semvec/pypi-packages huggingface dataset:
libopy 1.0.0
Package for transaction offline transaction signing
Requires Python: >=3.6

# libopy

## Installing<a name="installing"></a>

Installing from PyPI repository (https://pypi.org/project/libopy):

```bash
pip install libopy
```

## Usage<a name="usage"></a>

### Generating a wallet<a name="generating-a-wallet"></a>

```python
from libopy import generate_wallet

wallet = generate_wallet()
```

The value assigned to `wallet` will be a dictionary just like:

```python
{
    "seed": "YOUR_MNEMONIC_SEED",
    "derivation_path": "m/44'/118'/0'/0/0",
    "private_key": b"\xcc\xec^\xf6\xdcg\xe6\xb5\x89\xed\x8cG\x05\x03\xdf0:\xc9\x8b \x85\x8a\x14\x12\xd7\xa6a\x01\xcd\xf8\x88\x93",
    "public_key": b"\x13\x1d\xae\xa7\x9eO\x8e\xc5\xff\xa3sAw\xe6\xdd\xc9\xb8b\x06\x0eo\xc5a%z\xe3\xff\x1e\xd2\x8e5\xe7",
    "address": "libonomy5byhna3psjqfxnw4msrfzsr0g08yuyfxeht0qak",
}
```

### Converter functions<a name="converter-functions"></a>

#### Mnemonic seed to private key<a name="mnemonic-seed-to-private-key"></a>

```python
from libopy import BIP32DerivationError, seed_to_privkey

seed = (
    "YOUR_MNEMONIC_SEED"
)
try:
    privkey = seed_to_privkey(seed, path="m/44'/118'/0'/0/0")
except BIP32DerivationError:
    print("No valid private key in this derivation path!")
```

#### Private key to public key<a name="private-key-to-public-key"></a>

```python
from libopy import privkey_to_pubkey

privkey = bytes.fromhex(
    "1dcd05d7ac71e09d3cf7da666709ebd59362486ff9e99db0e8bc663570515ala"
)
pubkey = privkey_to_pubkey(privkey)
```

#### Public key to address<a name="public-key-to-address"></a>

```python
from libopy import pubkey_to_address

pubkey = bytes.fromhex(
    "1dcd05d7ac71e09d3cf7da666709ebd59362486ff9e99db0e8bc663570515ala"
)
addr = pubkey_to_address(pubkey)
```

#### Private key to address<a name="private-key-to-address"></a>

```python
from libopy import privkey_to_address

privkey = bytes.fromhex(
    "1dcd05d7ac71e09d3cf7da666709ebd59362486ff9e99db0e8bc663570515ala"
)
addr = privkey_to_address(privkey)
```

### Signing transactions<a name="signing-transactions"></a>

```python
from libopy import Transaction

tx = Transaction(
    privkey=bytes.fromhex(
        "1dcd05d7ac71e09d3cf7da666709ebd59362486ff9e99db0e8bc663570515ala"
    ),
    account_num=0,
    sequence=0,
    fee=0,
    gas=0,
    memo="",
    chain_id="chain-id",
    sync_mode="sync",
)
tx.add_transfer(
    recipient="libonomy5byhna3psjqfxnw4msrfzsr0g08yuyfxeht0qak", amount=1000000 
)
tx.add_transfer(recipient="libonomy5byhna3psjqfxnw4msrfzsr0g08yuyfxeht0qak", amount=1000000)
pushable_tx = tx.get_pushable()
```

One or more token transfers can be added to a transaction by calling the `add_transfer` method.

When the transaction is fully prepared, calling `get_pushable` will return a signed transaction in the form of a JSON string.
This can be used as request body when calling the `POST /txs` endpoint.
rangealert 0.0.1
Range bound trading screener
Requires Python: >=3.6

This module is not intended as advice to trade, it is for use in your trading analyses and algorithms. Use at your own risk.

This screener attempts to find range bound markets based on given inputs.

**Required data:**

-Pandas dataframe containing index as datetime and columns (High, Low, Open, Close) as float
-Define the number of breakout periods (default: 55 periods)
-Average True Range (ATR) window (default: 14 periods)
-ATR multiple (default: 1.5)- sensitivity used to determine a level at which the alert will provide a range signal

**Response:**

The response returned is a tuple of the signal and a plotly chart: (signal, chart) create_chart=False is default. The signal is one of three options: 1, 0

  * 1 - trading in a range
  * 0 - not trading in a range

**Dependencies:**

- pandas
- ta
- plotly

**Install module:**

https://pypi.org/project/rangealert/

pip install rangealert

**Detailed documentation:**

https://github.com/jonleonATX/range_trading_alert/blob/master/rangealert.ipynb
django-session-cleanup 4.0.0
A periodic task for removing expired Django sessions with Celery.

======================
Django Session Cleanup
======================

For projects that use the ``cached_db`` or ``db`` session engines, the
``django_session`` table can get quite large after a while.

Django provides the 'cleanup' management command for deleting expired sessions
from this table but you have to either run this command manually or
set-up a cron job.

Django Session Cleanup provides a periodic task for
`Celery <http://celeryproject.org/>`_ that will delete expired sessions.

Usage
-----

1. Run ``pip install django-session-cleanup``.

2. Add ``session_cleanup`` to ``INSTALLED_APPS`` in your project's settings.

3. Edit or create ``CELERYBEAT_SCHEDULE`` in your project's settings::

    from session_cleanup.settings import weekly_schedule
    CELERYBEAT_SCHEDULE = {
        ...
        'session_cleanup': weekly_schedule
    }
SwarmForm 1.0.2
SwarmForm Workflow Management Software

**SwarmForm**

SwarmForm is a distributed workflow management system for High Performance Computing environments. SwarmForm introduces task clustering to reduce the makespan of workflows executed using it by minimizing the overheads. SwarmForm follows a distributed architecture with independent programs controlling different functional layers in workflow management.

**Getting Started**

These instructions will get you familiar with the installation and basic functions of the SwarmForm.

**_Prerequisites_**

Following prerequisites should be installed to run SwarmForm.

* MongoDB
* Python 3.3+
* pip

**_Installation_**

To install SwarmForm, simply type

```
pip install SwarmForm
```

**_Basic Usage_**

Following is a step by step series of examples that tell you how to use the basic system functions.

* Initialize a SwarmForm launchpad YAML file

```
sform init
```


* Insert a SwarmFlow from file

```
sform add -sf <file path>
```

* Get SwarmFlow from SwarmPad

```
sform get_sf -id <SwarmFlow ID>
```

* Cluster the fireworks in the SwarmFlow and save the new SwarmFlow to the database

```
sform cluster -sf <SwarmFlow ID>
```
or

```
sform cluster -sf <SwarmFlow ID> -a <clustering algorithm rac/wpa> -cc <cluster count>
```

* Reset and re-initialize the SwarmForm database

```
sform reset
```

**Built With**

* [Python](https://www.python.org/) 
* [FireWorks](https://github.com/materialsproject/fireworks)

**Authors**

* **Kalana Dananjaya** - https://github.com/KalanaDananjaya
* **Ayesh Weerasinghe** - https://github.com/AyeshW
* **Randika Jayasekara** - https://github.com/rpjayasekara

**Publication**

A. Weerasinghe, K. Wijethunga, R. Jayasekara, I. Perera and A.
Wickramarachchi, "SwarmForm: A Distributed Workflow Management System with Task Clustering",
in 20th International Conference on Advances in ICT for Emerging Regions, Colombo, Sri Lanka, 2020.


Copyright 2021 © SwarmForm.