The PyDataweaver Project

The PyDataweaver is a Python tool that offers a simple to use, clean and a robust data integration platform.

The PydataWeaver supports data integration of spatial datasets (Raster and Vector data), as well as tabular datasets.

Problem solving in science involves and requires studying entities using a broad range of associations among the entities under study. These associations are obtained through collecting and integrating various sources and forms of data.

Since these heterogenous datasets are collected by various scientists, the datasets are domain based or centered around a unique subset of problems.

The pydataweaver bridges the gap scientist's face of not having readily unified datasets that can be used for multi dimension feature analysis. The data weaver handles the finding and integration of heterogeneous datasets forming a new dataset.

Dependencies

This package requires Python 3.3+, recommends Python 3.6+ and depends on the following packages:

 retriever
 PyMySQL>=0.4
 psycopg2>=2.0
 gdal
 future
 numpydoc
 pandas

They can be installed using pip.

sudo pip install -r requirements.txt

The package supports the following database management systems (DBMS):

DBMS	Spatial Datasets	Tabular Datasets
PostgreSQL	Yes	Yes
SQLite	No	Yes

Installing From Source

Either use pip to install directly from GitHub:

pip install git+https://[email protected]/weecology/pydataweaver.git

or:

1. Clone the repository
2. From the directory containing setup.py, run the following command: pip install .. You may need to include sudo at the beginning of the command depending on your system (i.e., sudo pip install .).

More extensive documentation for those that are interested in developing can be found here

Using the Command Line

After installing the package, run pydataweaver update to download the latest available dataset scripts. To see the full list of command line options and datasets run pydataweaver --help.

$ pydataweaver --help

usage: pydataweaver [-h] [-v] [-q] {help,ls,citation,license,join,update} ...

positional arguments:
  {help,ls,citation,license,join,update}
                        sub-command help
    help
    ls                  display a list all available datasets
    citation            view citation
    license             view dataset licenses
    join                integrate data using a data package script
    update              download updated versions of data package scripts

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -q, --quiet           suppress command-line output

To get a list of available dataset use pydataweaver ls

$ pydataweaver ls

Available datasets : 11

breed-bird-routes-bioclim
mammal-community-bioclim
mammal-community-masses
mammal-community-sites-all-bioclim
mammal-community-sites-bioclim
mammal-community-sites-harvard-linear-features
mammal-community-sites-harvard-linear-features-soils
mammal-community-sites-harvard-soil
mammal-diet-mammal-life-history
mammal-sites-bioclim-1-2
portal-plot-species

.
...

To view the citaion of the datasets use `pydataweaver citation [dataset-name] Running pydataweaver with no citation will provide the citation for the tool.

$ pydataweaver citation mammal-diet-mammal-life-history

Dataset:  mammal-diet-mammal-life-history
Description:   Integrated data set of mammal-life-hist and mammal-diet
Citations:
mammal-life-hist:    S. K. Morgan Ernest. 2003. ....
mammal-diet:    Kissling WD, Dalby L, Flojgaard C, Lenoir J, ...

Integrating Data

To integrate data, run pydataweaver join [data package name] and provide the connection configurations.

pydataweaver join postgres -h
usage: pydataweaver join postgres [-h] [--user [USER]] [--password [PASSWORD]]
                            [--host [HOST]] [--port [PORT]]
                            [--database [DATABASE]]
                            [--database_name [DATABASE_NAME]]
                            [--table_name [TABLE_NAME]]
                            dataset

positional arguments:
  dataset               file name

optional arguments:
  -h, --help            show this help message and exit
  --user [USER], -u [USER]
                        Enter your PostgreSQL username
  --password [PASSWORD], -p [PASSWORD]
                        Enter your password
  --host [HOST], -o [HOST]
                        Enter your PostgreSQL host
  --port [PORT], -r [PORT]
                        Enter your PostgreSQL port
  --database [DATABASE], -d [DATABASE]
                        Enter your PostgreSQL database name
  --database_name [DATABASE_NAME], -a [DATABASE_NAME]
                        Format of schema name
  --table_name [TABLE_NAME], -t [TABLE_NAME]
                        Format of table name

To use the pydataweaver with postges .pgpass file set

pydataweaver join postgres

or with command line configurations supplied

pydataweaver join postgres -u name-of-user -h host-name -d database-to-use

Contribution

If you find any operation that is not supported by this package, feel free to create a Github issue. Additionally, you are more than welcome to submit a pull request for a bug fix or additional feature.

If you find any operation that is not supported by this package, feel free to create a Github issue. Additionaly you are more than welcome to submit a pull request for a bug fix or additional feature.

Please take a look at the Code of Conduct governing contributions to this project.

Acknowledgments

Development of this software was funded by the Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative to Ethan White.