Install pyodbc: Use the pipinstallpyodbc command to install the library; 2. Connect SQLServer: Use the connection string containing DRIVER, SERVER, DATABASE, UID/PWD or Trusted_Connection through the pyodbc.connect() method, and support SQL authentication or Windows authentication respectively; 3. Check the installed driver: Run pyodbc.drivers() and filter the driver name containing 'SQLServer' to ensure that the correct driver name is used such as 'ODBCDriver17 for SQLServer'; 4. Key parameters of the connection string

Introduction to Statistical Arbitrage Statistical Arbitrage is a trading method that captures price mismatch in the financial market based on mathematical models. Its core philosophy stems from mean regression, that is, asset prices may deviate from long-term trends in the short term, but will eventually return to their historical average. Traders use statistical methods to analyze the correlation between assets and look for portfolios that usually change synchronously. When the price relationship of these assets is abnormally deviated, arbitrage opportunities arise. In the cryptocurrency market, statistical arbitrage is particularly prevalent, mainly due to the inefficiency and drastic fluctuations of the market itself. Unlike traditional financial markets, cryptocurrencies operate around the clock and their prices are highly susceptible to breaking news, social media sentiment and technology upgrades. This constant price fluctuation frequently creates pricing bias and provides arbitrageurs with

iter() is used to obtain the iterator object, and next() is used to obtain the next element; 1. Use iterator() to convert iterable objects such as lists into iterators; 2. Call next() to obtain elements one by one, and trigger StopIteration exception when the elements are exhausted; 3. Use next(iterator, default) to avoid exceptions; 4. Custom iterators need to implement the __iter__() and __next__() methods to control iteration logic; using default values is a common way to safe traversal, and the entire mechanism is concise and practical.

The recommended way to read files line by line in Python is to use withopen() and for loops. 1. Use withopen('example.txt','r',encoding='utf-8')asfile: to ensure safe closing of files; 2. Use forlineinfile: to realize line-by-line reading, memory-friendly; 3. Use line.strip() to remove line-by-line characters and whitespace characters; 4. Specify encoding='utf-8' to prevent encoding errors; other techniques include skipping blank lines, reading N lines before, getting line numbers and processing lines according to conditions, and always avoiding manual opening without closing. This method is complete and efficient, suitable for large file processing

TorunaPythonscriptwithargumentsinVSCode,configurelaunch.jsonbyopeningtheRunandDebugpanel,creatingoreditingthelaunch.jsonfile,andaddingthedesiredargumentsinthe"args"arraywithintheconfiguration.2.InyourPythonscript,useargparseorsys.argvtoacce

The system endianness can be detected by a variety of methods, the most commonly used is the union or pointer method. 1. Use a union: Assign uint32_t to 0x01020304, if the lowest address byte is 0x04, it is a small endian, and if it is 0x01, it is a big endian; 2. Use pointer conversion: Assign uint16_t to 0x0102, read the byte order through the uint8_t pointer, [0]==0x02 and [1]==0x01 is a small endian, otherwise it is a big endian; 3. Compilation-time detection: define the constexpr function to determine whether the (char)&int variable is 1, and combine ifconstexpr to determine the endian order during the compilation period; 4. Runtime macro encapsulation: use (char*)&amp

Gowillremainacornerstoneofmodernsoftwareinfrastructureduetoitsstability,performance,andstrongecosystem;1.Itsdominanceincloud-nativecomputingwillcontinuewithwidespreaduseinKubernetes,Docker,andCNCFprojects;2.Ongoingimprovementsingenerics,modulemanagem

Install the Boost library, 2. Write code for DNS resolution using Boost.Asio, 3. Compile and link the boost_system library, 4. Run the program to output the IP address parsed by www.google.com; this example shows how Boost.Asio simplifies network programming in C, implements cross-platform, type-safe synchronous DNS queries through io_context and tcp::resolver, and supports IPv4 and IPv6 address resolution, and finally prints all resolution results.