(source, name, body)`` \| etc \| \| \|
``Bind(value, name, body)`` \| etc \| Binds the result of ``value`` to
``name`` when evaluating ``body`` \| \| ``Emit(table, headings, rows)``
\| etc \| Emits ``table`` with ``headings`` and ``rows``. Note that
``table`` is a string, ``headings`` is a list of expressions, and
``rows`` is a list of lists of expressions. See explanation below for
emitted output. \| \| ``Apply(fn, args)`` \| etc \| Evaluates ``fn`` to
a function, and all of ``args``, then applies the function to the args.

Built in functions like ``api_data`` and basic arithmetic and comparison
are provided via the environment, referred to be name using ``Ref``, and
utilized via ``Apply``

Output Formats

Your MiniLinq may define multiple tables with headings in addition to
their body rows by using ``Emit`` expressions, or may simply return the
results of a single query.

If your MiniLinq does not contain any ``Emit`` expressions, then the
results of the expression will be printed to standard output as
pretty-printed JSON.

If your MiniLinq *does* contain ``Emit`` expressions, then there are
many formats available, selected via the ``--output-format <format>``
option, and it can be directed to a file with the ``--output <file>``
command-line option.

- ``csv``: Each table will be a CSV file within a Zip archive.
- ``xls``: Each table will be a sheet in an old-format Excel
- ``xlsx``: Each table will be a sheet in a new-format Excel
- ``json``: The tables will each be a member of a JSON dictionary,
printed to standard output
- ``markdown``: The tables will be streamed to standard output in
Markdown format (very handy for debugging your queries)
- ``sql``: All data will be idempotently "upserted" into the SQL
database you specify, including creating the needed tables and


Required dependencies will be automatically installed via pip. But since
you may not care about all export formats, the various dependencies
there are optional. Here is how you might install them:


# To export "xlsx"
$ pip install openpyxl

# To export "xls"
$ pip install xlwt

# To sync with a SQL database
$ pip install SQLAlchemy alembic


0. Sign up for github, if you have not already, at

1. Fork the repository at

2. Clone your fork, install into a ``virtualenv``, and start a feature


$ mkvirtualenv commcare-export
$ git clone
$ cd commcare-export
$ pip install -e .
$ git checkout -b my-super-duper-feature

3. Make your edits.

4. Make sure the tests pass. The best way to test for all versions is to
sign up for and turn on automatic continuous
testing for your fork.


$ py.test
=============== test session starts ===============
platform darwin -- Python 2.7.3 -- pytest-2.3.4
collected 17 items

tests/ .
tests/ ....
tests/ ........
tests/ .
tests/ ...

============ 17 passed in 2.09 seconds ============

5. Push the feature branch up


$ git push -u origin my-super-duper-feature

6. Visit\_USERNAME/commcare-export and submit a
pull request.

7. Accept our gratitude for contributing: Thanks!

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