Prerequisites¶

[1] Enhydris runs on all supported versions of Python 3. It does not run on Python 2. setuptools and pip are needed in order to install the rest of the Python modules.

[2] Enhydris has been tested with PostgreSQL+PostGIS and spatialite, the latter only in development.

[3] PIL/Pillow is not directly required by Enhydris, but by other python modules required my Enhydris. In theory, installing Enhydris with pip will indirectly result in also installing PIL/Pillow. However, it can be tricky to install, and it may be better to install a prepackaged version for your operating system. It must be compiled with libfreetype support. This is common in Linux distributions.

apt-get install python3 postgresql python3-setuptools python3-pip \
    python3-pil python3-gdal python3-pandas

Install Enhydris¶

Install Enhydris with pip install enhydris, probably specifying a version and using a virtualenv, like this:

virtualenv --system-site-packages --python=/usr/bin/python3 \
    [virtualenv_target_dir]
pip install 'enhydris>=1,<2'

You may or may not want to use the --system-site-packages parameter. The main reason to use it is that it will then use your systemwide python3-gdal, python3-pil and python3-pandas (and python3-psycopg2, if you use PostgreSQL), which means it won’t need to compile these for the virtualenv.

Configuring Enhydris¶

Execute enhydris-admin newinstance to create a new Enhydris configuration directory; for example:

cd /etc
enhydris-admin newinstance myinstance

The above will create directory /etc/myinstance with some files in it.

Open the created file settings.py and edit it according to the comments you will find in the file.

Initializing the database¶

In order to initialize your database and create the necessary database tables for Enhydris to run, run the following commands inside the Enhydris configuration directory:

python manage.py migrate
python manage.py createsuperuser

The above commands will also ask you to create a Enhydris superuser.

# Install PostgreSQL and PostGIS
apt-get install postgis postgresql-9.4-postgis

# Create database template
sudo -u postgres -s
createdb template_postgis
psql -d template_postgis -c "CREATE EXTENSION postgis;"
psql -d template_postgis -c \
   "UPDATE pg_database SET datistemplate='true' \
   WHERE datname='template_postgis';"
exit

# Create database
sudo -u postgres -s
createuser --pwprompt enhydris_user
createdb --template template_postgis --owner enhydris_user \
   enhydris_db
exit

local   all         all                               md5
host    all         all         127.0.0.1/32          md5
host    all         all         ::1/128               md5

service postgresql restart

cd C:\Program Files\PostgreSQL\9.4\bin
createdb template_postgis
psql -d template_postgis -c "CREATE EXTENSION postgis;"
psql -d template_postgis -c "UPDATE pg_database SET datistemplate='true'
   WHERE datname='template_postgis';"
createuser -U postgres --pwprompt enhydris_user
createdb --template template_postgis --owner enhydris_user enhydris_db

Running Enhydris¶

Inside the Enhydris configuration directory, run the following command:

python manage.py runserver

The above command will start the Django development server and set it to listen to port 8000. If you then start your browser and point it to http://localhost:8000/, you should see Enhydris in action. Note that this only listens to the localhost; if you want it to listen on all interfaces, use 0.0.0.0:8000 instead.

To use Enhydris in production, you need to setup a web server such as apache. This is described in detail in Deploying Django.

Post-install configuration: domain name¶

After you run Enhydris, logon as a superuser, visit the admin panel, go to Sites, edit the default site, and enter your domain name there instead of example.com. Emails to users for registration confirmation will contain links to that domain. Restart the Enhydris (by restarting apache/gunicorn/whatever) after changing the domain name.

Settings reference¶

These are the settings available to Enhydris, in addition to the Django settings.

ENHYDRIS_FILTER_DEFAULT_COUNTRY¶

When a default country is specified, the station search is locked within that country and the station search filter allows only searches in the selected country. If left blank, the filter allows all countries to be included in the search.

ENHYDRIS_FILTER_POLITICAL_SUBDIVISION1_NAME¶

ENHYDRIS_FILTER_POLITICAL_SUBDIVISION2_NAME¶

These are used only if FILTER_DEFAULT_COUNTRY is set. They are the names of the first and the second level of political subdivision in a certain country. For example, Greece is first divided in ‘districts’, then in ‘prefecture’, whereas the USA is first divided in ‘states’, then in ‘counties’.

ENHYDRIS_USERS_CAN_ADD_CONTENT¶

This must be configured before syncing the database. If set to True, it enables all logged in users to add content to the site (stations, instruments and timeseries). It enables the use of user space forms which are available to all registered users and also allows editing existing data. When set to False (the default), only privileged users are allowed to add/edit/remove data from the db.

ENHYDRIS_SITE_CONTENT_IS_FREE¶

If this is set to True, all registered users have access to the timeseries and can download timeseries data. If set to False (the default), the users may be restricted.

ENHYDRIS_TSDATA_AVAILABLE_FOR_ANONYMOUS_USERS¶

Setting this option to True will enable all users to download timeseries data without having to login first. The default is False.

ENHYDRIS_MIN_VIEWPORT_IN_DEGS¶

Set a value in degrees. When a geographical query has a bounding box with dimensions less than MIN_VIEWPORT_IN_DEGS, the map will have at least a dimension of MIN_VIEWPORT_IN_DEGS². Useful when showing a single entity, such as a hydrometeorological station. Default value is 0.04, corresponding to an area approximately 4×4 km.

ENHYDRIS_MAP_DEFAULT_VIEWPORT¶

A tuple containing the default viewport for the map in geographical coordinates, in cases of geographical queries that do not return anything. Format is (minlon, minlat, maxlon, maxlat) where lon and lat is in decimal degrees, positive for north/east, negative for west/south.

ENHYDRIS_TIMESERIES_DATA_DIR¶

The directory where the files with the time series data are stored; for example, /var/local/enhydris/timeseries_data. You must specify this in production. The default is timeseries_data, relative to the directory from which you start the server.

You might choose to put that under MEDIA_ROOT, but in that case all data might be publicly available, without permission checking.

ENHYDRIS_TS_GRAPH_BIG_STEP_DENOMINATOR¶

ENHYDRIS_TS_GRAPH_FINE_STEP_DENOMINATOR¶

Chart options for time series details page. The big step represents the max num of data points to be plotted, default is 200. The fine step are the max num of points between main data points to search for a maxima, default is 50.

ENHYDRIS_SITE_STATION_FILTER¶

This is a quick-and-dirty way to create a web site that only displays a subset of an Enhydris database. For example, the database of http://system.deucalionproject.gr/ is the same as that of http://openmeteo.org/; however, the former only shows stations relevant to the Deucalion project, because it has this setting:

ENHYDRIS_SITE_STATION_FILTER = {'owner__id__exact': '9'}

ENHYDRIS_DISPLAY_COPYRIGHT_INFO¶

If True, the station detail page shows copyright information for the station. By default, it is False. If all the stations in the database belong to one organization, you probably want to leave it to False. If the database is going to be openly accessed and contains data that belongs to many owners, you probably want to set it to True.

ENHYDRIS_WGS84_NAME¶

Sometimes Enhydris displays the reference system of the co-ordinates, which is always WGS84. In some installations, it is desirable to show something other than “WGS84”, such as “ETRS89”. This parameter specifies the name that will be displayed; the default is WGS84.

This is merely a cosmetic issue, which does not affect the actual reference system used, which is always WGS84. The purpose of this parameter is merely to enable installations in Europe to display “ETRS89” instead of “WGS84” whenever this is preferred. Given that the difference between WGS84 and ETRS89 is only a few centimeters, which is considerably less that the accuracy with which station co-ordinates are given, whether WGS84 or ETRS89 is displayed is actually irrelevant.

ENHYDRIS_MAP_BASE_LAYERS¶

A list of Javascript definitions of base layers to use on the map. The default is:

[r'''OpenLayers.Layer.OSM.Mapnik("Open Street Map",
    {isBaseLayer: true,
    attribution: "Map by <a href='http://www.openstreetmap.org/'>OSM</a>"})''',
 r'''OpenLayers.Layer.OSM.CycleMap("Open Cycle Map",
    {isBaseLayer: true,
        attribution: "Map by <a href='http://www.openstreetmap.org/'>OSM</a>"})'''
]

ENHYDRIS_MAP_BOUNDS¶

A pair of points, each one being a pair of co-ordinates in WGS84; the first one is the bottom-left point and the second is the top-right. The default is Greece:

ENHYDRIS_MAP_BOUNDS = ((19.3, 34.75), (29.65, 41.8))

The bounds are automatically enlarged in order to encompass all registered objects, so this setting is useful only if there are no objects or a few objects.

ENHYDRIS_MAP_MARKERS¶

The map can show different station types with different markers. For example:

ENHYDRIS_MAP_MARKERS = {
    '0': 'images/drop_marker.png',
    '1': 'images/drop_marker_cyan.png',
    '3': 'images/drop_marker_orange.png',
    '11': 'images/drop_marker_green.png',
}

In the example above, stations whose type id is 3 will be shown with drop_marker_orange.png, and any marker whose id is not one of 1, 3, or 11 will show with drop_marker.png. The files are URLs; if they are relative, they are relative to STATIC_URL.

The default is:

ENHYDRIS_MAP_MARKERS = {
    '0': 'images/drop_marker.png',
}

Version 1.0¶

Version 0.8¶

Version 0.6¶

Version 0.5¶

Version 0.2¶

Main principles¶

The Enhydris database is implemented in PostgreSQL. While the implementation of the database is through Django’s object-relational mapper, which is more or less RDBMS-independent, Enhydris uses PostgreSQL’s geographic features, so it is not portable. It also uses some custom PostgreSQL code for storing timeseries (however this is likely to change in the future).

In Django parlance, a model is a type of entity, which usually maps to a single database table. Therefore, in Django, we usually talk of models rather than of database tables, and we design models, which is close to a conceptual database design, leaving it to Django’s object-relational mapper to translate to the physical. In this text, we also speak more of models than of tables. Since a model is a Python class, we describe it as a Python class rather than as a relational database table. If, however, you feel more comfortable with tables, you can generally read the text understanding that a model is a table.

If you are interested in the physical structure of the database, you need to know the model translation rules, which are quite simple:

• The name of the table is the lower case name of the model, with a prefix. The prefix for the core of the database is hcore_. (More on the prefix below).
• Tables normally have an implicit integer id field, which is the primary key of the table.
• Table fields have the same name as model attributes, except for foreign keys.
• Foreign keys have the name of the model attribute suffixed with _id.
• When using multi-table inheritance, the primary key of the child table is also a foreign key to the id field of the parent table. The name of the database column for the key of the child table is the lower cased parent model name suffixed with _ptr_id.

There are two drawings that accompany this text: the drawing for the conceptual data model, and the drawing for the physical data model. You should avoid looking at the physical data model; it is cluttered and confusing, since it is machine-generated. It is only provided for the benefit of those who are not comfortable with Django’s object-relational mapping. However, it is best to learn to read the conceptual data model; if you become acquainted with the Django’s object-relational mapping rules listed above, you will be able to write SQL commands effortlessly, by using these rules in your head. The drawing of the physical data model is also far more likely to contain errors or to be outdated than the drawing and documentation for the conceptual data model.

The core of the Enhydris database is a list of measuring stations, with additional information such as instruments, photos, videos, and so on, and the hydrological and meteorological time series stored for each measuring station. This can be used in or assisted by many more applications, which may or may not be needed in each setup. A billing system is needed for agencies that charge for their data, but not for those who offer them freely or only internally. Some organisations may need to develop additional software for managing aqueducts, and some may not. Therefore, the core is kept as simple as possible. The core database tables use the hcore_ prefix. Other applications use another prefix. The name of a table is the lowercased model name preceeded by the prefix. For example, the table that corresponds to the Gentity model is hcore_gentity.

Lookup tables¶

Lookup tables are those that are used for enumerated values. For example, the list of variables is a lookup table. Most lookup tables in the Enhydris database have three fields: id, descr, and short_descr, and they all inherit the following abstract base class:

class enhydris.hcore.models.Lookup¶

This class contains the common attribute of the lookup tables:

descr¶

A multilingual character field with a descriptive name.

Most lookup tables are described in a relevant section of this document, where their description fits better; for example, StationType is described at Section Station and its related models.

Lentities¶

The Lentity is the superclass of people and groups. For example, a measuring station can belong either to an organisation or an individual. Lawyers use the word “entity” to refer to individuals and organisations together, but this would create confusion because of the more generic meaning of “entity” in computing; therefore, we use “lentity”, which is something like a legal entity. The lentity hierarchy is implemented by using Django’s multi-table inheritance.

class enhydris.hcore.models.Lentity¶

remarks¶

A multilingual text field of unlimited length.

class enhydris.hcore.models.Person¶

last_name¶

first_name¶

middle_names¶

initials¶

The above four are all multilingual character fields. The initials contain the initials without the last name. For example, for Antonis Michael Christofides, initials would contain the value “A. M.”.

class enhydris.hcore.models.Organization¶

name¶

acronym¶

name and acronym are both multilingual character fields.

Gentity and its direct descendants: Gpoint, Gline, Garea¶

A Gentity is a geographical entity. Examples of gentities (short for geographical entities) are measuring stations, cities, boreholes and watersheds. A gentity can be a point (e.g. stations and boreholes), a surface (e.g. lakes and watersheds), a line (e.g. aqueducts), or a network (e.g. a river). The gentities implemented in the core are measuring stations and water basins. The gentity hierarchy is implemented by using Django’s multi-table inheritance.

class enhydris.hcore.models.Gentity¶

name¶

A multilingual field with the name of the gentity, such as the name of a measuring station. Up to 200 characters.

short_name¶

A multilingual field with a short name of the gentity. Up to 50 characters.

remarks¶

A multilingual field with general remarks about the gentity. Unlimited length.

water_basin¶

The water basin where the gentity is.

water_division¶

The water division in which the gentity is. Foreign key to WaterDivision.

political_division¶

The country or other political division in which the gentity is. Foreign key to PoliticalDivision.

class enhydris.hcore.models.Gpoint(Gentity)¶

point¶

This is a GeoDjango PointField that stores the 2-d location of the point.

srid¶

Specifies the reference system in which the user originally entered the co-ordinates of the point. Valid srid‘s are registered at http://www.epsg-registry.org/. See also http://itia.ntua.gr/antonis/technical/coordinate-systems/.

approximate¶

This boolean field has the value True if the horizontal co-ordinates are approximate. This normally means that the user who specified the co-ordinates did not really know the location of the point, but for convenience placed it somewhere visually so that the GIS system can have a rough idea of where to show it and e.g. in which basin it is.

altitude¶

asrid¶

These attributes store the altitude. asrid specifies the reference system, which defines how altitude is to be understood. asrid can be empty, in which case, altitude is given in metres above mean sea level.

class enhydris.hcore.models.Gline(Gentity)¶

gpoint1¶

gpoint2¶

The starting and ending points of the line; foreign keys to Gpoint.

length¶

The length of the line in meters.

class enhydris.hcore.models.Garea(Gentity)¶

area¶

The size of the area in square meters.

Additional information for generic gentities¶

This section describes models that provide additional information about gentities.

class enhydris.hcore.models.PoliticalDivision(Garea)¶

From an administrative point of view, the world is divided into countries. Each country is then divided into further divisions, which may be called states, districts, counties, provinces, prefectures, and so on, which may be further subdivided. Greece, for example, is divided in districts, which are subdivided in prefectures. How these divisions and subdivisions are named, and the way and depth of subdividing, differs from country to country.

PoliticalDivision is a recursive model that represents such political divisions. The top-level political division is a country, and lower levels differ from country to country.

parent¶

For top-level political divisions, that is, countries, this attribute is null; otherwise, it points to the containing political division.

code¶

For top-level political divisions, that is, countries, this is the two-character ISO 3166 country code. For lower level political divisions, it can be a country-specific division code; for example, for US states, it can be the two-character state code. Up to five characters.

class enhydris.hcore.models.WaterDivision(Garea)¶

A water division is a collection of basins. Water divisions may be used for administrative purposes, each water division being under the authority of one organisation or organisational division. Usually a water division consists of adjacent basins or of nearby islands or both.

class enhydris.hcore.models.WaterBasin(Garea)¶

A water basin.

parent¶

If this is a subbasin, this field points to the containing water basin.

water_division¶

The water district in which the water basin is.

class enhydris.hcore.models.GentityAltCodeType(Lookup)¶

The different kinds of codes that a gentity may have; see GentityAltCode for more information.

class enhydris.hcore.models.GentityAltCode¶

While each gentity is automatically given an id by the system, some stations may also have alternative codes. For example, in Greece, if a database contains a measuring station that is owned by a specific organisation, the station has the id given to it by the database, but in addition it may have a code assigned by the organisation; some also have a code created by older inter-organisational efforts to create a unique list of stations in Greece; and some also have a WMO code. This model therefore stores alternative codes.

gentity¶

A foreign key to Gentity.

type¶

The type of alternative code; one of those listed in GentityAltCodeType.

value¶

A character field with the actual code.

class enhydris.hcore.models.FileType(Lookup)¶

A lookup that contains one additional field:

mime_type¶

The mime type, like image/jpeg.

class enhydris.hcore.models.GentityFile¶

This model stores general files for the gentity. For examples, for measuring stations, it can be photos, videos, sensor manuals, etc.

descr¶

A multilingual short description or legend of the file.

remarks¶

Multilingual remarks of unlimited length.

date¶

For photos, it should be the date the photo was taken. For other kinds of files, it can be any kind of date.

file_type¶

The type of the file; a foreign key to FileType.

content¶

The actual content of the file; a Django FileField. Note that, for generality, images are also stored in this attribute, and therefore they don’t use an ImageField, which means that the few facilities that ImageField offers are not available.

class enhydris.hcore.models.EventType(Lookup)¶

Stores types of events.

class enhydris.hcore.models.GentityEvent¶

An event is something that happens during the lifetime of a gentity and needs to be recorded. For example, for measuring stations, events such as malfunctions, maintenance sessions, and extreme weather phenomena observations can be recorded and provide a kind of log.

gentity¶

The Gentity to which the event refers.

date¶

The date of the event.

type¶

The EventType.

user¶

The username of the user who entered the event to the database.

report¶

A report about the event; a text field of unlimited length.

Station and its related models¶

class enhydris.hcore.models.StationType(Lookup)¶

The station type, such as “meteorological” or “stage measuring”.

class enhydris.hcore.models.Station(Gpoint)¶

owner¶

The Lentity that owns the station.

type¶

The StationType.

is_automatic¶

A boolean field showing whether the station is automatic.

start_date¶

end_date¶

An optional pair of dates indicating when the station started and stopped working.

overseers¶

The overseers are the persons who are or have been responsible for each meteorological station in the past. In the case of traditional (not automatic) stations, this means the weather observers. At a given time, each station has only one observer. This is a many-to-many field, through model Overseer.

class enhydris.hcore.models.Overseer¶

station¶

A foreign key to Station.

person¶

A foreign key to Person.

is_current¶

A boolean value indicating whether this person is the current observer. For current overseers, the end_date below must be null; however, a null end_date could also mean that the end_date is unknown, not necessarily that the overseer is the current overseer.

start_date¶

end_date¶

class enhydris.hcore.models.InstrumentType(Lookup)¶

The instrument type, such as “Thermometer”.

class enhydris.hcore.models.Instrument¶

A measuring instrument or sensor that belongs to a station.

station¶

The Station to which the instrument belongs.

type¶

The InstrumentType.

name¶

A multilingual field with a descriptive name.

remarks¶

A multilingual field with remarks of unlimited length.

manufacturer¶

The name of the manufacturer. For simplicity, this is not a foreign key to Organization; this would be overkill.

model¶

The model name.

start_date¶

end_date¶

The dates of start and end of operation.

Time series and related models¶

class enhydris.hcore.models.Variable(Lookup)¶

This model stores a variable, such as “precipitation”, “evaporation”, “temperature” etc.

class enhydris.hcore.models.UnitOfMeasurement(Lookup)¶

This model stores a unit of measurement. In addition to Lookup fields, it has the following additional fields:

symbol¶

The symbol used for the unit, in UTF-8 plain text.

variables¶

A many-to-many relationship to Variable.

class enhydris.hcore.models.TimeZone¶

This model stores time zones.

code¶

The code name of the time zone, such as CET or UTC.

utc_offset¶

A number, in minutes, with the offset of the time zone from UTC. For example, CET has a utc_offset of 60, whereas CDT is -300. This model only stores time zones with a constant utc offset, and not time zones with variable offsets. For example, we don’t store CT (North American Central Time), because this is different in summer and in winter; instead, we store CST (Central Standard Time) and CDT (Central Daylight Time), which are the two occurrences of CT. The time stamps of a given time series may not observe summer time; they must always have the same utc offset throught the time series.

class enhydris.hcore.models.TimeStep(Lookup)¶

This model holds time steps. The descr attribute inherited by Lookup holds a descriptive name for the time step, such as “daily” or “monthly”. The model has two additional attributes:

length_minutes¶

length_months¶

One of these two attributes must be zero. For example, a daily time step has length_minutes=1440 and length_months=0; an annual time step has length_minutes=0 and length_months=12.

class enhydris.hcore.models.Timeseries¶

Hold time series.

gentity¶

The Gentity to which the time series refers.

variable¶

The Variable of the time series.

unit_of_measurement¶

The UnitOfMeasurement.

name¶

A descriptive name for the time series.

precision¶

An integer specifying the precision of the values of the time series, in number of decimal digits. It can be negative; for example, a precision of -2 indicates that the values are accurate to the hundred, ex. 100, 200 etc.

time_zone¶

The TimeZone in which the time series’ timestamps are.

remarks¶

A text field of unlimited length.

instrument¶

The instrument that measured the time series; a foreign key to Instrument. This can be null, as there are time series that are not measured by instruments, as are, for example, time series resulting from processing of other time series.

hidden¶

A boolean field to control the visibility of timeseries in related pages.

time_step¶

timestamp_rounding_minutes¶

timestamp_rounding_months¶

timestamp_offset_minutes¶

timestamp_offset_months¶

The time_step is a foreign key to TimeStep. Some time series are completely irregular; in that case, time_step (and all other time step related attributes) is null. Otherwise, it contains an appropriate time step. For an explanation of the other four attributes, see the timeseries.TimeStep class. timestamp_offset_minutes and timestamp_offset_months must always be present if the time step is not null. The rounding attributes may, however, be null, if the time series is not strict, that is, if it does have a time step, but that time step contains irregularities. As an example, a time series measured by an automatic meteorological station every ten minutes will usually have a rounding of 0 minutes, which means the timestamps will end in :10, :20, :30, etc; but a clock error or a setup error could result in the timestamps ending in :11, :21, :31 for a brief period of time. In that case, we say that the time series has a nonstrict time step of 10 minutes, which means it has no specific rounding.

datafile¶

The file where the time series data are stored. The attribute is a Django FileField. The format of this file is documented in pd2hts as `text format`_.

Usually you don’t need to access this file directly; instead, use methods get_all_data(), set_data(), append_data(), get_first_line() and get_last_line().

start_date¶

end_date¶

The start and end date of the time series, or None if the time series is empty. These are redundant; the start and end date of the time series could be found with get_first_line() and get_last_line(). However, these attributes can easily be used in database queries. Normally you don’t need to set them; they are set automatically when the time series is saved. If you write to the datafile, you must subsequently call save() to update these fields.

get_all_data()¶

Return all data of the file in a pandas DataFrame.

set_data(data)¶

Replace all of the time series with data, which must be a filelike object containing time series data in `text format`_ or `file format`_. If it is in text format, the header is ignored.

append_data(data)¶

Same as set_data(), except that the data is appended to the already existing data. Raises ValueError if the new data is not more recent than the old data.

get_first_line()¶

get_last_line()¶

Return the first or last line of the data file (i.e. the first or last record of the time series in text format), or an empty string if the time series contains no records.

Overview¶

Normally the web pages of Enhydris are good if you are a human; but if you are a computer (a script that creates stations, for example), then you need a different interface. For that purpose, Enydris offers an API through HTTP, through which applications can communicate. For example, http://openmeteo.org/stations/d/1334/ shows you a weather station in human-readable format; http://openmeteo.org/api/Station/1334/ provides you data on the same station in machine-readable format.

The Webservice API is a work in progress: it was originally designed in order to provide the ability to replicate the data from one instance to another over the network. It was later extended to provide the possibility to create timeseries through a script. New functions are added to it as needed.

Client authentication¶

Some of the API functions are provided freely, while others require authentication. An example of the latter are functions which alter data; another example is data which are protected and need, for example, a subscription in order to be accessed. In such cases of restricted access, HTTP Basic authentication is performed.

Generic API calls¶

API calls are accessible under the /api/ url after which you just fill in the model name of the model you want to request. For example, to request all the stations you must provide the url http://base-address/api/Station/; the format in which the data will be returned depends on the HTTP Accept header. The same goes for the rest of the enhydris models (e.g. /api/Garea/, /api/Gentity/ etc). There is also the ability to request only one object of a specific type by appending its id in the url like this: http://base-address/api/Station/1000/.

See the data model reference for information on the models.

Creating new time series and stations¶

To create a new time series, you POST /api/Timeseries/; you must pass an appropriate csrf_token and a session id (you must be logged on as a user who has permission to do this), and pass the data in an appropriate format, such as JSON. Likewise, you can create new stations by POSTing /api/Station/; you can also delete stations and time series, and you can edit stations.

If you program in Python, you should use Pthelma’s enhydris_api module. Otherwise, you should read its code to see more concrete examples of how to use the API.

Appending data to a time series¶

To append data to a time series, you PUT api/tsdata. See the code of loggertodb for an example of how to do this.

Timeseries data and GentityFile¶

At http://base-address/api/tsdata/id/ (where id is the actual id of the timeseries object) you can get the timeseries data in `text format`_.

Cached time series data¶

At http://base-address/timeseries/data/?object_id=id (where id is the actual id of the time series object) you can get some time series data from specific positions (timestamps) as well as statistics and chart data. Data is cached so no need to read the entire time series and usually information is delivered fast.

Cached time series data are being used to display time series previews in time series detail pages. Also there are used for charting like in:

http://openmeteo.org/db/chart/ntuastation/

The response is a JSON object. An example is the following:

{
  "stats": {"min_tstmp": 1353316200000,
            "max": 6.0,
            "max_tstmp": 979495200000,
            "avg": 0.0094982613015400109,
            "vavg": null,
            "count": 10065,
            "last_tstmp": 1353316200000,
            "last": 0.0,
            "min": 0.0,
            "sum": 95.600000000000207,
            "vectors": [0, 0, 0, 0, 0, 0, 0, 0],
            "vsum": [0.0, 0.0]},
  "data": [[911218200000, "0.0", 1],
           [913349400000, "4.8", 3551],
           ...,
           [1350248400000, "0.0", 710001],
           [1353316200000, "0.0", 715149]]
}

“stats”

An object holding statistics for the given interval (see bellow)

“last”

Last value observed for the given interval

“last_tstmp”

The timestamp for the last value

“max”

Is the maximum value observed for the given interval (see bellow)

“max_tstmp”

The timestamp where the maximum value is observed

“min”

The minimum value for the given interval

“min_tstmp”

The timestamp where minimum value is observed

“avg”

The average value for the given interval

“vavg”

A vector average in decimal degrees for vector variables such as wind direction etc.

“count”

The actual number of records used for statistics

“sum”

The sum of values for the given interval

“vsum”

Two components of sum (vector sum) Sx, Sy, computed by the cosines, sinus.

“vectors”

The percentage of vector variable for eight distinct directions (N, NE, E, SE, S, SW, W and NW).

“data”

An object holding an array of charting values. Each item of the array holds [timestamp, value, index]. Timestamp is a javascript timestamp, value if a floating point number or null, index is the actual index of the value in the whole time series records.

You have to specify at least the object_id GET parameter in order to obtain some data. The default time interval is the whole time series. In the case of the whole time series a rough image of the time series is displayed which is not precise. Statistics also can be no precise.

In example for 10-minute time step time series, chart and statistics can be precise for intervals of one month the most.

Besides object_id some other parameters can be given as GET parameters to specify the desired interval etc:

start_pos

an index number specifying the begining of an interval. Index can be zero (0) for the begining of the time series or at most last record number minus one.

end_pos

an index number specifying the end of an interval.

last

A string defining an interval from a pre-defined set:

• day
• week
• month
• year
• moment (returns one value only for the last moment)
• hour
• twohour

By default the end of the interval is the end of the time series. If time-series is auto-updated it shows the last measurements.

date

Can be used in conjuction with the last parameter to display in interval beginning at the specified date. Date format: yyyy-mm-dd

time

Can be used in conjuction with last and date parameters to specify the beginning time of the interval. Accepted format: HH:MM

exact_datetime

A boolean parameter (set to true to activate). Specifies that date times should be existing in time series record or else it returns null. If not activated, it returns the closest periods with data to the specified interval.

start_offset

An offset in minutes for the beginning of the interval. It can be used i.e. to exclude the first value of a daily interval, so the statistics are computed correct i.e. from 144 10-min values rather than 145 values (e.g. from 00:10 to 24:00 rather than 00:00 to 24:00). Suggested value for a ten minute time series is 10

vector

A boolean parameter. Set to ‘true’ to activate. Then vector statistics are being calculated.

jsoncallback=?

If you’re running into the Same Origin Policy, which doesn’t (normally) allow ajax requests to cross origins you should add the GET parameter above to obtain the cached time series data set.

A full example to get some daily values for a time series:

https://openmeteo.org/db/timeseries/data/?object_id=230&last=day&exact_datetime=true&date=2012-11-01&time=00:00

Permission Objects¶

Each instance of the Permission class represents a relationship between a user and an object and it is identified by its name. The permission name can be any string like ‘edit’, ‘read’ or ‘delete’ and usually describes the kind of permission it implements.

class permissions.Permission(name, content_type, object_id, content_object[, User, Group])¶

name¶

The name of the permission. Usually it’s a string denoting the meaning of the permission ( eg ‘edit’, ‘read’, ‘delete’, etc)

content_type¶

This attribute stores the content type of the object over which this permission is effective.

object_id¶

This is the id of the related object.

content_object¶

This is a foreign key to the actual object (object instance) over this permission is effective.

user¶

If the permission is effective for a single user, this field points to this user otherwise it is null.

group¶

If the permission is effective for a whole group, this field points to this group otherwise it is null.

User/Group methods¶

As told before, the row level permissions add various methods to the User and Group models with which one can add/edit/delete permissions over various objects and/or QuerySets.

class User:

permissions.add_row_perm(instance, perm)¶

This method takes an object instance and the name of the permission and adds this permission for the calling user over the object instance given. For example:

>>> station = Station.objects.get(id='10001')
>>> user = User.objects.get(username='testuser')
>>> user.add_row_perm(station, 'edit')

permissions.del_row_perm(instance, perm)¶

This method takes an object instance and a permission name and if the user has that permission over the object, the method deletes it. If the user doesn’t have that permisssion, nothing happens.

>>> station = Station.objects.get(id='10001')
>>> user = User.objects.get(username='testuser')
>>> user.del_row_perm(station, 'edit')

permissions.has_row_perm(instance, perm)¶

This method takes an object instance and a permission name and checks whether the calling user has that permission over the object instance. If this method is called from a superuser, it always returns True. For example:

>>> station = Station.objects.get(id='10001')
>>> user = User.objects.get(username='testuser')
>>> user.has_row_perm(station, 'edit')
False

permissions.get_rows_with_permission(instance, perm)¶

This method is used to return all instances of the same conten type as the given instance over which the user has the perm permission. For example:

>>> user = User.objects.get(username='testuser')
>>> user.get_rows_with_permission(Station,'edit')

This will return all Stations that the user can ‘edit’.

class Group:

All methods and their usage are the same as with User. However, it’s worth noting that once a user inherits a permission from a group, the only way to remove that permission is to leave the group since using del_row_perm() from the user won’t affect the group permissions.

permissions.add_row_perm(instance, perm)

permissions.del_row_perm(instance, perm)

permissions.has_row_perm(instance, perm)

permissions.get_rows_with_permission(instance, perm)