Iterator for FilterCollection

README.md

@@ -2,15 +2,15 @@
 
 ![pyaro-logo](docs/pics/pyaro256.png "The library that solves the mystery of reading airquality measurement databases.")
 
-The library that solves the mystery of reading airquality measurement databases. (Pronounciation as in French: Poirot)
+The library that solves the mystery of reading airquality measurement databases. (Pronunciation as in French: Poirot)
 
 ## About
 
 Pyaro is an interface which uses a simple access pattern to different air-pollution databases.
 The goal of pyro was threefold.
 
 1. A simple interface for different types of air-pollution databases
-2. A programatic interface to these databases easily usable by large applications like [PyAerocom](https://pyaerocom.readthedocs.io)
+2. A programmatic interface to these databases easily usable by large applications like [PyAerocom](https://pyaerocom.readthedocs.io)
 3. Easy extension for air-pollution database providers or programmers giving the users (1. or 2.) direct access
     their databases without the need of a new API.
 

docs/Ungriddeddata.rst

@@ -3,7 +3,7 @@ UngriddedData
 ===================
 
 UngriddedData is the main class for holding ungridded data -- mostly used for obervational data -- in pyaerocom.
-The class can either be instanciated and filled manually (see below for structure), or be created from a dictionary of StationData objects :ref:`_stationsdata_overview`.
+The class can either be instantiated and filled manually (see below for structure), or be created from a dictionary of StationData objects :ref:`_stationsdata_overview`.
 
 ..  image:: ./pics/UngriddedData.svg
     :alt: some image

docs/index.rst

@@ -2,7 +2,7 @@
 pyaro - Airquality Reader-interface for Observations
 ***************************
 
-Website of pyaro, the Python library that solves the mystery of reading airquality measurement databases. (Pronounciation as in French: Poirot)
+Website of pyaro, the Python library that solves the mystery of reading airquality measurement databases. (Pronunciation as in French: Poirot)
 
 About
 ============
@@ -11,7 +11,7 @@ Pyaro is an interface which uses a simple access pattern to different air-pollut
 The goal of pyro was threefold.
 
     1. A simple interface for different types of air-pollution databases
-    2. A programatic interface to these databases easily usable by large applications like `PyAerocom <https://pyaerocom.readthedocs.io>`_
+    2. A programmatic interface to these databases easily usable by large applications like `PyAerocom <https://pyaerocom.readthedocs.io>`_
     3. Easy extension for air-pollution database providers or programmers giving the users (1. or 2.) direct access
        their databases without the need of a new API.
 

docs/puml/Filter.puml

@@ -6,7 +6,7 @@ class timeseries.FilterFactory {
     +list(): [str]
 }
 note right of timeseries.FilterFactory
-  Singelton
+  Singleton
   instance available as
   pyaro.timeseries.filters
 end note

docs/puml/UngriddedData.puml

@@ -30,7 +30,7 @@ end note
 entity "metadata" {
   *station_id: float
   --
-  *var_info|varibales : list_of_varnames|dictionary
+  *var_info|variables : list_of_varnames|dictionary
   *instrument_name
   *latitude: float
   *longitude: float

docs/tutorials/pyaerocom.ipynb

@@ -739,7 +739,7 @@
    "id": "49b0a0fc-2e7a-435b-92b5-3fbab19db9f7",
    "metadata": {},
    "source": [
-    "Configs can become large and complicated. Thus we don't want to have to rewrite these config each time. We have intruduced a catalog system to save configurations. This is done in using YAML files.\n",
+    "Configs can become large and complicated. Thus we don't want to have to rewrite these config each time. We have introduced a catalog system to save configurations. This is done in using YAML files.\n",
     "\n",
     "The plan is to have one default catalog that is distributed with pyaerocom, which holds the most used configurations, and the option to have personal catalogs which the user can make themselves.\n",
     "\n",

src/pyaro/plugins.py

@@ -40,7 +40,7 @@ def list_timeseries_engines() -> dict[str, TimeseriesEngine]:
     Notes
     -----
     This function lives in the backends namespace (``engs=pyaro.list_timeseries_enginess()``).
-    More information about each reader is available via the TimeserieEngine obj.url() and
+    More information about each reader is available via the TimeseriesEngine obj.url() and
     obj.description()
 
     # New selection mechanism introduced with Python 3.10. See GH6514.
@@ -54,7 +54,7 @@ def open_timeseries(name, *args, **kwargs) -> TimeseriesReader:
     directly to the TimeseriesReader.open_reader() function
 
     :param name: the name of the entrypoint as key in list_timeseries_readers
-    :return: an implementation-object of a TimeseriesReader openend to a location
+    :return: an implementation-object of a TimeseriesReader opened to a location
     """
     engine = list_timeseries_engines()[name]
 

src/pyaro/timeseries/Engine.py

@@ -2,7 +2,7 @@
 
 
 class Engine(abc.ABC):
-    """The engine is the 'singelton' generator object for databases of the engines type."""
+    """The engine is the 'singleton' generator object for databases of the engines type."""
 
     @abc.abstractmethod
     def open(self, filename_or_obj_or_url, *, filters=None):

src/pyaro/timeseries/Filter.py

@@ -143,7 +143,7 @@ def get(self, name, **kwargs):
         return filter.__class__(**kwargs)
 
     def list(self) -> dict[str, Filter]:
-        """List all available filter-names and their initalizations"""
+        """List all available filter-names and their initializations"""
         return types.MappingProxyType(self._filters)
 
 
@@ -164,7 +164,7 @@ class FilterCollectionException(Exception):
 
 
 class FilterCollection:
-    """A collection of DataIndexFilters which can be appied together.
+    """A collection of DataIndexFilters which can be applied together.
 
     :param filterlist: _description_, defaults to []
     :return: _description_
@@ -215,6 +215,9 @@ def filter(self, ts_reader, variable: str) -> Data:
         data = ts_reader.data(variable)
         return self.filter_data(data, stations, variables)
 
+    def __iter__(self):
+        return self._filters.__iter__()
+
 
 @registered_filter
 class VariableNameFilter(Filter):
@@ -340,7 +343,7 @@ def name(self):
 
     def has_station(self, station) -> bool:
         if len(self._include) > 0:
-            if not station in self._include:
+            if station not in self._include:
                 return False
         if station in self._exclude:
             return False
@@ -371,7 +374,7 @@ def name(self):
 
     def has_country(self, country) -> bool:
         if len(self._include) > 0:
-            if not country in self._include:
+            if country not in self._include:
                 return False
         if country in self._exclude:
             return False
@@ -769,7 +772,7 @@ class TimeResolutionFilter(DataIndexFilter):
     certain time-resolutions. Time-resolutions are not exact, and might be interpreted
     slightly differently by different observation networks.
 
-    Default named time-resoultions are
+    Default named time-resolutions are
         * minute: 59 to 61 s (+-1sec)
         * hour: 59*60 s to 61*60 s (+-1min)
         * day: 22:59:00 to 25:01:00 to allow for leap-days and a extra min
@@ -989,7 +992,7 @@ def _convert_altitude_to_meters(self, topo_xr):
         Method which attempts to convert the altitude variable in the gridded topography data
         to meters.
 
-        :param topo_xr xarray dataset containting topo
+        :param topo_xr xarray dataset containing topo
         :raises TypeError
             If conversion isn't possible.
         :return xr.DataArray

src/pyaro/timeseries/Reader.py

@@ -30,7 +30,7 @@ def metadata(self) -> dict[str, str]:
         return dict()
 
     @abc.abstractmethod
-    def data(self, varname) -> Data:
+    def data(self, varname: str) -> Data:
         """Return all data for a variable
 
         :param varname: variable name as returned from variables

src/pyaro/timeseries/Wrappers.py

@@ -4,7 +4,7 @@
 
 class VariableNameChangingReader(Reader):
     """A pyaro.timeseries.Reader wrapper taking a real Reader implementation and
-    changing variable names in the original reader. Exampel:
+    changing variable names in the original reader. Example:
 
         with VariableNameChangingReader(pyaro.open_timeseries(file, filters=[]),
                                         {'SOx': 'oxidised_sulphur'}) as ts: