First version

.gitignore

@@ -0,0 +1,6 @@
+
+.*
+*.pyc
+__pycache__
+dist
+build

LICENSE.txt

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+
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MANIFEST.in

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+include requirements.txt
+include test-requirements.txt
+include extra-requirements.txt
+include README.md
+include LICENSE.txt
+graft keepit

Makefile

@@ -0,0 +1,4 @@
+release:
+	python setup.py sdist
+	python setup.py bdist_wheel
+	twine upload --skip-existing dist/* 

README.md

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+# KEEP IT
+
+This is a **WORK IN PROGRESS**.
+
+`keepit` provides advanced memoization to disk for functions.
+In other words, it records the results of important functions between executions.
+
+`keepit` saves the results of calling a function to disk, so calling the function with the exact same parameters will re-use the stored copy of the results, leading to much faster times.
+
+
+Example usage:
+
+```
+import pandas as pd
+from keepit import keepit
+
+@keepit('myresults.tsv')
+def expensive_function(number=1):
+    df = pd.DataFrame()
+    # Perform a really expensive operation, maybe access to disk?
+    return df
+
+# When a results file for the function does not exist
+# this may take a long time
+expensive_function(number=1)
+# Now a myresults.tsv_{some hash) has been generated
+
+# This is almost instantaneous:
+expensive_function(number=1)
+
+# Files are specific to each parameter execution, 
+# so this will again take a long time:
+expensive_function(number=42)
+# After this, we should have two files, one for number=1, 
+# and another one for number=42.
+
+```
+
+
+
+

keepit/VERSION

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+0.2.2

keepit/__init__.py

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+import os
+import unicodedata
+import inspect
+import re
+import pandas as pd
+from functools import wraps, partial
+from glob import glob
+import logging
+import pickle
+import hashlib
+
+from collections import namedtuple
+
+from .backends import Pickle, Entry
+
+logger = logging.getLogger(__name__)
+
+
+def _slugify(value):
+    """
+    Normalizes string, converts to lowercase, removes non-alpha characters,
+    and converts spaces to hyphens.
+    Source:
+    http://stackoverflow.com/questions/295135/turn-a-string-into-a-valid-filename-in-python
+    """
+    value = unicodedata.normalize('NFKD', value).encode('ascii', 'ignore')
+    value = re.sub(r'[^\w\s-]', '', value.decode('utf-8', 'ignore'))
+    value = value.strip().lower()
+    value = re.sub(r'[-\s]+', '-', value)
+    return value
+
+
+def hash_df(df):
+    '''Hashes a pandas dataframe'''
+    return hashlib.sha256(pd.util.hash_pandas_object(df, index=True).values).hexdigest()
+
+
+def hash_object(obj):
+    return hashlib.sha256(pickle.dumps(obj)).hexdigest()
+
+
+def hash_element(elem):
+    if isinstance(elem, pd.DataFrame):
+        return hash_df(elem)
+    pick = pickle.dumps(elem)
+    return hashlib.sha256(pick).hexdigest()
+
+
+def func_hasher(f, *args, fname=None, element_hasher=hash_element, **kwargs):
+
+    sig = inspect.signature(f)
+    func = partial(f, *args, **kwargs)
+    bound = sig.bind_partial(*args, **kwargs)
+    bound.apply_defaults()
+
+    reqs = {}
+    for k, v in bound.arguments.items():
+        reqs[k] = v
+
+    fname = fname or '{}_{}'.format(f.__name__, f.__module__)
+
+    args_hash = hash_object(reqs)
+    name = '{}_{}'.format(fname, args_hash)
+
+    return _slugify(name), func, reqs
+
+
+Result = namedtuple('Result', ['func', 'args', 'value'])
+
+
+class HashedFunc:
+
+    def __init__(self, func, fname=None, tags=[], backend=Pickle()):
+        self.func = func
+        self.tags = tags
+        self.backend = backend
+        self.sig = inspect.signature(func)
+        self.fname = fname or '{}_{}'.format(self.func.__name__,
+                                             self.func.__module__)
+
+    def hash(self, *args, **kwargs):
+        return func_hasher(self.func, *args, fname=self.fname, **kwargs, element_hasher=self.hash_element)
+
+    def hash_element(self, elem):
+        return hash_element(elem)
+
+    def __call__(self, *args, cache_force=False, tags=[], **kwargs):
+
+        if os.environ.get('no_cache'):
+            return self.func(*args, **kwargs)
+
+        func_id, func, requirements = self.hash(*args, **kwargs)
+        print(func_id)
+
+        if cache_force or not self.backend.exists(func_id):
+            res = func()
+            e = Entry(tags=[self.fname, ],
+                      id=func_id,
+                      content=Result(func_id, requirements, res))
+            self.backend.put(e)
+            # hash = self.hash_element(res)
+            # self.backend.put(hash, res, tags=self.tags+tags)
+            # for req_hash, req_value in requirements.items():
+            #     if not self.backend.find(req_hash):
+            #         self.backend.put(req_hash, req_value)
+        else:
+            res = self.backend.get(func_id).content.value
+        return res
+
+    def drop(self, *args, **kwargs):
+        func_id, func, requirements = self.hash(*args, **kwargs)
+        if self.backend.exists(func_id):
+            self.backend.remove(func_id)
+
+    def drop_all(self):
+        for f in self.list():
+            self.backend.remove(f.id)
+
+    def list(self):
+        return list(self.backend.find(tags=[self.fname, ]))
+
+
+def keepit(fname=None, hasher=HashedFunc, **kwargs):
+    def outer(of):
+        return hasher(of, fname=fname, **kwargs)
+    return outer
+
+
+def diff(df1, df2):
+    return pd.concat([df1, df2]).drop_duplicates(keep=False)

keepit/backends/__init__.py

@@ -0,0 +1,97 @@
+import os
+import pickle
+import time
+import sqlite3
+
+from glob import glob
+
+from pathlib import Path
+
+ROOT = os.path.join(Path.home(), '.keepit')
+
+
+ROOT = os.path.abspath(os.path.basename(__file__))
+CACHE_DIR = os.environ.get('CACHE_DIR', os.path.join(ROOT, '_cache'))
+
+
+class NotFound(Exception):
+    pass
+
+
+class BackEnd():
+
+    def exists(self, oid):
+        raise NotImplementedError()
+
+    def read(self, oid):
+        raise NotImplementedError()
+
+    def put(self, entry):
+        raise NotImplementedError()
+
+    def remove(self, oid):
+        raise NotImplementedError()
+
+    def find(self, *args, **kwargs):
+        return list(self.ifind(*args, **kwargs))
+
+    def ifind(self, oid=None, tags=[]):
+        raise NotImplementedError()
+
+    def erase_all(self):
+        for entry in self.find():
+            self.remove(entry.id)
+
+
+class Entry:
+
+    def __init__(self, id, content, tags=[], timestamp=None):
+        self.id = id
+        self.timestamp = time.localtime(timestamp or time.time())
+        self.content = content
+        self.tags = set(tags)
+
+    def __repr__(self):
+        return str(self)
+
+    def __str__(self):
+        return '{} @ {} [{}]'.format(self.id, time.strftime('%Y-%m-%d %H:%M', self.timestamp), ','.join(self.tags))
+
+
+class Pickle(BackEnd):
+    res_folder = 'keepit_cache'
+
+    def __init__(self):
+        pass
+
+    def _filename(self, oid):
+        return os.path.join(self.res_folder, "{}.pickle".format(oid))
+
+    def _open(self, fpath, abs=False):
+        if not abs:
+            fpath = self._filename(fpath)
+        with open(fpath, 'rb') as f:
+            return pickle.load(f)
+
+    def put(self, entry):
+        if not os.path.exists(self.res_folder):
+            os.makedirs(self.res_folder)
+        with open(self._filename(entry.id), 'wb') as f:
+            pickle.dump(entry, f)
+
+    def exists(self, oid):
+        return os.path.exists(self._filename(oid))
+
+    def get(self, oid):
+        s = self._open(oid)
+        return s
+
+    def remove(self, oid):
+        return os.remove(self._filename(oid))
+
+    def ifind(self, oid=None, tags=[]):
+        target = set(tags)
+        for f in glob(os.path.join(self.res_folder, '*')):
+            e = self._open(f, abs=True)
+            if (not oid or f.id == oid) and e.tags.issuperset(tags):
+                yield e

keepit/version.py

@@ -0,0 +1,19 @@
+import os
+import logging
+
+logger = logging.getLogger(__name__)
+
+ROOT = os.path.dirname(__file__)
+DEFAULT_FILE = os.path.join(ROOT, 'VERSION')
+
+
+def read_version(versionfile=DEFAULT_FILE):
+    try:
+        with open(versionfile) as f:
+            return f.read().strip()
+    except IOError:  # pragma: no cover
+        logger.error('Running an unknown version of senpy. Be careful!.')
+        return '0.0'
+
+
+__version__ = read_version()

setup.py

@@ -0,0 +1,51 @@
+from setuptools import setup
+
+with open('keepit/VERSION') as f:
+    __version__ = f.read().strip()
+    assert __version__
+
+
+def parse_requirements(filename):
+    """ load requirements from a pip requirements file """
+    with open(filename, 'r') as f:
+        lineiter = list(line.strip() for line in f)
+    return [line for line in lineiter if line and not line.startswith("#")]
+
+
+install_reqs = parse_requirements("requirements.txt")
+test_reqs = parse_requirements("test-requirements.txt")
+
+
+# read the contents of your README file
+from os import path
+this_directory = path.abspath(path.dirname(__file__))
+with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
+    long_description = f.read()
+
+
+setup(
+    name='keepit',
+    python_requires='>3.3',
+    packages=['keepit'],  # this must be the same as the name above
+    version=__version__,
+    license='Apache License 2.0',
+    description=('advanced memoization/caching of functions with data analytics in mind'),
+    long_description=long_description,
+    long_description_content_type='text/markdown',
+    author='J. Fernando Sanchez',
+    author_email='balkian@gmail.com',
+    url='https://github.com/balkian/keepit',  # use the URL to the github repo
+    download_url='https://github.com/balkian/keepit/archive/{}.tar.gz'.format(
+        __version__),
+    keywords=['data analysis', 'memoization', 'cache'],
+    classifiers=[
+        'Programming Language :: Python :: 3',
+    ],
+    install_requires=install_reqs,
+    tests_require=test_reqs,
+    setup_requires=['pytest-runner', ],
+    include_package_data=True,
+    entry_points={
+        'console_scripts':
+        ['keepit = keepit.__main__:main',]
+    })

tests/create_custom.py

@@ -0,0 +1,13 @@
+from keepit import keepit
+
+ORIGIN = None
+
+
+@keepit('myfunction')
+def custom_function():
+    return ORIGIN
+
+
+if __name__ == '__main__':
+    ORIGIN = 'main'
+    custom_function()

tests/test.tsv

@@ -0,0 +1,3 @@
+	int	str	bool	other
+0	0	hola	True	
+1	1	adiós	False	5.0

tests/test_main.py

@@ -0,0 +1,98 @@
+import sys
+import os
+import subprocess
+from unittest import TestCase
+
+from keepit import keepit, diff, hash_df
+from keepit.backends import Pickle
+
+import pandas as pd
+
+# df = pd.DataFrame([[0, 'hola', True, None], [1, 'adiós', False, 5]], columns=['int', 'str', 'bool', 'other'])
+
+this_directory = os.path.abspath(os.path.dirname(__file__))
+
+
+count = 0
+
+@keepit()
+def prueba(first, name='something', value=29):
+    global count
+    count += 1
+    return pd.DataFrame([[count, first, name, value], ], columns=['time', 'first', 'name', 'value'])
+
+
+@keepit()
+def prueba_df():
+    return pd.read_csv(os.path.join(this_directory, 'test.tsv'), sep='\t')
+
+
+@keepit()
+def prueba_df_argument(df):
+    return count
+
+
+class TestMain(TestCase):
+
+
+    def setUpClass():
+        back = Pickle()
+        back.erase_all()
+        assert not back.find()
+        assert (not os.path.exists(back.res_folder)) or (not os.listdir(back.res_folder))
+
+    def tearDownClass():
+        back = Pickle()
+        back.erase_all()
+
+    def test_basic(self):
+
+        try:
+            prueba()
+        except TypeError:
+            pass
+
+        p1 = prueba('hello')
+        print(p1)
+        p2 = prueba('hello')
+        print(p2)
+        print(diff(p1, p2))
+        assert p1.equals(p2)  # Columns and rows are equal
+
+        p3 = prueba('other')
+        print(p3)
+        assert not p1.equals(p3)
+
+        p4 = prueba('hello', name='different')
+        print(p4)
+        assert not p1.equals(p4)
+
+    def test_list_and_drop(self):
+        assert len(prueba.list()) > 0
+        prueba.drop_all()
+        assert len(prueba.list()) == 0
+
+    def test_df(self):
+        df1 = prueba_df()
+        df2 = prueba_df()
+
+        assert df1.equals(df2)
+        assert hash_df(df1) == hash_df(df2)
+        prueba_df.drop_all()
+
+    def test_different_program(self):
+        '''A value saved by a different interpreter should be reusable.'''
+        from create_custom import custom_function
+        custom_function.drop_all()
+        subprocess.check_call([sys.executable, os.path.join(this_directory, 'create_custom.py')])
+        # create_custom returns different results when run as a script.
+        # We make sure we are using the "stored" value, and not the result from the imported function
+        assert custom_function() == 'main'
+
+    def test_df_arg(self):
+
+        df1 = pd.read_csv(os.path.join(this_directory, 'test.tsv'), sep='\t')
+        res1 = prueba_df_argument(df1)
+        df2 = pd.read_csv(os.path.join(this_directory, 'test.tsv'), sep='\t')
+        res2 = prueba_df_argument(df2)
+        assert res1 == res2