# bibliometrics
| __Packages and Releases__ | [](https://pypi.org/project/bibliometrics/) [](https://github.com/cicirello/bibliometrics/releases) |
| :--- | :--- |
| __PyPI Downloads__ | [](https://pepy.tech/project/bibliometrics) [](https://pepy.tech/project/bibliometrics) [](https://pepy.tech/project/bibliometrics) |
| __Build Status__ | [](https://github.com/cicirello/bibliometrics/actions/workflows/build.yml) [](https://github.com/cicirello/bibliometrics/actions/workflows/codeql-analysis.yml) |
| __Security__ | [](https://snyk.io/vuln/pip%3Abibliometrics) |
| __Other Info__ |  [](https://github.com/cicirello/bibliometrics/blob/main/LICENSE) [](https://github.com/cicirello/bibliometrics) |
| __Support__ | [](https://github.com/sponsors/cicirello) [](https://liberapay.com/cicirello) [](https://ko-fi.com/cicirello) |
This command line utility does the following:
* retrieves the first page of your Google Scholar profile;
* parses from that page your total citations, your five-year citation count, your h-index, your i10-index, and the number of citations of your most-cited paper;
* computes your o-index ([https://arxiv.org/abs/1511.01545](https://arxiv.org/abs/1511.01545));
* computes your g-index provided if it is less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));
* computes your i100-index, i1000-index, and i10000-index ([doi:10.1007/s11192-020-03831-9](https://doi.org/10.1007/s11192-020-03831-9)), hiding any that are 0, and provided they are less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));
* computes your w-index ([doi:10.1002/asi.21276](https://doi.org/10.1002/asi.21276)), hiding if equal to 0, and provided it is less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));
* computes your e-index ([doi:10.1371/journal.pone.0005429](https://doi.org/10.1371/journal.pone.0005429)), your r-index ([doi:10.1007/s11434-007-0145-9](https://doi.org/10.1007/s11434-007-0145-9)), and your a-index provided that your h-index is at most 100 ([reason for limitation later](#respect-google-scholars-robotstxt));
* computes your h-median provided that your h-index is less than 200 ([reason for limitation later](#respect-google-scholars-robotstxt));
* computes your m-quotient, if you configure the year of your first publication in the configuration file;
* generates a JSON file summarizing these bibliometrics;
* generates one or more SVG images summarizing these bibliometrics; and
* includes all bibliometrics that are non-zero by default, but enables user-configurable list of bibliometrics.
The intention of this utility is as a tool for a researcher to generate an SVG of their own
bibliometrics only. For example, I am using it to generate and update such an SVG for my own
profile twice monthly. It is not intended for analyzing multiple researchers' bibliometrics,
and requests for such functionality will be rejected (there are other tools for that).
__Blog Post:__ [Your Citation Metrics in an SVG for Your Website](https://dev.to/cicirello/your-citation-metrics-in-an-svg-for-your-website-17bp) (Posted on DEV.to on July 22, 2022)
## Table of Contents
This README is organized as follows:
* [Supported Bibliometrics](#supported-bibliometrics): list of the bibliometrics with
brief descriptions of what they are.
* [Samples](#samples): provides examples of the output of this utility.
* [Configuration](#configuration): explains how to configure the utility, such as colors for the SVG,
file locations, etc.
* [Configuring the Scholar ID](#configuring-the-scholar-id): explains the two ways of providing your
Google Scholar ID to the utility.
* [Usage](#usage): how to install and run.
* [Respect Google Scholar's robots.txt](#respect-google-scholars-robotstxt): explains
the relevant portions of Google Scholar's robots.txt as it relates to this, or any
tool, designed to gather information from Scholar. Note that most other tools that
provide more functionality (e.g., all of the ones I looked at before implementing
this) do not respect that robots.txt. If you wish to submit an issue or pull request
requesting additional functionality, please know that any such request must be possible
to implement without violating Scholar's robots.txt. Otherwise, the issue or pull request
will be closed.
* [Support the Project](#support-the-project): different ways that you can support the project.
* [Contribute](#contribute): contribution guidelines.
* [License](#license).
## Supported Bibliometrics
The bibliometrics utility computes the following bibliometrics:
* Total citations: total number of citations to the researcher's publications.
* Five-year citations: total citations within past 5 years.
* Most-cited paper: number of citations to the researcher's most-cited paper.
* [h-index](https://doi.org/10.1073/pnas.0507655102): the maximum h such that
the researcher's h most-cited papers have been cited at least h times each.
* m-quotient: h-index / n, the number of years since first publication, which
was introduced in the same article as the h-index itself as a way of adjusting
for length of publication history.
* [g-index](https://doi.org/10.1007/s11192-006-0144-7): the maximum g such
that the researcher's g most-cited papers have been cited an average of g
times each.
* [i10-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers
cited at least 10 times each.
* [i100-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers
cited at least 100 times each.
* [i1000-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers
cited at least 1000 times each.
* [i10000-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers
cited at least 10000 times each.
* [w-index](https://doi.org/10.1002/asi.21276): number of papers cited at least 10w times each.
* [o-index](https://arxiv.org/abs/1511.01545): the geometric mean of the researcher's
h-index and number of citations to the most-cited paper.
* Various bibliometrics intended to complement the h-index, providing additional
information about the researcher's h-core, where the h-core refers to the
h most-cited papers. These complementary bibliometrics include the following:
* h-median: the median citations of the papers in the researcher's h-core.
* [e-index](https://doi.org/10.1371/journal.pone.0005429): the square root of
the excess citations to the papers in the h-core, where excess citations is
defined as the total citations to the papers in the h-core minus $h^2$.
* [r-index](https://doi.org/10.1007/s11434-007-0145-9): the square root of the
total citations to the papers in the researcher's h-core.
* a-index: the average number of citations to the papers in the researcher's h-core.
## Samples
Here are a couple sample SVGs.
Here is a sample of the JSON summary also generated by the utility:
```JSON
{
"a-index": 71.56,
"e-index": 34.12,
"five-year-cites": 364,
"g-index": 44,
"h-index": 25,
"h-median": 48,
"i10-index": 33,
"i100-index": 3,
"m-quotient": 1.0,
"most-cited": 228,
"o-index": 75,
"r-index": 42.3,
"total-cites": 2052,
"w-index": 8
}
```
The keys in this JSON are all lowercased, and correspond to the keys expected if you
customize the order in your configuration file. However, in your configuration file
they are case-insensitive. See the next section for how to configure.
The above sample is also found in this
repository: [bibliometrics.json](https://github.com/cicirello/bibliometrics/blob/main/bibliometrics.json),
and the sample SVGs are found in the [images](https://github.com/cicirello/bibliometrics/blob/main/images) directory.
## Configuration
The utility looks for a configuration file `.bibliometrics.config.json` in your current
working directory (please note the `.` at the start of the filename). A sample is found
at the root of this repository: [.bibliometrics.config.json](https://github.com/cicirello/bibliometrics/blob/main/.bibliometrics.config.json).
To generate the JSON summary of your bibliometrics, specify the filename (optionally with path)
via the `"jsonOutputFile"` field. If this field is not present, then no JSON file will be generated.
To compute the m-quotient, you must provide the year of your first publication in the `"firstPubYear"`
field. The bibliometrics utility does not attempt to scrape this from your Scholar profile.
To change the order that the bibliometrics appear in the SVG, or to explicitly exclude one or more
bibliometrics, you can use the `"include"` field. This field is an array of keys associated with the
various bibliometrics. If this field is not present, then the following default order is
used: `[ "total-cites", "five-year-cites", "most-cited", "h-index", "g-index", "i10-index", "i100-index", "i1000-index", "i10000-index", "w-index", "o-index", "h-median", "m-quotient", "e-index", "r-index", "a-index" ]`. There is no
reason to use this field if the only thing you want to do is to exclude bibliometrics that have the
value 0. Such bibliometrics will be excluded by default. The list of keys for the bibliometrics to
include is case-insensitive.
The `"svgConfig"` field is an array of JSON objects, such that each object configures one SVG. Each
of the JSON objects in this array includes the following fields:
* `"filename"` is the filename (optionally with path) to the target SVG file.
* `"background"` is the background color.
* `"border"` is the border color.
* `"title"` is the title color.
* `"text"` is the color of the rest of the text.
* `"include"` is similar to the top-level field of the same name, but applies only to one SVG, whereas the top-level field applies to all. If both the top-level `"include"` field and the more specific field by the same name are used, then the top-level `"include"` overrides the default, and the individual SVG's `"include"` in turn overrides the top-level `"include"`.
The colors can be defined in any format that is valid within an SVG. For example, you can specify
RGB, two hex digits for each color channel, with `#010409`; or RGB with one hex digit for each color
channel, `#123`. You can also use SVG named colors, such as `white`, as well as RGBA such as
`rgba(56,139,253,0.4)`. If it is valid as a color in SVG, then it should work. The utility simply inserts
it for the relevant color within the SVG without validation.
Here is a sample `.bibliometrics.config.json` (using the default order of the bibliometrics,
and providing the year of first publication):
```JSON
{
"jsonOutputFile": "bibliometrics.json",
"firstPubYear": 1999,
"svgConfig": [
{
"background": "#010409",
"border": "rgba(56,139,253,0.4)",
"filename": "images/bibliometrics2.svg",
"text": "#c9d1d9",
"title": "#58a6ff"
},
{
"background": "#f6f8fa",
"border": "rgba(84,174,255,0.4)",
"filename": "images/bibliometrics.svg",
"text": "#24292f",
"title": "#0969da"
}
]
}
```
Here is another sample that generates three SVGs, overriding the default order at the top-level
to exclude the i10-index (and related indexes), and then overriding it again for one of the
three SVGs to additionally exclude the g-index, w-index, o-index, h-median, e-index, r-index,
and a-index. This example also does not specify "firstPubYear", which means that the m-quotient
won't be calculated:
```JSON
{
"jsonOutputFile": "bibliometrics.json",
"include": [
"total-cites",
"five-year-cites",
"most-cited",
"h-index",
"g-index",
"w-index",
"o-index",
"h-median",
"e-index",
"r-index",
"a-index"
],
"svgConfig": [
{
"background": "#010409",
"border": "rgba(56,139,253,0.4)",
"filename": "images/bibliometrics3.svg",
"text": "#c9d1d9",
"title": "#58a6ff"
},
{
"background": "#010409",
"border": "rgba(56,139,253,0.4)",
"filename": "images/bibliometrics2.svg",
"text": "#c9d1d9",
"title": "#58a6ff",
"include": ["total-cites", "five-year-cites", "most-cited", "h-index"]
},
{
"background": "#f6f8fa",
"border": "rgba(84,174,255,0.4)",
"filename": "images/bibliometrics.svg",
"text": "#24292f",
"title": "#0969da"
}
]
}
```
## Configuring the Scholar ID
There are two ways to provide your Google Scholar ID to the utility:
* in the configuration file (see above section) via a field `"scholarID"` (not shown in the example in the
repository); or
* via an environment variable `SCHOLAR_ID`.
## Usage
### Installing
To install from PyPi (Unix and MacOS):
```Shell
python3 -m pip install bibliometrics
```
To install from PyPI (Windows):
```Shell
py -m pip install bibliometrics
```
To upgrade to latest version from PyPi (Unix and MacOS):
```Shell
python3 -m pip install --upgrade bibliometrics
```
To upgrade to latest version from PyPI (Windows):
```Shell
py -m pip install --upgrade bibliometrics
```
### Running
To use this utility, first ensure that you configure it as specified above. Then execute the following (Unix and MacOS):
```Shell
python3 -m bibliometrics
```
Or on Windows:
```Shell
py -m bibliometrics
```
## Respect Google Scholar's robots.txt
If you use this utility, please respect Google Scholar's robots.txt. The reason that the
g-index (as well as i100-index, i1000-index, i10000-index, w-index) is only computed by this utility
if it is less than 100 derives from Scholar's robots.txt. Likewise, the reason that the
e-index, r-index, and a-index are only computed if your h-index is at most 100 relates to
this as well. In the case of the h-median, we can compute it as long as your h-index is less
than 200. Here is the relevant excerpt:
```robots.txt
Allow: /citations?user=
Disallow: /citations?*cstart=
```
The first line above allows getting a user's profile page. But the second line
above disallows querying a specific starting reference. This means if you are respecting
Google Scholar's robots.txt then you are limited to the first page of the profile, which
can include up to 100 publications. Therefore, we can compute g-index as long as it is not
greater than 100. However, if we compute 100, we cannot be certain if it is correct or if
it is actually higher, so this utility excludes a g-index of 100 as well. The same is true
for i100-index, i1000-index, and i10000-index. There is a similar issue for e-index, r-index,
and a-index. In those cases, to compute the relevant bibliometric, we need the number of
citations of your h most-cited articles. Therefore, we only compute these if your h-index is
at most 100.
## Support the Project
You can support the project in a number of ways:
* __Starring__: If you find this utility
useful, consider starring the GitHub repository.
* __Sharing with Others__: Consider sharing it with others who
you feel might find it useful.
* __Reporting Issues__: If you find a bug or have a suggestion for
a new feature, please report it via
the [Issue tracker](https://github.com/cicirello/bibliometrics/issues). Please
note, however, that feature requests will be evaluated for whether they
can be implemented while respecting Google Scholar's robots.txt, which means
limited to what can be computed from the first page of your Google Scholar
profile.
* __Contributing Code__: If there is an open issue that you think
you can help with, submit a pull request.
* __Sponsoring__: You can also consider sponsoring via one of the following:
| [](https://github.com/sponsors/cicirello) | [](https://liberapay.com/cicirello) |
| :---: | :---: |
| [](https://ko-fi.com/cicirello) | |
## Contribute
If you would like to contribute start by reading
the [contribution guidelines](https://github.com/cicirello/.github/blob/main/CONTRIBUTING.md).
This project has adopted
the [Contributor Covenant Code of Conduct](https://github.com/cicirello/.github/blob/main/CODE_OF_CONDUCT.md).
The intention of this utility is as a tool for a researcher to generate an SVG of their own
bibliometrics, so issues requesting, or pull requests implementing, support for multiple scholar
profiles will be rejected.
## License
The code in this repository is released under
the [MIT License](https://github.com/cicirello/bibliometrics/blob/main/LICENSE).
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"description": "# bibliometrics\n\n| __Packages and Releases__ | [](https://pypi.org/project/bibliometrics/) [](https://github.com/cicirello/bibliometrics/releases) |\n| :--- | :--- |\n| __PyPI Downloads__ | [](https://pepy.tech/project/bibliometrics) [](https://pepy.tech/project/bibliometrics) [](https://pepy.tech/project/bibliometrics) |\n| __Build Status__ | [](https://github.com/cicirello/bibliometrics/actions/workflows/build.yml) [](https://github.com/cicirello/bibliometrics/actions/workflows/codeql-analysis.yml) |\n| __Security__ | [](https://snyk.io/vuln/pip%3Abibliometrics) |\n| __Other Info__ |  [](https://github.com/cicirello/bibliometrics/blob/main/LICENSE) [](https://github.com/cicirello/bibliometrics) |\n| __Support__ | [](https://github.com/sponsors/cicirello) [](https://liberapay.com/cicirello) [](https://ko-fi.com/cicirello) |\n\nThis command line utility does the following:\n* retrieves the first page of your Google Scholar profile;\n* parses from that page your total citations, your five-year citation count, your h-index, your i10-index, and the number of citations of your most-cited paper;\n* computes your o-index ([https://arxiv.org/abs/1511.01545](https://arxiv.org/abs/1511.01545));\n* computes your g-index provided if it is less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));\n* computes your i100-index, i1000-index, and i10000-index ([doi:10.1007/s11192-020-03831-9](https://doi.org/10.1007/s11192-020-03831-9)), hiding any that are 0, and provided they are less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));\n* computes your w-index ([doi:10.1002/asi.21276](https://doi.org/10.1002/asi.21276)), hiding if equal to 0, and provided it is less than 100 ([reason for limitation later](#respect-google-scholars-robotstxt));\n* computes your e-index ([doi:10.1371/journal.pone.0005429](https://doi.org/10.1371/journal.pone.0005429)), your r-index ([doi:10.1007/s11434-007-0145-9](https://doi.org/10.1007/s11434-007-0145-9)), and your a-index provided that your h-index is at most 100 ([reason for limitation later](#respect-google-scholars-robotstxt));\n* computes your h-median provided that your h-index is less than 200 ([reason for limitation later](#respect-google-scholars-robotstxt));\n* computes your m-quotient, if you configure the year of your first publication in the configuration file;\n* generates a JSON file summarizing these bibliometrics;\n* generates one or more SVG images summarizing these bibliometrics; and\n* includes all bibliometrics that are non-zero by default, but enables user-configurable list of bibliometrics.\n\nThe intention of this utility is as a tool for a researcher to generate an SVG of their own \nbibliometrics only. For example, I am using it to generate and update such an SVG for my own\nprofile twice monthly. It is not intended for analyzing multiple researchers' bibliometrics,\nand requests for such functionality will be rejected (there are other tools for that).\n\n__Blog Post:__ [Your Citation Metrics in an SVG for Your Website](https://dev.to/cicirello/your-citation-metrics-in-an-svg-for-your-website-17bp) (Posted on DEV.to on July 22, 2022) \n\n## Table of Contents\n\nThis README is organized as follows:\n* [Supported Bibliometrics](#supported-bibliometrics): list of the bibliometrics with\n brief descriptions of what they are.\n* [Samples](#samples): provides examples of the output of this utility.\n* [Configuration](#configuration): explains how to configure the utility, such as colors for the SVG,\n file locations, etc.\n* [Configuring the Scholar ID](#configuring-the-scholar-id): explains the two ways of providing your\n Google Scholar ID to the utility.\n* [Usage](#usage): how to install and run.\n* [Respect Google Scholar's robots.txt](#respect-google-scholars-robotstxt): explains \n the relevant portions of Google Scholar's robots.txt as it relates to this, or any \n tool, designed to gather information from Scholar. Note that most other tools that \n provide more functionality (e.g., all of the ones I looked at before implementing \n this) do not respect that robots.txt. If you wish to submit an issue or pull request \n requesting additional functionality, please know that any such request must be possible \n to implement without violating Scholar's robots.txt. Otherwise, the issue or pull request \n will be closed.\n* [Support the Project](#support-the-project): different ways that you can support the project.\n* [Contribute](#contribute): contribution guidelines.\n* [License](#license).\n\n## Supported Bibliometrics\n\nThe bibliometrics utility computes the following bibliometrics:\n* Total citations: total number of citations to the researcher's publications.\n* Five-year citations: total citations within past 5 years.\n* Most-cited paper: number of citations to the researcher's most-cited paper.\n* [h-index](https://doi.org/10.1073/pnas.0507655102): the maximum h such that\n the researcher's h most-cited papers have been cited at least h times each.\n* m-quotient: h-index / n, the number of years since first publication, which\n was introduced in the same article as the h-index itself as a way of adjusting\n for length of publication history.\n* [g-index](https://doi.org/10.1007/s11192-006-0144-7): the maximum g such \n that the researcher's g most-cited papers have been cited an average of g \n times each.\n* [i10-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers \n cited at least 10 times each.\n* [i100-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers \n cited at least 100 times each.\n* [i1000-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers \n cited at least 1000 times each.\n* [i10000-index](https://doi.org/10.1007/s11192-020-03831-9): number of papers \n cited at least 10000 times each.\n* [w-index](https://doi.org/10.1002/asi.21276): number of papers cited at least 10w times each.\n* [o-index](https://arxiv.org/abs/1511.01545): the geometric mean of the researcher's\n h-index and number of citations to the most-cited paper.\n* Various bibliometrics intended to complement the h-index, providing additional\n information about the researcher's h-core, where the h-core refers to the\n h most-cited papers. These complementary bibliometrics include the following:\n * h-median: the median citations of the papers in the researcher's h-core.\n * [e-index](https://doi.org/10.1371/journal.pone.0005429): the square root of \n the excess citations to the papers in the h-core, where excess citations is \n defined as the total citations to the papers in the h-core minus $h^2$. \n * [r-index](https://doi.org/10.1007/s11434-007-0145-9): the square root of the\n total citations to the papers in the researcher's h-core.\n * a-index: the average number of citations to the papers in the researcher's h-core.\n\n\n## Samples\n\nHere are a couple sample SVGs.\n\n\n\n\n\nHere is a sample of the JSON summary also generated by the utility:\n\n```JSON\n{\n \"a-index\": 71.56,\n \"e-index\": 34.12,\n \"five-year-cites\": 364,\n \"g-index\": 44,\n \"h-index\": 25,\n \"h-median\": 48,\n \"i10-index\": 33,\n \"i100-index\": 3,\n \"m-quotient\": 1.0,\n \"most-cited\": 228,\n \"o-index\": 75,\n \"r-index\": 42.3,\n \"total-cites\": 2052,\n \"w-index\": 8\n}\n```\n\nThe keys in this JSON are all lowercased, and correspond to the keys expected if you \ncustomize the order in your configuration file. However, in your configuration file\nthey are case-insensitive. See the next section for how to configure.\n\nThe above sample is also found in this \nrepository: [bibliometrics.json](https://github.com/cicirello/bibliometrics/blob/main/bibliometrics.json), \nand the sample SVGs are found in the [images](https://github.com/cicirello/bibliometrics/blob/main/images) directory.\n\n## Configuration\n\nThe utility looks for a configuration file `.bibliometrics.config.json` in your current \nworking directory (please note the `.` at the start of the filename). A sample is found\nat the root of this repository: [.bibliometrics.config.json](https://github.com/cicirello/bibliometrics/blob/main/.bibliometrics.config.json).\n\nTo generate the JSON summary of your bibliometrics, specify the filename (optionally with path)\nvia the `\"jsonOutputFile\"` field. If this field is not present, then no JSON file will be generated.\n\nTo compute the m-quotient, you must provide the year of your first publication in the `\"firstPubYear\"`\nfield. The bibliometrics utility does not attempt to scrape this from your Scholar profile.\n\nTo change the order that the bibliometrics appear in the SVG, or to explicitly exclude one or more\nbibliometrics, you can use the `\"include\"` field. This field is an array of keys associated with the\nvarious bibliometrics. If this field is not present, then the following default order is \nused: `[ \"total-cites\", \"five-year-cites\", \"most-cited\", \"h-index\", \"g-index\", \"i10-index\", \"i100-index\", \"i1000-index\", \"i10000-index\", \"w-index\", \"o-index\", \"h-median\", \"m-quotient\", \"e-index\", \"r-index\", \"a-index\" ]`. There is no\nreason to use this field if the only thing you want to do is to exclude bibliometrics that have the\nvalue 0. Such bibliometrics will be excluded by default. The list of keys for the bibliometrics to\ninclude is case-insensitive.\n\nThe `\"svgConfig\"` field is an array of JSON objects, such that each object configures one SVG. Each\nof the JSON objects in this array includes the following fields:\n* `\"filename\"` is the filename (optionally with path) to the target SVG file.\n* `\"background\"` is the background color.\n* `\"border\"` is the border color.\n* `\"title\"` is the title color.\n* `\"text\"` is the color of the rest of the text.\n* `\"include\"` is similar to the top-level field of the same name, but applies only to one SVG, whereas the top-level field applies to all. If both the top-level `\"include\"` field and the more specific field by the same name are used, then the top-level `\"include\"` overrides the default, and the individual SVG's `\"include\"` in turn overrides the top-level `\"include\"`.\n\nThe colors can be defined in any format that is valid within an SVG. For example, you can specify\nRGB, two hex digits for each color channel, with `#010409`; or RGB with one hex digit for each color \nchannel, `#123`. You can also use SVG named colors, such as `white`, as well as RGBA such as\n`rgba(56,139,253,0.4)`. If it is valid as a color in SVG, then it should work. The utility simply inserts\nit for the relevant color within the SVG without validation.\n\nHere is a sample `.bibliometrics.config.json` (using the default order of the bibliometrics,\nand providing the year of first publication):\n\n```JSON\n{\n \"jsonOutputFile\": \"bibliometrics.json\",\n \"firstPubYear\": 1999,\n \"svgConfig\": [\n {\n \"background\": \"#010409\",\n \"border\": \"rgba(56,139,253,0.4)\",\n \"filename\": \"images/bibliometrics2.svg\",\n \"text\": \"#c9d1d9\",\n \"title\": \"#58a6ff\"\n },\n {\n \"background\": \"#f6f8fa\",\n \"border\": \"rgba(84,174,255,0.4)\",\n \"filename\": \"images/bibliometrics.svg\",\n \"text\": \"#24292f\",\n \"title\": \"#0969da\"\n }\n ]\n}\n```\n\nHere is another sample that generates three SVGs, overriding the default order at the top-level \nto exclude the i10-index (and related indexes), and then overriding it again for one of the \nthree SVGs to additionally exclude the g-index, w-index, o-index, h-median, e-index, r-index, \nand a-index. This example also does not specify \"firstPubYear\", which means that the m-quotient\nwon't be calculated:\n\n```JSON\n{\n \"jsonOutputFile\": \"bibliometrics.json\",\n \"include\": [\n \"total-cites\", \n \"five-year-cites\", \n \"most-cited\", \n \"h-index\", \n \"g-index\", \n \"w-index\",\n \"o-index\",\n \"h-median\",\n \"e-index\", \n \"r-index\", \n \"a-index\"\n ],\n \"svgConfig\": [\n {\n \"background\": \"#010409\",\n \"border\": \"rgba(56,139,253,0.4)\",\n \"filename\": \"images/bibliometrics3.svg\",\n \"text\": \"#c9d1d9\",\n \"title\": \"#58a6ff\"\n },\n {\n \"background\": \"#010409\",\n \"border\": \"rgba(56,139,253,0.4)\",\n \"filename\": \"images/bibliometrics2.svg\",\n \"text\": \"#c9d1d9\",\n \"title\": \"#58a6ff\",\n \"include\": [\"total-cites\", \"five-year-cites\", \"most-cited\", \"h-index\"]\n },\n {\n \"background\": \"#f6f8fa\",\n \"border\": \"rgba(84,174,255,0.4)\",\n \"filename\": \"images/bibliometrics.svg\",\n \"text\": \"#24292f\",\n \"title\": \"#0969da\"\n }\n ]\n}\n```\n\n## Configuring the Scholar ID\n\nThere are two ways to provide your Google Scholar ID to the utility:\n* in the configuration file (see above section) via a field `\"scholarID\"` (not shown in the example in the\n repository); or\n* via an environment variable `SCHOLAR_ID`.\n\n## Usage\n\n### Installing\n\nTo install from PyPi (Unix and MacOS):\n\n```Shell\npython3 -m pip install bibliometrics\n```\n\nTo install from PyPI (Windows):\n\n```Shell\npy -m pip install bibliometrics\n```\n\nTo upgrade to latest version from PyPi (Unix and MacOS):\n\n```Shell\npython3 -m pip install --upgrade bibliometrics\n```\n\nTo upgrade to latest version from PyPI (Windows):\n\n```Shell\npy -m pip install --upgrade bibliometrics\n```\n\n### Running\n\nTo use this utility, first ensure that you configure it as specified above. Then execute the following (Unix and MacOS):\n\n```Shell\npython3 -m bibliometrics\n```\n\nOr on Windows:\n\n```Shell\npy -m bibliometrics\n```\n\n## Respect Google Scholar's robots.txt\n\nIf you use this utility, please respect Google Scholar's robots.txt. The reason that the\ng-index (as well as i100-index, i1000-index, i10000-index, w-index) is only computed by this utility \nif it is less than 100 derives from Scholar's robots.txt. Likewise, the reason that the\ne-index, r-index, and a-index are only computed if your h-index is at most 100 relates to \nthis as well. In the case of the h-median, we can compute it as long as your h-index is less\nthan 200. Here is the relevant excerpt:\n\n```robots.txt\nAllow: /citations?user=\nDisallow: /citations?*cstart=\n```\n\nThe first line above allows getting a user's profile page. But the second line\nabove disallows querying a specific starting reference. This means if you are respecting\nGoogle Scholar's robots.txt then you are limited to the first page of the profile, which\ncan include up to 100 publications. Therefore, we can compute g-index as long as it is not\ngreater than 100. However, if we compute 100, we cannot be certain if it is correct or if\nit is actually higher, so this utility excludes a g-index of 100 as well. The same is true\nfor i100-index, i1000-index, and i10000-index. There is a similar issue for e-index, r-index, \nand a-index. In those cases, to compute the relevant bibliometric, we need the number of \ncitations of your h most-cited articles. Therefore, we only compute these if your h-index is \nat most 100.\n\n## Support the Project\n\nYou can support the project in a number of ways:\n* __Starring__: If you find this utility \n useful, consider starring the GitHub repository.\n* __Sharing with Others__: Consider sharing it with others who\n you feel might find it useful.\n* __Reporting Issues__: If you find a bug or have a suggestion for\n a new feature, please report it via \n the [Issue tracker](https://github.com/cicirello/bibliometrics/issues). Please\n note, however, that feature requests will be evaluated for whether they\n can be implemented while respecting Google Scholar's robots.txt, which means\n limited to what can be computed from the first page of your Google Scholar \n profile. \n* __Contributing Code__: If there is an open issue that you think\n you can help with, submit a pull request.\n* __Sponsoring__: You can also consider sponsoring via one of the following:\n\n| [](https://github.com/sponsors/cicirello) | [](https://liberapay.com/cicirello) |\n| :---: | :---: |\n| [](https://ko-fi.com/cicirello) | |\n \n## Contribute\n\nIf you would like to contribute start by reading \nthe [contribution guidelines](https://github.com/cicirello/.github/blob/main/CONTRIBUTING.md).\nThis project has adopted \nthe [Contributor Covenant Code of Conduct](https://github.com/cicirello/.github/blob/main/CODE_OF_CONDUCT.md).\n\nThe intention of this utility is as a tool for a researcher to generate an SVG of their own \nbibliometrics, so issues requesting, or pull requests implementing, support for multiple scholar \nprofiles will be rejected.\n\n## License\n\nThe code in this repository is released under\nthe [MIT License](https://github.com/cicirello/bibliometrics/blob/main/LICENSE).\n",
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