functools

implementing functools.partial that prepends additional arguments

由 血红的双手。 提交于 2020-01-01 09:05:50
问题 The documentation for functools.partial says that it is "roughly equivalent to": def partial(func, *args, **keywords): def newfunc(*fargs, **fkeywords): newkeywords = keywords.copy() newkeywords.update(fkeywords) return func(*(args + fargs), **newkeywords) # line to change newfunc.func = func newfunc.args = args newfunc.keywords = keywords return newfunc If I wanted to implement a version that prepends the additional arguments, it seems like I'd just have to change the indicated line. Are

Dynamically created method and decorator, got error 'functools.partial' object has no attribute '__module__'

由 ∥☆過路亽．° 提交于 2019-12-30 02:44:12
问题 I am currently using EndpointsModel to create a RESTful API for all my models on AppEngine. Since it is RESTful, these api have a lot of repeat code which I want to avoid. For example: class Reducer(EndpointsModel): name = ndb.StringProperty(indexed=False) @endpoints.api( name="bigdata", version="v1", description="""The BigData API""", allowed_client_ids=ALLOWED_CLIENT_IDS, ) class BigDataApi(remote.Service): @Reducer.method( path="reducer", http_method="POST", name="reducer.insert", user

How to write a wrapper to fix arbitrary parameters in a function

由 我是研究僧i 提交于 2019-12-24 11:58:45
问题 I would like to write a curve-fitting script that allows me to fix parameters of a function of the form: def func(x, *p): assert len(p) % 2 == 0 fval = 0 for j in xrange(0, len(p), 2): fval += p[j]*np.exp(-p[j+1]*t) return fval For example, let's say I want p = [p1, p2, p3, p4], and I want p2 and p3 to be constant A and B (going from a 4-parameter fit to a 2-parameter fit). I understand that functools.partial doesn't let me do this which is why I want to write my own wrapper. But I am having

Python functools.lru_cache eviction callback or equivalent

由 天大地大妈咪最大 提交于 2019-12-23 20:21:08
问题 Is it possible to define a callback for functools.lru_cache when an item is evicted? In the callback the cached value should also be present. If not, maybe someone knows a light-weight dict-like cache that supports eviction and callbacks? 回答1: I will post the solution I used for future reference. I used a package called cachetools (https://github.com/tkem/cachetools). You can install by simply $ pip install cachetools . It also has decorators similar to the Python 3 functools.lru_cache (https

itertools.accumulate() versus functools.reduce()

由 ￣綄美尐妖づ 提交于 2019-12-20 12:28:26
问题 In Python 3.3, itertools.accumulate(), which normally repeatedly applies an addition operation to the supplied iterable, can now take a function argument as a parameter; this means it now overlaps with functools.reduce(). With a cursory look, the main differences between the two now would seem to be: accumulate() defaults to summing but doesn't let you supply an extra initial condition explicitly while reduce() doesn't default to any method but does let you supply an initial condition for use

Differences between functools.partial and a similar lambda?

由 不想你离开。 提交于 2019-12-17 18:54:26
问题 In Python, suppose I have a function f that I want to pass around with some secondary arguments (assume for simplicity that it's just the first argument that remains variable). What are the differences between doing it these two ways (if any)? # Assume secondary_args and secondary_kwargs have been defined import functools g1 = functools.partial(f, *secondary_args, **secondary_kwargs) g2 = lambda x: f(x, *secondary_args, **secondary_kwargs) In the doc page for partial, for example, there is

Using functools.partial to make custom filters for pdfquery getting attribute error

由 蓝咒 提交于 2019-12-13 03:54:48
问题 Background I'm using pdfquery to parse multiple files like this one. Problem I'm trying to write a generalized filer function, building off of the custom selectors mentioned in pdfquery's docs, that can take a specific range as an argument. Because this is referenced I thought I could get around this by supplying a partial function using functools.partial (as seen below) Input import pdfquery import functools def load_file(PDF_FILE): pdf = pdfquery.PDFQuery(PDF_FILE) pdf.load() return pdf

Python library functions taking no keyword arguments

由 你。 提交于 2019-12-10 13:54:55
问题 This problem originated when I tried to apply a more functional approach to problems in python. What I tried to do is simply square a list of numbers, no biggie. from operator import pow from functools import partial squared = list(map(partial(pow, b=2), range(10)) As it turns out, this didn't work. TypeError: pow() takes no keyword arguments Confused I checked if pow(b=2, a=3) did. It didn't. I've checked the operator source code, nothing suspicious. Confused, I've begun to doubt my own

Memoize a function so that it isn't reset when I rerun the file in Python

由 泄露秘密 提交于 2019-12-07 22:42:49
问题 I often do interactive work in Python that involves some expensive operations that I don't want to repeat often. I'm generally running whatever Python file I'm working on frequently. If I write: import functools32 @functools32.lru_cache() def square(x): print "Squaring", x return x*x I get this behavior: >>> square(10) Squaring 10 100 >>> square(10) 100 >>> runfile(...) >>> square(10) Squaring 10 100 That is, rerunning the file clears the cache. This works: try: safe_square except NameError:

Memoize a function so that it isn't reset when I rerun the file in Python

由 一世执手 提交于 2019-12-06 12:26:04
I often do interactive work in Python that involves some expensive operations that I don't want to repeat often. I'm generally running whatever Python file I'm working on frequently. If I write: import functools32 @functools32.lru_cache() def square(x): print "Squaring", x return x*x I get this behavior: >>> square(10) Squaring 10 100 >>> square(10) 100 >>> runfile(...) >>> square(10) Squaring 10 100 That is, rerunning the file clears the cache. This works: try: safe_square except NameError: @functools32.lru_cache() def safe_square(x): print "Squaring", x return x*x but when the function is
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