semvec/pypi-packages huggingface dataset:
upsilon-py 1.0.1
Connect to NumWorks calculators using Python
Requires Python: >=3.10,<4.0

# Upsilon.py

Upsilon.py is a wrapper for [upsilon.js]. It allow controlling the NumWorks from
Python. To use this library, because of the dependency on Upsilon.js, you will
need a working installation of [Node] with [Npm]

## Installation

To install Upsilon.py, you can use pip:

```bash
python3 -m pip install upsilon.py
```

After the installation, you will have to install Upsilon.js and its
dependencies:

```bash
npm install -g "upsilon.js@^1.4.1" usb
```

## Usage

To use Upsilon.py, you will need to import it:

```python
import upsilon_py
```

Then, you can create a new NumWorks object:

```python
numworks = upsilon_py.NumWorks()
```

You will then be able to start the object and connect to the NumWorks:

```python
await numworks.start()
await numworks.connect()
```

Now, the connection is established, you can send commands to the NumWorks:

```python
# Get the status of the NumWorks (connected/disconnected)
status = await numworks.status()
print("Status:", status)

# Get the model of the NumWorks (return 100/110/120)
model = await numworks.get_model()
print("Model:", model)

# Get the platform info of the NumWorks (information about the OS)
platform_info = await numworks.get_platform_info()
print("Platform info:", platform_info)

# Backup the storage of the NumWorks
storage = await numworks.backup_storage()

# Add a file to the storage
storage["records"].append({
    "name": "Test",
    "type": "py",
    "autoImport": True,
    "code": "print(\"Hello World!\")"
})

# Install the modified storage
await numworks.install_storage(storage)

# Stop the object (you can also use numworks.disconnect() to keep the object
# running and connect to another NumWorks)
await numworks.stop()
```



[upsilon.js]: https://www.npmjs.com/package/upsilon.js
[Node]: https://nodejs.org/en/
[Npm]: https://www.npmjs.com/
TERRA-GA-TXT-Classification 0.0.23
GA for best models for texts classification
Requires Python: >=3.6

'''
This is a set of modules for creating GA for txt classification.


1. from TERRA_GA.TXT_Classification_GA import TXT_create_Conv_Net

IMG_create_Conv_Net()

2. from TERRA_GA.TXT_Classification_GA import visualize_mean_accuracy

visualize_mean_accuracy(mean_val, max_val)

3. from TERRA_GA.TXT_Classification_GA import Recovery_Conv_Net

Recovery_Conv_Net()

4. from TERRA_GA.TXT_Classification_GA import show_info

show_info()

'''
'''
MIT License

Copyright (c) [year] [fullname]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), 
to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
 WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 '''
esp-idf-ldgen 0.1.0
Linker Script Generator
Requires Python: >=3.7
Keywords: espressif,embedded,linker,build

## Linker Script Generator

Contains code that implements linker script generation, `ldgen`. For more information about the feature,
see [linker-script-generation][1].

### Source Files

The following are the source files in the directory:

- `ldgen.py` - Python executable that gets called during build.
- `entity.py` - contains classes related to entities (library, object, symbol or combination of the above) with mappable input sections.
- `fragments.py` - contains classes for parsing the different types of fragments in linker fragment files.
- `generation.py` - contains bulk of the logic used to process fragments into output commands.
- `sdkconfig.py` - used for evaluating conditionals in fragment files.
- `linker_script.py` - augments the input linker script template with output commands from generation process to produce the output linker script.
- `output_commands.py` - contains classes that represent the output commands in the output linker script.
- `ldgen_common.py` - contains miscellaneous utilities/definitions that can be used in the files mentioned above.

### Tests

Unit tests are in the `test` directory. These tests are run as part of CI in the job `test_ldgen`.

There is also a test app for `ldgen` in the [esp-idf repository][2].

### Build System

Linker script generation is a part of the build process. The [ldgen.cmake][3]
build script contain the build-system-side implementation for CMake.

### Basic Flow

The build system invokes `ldgen.py`, passing some information from the build.

The linker fragment files are parsed by `fragments.py`, evaluating conditional expressions
with `sdkconfig.py`.

From the parsed fragments, `generation.py` generates output commands defined in `output_commands.py`,
with some help from `entity.py`.

`linker_script.py` writes the output linker script, replacing markers with output commands generated.

More details about the implementation are in the respective source files.

[1]: https://docs.espressif.com/projects/esp-idf/en/latest/esp32/api-guides/linker-script-generation.html
[2]: https://github.com/espressif/esp-idf/tree/master/tools/test_apps/build_system/ldgen_test
[3]: https://github.com/espressif/esp-idf/blob/master/tools/cmake/ldgen.cmake
Fx-profitude-forex-trading-system-by-russ-horn-free-download 1
Fx profitude forex trading system by russ horn free download
Requires Python: >=3.6

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