Skip to content

Projects developed during the Spring 2016 iteration of the Data Mechanics course at Boston University.

Notifications You must be signed in to change notification settings

data-mechanics/course-2016-spr-proj

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

course-2016-spr-proj

Project repository for the course project in the Spring 2016 iteration of the Data Mechanics course at Boston University.

In this project, you will implement components that obtain a few data sets from web services of your choice, insert them into the data set repository with appropriate provenance information, and combine them into at least two additional derived data sets (also with appropriate provenance information).

This project description will be updated as we continue work on the infrastructure.

MongoDB infrastructure

Setting up

We have committed setup scripts for a MongoDB database that will set up the database and collection management functions that ensure users sharing the project data repository can read everyone's collections but can only write to their own collections. Once you have installed your MongoDB instance, you can prepare it by first starting mongod without authentication:

mongod --dbpath "<your_db_path>"

If you're setting up after previously running setup.js, you may want to reset (i.e., delete) the repository as follows.

mongo reset.js

Next, make sure your user directories (e.g., alice_bob if Alice and Bob are working together on a team) are present in the same location as the setup.js script, open a separate terminal window, and run the script:

mongo setup.js

Your MongoDB instance should now be ready. Stop mongod and restart it, enabling authentication with the --auth option:

mongod --auth --dbpath "<your_db_path>"

Working on data sets with authentication

With authentication enabled, you can start mongo on the repository (called repo by default) with your user credentials:

mongo repo -u alice_bob -p alice_bob --authenticationDatabase "repo"

However, you should be unable to create new collections using db.createCollection() in the default repo database created for this project:

> db.createCollection("EXAMPLE");
{
  "ok" : 0,
  "errmsg" : "not authorized on repo to execute command { create: \"EXAMPLE\" }",
  "code" : 13
}

Instead, load the server-side functions so that you can use the customized createTemp() or createPerm() functions, which will create collections that can be read by everyone but written only by you:

> db.loadServerScripts();
> var EXAMPLE = createPerm("EXAMPLE");

Notice that this function also prefixes the user name to the name of the collection (unless the prefix is already present in the name supplied to the function).

> EXAMPLE
alice_bob.EXAMPLE
> db.alice_bob.EXAMPLE.insert({value:123})
WriteResult({ "nInserted" : 1 })
> db.alice_bob.EXAMPLE.find()
{ "_id" : ObjectId("56b7adef3503ebd45080bd87"), "value" : 123 }

For temporary collections that are only necessary during intermediate steps of of a computation, use createTemp(); for permanent collections that represent data that is imported or derived, use createPerm().

If you do not want to run db.loadServerScripts() every time you open a new terminal, you can use a .mongorc.js file in your home directory to store any commands or calls you want issued whenever you run mongo.

Required libraries and tools

On Fedora-based Linux systems, you can use the following to install all the required libraries and tools:

yum -y install $(cat requirements.yum)

Some projects require the Z3 Theorem Prover. To install it, first clone the Z3 repository:

git clone https://github.com/Z3Prover/z3.git

You can then install Z3 by following the instructions in the Z3 README. The instructions for a Linux environment are duplicated below:

cd z3
python scripts/mk_make.py
cd build
make
sudo make install

Python infrastructure

Make sure your Python environment has all the libraries required by the various projects (note that on your system, the Python 3 executable may have a different name, such as python3):

python -m pip install -r requirements.python

To use PyMongo with the above interface, run the pymongo_dm.py script at the top of your modules or script:

exec(open('../pymongo_dm.py').read())

The script alice_bob/example.py is an example that illustrates how the wrappers can be used. It also provides a detailed example of how to record appropriate provenance information using the prov module.

About

Projects developed during the Spring 2016 iteration of the Data Mechanics course at Boston University.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published