| Name | nsequence JSON |
| Version |
0.1.8
JSON |
| download |
| home_page | |
| Summary | A Library for Manipulating Progressions or Sequences |
| upload_time | 2024-02-17 22:14:11 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.6 |
| license | Copyright 2024, Isaac Houngue Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. 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While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. 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You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. 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| keywords |
progression
arithmetic progression
sequence
fonctional sequence
progression terms computation
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# NSequence
NSequence is a Python library designed for handling progressions or sequences. It allows users to define sequences through functional expressions, and offers capabilities for various computations.
## Key Features
- **Versatile Sequence Handling**: NSequence supports every type of sequence, as long as it can be expressed with a unary function.
- **Error Handling**: The library includes robust error handling for scenarios such as arity mismatches, unexpected positions or indices, inversion errors, and index not found situations.
- **Custom Indexing**: Users can define custom indexing functions to map sequence positions to unique indices, accommodating sequences with non-standard progressions or skipped elements. This feature enhances the library's versatility in sequence management.
- **Inverse Functionality**: For invertible sequences, NSequence facilitates finding the index of a given term and vice versa and provides various operations based on the inversion.
- **Nearest Term Search**: NSequence allows you to find the index of the nearest term to a given value in the sequence. It provides flexibility in handling tie-breakers and preferences.
- **Iterator Protocol Support**: NSequence supports the iterator protocol, allowing seamless iteration over sequence elements.
- **Sequence Protocol Support**: NSequence adheres to the sequence protocol, ensuring compatibility with other Python sequences and enabling familiar operations such as indexing and slicing.
## Installation
You can install NSequence using pip:
```bash
pip install nsequence
```
## Testing
You can install the dependencies to run the tests using pip:
```bash
pip install nsequence[dev]
```
## Getting Started
```python
from NSequence import NSequence
def my_function(x):
# Do something with x and return what you want
# ...
return x * 2
# Create your sequence
my_sequence = NSequence(func=my_function)
# Use the sequence functionalities
term_3 = my_sequence.nth_term(3)
sum_first_5_terms = my_sequence.sum_up_to_nth_term(5)
```
```python
# Create a linear sequence: f(x) = 2x + 3
linear_sequence = NSequence(func=lambda x: 2 * x + 3)
# Compute the 5th term
term_5 = linear_sequence.nth_term(5)
# Find the index of the term 13
index_of_13 = linear_sequence.index_of_term(13)
# Calculate the sum of the first 10 terms
sum_first_10_terms = linear_sequence.sum_up_to_nth_term(10)
```
```python
# Create a quadratic sequence: f(x) = x^2 + 3
quadratic_sequence = NSequence(func=lambda x: x ** 2 + 3)
# Get the nearest term to 20
nearest_term_to_20 = quadratic_sequence.nearest_term(20)
# Count the terms between 10 and 50
count_terms_between_10_and_50 = quadratic_sequence.count_terms_between_terms(10, 50)
```
```python
# Create an invertible sequence with inverse function
invertible_sequence = NSequence(func=lambda x: 2 * x, inverse_func=lambda y: y / 2)
# Find the index of the term 8
index_of_8 = invertible_sequence.index_of_term(8)
# Compute the terms between indices 5 and 10
terms_between_5_and_10 = invertible_sequence.terms_between_indices(5, 10)
```
## Real-world Usage
Imagine you're developing a complex event reminder system, where specific data _could_ be
attached to each reminder. You don't want to save in db, reminders to which the user
hasn't attached any specific data (you're seeing it as resource waste). But, for forecasting and
planning purposes, you want to be able to retrieve
for a given event recall data (or metadata inferred from the related event) for a
given period in the past (or future).
The set of reminders can be conceptualized as a mathematical sequence, where each
term represents a distinct instance of the scheduled event reminder.
Consider an event requiring reminders every `F` hours starting from a date `D`.
We can establish a direct mathematical relationship between
each reminder instance and its timing. And we can then define the reminder sequence
using the formular `R(n) = D + F*(n-1)` or `R(n) = (D-F) + F*n`, where `R(n)` represents the `n-th` reminder
date.
NSequence can be utilized to enhance your code's capabilities in solving the
previous problem by leveraging the available methods.
```python
from datetime import datetime, timedelta
from nsequence import NSequence
# Define start date and frequency in hours
start_date = datetime(2024, 1, 1)
frequency_hours = timedelta(hours=2)
# Define the reminder function using the R(n) formula
def reminder_func(n):
# R(n) = start_date + frequency_hours * (n-1)
return start_date + frequency_hours * (n-1)
def reminder_inverse_func(reminder_date):
return (reminder_date - start_date + frequency_hours) / frequency_hours
# Initialize NSequence with the reminder function
reminder_sequence = NSequence(
func=reminder_func,
# Set initial_index to 1
initial_index=1,
inverse_func=reminder_inverse_func
)
# Example: Get the 5th reminder date
fifth_reminder_date = reminder_sequence.nth_term(5)
print(f"The 5th reminder is scheduled for: {fifth_reminder_date}")
# Example: Get the reminders scheduled between two different dates
date1 = datetime(2024, 1, 1)
date2 = datetime(2024, 2, 4)
scheduled_reminders_between_dates = reminder_sequence.terms_between_terms(date1, date2)
print(f"The scheduled reminder between {date1} and {date2} are: {scheduled_reminders_between_dates}")
# See bellow for more methods available
```
- _NSequence has custom indexing support to handle more complex sequence definition._
- _Inheritance can be used to override the default methods if the default implementation does not suit your needs
especially in the cases where the return type of the sequence's function is not float._
## Key Methods
---
### Constructor .i.e `__init__`
Initializes a new sequence instance.
#### Parameters
- `func`: The primary function defining the sequence. This function must accept an integer position and return the corresponding sequence term.
- `inverse_func`: An optional inverse function for `func`, allowing for the computation of positions or indices based on sequence term values.
- `indexing_func`: An optional function that maps sequence positions to custom indices, enabling non-standard indexing schemes.
- `indexing_inverse_func`: The inverse of `indexing_func`, allowing for the determination of sequence positions from indices.
- `initial_index`: The starting index for the sequence, defaults to 0. This parameter is ignored if `indexing_func` is provided, as the initial index will then be derived from the indexing function.
- `position_limit` An optional limit to the number of positions available in the sequence .i.e the length of the sequence. Defaults to 1,000,000.
#### Raises
- `ArityMismatchError`: Raised if the provided function does not accept exactly one argument.
- `TypeError`: Raised if the provided argument is not a callable function.
### `nth_term`
Computes the sequence term at the given position.
#### Parameters
- `position`: Position in the sequence to calculate the term for.
### `position_of_index`
Determines the sequence position of a given index, useful when custom indexing is used.
#### Parameters
- `index`: The index for which to find the corresponding sequence position.
#### Raises
- `IndexNotFoundError`: Raised if the user provides custom indexing function and the index is not found sequence's `position_limit`.
### `nearest_entry`
Finds the nearest sequence entry (both the index and the term) to a given term.
#### Parameters
- `term_neighbor`: The term to find the nearest sequence entry for.
- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.
- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).
- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).
- `prefer_left_term`: Preference for the left term in case of equidistant terms.
#### Raises
- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.
### `nearest_term_index`
Finds the index of the nearest term to a given value in the sequence.
#### Parameters
- `term_neighbor`: The value to find the nearest sequence term to.
- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.
- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).
- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).
- `prefer_left_term`: Preference for the left term in case of equidistant terms.
#### Raises
- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.
### `nearest_term`
Retrieves the term in the sequence that is nearest to a specified value.
#### Parameters
- `term_neighbor`: The value to find the nearest sequence term for.
- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.
- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).
- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).
- `prefer_left_term`: Preference for the left term in case of equidistant terms.
#### Raises
- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.
- `InversionError`: Raised if `inversion_technic` is set to True and the sequence does not have `inverse_func`.
### `count_terms_between_terms_neighbors`
Counts the number of terms located between the nearest terms to two specified values. This method is particularly useful for sequences where each term
has a unique and identifiable neighbor, allowing for the counting of terms that lie directly
between two specific values.
#### Parameters
- `term_neighbor1`: The first value. This method finds the nearest term to this value
that does not prefer the left term, effectively preferring the right or equal term.
- `term_neighbor2`: The second value. The value of the second neighbor. Unlike for `term_neighbor1`, this method finds the
nearest term to this value that prefers the left term, if such a term exists.
### `terms_between_terms`
Computes a list of sequence terms located between two given terms, inclusive.
#### Parameters
- `term1`: The first term.
- `term2`: The second term.
#### Raises
- `InversionError`: Raised if `inverse_func` is not defined.
- `ValueError`: Raised if calculated indices are not valid or if `term1_index` or
`term2_index` are not integers.
### `sum_up_to_nth_term`
Calculates the sum of the sequence up to the nth term.
#### Parameters
- `n`: The position up to which the sum is to be calculated. Must be a positive integer.
### `index_of_term`
Returns the sum of the sequence up to the nth term.
#### Parameters
- `term`: The sequence term to find the index for.
- `inversion_technic`: If True and no inverse function is provided, uses a brute-force search to find the index. Defaults to True.
- `exact_exception`: If True, raises an exception if the term does not exactly match any sequence term. Defaults to True.
#### Raises
- `InversionError`: Raised if `inversion_technic` is True and no inverse function is provided.
- `ValueError`: Raised if `exact_exception` is True and the term is not found in the sequence.
### `count_terms_between_indices`
Counts the number of terms between two indices in the sequence.
#### Parameters
- `index1`: The starting index.
- `index2`: The ending index.
### `count_terms_between_terms`
Counts the number of terms between two given terms in the sequence. It uses
the sequence's inverse function.
This method is meaningful for sequences where a bijective (one-to-one and
onto) relationship exists between terms and their indices.
#### Parameters
- `term1`: The first term in the sequence.
- `term2`: The second term in the sequence.
#### Raises
- `InversionError`: Raised if an inverse function has not been defined or is not
applicable, indicating that term indices cannot be accurately determined.
## Properties
### `initial_index`
The initial index provided while creating the sequence.
### `initial_term`
The initial term of the sequence.
### `position_limit`
The actual length of the sequence.
## More
The support for Iterator and Sequence Protocol allows you to do things like this:
```python
my_sequence = NSequence(func=lambda x: x**3 + 4, position_limit=20)
# Print each element/term of the sequence
for term in my_sequence:
print(term)
# Slice to get a range of terms
print(my_sequence[start:end:step])
```
Read about Iterator protocol [here](https://docs.python.org/3/c-api/iter.html) and Sequence protocol [here](https://docs.python.org/3/c-api/sequence.html).
---
## Authors
- **Isaac Houngue** [<hjisaac.h at gmail>](mailto:hjisaac.h@gmail.com)
Feel free to contribute, report issues, or suggest enhancements. Did you know that sequences are everywhere 🤔? Happy sequencing! 📈
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"description": "# NSequence\n\nNSequence is a Python library designed for handling progressions or sequences. It allows users to define sequences through functional expressions, and offers capabilities for various computations.\n\n\n## Key Features\n\n- **Versatile Sequence Handling**: NSequence supports every type of sequence, as long as it can be expressed with a unary function.\n\n- **Error Handling**: The library includes robust error handling for scenarios such as arity mismatches, unexpected positions or indices, inversion errors, and index not found situations.\n\n- **Custom Indexing**: Users can define custom indexing functions to map sequence positions to unique indices, accommodating sequences with non-standard progressions or skipped elements. This feature enhances the library's versatility in sequence management.\n\n- **Inverse Functionality**: For invertible sequences, NSequence facilitates finding the index of a given term and vice versa and provides various operations based on the inversion. \n\n- **Nearest Term Search**: NSequence allows you to find the index of the nearest term to a given value in the sequence. It provides flexibility in handling tie-breakers and preferences.\n\n- **Iterator Protocol Support**: NSequence supports the iterator protocol, allowing seamless iteration over sequence elements.\n\n- **Sequence Protocol Support**: NSequence adheres to the sequence protocol, ensuring compatibility with other Python sequences and enabling familiar operations such as indexing and slicing.\n\n## Installation\n\nYou can install NSequence using pip:\n\n```bash\npip install nsequence\n```\n\n## Testing\n\nYou can install the dependencies to run the tests using pip:\n\n```bash\npip install nsequence[dev]\n```\n\n## Getting Started\n\n```python\nfrom NSequence import NSequence\n\ndef my_function(x):\n # Do something with x and return what you want\n # ...\n return x * 2\n\n# Create your sequence\nmy_sequence = NSequence(func=my_function)\n\n# Use the sequence functionalities\nterm_3 = my_sequence.nth_term(3)\nsum_first_5_terms = my_sequence.sum_up_to_nth_term(5)\n```\n\n```python\n# Create a linear sequence: f(x) = 2x + 3\nlinear_sequence = NSequence(func=lambda x: 2 * x + 3)\n\n# Compute the 5th term\nterm_5 = linear_sequence.nth_term(5)\n\n# Find the index of the term 13\nindex_of_13 = linear_sequence.index_of_term(13)\n\n# Calculate the sum of the first 10 terms\nsum_first_10_terms = linear_sequence.sum_up_to_nth_term(10)\n```\n\n```python\n# Create a quadratic sequence: f(x) = x^2 + 3\nquadratic_sequence = NSequence(func=lambda x: x ** 2 + 3)\n\n# Get the nearest term to 20\nnearest_term_to_20 = quadratic_sequence.nearest_term(20)\n\n# Count the terms between 10 and 50\ncount_terms_between_10_and_50 = quadratic_sequence.count_terms_between_terms(10, 50)\n```\n\n```python\n# Create an invertible sequence with inverse function\ninvertible_sequence = NSequence(func=lambda x: 2 * x, inverse_func=lambda y: y / 2)\n\n# Find the index of the term 8\nindex_of_8 = invertible_sequence.index_of_term(8)\n\n# Compute the terms between indices 5 and 10\nterms_between_5_and_10 = invertible_sequence.terms_between_indices(5, 10)\n```\n\n## Real-world Usage\n\nImagine you're developing a complex event reminder system, where specific data _could_ be \nattached to each reminder. You don't want to save in db, reminders to which the user \nhasn't attached any specific data (you're seeing it as resource waste). But, for forecasting and\nplanning purposes, you want to be able to retrieve \nfor a given event recall data (or metadata inferred from the related event) for a \ngiven period in the past (or future).\n\nThe set of reminders can be conceptualized as a mathematical sequence, where each \nterm represents a distinct instance of the scheduled event reminder.\n\nConsider an event requiring reminders every `F` hours starting from a date `D`. \nWe can establish a direct mathematical relationship between \neach reminder instance and its timing. And we can then define the reminder sequence \nusing the formular `R(n) = D + F*(n-1)` or `R(n) = (D-F) + F*n`, where `R(n)` represents the `n-th` reminder \ndate.\n\nNSequence can be utilized to enhance your code's capabilities in solving the\nprevious problem by leveraging the available methods.\n\n```python\n\nfrom datetime import datetime, timedelta\nfrom nsequence import NSequence\n\n# Define start date and frequency in hours\nstart_date = datetime(2024, 1, 1)\nfrequency_hours = timedelta(hours=2)\n\n# Define the reminder function using the R(n) formula\ndef reminder_func(n):\n # R(n) = start_date + frequency_hours * (n-1)\n return start_date + frequency_hours * (n-1)\n\ndef reminder_inverse_func(reminder_date):\n return (reminder_date - start_date + frequency_hours) / frequency_hours\n\n# Initialize NSequence with the reminder function\nreminder_sequence = NSequence(\n func=reminder_func, \n # Set initial_index to 1\n initial_index=1, \n inverse_func=reminder_inverse_func\n)\n\n# Example: Get the 5th reminder date\nfifth_reminder_date = reminder_sequence.nth_term(5)\nprint(f\"The 5th reminder is scheduled for: {fifth_reminder_date}\")\n\n# Example: Get the reminders scheduled between two different dates\ndate1 = datetime(2024, 1, 1)\ndate2 = datetime(2024, 2, 4)\n\nscheduled_reminders_between_dates = reminder_sequence.terms_between_terms(date1, date2)\nprint(f\"The scheduled reminder between {date1} and {date2} are: {scheduled_reminders_between_dates}\")\n\n# See bellow for more methods available\n```\n\n- _NSequence has custom indexing support to handle more complex sequence definition._\n\n- _Inheritance can be used to override the default methods if the default implementation does not suit your needs\nespecially in the cases where the return type of the sequence's function is not float._\n\n## Key Methods\n\n\n\n---\n### Constructor .i.e `__init__`\n\nInitializes a new sequence instance.\n\n#### Parameters\n\n- `func`: The primary function defining the sequence. This function must accept an integer position and return the corresponding sequence term.\n\n- `inverse_func`: An optional inverse function for `func`, allowing for the computation of positions or indices based on sequence term values.\n\n- `indexing_func`: An optional function that maps sequence positions to custom indices, enabling non-standard indexing schemes.\n\n- `indexing_inverse_func`: The inverse of `indexing_func`, allowing for the determination of sequence positions from indices.\n\n- `initial_index`: The starting index for the sequence, defaults to 0. This parameter is ignored if `indexing_func` is provided, as the initial index will then be derived from the indexing function.\n\n- `position_limit` An optional limit to the number of positions available in the sequence .i.e the length of the sequence. Defaults to 1,000,000.\n\n\n\n#### Raises\n- `ArityMismatchError`: Raised if the provided function does not accept exactly one argument.\n- `TypeError`: Raised if the provided argument is not a callable function.\n\n### `nth_term`\nComputes the sequence term at the given position.\n\n#### Parameters\n- `position`: Position in the sequence to calculate the term for.\n\n\n### `position_of_index`\nDetermines the sequence position of a given index, useful when custom indexing is used.\n\n#### Parameters\n- `index`: The index for which to find the corresponding sequence position.\n\n#### Raises\n- `IndexNotFoundError`: Raised if the user provides custom indexing function and the index is not found sequence's `position_limit`. \n\n### `nearest_entry`\nFinds the nearest sequence entry (both the index and the term) to a given term.\n\n#### Parameters\n- `term_neighbor`: The term to find the nearest sequence entry for.\n- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.\n- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).\n- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).\n- `prefer_left_term`: Preference for the left term in case of equidistant terms.\n\n#### Raises\n- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.\n\n### `nearest_term_index`\nFinds the index of the nearest term to a given value in the sequence.\n\n#### Parameters\n- `term_neighbor`: The value to find the nearest sequence term to.\n- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.\n- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).\n- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).\n- `prefer_left_term`: Preference for the left term in case of equidistant terms.\n\n#### Raises\n- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.\n\n### `nearest_term`\nRetrieves the term in the sequence that is nearest to a specified value.\n\n#### Parameters\n- `term_neighbor`: The value to find the nearest sequence term for.\n- `inversion_technic`: Whether to use the inversion technique for finding the nearest term.\n- `starting_position`: The starting position for the iterative search (ignored if `inversion_technic` is True).\n- `iter_limit`: The maximum number of iterations for the search (ignored if `inversion_technic` is True).\n- `prefer_left_term`: Preference for the left term in case of equidistant terms.\n\n#### Raises\n- `NotImplementedError`: Raised if the calculation fails, due to `TypeError`, `ValueError` or `ArithmeticError`.\n- `InversionError`: Raised if `inversion_technic` is set to True and the sequence does not have `inverse_func`.\n\n### `count_terms_between_terms_neighbors`\nCounts the number of terms located between the nearest terms to two specified values. This method is particularly useful for sequences where each term\nhas a unique and identifiable neighbor, allowing for the counting of terms that lie directly\nbetween two specific values.\n\n#### Parameters\n- `term_neighbor1`: The first value. This method finds the nearest term to this value\n that does not prefer the left term, effectively preferring the right or equal term.\n- `term_neighbor2`: The second value. The value of the second neighbor. Unlike for `term_neighbor1`, this method finds the\n nearest term to this value that prefers the left term, if such a term exists.\n\n### `terms_between_terms`\nComputes a list of sequence terms located between two given terms, inclusive.\n\n#### Parameters\n- `term1`: The first term.\n- `term2`: The second term.\n\n#### Raises\n- `InversionError`: Raised if `inverse_func` is not defined.\n- `ValueError`: Raised if calculated indices are not valid or if `term1_index` or\n`term2_index` are not integers.\n\n### `sum_up_to_nth_term`\nCalculates the sum of the sequence up to the nth term. \n\n#### Parameters\n- `n`: The position up to which the sum is to be calculated. Must be a positive integer.\n\n### `index_of_term`\nReturns the sum of the sequence up to the nth term.\n\n#### Parameters\n- `term`: The sequence term to find the index for.\n- `inversion_technic`: If True and no inverse function is provided, uses a brute-force search to find the index. Defaults to True.\n- `exact_exception`: If True, raises an exception if the term does not exactly match any sequence term. Defaults to True.\n\n#### Raises\n- `InversionError`: Raised if `inversion_technic` is True and no inverse function is provided.\n- `ValueError`: Raised if `exact_exception` is True and the term is not found in the sequence.\n\n### `count_terms_between_indices`\nCounts the number of terms between two indices in the sequence.\n\n#### Parameters\n- `index1`: The starting index.\n- `index2`: The ending index.\n\n\n### `count_terms_between_terms`\nCounts the number of terms between two given terms in the sequence. It uses \nthe sequence's inverse function.\n\nThis method is meaningful for sequences where a bijective (one-to-one and\nonto) relationship exists between terms and their indices.\n\n#### Parameters\n- `term1`: The first term in the sequence.\n- `term2`: The second term in the sequence.\n\n#### Raises\n- `InversionError`: Raised if an inverse function has not been defined or is not\napplicable, indicating that term indices cannot be accurately determined.\n\n## Properties\n\n### `initial_index`\nThe initial index provided while creating the sequence.\n\n### `initial_term`\nThe initial term of the sequence.\n\n### `position_limit`\nThe actual length of the sequence.\n\n## More\nThe support for Iterator and Sequence Protocol allows you to do things like this:\n\n```python\nmy_sequence = NSequence(func=lambda x: x**3 + 4, position_limit=20)\n\n# Print each element/term of the sequence\nfor term in my_sequence:\n print(term)\n\n# Slice to get a range of terms\nprint(my_sequence[start:end:step])\n\n```\nRead about Iterator protocol [here](https://docs.python.org/3/c-api/iter.html) and Sequence protocol [here](https://docs.python.org/3/c-api/sequence.html).\n\n---\n\n## Authors\n\n- **Isaac Houngue** [<hjisaac.h at gmail>](mailto:hjisaac.h@gmail.com)\n\nFeel free to contribute, report issues, or suggest enhancements. Did you know that sequences are everywhere \ud83e\udd14? Happy sequencing! \ud83d\udcc8\n",
"bugtrack_url": null,
"license": "Copyright 2024, Isaac Houngue Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. 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If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. 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You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. 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The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. 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While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONSLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ``` Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets \"[]\" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same \"printed page\" as the copyright notice for easier identification within third-party archives. ``` ",
"summary": "A Library for Manipulating Progressions or Sequences",
"version": "0.1.8",
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"changelog": "https://github.com/wehappit/nsequence/blob/main/CHANGELOG.md",
"documentation": "https://github.com/wehappit/nsequence",
"homepage": "https://github.com/wehappit/nsequence",
"repository": "https://github.com/wehappit/nsequence"
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