Improve logger testing + add readers

setup.py

@@ -24,8 +24,11 @@ setup(name='torchy_baselines',
             'sphinx-autobuild',
             'sphinx-rtd-theme'
         ],
-        'render': [
-            'opencv-python'
+        'extra': [
+            # For render
+            'opencv-python',
+            # For reading logs
+            'pandas'
         ]
       },
       description='Pytorch version of Stable Baselines, implementations of reinforcement learning algorithms.',

tests/test_logger.py

@@ -0,0 +1,82 @@
+import os
+import shutil
+
+import pytest
+import numpy as np
+
+from torchy_baselines.common.logger import (make_output_format, read_csv, read_json, DEBUG, ScopedConfigure,
+    info, debug, set_level, configure, logkv, logkvs, dumpkvs, logkv_mean, warn, error, reset)
+
+KEY_VALUES = {
+    "test": 1,
+    "b": -3.14,
+    "8": 9.9,
+    "l": [1, 2],
+    "a": np.array([1, 2, 3]),
+    "f": np.array(1),
+    "g": np.array([[[1]]]),
+}
+
+LOG_DIR = '/tmp/torchy_baselines/'
+
+
+def test_main():
+    """
+    tests for the logger module
+    """
+    info("hi")
+    debug("shouldn't appear")
+    set_level(DEBUG)
+    debug("should appear")
+    folder = "/tmp/testlogging"
+    if os.path.exists(folder):
+        shutil.rmtree(folder)
+    configure(folder=folder)
+    logkv("a", 3)
+    logkv("b", 2.5)
+    dumpkvs()
+    logkv("b", -2.5)
+    logkv("a", 5.5)
+    dumpkvs()
+    info("^^^ should see a = 5.5")
+    logkv_mean("b", -22.5)
+    logkv_mean("b", -44.4)
+    logkv("a", 5.5)
+    dumpkvs()
+    with ScopedConfigure(None, None):
+        info("^^^ should see b = 33.3")
+
+    with ScopedConfigure("/tmp/test-logger/", ["json"]):
+        logkv("b", -2.5)
+        dumpkvs()
+
+    reset()
+    logkv("a", "longasslongasslongasslongasslongasslongassvalue")
+    dumpkvs()
+    warn("hey")
+    error("oh")
+    logkvs({"test": 1})
+
+
+@pytest.mark.parametrize('_format', ['stdout', 'log', 'json', 'csv'])
+def test_make_output(_format):
+    """
+    test make output
+
+    :param _format: (str) output format
+    """
+    writer = make_output_format(_format, LOG_DIR)
+    writer.writekvs(KEY_VALUES)
+    if _format == "csv":
+        read_csv(LOG_DIR + 'progress.csv')
+    elif _format == 'json':
+        read_json(LOG_DIR + 'progress.json')
+    writer.close()
+
+
+def test_make_output_fail():
+    """
+    test value error on logger
+    """
+    with pytest.raises(ValueError):
+        make_output_format('dummy_format', LOG_DIR)

torchy_baselines/common/logger.py

@@ -505,3 +505,68 @@ def configure(folder=None, format_strs=None):
 
     Logger.CURRENT = Logger(folder=folder, output_formats=output_formats)
     log('Logging to %s' % folder)
+
+
+def reset():
+    """
+    reset the current logger
+    """
+    if Logger.CURRENT is not Logger.DEFAULT:
+        Logger.CURRENT.close()
+        Logger.CURRENT = Logger.DEFAULT
+        log('Reset logger')
+
+
+class ScopedConfigure(object):
+    def __init__(self, folder=None, format_strs=None):
+        """
+        Class for using context manager while logging
+
+        usage:
+        with ScopedConfigure(folder=None, format_strs=None):
+            {code}
+
+        :param folder: (str) the logging folder
+        :param format_strs: ([str]) the list of output logging format
+        """
+        self.dir = folder
+        self.format_strs = format_strs
+        self.prevlogger = None
+
+    def __enter__(self):
+        self.prevlogger = Logger.CURRENT
+        configure(folder=self.dir, format_strs=self.format_strs)
+
+    def __exit__(self, *args):
+        Logger.CURRENT.close()
+        Logger.CURRENT = self.prevlogger
+
+
+# ================================================================
+# Readers
+# ================================================================
+
+def read_json(fname):
+    """
+    read a json file using pandas
+
+    :param fname: (str) the file path to read
+    :return: (pandas DataFrame) the data in the json
+    """
+    import pandas
+    data = []
+    with open(fname, 'rt') as file_handler:
+        for line in file_handler:
+            data.append(json.loads(line))
+    return pandas.DataFrame(data)
+
+
+def read_csv(fname):
+    """
+    read a csv file using pandas
+
+    :param fname: (str) the file path to read
+    :return: (pandas DataFrame) the data in the csv
+    """
+    import pandas
+    return pandas.read_csv(fname, index_col=None, comment='#')