CPython compiled failed in macOS

version: macOS 10.14.4, Apple LLVM version 10.0.1 (clang-1001.0.46.4). I cloned the CPython source code from GitHub then compiled it which used to work quite well. However, I messed up my terminal a few days ago for installing gdb. Now when I try to compile the latest CPython source code with ./co

Duplicate function in thread_pthread.h

When I try to understand the code about the thread. I found the thread_pthread.h file has some duplicate functions. Like `PyThread_free_lock`, `PyThread_release_lock`, `PyThread_acquire_lock_timed`. IIUC, C doesn't support function overload. So why we have functions with the same name and args? --

write function call _io_BufferedWriter_write_impl twice?

My script looks like this: f = open('myfile', 'a+b') f.write(b'abcde') And I also add a `printf` statement in the _io_BufferedWriter_write_impl function. static PyObject *

Questions about the IO modules and C-api

I have some questions about the IO modules. 1. My script: f = open('myfile, 'a+b') f.close() I added a printf statement at the beginning of _io_open_impl , the output is: _io_open _io_open _io_open

Understand workflow about reading and writing files in Python

I'm trying to understand the workflow of how python read/writes files with buffer. I drew a diagram for it. I will be appreciated if someone can review the diagram :D [image: 屏幕快照 2019-06-15 下午12.50.57.png] -- https://mail.python.org/mailman/listinfo/python-list

Understand workflow about reading and writing files in Python

I'm trying to understand the workflow of how Python read/writes data with buffer. I will be appreciated if someone can review it. ### Read n data 1. If the data already in the buffer, return data 2. If the data not in the buffer: 1. copy all the current data from the buffer 2. create a new

Fwd: Understand workflow about reading and writing files in Python

1) is likely not that of (3) - otherwise why use a > "buffer"? The size of (2) must be larger than (1) and larger than (2) - > for reasons already illustrated. > Is this a typo? (2) larger than (1) larger than (2)? > > I recall learning how to use buffers with a series of hand

Re: Understand workflow about reading and writing files in Python

When you said "C-runtime buffered I/O", are you talking about Standard I/O in C (FILE * object)? AFAIN, In CPython, we didn't use Standard I/O, right? Dennis Lee Bieber 于2019年6月25日周二 上午12:48写道： > On Mon, 24 Jun 2019 15:18:26 +1200, DL Neil > declaimed the following: > > > > > >However, the OpSy

Re: Understand workflow about reading and writing files in Python

DL Neil 于2019年6月24日周一 上午11:18写道： > Yes, better to reply to list - others may 'jump in'... > > > On 20/06/19 5:37 PM, Windson Yang wrote: > > Thank you so much for you review DL Neil, it really helps :D. However, > > there are some parts still confused me,

fopen() and open() in cpython

After my investigation, I found Since Python maintains its own buffer when read/write files, the build-in python open() function will call the open() system call instead of calling standard io fopen() for caching. So when we read/write a file in Python, it would not call fopen(), fopen() only use

Re: fopen() and open() in cpython

Thank you so much for the answer, now it makes sense :D eryk sun 于2019年8月15日周四 上午12:27写道： > On 8/13/19, Windson Yang wrote: > > After my investigation, I found Since Python maintains its own buffer > when > > read/write files, the build-in python open() function wi

How should we use global variables correctly?

I can 'feel' that global variables are evil. I also read lots of articles proves that (http://wiki.c2.com/?GlobalVariablesAreBad). However, I found CPython Lib use quite a lot of `global` keyword. So how should we use `global` keyword correctly? IIUC, it's fine that we use `global` keyword inside t

Re: How should we use global variables correctly?

Thank you all for the great explanation, I still trying to find some good example to use 'global', In CPython, I found an example use 'global' in cpython/Lib/zipfile.py _crctable = None def _gen_crc(crc): for j in range(8): if crc & 1: crc = (crc >> 1) ^

Re: How should we use global variables correctly?

the global.py is short and clean enough (didn't have a lot of other class), they are pretty much the same. Or I missed something? Chris Angelico 于2019年8月23日周五 上午9:34写道： > On Fri, Aug 23, 2019 at 11:24 AM Windson Yang wrote: > > > > Thank you all for the great explanation,

Re: How should we use global variables correctly?

gt;>short and clean enough (didn't have a lot of other class), they are > pretty > >>much the same. Or I missed something? > >> > > > >One difference is that you could have many instances of Example, each > >with its own value of 'foo', whereas

What make function with huge list so slow

I have two functions to calculate Fibonacci numbers. fib_dp use a list to store the calculated number. fib_dp2 just use two variables. def fib_dp(n): if n <= 1: return n dp = [0] * (n+1) dp[0], dp[1] = 0, 1 for i in range(2, n+1): dp[i] =

Re: What make function with huge list so slow

Thank you, Chris. I tried your suggestions. I don't think that is the reason, fib_dp_look() and fib_dp_set() which also allocation a big list can return in 2s. Chris Angelico 于2019年8月25日周日 上午11:27写道： > On Sun, Aug 25, 2019 at 12:56 PM Windson Yang wrote: > > > > I h

Re: What make function with huge list so slow

'I'm just running them in succession and seeing how long they'. The full code looks like this, this is only an example.py here. and I run 'time python3 example.py' for each function. def fib_dp(n): dp = [0] * (n+1) if n <= 1: return n dp[0], dp[1] = 0, 1

Re: What make function with huge list so slow

> Figure out how much memory fib_dp is holding on to right before it returns > the answer. fib(40) is a _big_ number! And so is fib(39), and > fib(38), and fib(37), etc. By the time you're done, you're holding > on to quite a huge pile of storage here. Depending on how much phys