It is strongly advised to install scipy, numpy and shapely (globaly) as binary packages and not through virtualenv, because of their large number of non-python dependencies. E.g. on Debian/Ubuntu systems use sudo apt-get install python3-numpy python3-scipy python3-shapely to install. Make sure access to the global packages is activated in the virtual environment (e.g. through toggleglobalsitepackages in virtualenvwrapper).

When compiling entirely from source, You also might need to install the following libraries: (for shapely): libgeos-dev; (for scipy): libblas-dev, liblapack-dev, gfortran.

Imports the OSM data for Germany. The following tables are created: Country, State, District and Cities. The data is imported from germany-latest.osm.pbf, obtained from geofabrik. The pbf file needs to be placed in data/.

The importer used is imposm3, which is included in the vagrant setup (and will be executed within the VM). The import uses a custem mapping, which is provided in importer/mapping.json. The import is conducted in two steps: First, the data is imported to the tables Osm_Admin and Osm_Places. Second the Country, State, District and Cities tables are created from these tables.

Prerequisite: No contrib tables, delete if existing: python manage.py drop_tables -t contrib

To import all the OSM data use the manage script. To invoke the whole pipeline use the following command (will take several hours):

python manage.py import_osm --imposm --simplify --load --drop_tables

• --imposm the first import step (see above)
• --simplify simplify all map data (borders)
• --load the second import step (see above)
• --drop-tables deletes the Osm_Admin and Osm_Places tables after a successful import

All the above steps can be invoked separately.

python manage.py import_osm --drop_tables --imposm --load
DYLD_LIBRARY_PATH=/Applications/Postgres.app/Contents/Versions/9.3/lib python manage.py import_osm --drop_tables --load

Imports weather observation data from the DWD (Deutscher Wetterdienst). The importer is a adopted version from cholin. Per default, it downloads all the [recent daily observations] (ftp://ftp.dwd.de/pub/CDC/observations_germany/climate/daily/kl).

Details on the importer from cholin:

The importer downloads the station summary file to get a list of all weather stations. After that it downloads for each station the corresponding zip file (with measurement data), extracts it in-memory and parses it. To get information about which weather station is the nearest for a given point, it also calculates a region polygon for each station. This is done by computing the voronoi diagram for all stations. The resulting regions may be outside of the country germany. To avoid this there is a polygon of the border of germany (data is from naturalearthdata.com - country extraction and exportation as geojson with qgis). For each region we calculate the intersection with this polygon and use the result as final region (Multi)Polygon.

Use the importer with the manage.py script:

To download all data and import all observation data:

python manage.py import_dwd

Create an intermediate result in data/weather.json:

python manage.py import_dwd --to_json

Import the intermediate result from data/weather.json:

python manage.py import_dwd --from_json

python manage.py import_dwd --to_json
DYLD_LIBRARY_PATH=/Applications/Postgres.app/Contents/Versions/9.3/lib ython manage.py import_dwd --from_json

Importing the Forecast Data is done in two steps. First you have to download the GRIB files from the NOAA FTP servers. Then you have to import them as Postgis Raster.

For downloading the GFS data a date range and a target directory has to be specified. The format for the start and enddate is YYYYMMDDHH or latest for the most recently available GFS calculation. Optionally the forecast hours can be specified as a range (Defaults to download from 0 to 129 in 3 hour steps).

usage: run_gfs.py download [-h] [--hours_start HOURS_START]
                           [--hours_stop HOURS_STOP] [--hours_step HOURS_STEP]
                           [startdate] [enddate] datadir

For example, assuming data should be stored to data/forecasts:

./run_gfs.py download 2014121112 2015011306 data/forecasts

To import the downloaded data, the download directory and a data range has to be specified:

usage: run_gfs.py import [-h] datadir [startdate] [enddate]

For example, assuming the data is stored in data/forecasts:

./run_gfs.py import data/forecasts 2014121112 2015011306

To speed up some queries, the area contribution of the region (voronoi cell) of weather stations to states and districts is precomputed and materialized. Run python manage.py calculate_contrib_area to create and fill the ContribState and ContribDistrict tables.

Python inherist the standard locale from the current shell environment. If this is not set to utf8 it tries to convert to ASCII, which produces. UnicodeEncodeError: 'ascii' codec can't encode character Test with $ locale, this should show utf-8. If not, fix with

export LANG=en_US.UTF-8
export LC_ALL=en_US.UTF-8

The libssl version Mac OS X uses might be too old for psycopg, resulting in an error like the following:

...
ImportError: dlopen(...lib/python3.4/site-packages/psycopg2/_psycopg.so, 2): Library not loaded: libssl.1.0.0.dylib
  Referenced from: ...lib/python3.4/site-packages/psycopg2/_psycopg.so
  Reason: image not found

This can be solved by changing the dynamic shared library install names in the psycopq binary. First, find out the version psycopq is using:

otool -L /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so
$ /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so:
	/usr/local/lib/libpq.5.dylib (compatibility version 5.0.0, current version 5.6.0)
	libssl.1.0.0.dylib (compatibility version 1.0.0, current version 1.0.0)
	libcrypto.1.0.0.dylib (compatibility version 1.0.0, current version 1.0.0)
	/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1213.0.0)
	/usr/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 283.0.0)

Now, change the the shared libraries for libssl and libcrypto (using the libraries provided by Postgres.app):

install_name_tool -change libssl.1.0.0.dylib /Applications/Postgres.app/Contents/Versions/9.3/lib/libssl.1.0.0.dylib /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so
install_name_tool -change libcrypto.1.0.0.dylib /Applications/Postgres.app/Contents/Versions/9.3/lib/libcrypto.1.0.0.dylib /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so

psycopq now uses the correct libraries:

otool -L /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so                                                                                                                                                   
$ /Users/jvf/miniconda3/envs/env-sw/lib/python3.4/site-packages/psycopg2/_psycopg.so:
	/usr/local/lib/libpq.5.dylib (compatibility version 5.0.0, current version 5.6.0)
	/Applications/Postgres.app/Contents/Versions/9.3/lib/libssl.1.0.0.dylib (compatibility version 1.0.0, current version 1.0.0)
	/Applications/Postgres.app/Contents/Versions/9.3/lib/libcrypto.1.0.0.dylib (compatibility version 1.0.0, current version 1.0.0)
	/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1213.0.0)
	/usr/lib/libgcc_s.1.dylib (compatibility version 1.0.0, current version 283.0.0)

It is strongly recommended to do all this in an virtual environment to not mess up your system!

Source: More Information: superuser.com

Another possibilty is to prefix commands with DYLD_LIBRARY_PATH and DYLD_FRAMEWORK_PATH, but this works less reliable and potentially messes up the linking of other libraries. Example:

DYLD_LIBRARY_PATH=$(HOME)/lib:/usr/local/lib:/lib:/usr/lib:/Applications/Postgres.app/Contents/Versions/9.3/lib,DYLD_FRAMEWORK_PATH=/Library/Frameworks:/Network/Library/Frameworks:/System/Library/Frameworks python manage.py import_dwd

providing an alternative path for a newer version of libssl to the dynamic linker (in this example the libs from Postgres.app are used, but can link against a homebrew installed version as well):

export DYLD_LIBRARY_PATH=$(HOME)/lib:/usr/local/lib:/lib:/usr/lib:/Applications/Postgres.app/Contents/Versions/9.3/lib
export DYLD_FRAMEWORK_PATH=/Library/Frameworks:/Network/Library/Frameworks:/System/Library/Frameworks

Source: stackoverflow.com