Adds developer quality of life dev enhancements

.flake8

@@ -0,0 +1,3 @@
+[flake8]
+max-line-length = 88
+ignore = E203, W503

.pylintrc

@@ -1,7 +1,6 @@
 [MESSAGES CONTROL]
 
-disable=print-statement,
-        singleton-comparison,
+disable=singleton-comparison,
         no-member,
         too-few-public-methods,
         protected-access,
@@ -10,7 +9,8 @@ disable=print-statement,
         duplicate-code,
         import-error,
         nan-comparison,
-        consider-using-set-comprehension
+        consider-using-set-comprehension,
+        consider-using-f-string,
 
 [BASIC]
 

Makefile

@@ -0,0 +1,24 @@
+PACKAGE_NAME = meteostat
+
+.PHONY: all help lint tests run
+
+all: help
+
+help: ## Show this help
+	@echo 'Usage: make COMMAND'
+	@echo
+	@echo "Commands:"
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-15s\033[0m %s\n", $$1, $$2}'
+
+lint: ## Run black, pylint and flake8
+	black --check $(PACKAGE_NAME) ./tests
+	pylint $(PACKAGE_NAME)
+	flake8 $(PACKAGE_NAME)
+
+tests: ## Run tests with coverage and linting
+	pytest --version
+	pytest tests/ --log-cli-level=INFO --cov-branch --cov=$(PACKAGE_NAME) --cov-report xml
+
+format: ## Format the Python code using black
+	black $(PACKAGE_NAME)
+	black tests/

README.md

@@ -35,6 +35,13 @@ The Meteostat Python library is divided into multiple classes which provide acce
   * [Data Sources](https://dev.meteostat.net/sources.html)
   * [Terms & License](https://dev.meteostat.net/terms.html)
 
+### Class Diagram
+![Classes](classes.png)
+
+
+### Package Diagram
+![Packages](packages.png)
+
 ## Example
 
 Let's plot 2018 temperature data for Vancouver, BC:
@@ -69,6 +76,16 @@ Take a look at the expected output:
 
 Instructions on building and testing the Meteostat Python package can be found in the [documentation](https://dev.meteostat.net/python/contributing.html). More information about the Meteostat bulk data interface is available [here](https://dev.meteostat.net/bulk/).
 
+## Developer setup for contributions
+
+- Fork the repository
+- Create a new python virtual environment
+- Activate virtual environment
+- run pip install -U pip [get the latest version of pip]
+- run pip install -r requirements_dev.in [install all packages required to hack the code]
+- You can now use the Makefile to run tests and check style formatting as well as generate coverage information
+- Hack Away
+
 ## Donating
 
 If you want to support the project financially, you can make a donation using one of the following services:

meteostat/__init__.py

@@ -14,11 +14,11 @@
 __appname__ = "meteostat"
 __version__ = "1.6.7"
 
-from .interface.base import Base
-from .interface.timeseries import TimeSeries
-from .interface.stations import Stations
-from .interface.point import Point
-from .interface.hourly import Hourly
-from .interface.daily import Daily
-from .interface.monthly import Monthly
-from .interface.normals import Normals
+from .interface.base import Base  # noqa
+from .interface.timeseries import TimeSeries  # noqa
+from .interface.stations import Stations  # noqa
+from .interface.point import Point  # noqa
+from .interface.hourly import Hourly  # noqa
+from .interface.daily import Daily  # noqa
+from .interface.monthly import Monthly  # noqa
+from .interface.normals import Normals  # noqa

meteostat/core/cache.py

@@ -53,7 +53,6 @@ def clear_cache(cls, max_age: int = None) -> None:
     """
 
     if os.path.exists(cls.cache_dir + os.sep + cls.cache_subdir):
-
         # Set max_age
         if max_age is None:
             max_age = cls.max_age
@@ -63,7 +62,6 @@ def clear_cache(cls, max_age: int = None) -> None:
 
         # Go through all files
         for file in os.listdir(cls.cache_dir + os.sep + cls.cache_subdir):
-
             # Get full path
             path = os.path.join(cls.cache_dir + os.sep + cls.cache_subdir, file)
 

meteostat/core/loader.py

@@ -28,10 +28,8 @@ def processing_handler(
 
     # Multi-core processing
     if cores > 1 and len(datasets) > 1:
-
         # Create process pool
         with Pool(cores) as pool:
-
             # Process datasets in pool
             output = pool.starmap(load, datasets)
 
@@ -41,10 +39,8 @@ def processing_handler(
 
     # Multi-thread processing
     elif threads > 1 and len(datasets) > 1:
-
         # Create process pool
         with ThreadPool(threads) as pool:
-
             # Process datasets in pool
             output = pool.starmap(load, datasets)
 
@@ -54,7 +50,6 @@ def processing_handler(
 
     # Single-thread processing
     else:
-
         for dataset in datasets:
             output.append(load(*dataset))
 
@@ -77,7 +72,6 @@ def load_handler(
     """
 
     try:
-
         # Read CSV file from Meteostat endpoint
         df = pd.read_csv(
             endpoint + path,
@@ -94,7 +88,6 @@ def load_handler(
             )
 
     except (FileNotFoundError, HTTPError):
-
         # Create empty DataFrane
         df = pd.DataFrame(columns=[*types])
 

meteostat/interface/daily.py

@@ -93,7 +93,6 @@ def __init__(
         model: bool = True,  # Include model data?
         flags: bool = False,  # Load source flags?
     ) -> None:
-
         # Initialize time series
         self._init_time_series(loc, start, end, model, flags)
 

meteostat/interface/hourly.py

@@ -105,15 +105,14 @@ def _set_time(
         """
 
         # Don't use chunks if full dataset is requested
-        if start == None:
+        if start is None:
             self.chunked = False
 
         if timezone:
             # Save timezone
             self._timezone = timezone
 
             if start and end:
-
                 # Initialize time zone
                 timezone = pytz.timezone(self._timezone)
 
@@ -124,7 +123,9 @@ def _set_time(
                 end = timezone.localize(end, is_dst=None).astimezone(pytz.utc)
 
         if self.chunked:
-            self._annual_steps = [start.year + i for i in range(end.year - start.year + 1)]
+            self._annual_steps = [
+                start.year + i for i in range(end.year - start.year + 1)
+            ]
 
         self._start = start
         self._end = end
@@ -138,7 +139,6 @@ def __init__(
         model: bool = True,  # Include model data?
         flags: bool = False,  # Load source flags?
     ) -> None:
-
         # Set time zone and adapt period
         self._set_time(start, end, timezone)
 

meteostat/interface/meteodata.py

@@ -49,12 +49,10 @@ def _load_data(self, station: str, year: Union[int, None] = None) -> None:
 
         # Check if file in cache
         if self.max_age > 0 and file_in_cache(path, self.max_age):
-
             # Read cached data
             df = pd.read_pickle(path)
 
         else:
-
             # Get data from Meteostat
             df = load_handler(
                 self.endpoint, file, self._columns, self._types, self._parse_dates
@@ -119,7 +117,6 @@ def _get_data(self) -> None:
         """
 
         if len(self._stations) > 0:
-
             # Get list of datasets
             datasets = self._get_datasets()
 
@@ -143,9 +140,7 @@ def _resolve_point(
             return None
 
         if method == "nearest":
-
             if adapt_temp:
-
                 # Join elevation of involved weather stations
                 data = self._data.join(stations["elevation"], on="station")
 
@@ -156,7 +151,6 @@ def _resolve_point(
                 data = data.drop("elevation", axis=1).round(1)
 
             else:
-
                 data = self._data
 
             if self.granularity == Granularity.NORMALS:
@@ -168,7 +162,6 @@ def _resolve_point(
                 ).agg("first")
 
         else:
-
             # Join score and elevation of involved weather stations
             data = self._data.join(stations[["score", "elevation"]], on="station")
 

meteostat/interface/monthly.py

@@ -84,7 +84,6 @@ def __init__(
         model: bool = True,  # Include model data?
         flags: bool = False,  # Load source flags?
     ) -> None:
-
         # Set start date
         if start is not None:
             start = start.replace(day=1)

meteostat/interface/normals.py

@@ -79,7 +79,6 @@ def __init__(
         start: int = None,
         end: int = None,
     ) -> None:
-
         # Set list of weather stations
         if isinstance(loc, pd.DataFrame):
             self._stations = loc.index

meteostat/interface/point.py

@@ -53,7 +53,6 @@ class Point:
     _alt: int = None
 
     def __init__(self, lat: float, lon: float, alt: int = None) -> None:
-
         self._lat = lat
         self._lon = lon
         self._alt = alt
@@ -90,7 +89,7 @@ def get_stations(
         # Apply inventory filter
         if freq and start and end:
             age = (datetime.now() - end).days
-            if model == False or age > 180:
+            if model is False or age > 180:
                 stations = stations.inventory(freq, (start, end))
 
         # Apply altitude filter
@@ -110,7 +109,6 @@ def get_stations(
 
         # Score values
         if self.radius:
-
             # Calculate score values
             stations["score"] = (
                 (1 - (stations["distance"] / self.radius)) * self.weight_dist

meteostat/interface/stations.py

@@ -80,12 +80,10 @@ def _load(self) -> None:
 
         # Check if file in cache
         if self.max_age > 0 and file_in_cache(path, self.max_age):
-
             # Read cached data
             df = pd.read_pickle(path)
 
         else:
-
             # Get data from Meteostat
             df = load_handler(
                 self.endpoint, file, self._columns, self._types, self._parse_dates, True
@@ -102,7 +100,6 @@ def _load(self) -> None:
         self._data = df
 
     def __init__(self) -> None:
-
         # Get all weather stations
         self._load()
 
@@ -179,12 +176,12 @@ def inventory(
 
         if required is True:
             # Make sure data exists at all
-            temp._data = temp._data[(pd.isna(temp._data[freq + "_start"]) == False)]
+            temp._data = temp._data[(pd.isna(temp._data[freq + "_start"]) is False)]
 
         elif isinstance(required, tuple):
             # Make sure data exists across period
             temp._data = temp._data[
-                (pd.isna(temp._data[freq + "_start"]) == False)
+                (pd.isna(temp._data[freq + "_start"]) is False)
                 & (temp._data[freq + "_start"] <= required[0])
                 & (
                     temp._data[freq + "_end"] + timedelta(seconds=temp.max_age)
@@ -195,7 +192,7 @@ def inventory(
         else:
             # Make sure data exists on a certain day
             temp._data = temp._data[
-                (pd.isna(temp._data[freq + "_start"]) == False)
+                (pd.isna(temp._data[freq + "_start"]) is False)
                 & (temp._data[freq + "_start"] <= required)
                 & (
                     temp._data[freq + "_end"] + timedelta(seconds=temp.max_age)

meteostat/interface/timeseries.py

@@ -57,12 +57,10 @@ def _load_flags(self, station: str, year: Union[int, None] = None) -> None:
 
         # Check if file in cache
         if self.max_age > 0 and file_in_cache(path, self.max_age):
-
             # Read cached data
             df = pd.read_pickle(path)
 
         else:
-
             # Get data from Meteostat
             df = load_handler(
                 self.endpoint,
@@ -99,7 +97,6 @@ def _get_flags(self) -> None:
         """
 
         if len(self._stations) > 0:
-
             # Get list of datasets
             datasets = self._get_datasets()
 

meteostat/series/aggregate.py

@@ -19,7 +19,6 @@ def aggregate(self, freq: str = None, spatial: bool = False):
     """
 
     if self.count() > 0 and not self._data.isnull().values.all():
-
         # Create temporal instance
         temp = copy(self)
 

meteostat/series/interpolate.py

@@ -18,7 +18,6 @@ def interpolate(self, limit: int = 3):
     """
 
     if self.count() > 0 and not self._data.isnull().values.all():
-
         # Create temporal instance
         temp = copy(self)
 

meteostat/series/normalize.py

@@ -27,7 +27,6 @@ def normalize(self):
     temp = copy(self)
 
     if temp._start and temp._end and temp.coverage() < 1:
-
         # Create result DataFrame
         result = pd.DataFrame(columns=temp._columns[temp._first_met_col :])
 

requirements.in

@@ -0,0 +1,6 @@
+pandas>=1.1
+pytz
+numpy
+matplotlib
+wheel
+twine