TGINSIGHT SIMILAR POSTS
Source channel @olddriverGDstudy · Post #98 · Sep 12
#舔逼三步 第一步（初舔B） 亲阴唇时要把女性的明唇尽量吸吮到嘴里，用舌头轻扫轻舔，女性会觉得阴唇部位特别有点痒，她很想你亲更多位置，亲得更广些，别理她们，你亲你的就行了，你可以趁着她们正享受着的时候，轻轻的咬一下她的阴唇她肯定会“啊”的一下惊叫，身子抽动一下，在她还没来得及说话时，你快速把嘴唇整个贴在她的阴道口，这种做法可以让女性一下子感觉到整个阴部很温暖很舒服， 刚才的那声“啊”还没叫完就变成“噢”的一轻呼了。这时开始应该动手了，你应该用大拇指轻轻的将她的阴唇向两边分开蛋出女性的阴道口，用舌头在阴道口周围打转绕圈，时轻时重，时而整个嘴唇贴上。 这时候你可以稍为停下不亲阴道口，而是用湿润的舌尖轻轻撩几下她的阴蒂，把她的感觉从明蒂里撩拨起来，女性会轻叫几下，然后你再回去亲她的明道口和阴唇。 第二步（挑逗期） 不要在这时候再亲她的阴蒂，要让女性半吊在那种感觉里，而且男性要开始从女性的会阴处向阴蒂方向往上轻舔，慢点，舌头到达阴道口时左右拨动，把阴唇一边拨开一边向上继续舔，一点点向阴蒂部位接近。就是偏不要亲到阴蒂那，差不多到的时候你用舌尖轻轻的，越轻越好，只是在她的阴蒂上轻扫轻点一下（舌头要含点口水) ，随即反方向按上述亲法朝阴道口部位舔去。这样会把女性给急死的，她一急，自然就兴奋了。亲阴道口时，舌头长的男性可以尝试把舌头插入女性的明道内搅动。舌头宽厚的男性可以把舌头由阴道口自下往上扫动。 第三步（猛攻） 现在开始可以集中精力夺取“珍珠”了，清把舌头上移至女性的阴蒂处集中精力。女性的阴蒂是非常敏感的，如果你太大力舔动，她的痛感多过快感，就没意思了。亲吻阴蒂要注意几点，舌头一定要湿、轻、尖，一定要保持舌头湿润，亲舔阴蒂时一定要轻，要用舌尖来舔。进攻明蒂要用“点、挑、拨、压、搅”五字诀。点，是指用舌尖轻点轻触女性的阴蒂顶端;挑，是指舌头从阴蒂下面向上挑动；拔，是用舌头左右拨动女性的阴蒂；压，是时不时用舌头压女性的阴蒂，把它稍为压下即可；搅，是当你含住女性的阴蒂时用舌头在明蒂四周搅动。进攻明蒂要用“点、挑、拨、压、视员五字决，点，是指用舌尖轻点控用女性的阴蒂顶端;挑，是指舌头从阴蒂下面向上挑动; 拔，是用舌头左右拨动女性的阴蒂;压，是时不时用活头压女性的阴蒂，把它稍为压下即可， 搅，是当你含住女性的阴蒂时用舌头在阴蒂四周搅动。你可以感觉到她们的阴蒂下似乎有点筋会在跳动，这在你含着女性的阴蒂时感觉非常明显。不要随便中断女性的感觉，动作要平均，因为你突然而快节奏的动作很容易让女性到达高潮。觉得可以给对方高潮时，应该用整个嘴唇含住女性的阴蒂部位， 上嘴唇压在阴蒂上方的阴毛根部，下嘴唇左石分开女性的阴唇，尽量贴近阴道口,用口含住女性的阴蒂(留点空间)，让女性觉得她的阴蒂是飘浮在你的嘴里的，用五字决发动进攻。让对方猛的一阵抽搐，看着她快到时，轻轻一放，然后马上又含上去。 (评论区附图解) 标签：#知识，#技巧
Search: #cpython
@djangoproject · Post #131 · 09/01/2016, 03:27 AM
http://www.lfd.uci.edu/~gohlke/pythonlibs/ This page provides 32- and 64-bit Windows binaries of many scientific open-source extension #packages for the official #CPython distribution of the #Python programming language. The files are unofficial (meaning: informal, unrecognized, personal, unsupported, no warranty, no liability, provided "as is") and made available for testing and evaluation purposes.
@djangoproject · Post #164 · 09/17/2016, 10:20 AM
https://www.buzzfeed.com/andrewkelleher/deep-exploration-into-python-lets-review-the-dict-module?utm_term=.rhDeZBxA8#.bgB5DM0Z9 In this series, we’ll take a look at various modules and pieces of functionality of the #Python language. We’ll look at design choices, their impact, and their evolution. We’ll also look at the design of the language itself and learn about the operations of the interpreter as it parses the language all the way to the main eval loop. Finally, we’ll attempt to give practical takeaways that fall out of a deeper understanding of the language. The #cpython implementation of Python (which is the standard on most machines) has been ported over to GitHub from its home in Mercurial. I think it also had a time under #SVN, but the engineers managed to preserve (for the most part) the commit logs.
@aigcrubbish · Post #6 · 08/23/2024, 06:57 AM
CPython zipfile 模块高危漏洞 CVE-2024-8088 CPython 的 zipfile 模块存在一个高危漏洞，编号为 CVE-2024-8088。该漏洞会导致在处理恶意构造的 zip 档案时，程序陷入无限循环。具体来说，当使用 zipfile.Path 类及其方法（如 namelist()`、`iterdir()`、`extractall() 等）遍历 zip 档案条目名称时，可能会触发无限循环。 此漏洞的根本原因在于 zipfile._path._ancestry() 方法中的路径处理不当。具体来说，代码中的 path.rstrip(posixpath.sep) 和 while 循环条件未正确处理路径，导致无限循环。例如，`posixpath.split("//") 返回 ("//", "")，而 "//" != posixpath.sep` 导致循环无法退出。 该漏洞已被修复，建议更新 CPython 并加强输入验证，以防止潜在的拒绝服务攻击。 原文链接：https://www.openwall.com/lists/oss-security/2024/08/22/1https://www.openwall.com/lists/oss-security/2024/08/22/4 标签：#CPython#漏洞#zipfile#无限循环 #AIGC
@djangoproject · Post #156 · 09/06/2016, 01:43 AM
https://wiki.python.org/moin/GlobalInterpreterLock In #CPython, the #global#interpreter lock, or #GIL, is a mutex that prevents multiple native #threads from executing Python bytecodes at once. This lock is necessary mainly because CPython's memory management is not thread-safe. (However, since the GIL exists, other features have grown to depend on the guarantees that it enforces.)
@djangoproject · Post #551 · 01/23/2018, 04:28 PM
http://lxml.de/ #lxml is the most feature-rich and easy-to-use library for processing #XML and #HTML in the Python language. The lxml XML toolkit is a Pythonic binding for the #C libraries #libxml2 and #libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python #API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all #CPython versions from 2.6 to 3.6. See the introduction for more information about background and goals of the lxml project. Some common questions are answered in the FAQ.
@djangoproject · Post #523 · 12/13/2017, 08:27 PM
http://www.jaggedverge.com/2017/11/how-a-web-page-request-makes-it-down-to-the-metal/ How a web page request makes it down to the metal by : Janis Posted in : Tutorials, work-in-progess Tags : #NGINX, #Python No Comments The other day I was interested in how many steps occur between sending a #POST or #GET#request from a website to the actual processing that happens on the CPU of the #server. I figured that I knew bits and pieces of the puzzle but I wanted to see the complete path from the highest levels of abstraction all the way to the lowest without missing anything too big in-between. It turns out that in a modern web system there are a lot of steps. I have been really fascinated by this much like the explorer that wants to find a path from one known place to another. If you are interested in better understanding how your computer works you might find walking along this path with your tech stack helpful. Frontend prelude: GET request Browser page #rendering POST request sidenote: #CSRF#token Network stack sidenote: The Internet #TCP sidenote: more comprehensive treatment of network stack Backend Handling web request #WSGI #Django Django URL routing Django views Python implementations #CPython CPython bytecode CPython bytecode execution details Machine Code CPython to machine code Machine code execution Hardware implementation details Microcode Processor #pipeline Silicon implementation of addition Silicon adder unit AND gate Transistor