byteorder | Rust library for reading/writing numbers | Cryptography library
kandi X-RAY | byteorder Summary
kandi X-RAY | byteorder Summary
Rust library for reading/writing numbers in big-endian and little-endian.
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QUESTION
According to Wikipedia, the ASCII is a 7-bit encoding. Since each address (then and now) stores 8 bits, the extraneous 8th bit can bit used as a parity bit.
The committee voted to use a seven-bit code to minimize costs associated with data transmission. Since perforated tape at the time could record eight bits in one position, it also allowed for a parity bit for error checking if desired.[3]:217, 236 §5 Eight-bit machines (with octets as the native data type) that did not use parity checking typically set the eighth bit to 0.
Nothing seems to mandate that the 8th bit in a byte storing an ASCII character has to be 0. Therefore, when decoding ASCII characters, do we have to account for the possibility that the 8th bit may be set to 1? Python doesn't seem to take this into account — should it? Or are we guaranteed that the parity bit is always 0 (by some official standard)?
ExampleIf the parity bit is 0 (default), then Python can decode a character ('@'):
...ANSWER
Answered 2021-Jun-12 at 11:39The fact that the parity bit CAN be set is just an observation, not a generally followed protocol. That being said, I know of no programming languages that actually care about parity when decoding ASCII. If the highest bit is set, the number is simply treated as >=128, which is out of range of the known ASCII characters.
QUESTION
I am trying to use Python (PyCharm) to read a register on a modbus device. I have confirmed the COM port, Baud rate and other communication settings and I can use the devices application to read the value (it is a water level logger). I am getting no response from the instrument.
Register is readable in mbpoll using -
...ANSWER
Answered 2021-Jun-03 at 05:31The device manual isn't clear about the register start address, but the first register it mentions has the address of 1.
Similarly, the mbpoll command-line utility (not the one with GUI) isn't very clear about the start address. But its documentation mentions that the default value for -r parameter is 1.
I think it's safe to assume that both use the same addressing which starts from 1, as the command-line tool has no problems accessing the value.
But MinimalModbus API clearly mentions that its register start address is 0. So when using this library, you need to use registeraddress = 45 for accessing the temperature, not 46 or 40046.
But why won't 46 work? Normally, one would expect it to grab data starting from the next register and print some garbage, but not timeout. But we can't know how the device works internally. Maybe a request to access the temperature register actually triggers some measurement function and then returns a value. A request to access an unaligned data (with a wrong register value) can be simply rejected by the firmware.
If you still get timeouts with registeraddress = 45, your Python runtime may have some problems accessing the serial port. As I stated in my comment, I recommend using a logic analyzer to see what's going on on the wire. Without such a tool, you're doing blind-debugging.
QUESTION
I'm doing a socket communication between a Python and a Java process. I'm trying to send an int with java and receive it in Python.
Java side (sender):
...ANSWER
Answered 2021-May-28 at 08:14I guess you are not doing anything logically wrong, but this seems to be the way TCP works with it. In documentation about using sockets, although an amount is expected, the reception is in a loop waiting to get the expected amount of data.
Try doing the same. I.E. in pseudocode:
QUESTION
I have two threads, one is listening on a socket and adding to the queue, the other subtracting from the queue and submitting for processing. The second thread has a sleep when the queue is empty. This sleep somehow affects the first thread, that is, if you remove sleep or make it larger, then the delay in socket.receive of the first thread increases. If I keep the sleep as low as possible, it gets better, but not perfect. What am I doing wrong?
...ANSWER
Answered 2021-May-18 at 10:23Actually you don't need to sleep, use proper queue classes instead, like LinkedBlockingQueue, I also remove the flags since you don't need them also, use interrupt() to stop a thread blocked waiting for a queue element:
QUESTION
Input Byte array = [b'\x03\x00', b'\x04\x00', b'\x05\x00', b'\x05\x00', b'\x05\x00', b'\x06\x00', b'\x07\x00',
b'\x08\x00', b'\t\x00', b'\n\x00', b'\t\x00', b'\x08\x00', b'\x07\x00', b'\x06\x00']
ANSWER
Answered 2021-May-11 at 03:49You need to close the file after writing to it before opening it again. Due to buffering, the file may not be written to disk until it is closed or the buffer is flushed. Closing the file flushes the buffer and writes it to disk.
QUESTION
I have a list of bytes, like so
...ANSWER
Answered 2021-May-14 at 07:51You can do this using a structured array. So given:
QUESTION
The issue seems to be with displaying the HTML with styling rendered by pandas in Google Chrome and Microsoft Edge.
JupyterLab in Firefox correctly displays all of the styled rows and correctly renders an output HTML file.
The updated questions are
- Why doesn't the HTML rendered by pandas completely display all the styling in Chrome or Edge?
- Is there a more efficient way to apply the styling done by pandas so the HTML also works in Chrome and Edge?
Versions:
pandas v1.2.4Chrome v90.0.4430.93 (Official Build) (64-bit)Edge v90.0.818.56 (Official build) (64-bit)
- Questions - they are interrelated:
- Why aren't all of the rows displaying the background styling in Jupyter or writing to HTML?
- All rows should have green styling, but the last 5 do not display the styling.
- How can all of the rows be made to display the background styling?
- Why aren't all of the rows displaying the background styling in Jupyter or writing to HTML?
- Given a large dataframe, in this case
474 rows x 35 columns, the applied styling stops displaying. - If the number of rows or columns increases beyond this size, then more rows aren't displayed.
- We can see from the styling map, that the rows are correctly mapped with a background color, but it isn't displayed.
- If the number of rows or columns is reduced, then all of the rows display the correct styling.
- Tested in
jupyterlab v3.0.11 - Tested in
PyCharm 2021.1 (Professional Edition) Build #PY-211.6693.115, built on April 6, 2021saving the redendered styler to a file has the same result, so this isn't just an issue withjupyter. - Tested in the console
- This issue is reproducible on two different systems, that I have tried.
- If the shape is reduced to
471 rows × 35 columnsor474 rows × 34 columns, then all rows correctly display the highlighting. - Associated pandas bug report: 40913
ANSWER
Answered 2021-Apr-15 at 15:07- Per bug #39400, the issue occurs for large DataFrames because Styler puts all CSS ids on a single attribute, which are not resolved be all browsers.
- In the following small snippet, see that all the ids are at the top.
- The snippet ids are for 5 rows and 35 columns, though only data for 1 table row is included.
QUESTION
I'm trying to use my model in the tflitecamerademo example.
The demo crashes with the following reason
java.lang.IllegalArgumentException: Cannot copy to a TensorFlowLite tensor (input_1) with 150528 bytes from a Java Buffer with 602112 bytes.
I initialize the byte buffer following google's example
...ANSWER
Answered 2021-May-06 at 17:42This is caused by type mismatch.
According to model description you have integer type input/output, maybe quantized model.
You are trying to prepare floating point data buffer to feed. There are 2 most common solutions:
1)Prepare uint8 data. Write bitmap pixels as 1 byte uint8s into bytebuffer:
QUESTION
how can I get audio input in real time from QAudioInput, store it in a NumPy array and pass it to SciPy FFT? What I have tried:
...ANSWER
Answered 2021-May-05 at 21:38data.toUInt() converts whole byte array to one uint value - not what you want. To get sample values you can use either numpy.frombuffer or struct.unpack.
QUESTION
I have a java.nio.ByteBuffer, which I need to pass to a Cassandra table that has a field as a blob.
Here is the relevant code for a toy example:
...ANSWER
Answered 2021-Apr-29 at 11:57Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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