大约有 26,000 项符合查询结果(耗时:0.0380秒) [XML]

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How to use pip with Python 3.x alongside Python 2.x

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Laravel Eloquent ORM Transactions

... if there is an easy way to setup MySQL transactions using innoDB in the same fashion as PDO, or if I would have to extend the ORM to make this possible? ...
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builder for HashMap

Guava provides us with great factory methods for Java types, such as Maps.newHashMap() . 15 Answers ...
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The type or namespace name 'DbContext' could not be found [closed]

I am VERY new to ASP.NET MVC (3) and am having a hard time resolving a build error in Visual Studio: 30 Answers ...
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jQuery Selector: Id Ends With?

Is there a selector that I can query for elements with an ID that ends with a given string? 9 Answers ...
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Good introduction to the .NET Reactive Framework [closed]

Aside from the Microsoft documentation, is there a good introduction and tutorial to the Microsoft Reactive (Rx) framework? ...
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Show/Hide the console window of a C# console application

... I feel like such a numpty, it seems so obvious when pointed out to me. I found this so hard to google. – Crouch Nov 26 '14 at 12:39 10 ...
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What is that “total” in the very first line after ls -l? [closed]

... You can find the definition of that line in the ls documentation for your platform. For coreutils ls (the one found on a lot of Linux systems), the information can be found via info coreutils ls: For each directory that is listed, preface the files with a line `total B...
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Find and Replace text in the entire table using a MySQL query

... For a single table update UPDATE `table_name` SET `field_name` = replace(same_field_name, 'unwanted_text', 'wanted_text') From multiple tables- If you want to edit from all tables, best way is to take the dump and then find/replace and upload it back. ...
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How to do exponential and logarithmic curve fitting in Python? I found only polynomial fitting

...tional to y. polyfit supports weighted-least-squares via the w keyword argument. >>> x = numpy.array([10, 19, 30, 35, 51]) >>> y = numpy.array([1, 7, 20, 50, 79]) >>> numpy.polyfit(x, numpy.log(y), 1) array([ 0.10502711, -0.40116352]) # y ≈ exp(-0.401) * exp(0.105 * ...